Annotation of imach/src/imach.c, revision 1.357
1.357 ! brouard 1: /* $Id: imach.c,v 1.356 2023/05/23 12:08:43 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.357 ! brouard 4: Revision 1.356 2023/05/23 12:08:43 brouard
! 5: Summary: 0.99r46
! 6:
! 7: * imach.c (Module): Fixed PROB_r
! 8:
1.356 brouard 9: Revision 1.355 2023/05/22 17:03:18 brouard
10: Summary: 0.99r46
11:
12: * imach.c (Module): In the ILK....txt file, the number of columns
13: before the covariates values is dependent of the number of states (16+nlstate): 0.99r46
14:
1.355 brouard 15: Revision 1.354 2023/05/21 05:05:17 brouard
16: Summary: Temporary change for imachprax
17:
1.354 brouard 18: Revision 1.353 2023/05/08 18:48:22 brouard
19: *** empty log message ***
20:
1.353 brouard 21: Revision 1.352 2023/04/29 10:46:21 brouard
22: *** empty log message ***
23:
1.352 brouard 24: Revision 1.351 2023/04/29 10:43:47 brouard
25: Summary: 099r45
26:
1.351 brouard 27: Revision 1.350 2023/04/24 11:38:06 brouard
28: *** empty log message ***
29:
1.350 brouard 30: Revision 1.349 2023/01/31 09:19:37 brouard
31: Summary: Improvements in models with age*Vn*Vm
32:
1.348 brouard 33: Revision 1.347 2022/09/18 14:36:44 brouard
34: Summary: version 0.99r42
35:
1.347 brouard 36: Revision 1.346 2022/09/16 13:52:36 brouard
37: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
38:
1.346 brouard 39: Revision 1.345 2022/09/16 13:40:11 brouard
40: Summary: Version 0.99r41
41:
42: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
43:
1.345 brouard 44: Revision 1.344 2022/09/14 19:33:30 brouard
45: Summary: version 0.99r40
46:
47: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
48:
1.344 brouard 49: Revision 1.343 2022/09/14 14:22:16 brouard
50: Summary: version 0.99r39
51:
52: * imach.c (Module): Version 0.99r39 with colored dummy covariates
53: (fixed or time varying), using new last columns of
54: ILK_parameter.txt file.
55:
1.343 brouard 56: Revision 1.342 2022/09/11 19:54:09 brouard
57: Summary: 0.99r38
58:
59: * imach.c (Module): Adding timevarying products of any kinds,
60: should work before shifting cotvar from ncovcol+nqv columns in
61: order to have a correspondance between the column of cotvar and
62: the id of column.
63: (Module): Some cleaning and adding covariates in ILK.txt
64:
1.342 brouard 65: Revision 1.341 2022/09/11 07:58:42 brouard
66: Summary: Version 0.99r38
67:
68: After adding change in cotvar.
69:
1.341 brouard 70: Revision 1.340 2022/09/11 07:53:11 brouard
71: Summary: Version imach 0.99r37
72:
73: * imach.c (Module): Adding timevarying products of any kinds,
74: should work before shifting cotvar from ncovcol+nqv columns in
75: order to have a correspondance between the column of cotvar and
76: the id of column.
77:
1.340 brouard 78: Revision 1.339 2022/09/09 17:55:22 brouard
79: Summary: version 0.99r37
80:
81: * imach.c (Module): Many improvements for fixing products of fixed
82: timevarying as well as fixed * fixed, and test with quantitative
83: covariate.
84:
1.339 brouard 85: Revision 1.338 2022/09/04 17:40:33 brouard
86: Summary: 0.99r36
87:
88: * imach.c (Module): Now the easy runs i.e. without result or
89: model=1+age only did not work. The defautl combination should be 1
90: and not 0 because everything hasn't been tranformed yet.
91:
1.338 brouard 92: Revision 1.337 2022/09/02 14:26:02 brouard
93: Summary: version 0.99r35
94:
95: * src/imach.c: Version 0.99r35 because it outputs same results with
96: 1+age+V1+V1*age for females and 1+age for females only
97: (education=1 noweight)
98:
1.337 brouard 99: Revision 1.336 2022/08/31 09:52:36 brouard
100: *** empty log message ***
101:
1.336 brouard 102: Revision 1.335 2022/08/31 08:23:16 brouard
103: Summary: improvements...
104:
1.335 brouard 105: Revision 1.334 2022/08/25 09:08:41 brouard
106: Summary: In progress for quantitative
107:
1.334 brouard 108: Revision 1.333 2022/08/21 09:10:30 brouard
109: * src/imach.c (Module): Version 0.99r33 A lot of changes in
110: reassigning covariates: my first idea was that people will always
111: use the first covariate V1 into the model but in fact they are
112: producing data with many covariates and can use an equation model
113: with some of the covariate; it means that in a model V2+V3 instead
114: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
115: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
116: the equation model is restricted to two variables only (V2, V3)
117: and the combination for V2 should be codtabm(k,1) instead of
118: (codtabm(k,2), and the code should be
119: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
120: made. All of these should be simplified once a day like we did in
121: hpxij() for example by using precov[nres] which is computed in
122: decoderesult for each nres of each resultline. Loop should be done
123: on the equation model globally by distinguishing only product with
124: age (which are changing with age) and no more on type of
125: covariates, single dummies, single covariates.
126:
1.333 brouard 127: Revision 1.332 2022/08/21 09:06:25 brouard
128: Summary: Version 0.99r33
129:
130: * src/imach.c (Module): Version 0.99r33 A lot of changes in
131: reassigning covariates: my first idea was that people will always
132: use the first covariate V1 into the model but in fact they are
133: producing data with many covariates and can use an equation model
134: with some of the covariate; it means that in a model V2+V3 instead
135: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
136: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
137: the equation model is restricted to two variables only (V2, V3)
138: and the combination for V2 should be codtabm(k,1) instead of
139: (codtabm(k,2), and the code should be
140: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
141: made. All of these should be simplified once a day like we did in
142: hpxij() for example by using precov[nres] which is computed in
143: decoderesult for each nres of each resultline. Loop should be done
144: on the equation model globally by distinguishing only product with
145: age (which are changing with age) and no more on type of
146: covariates, single dummies, single covariates.
147:
1.332 brouard 148: Revision 1.331 2022/08/07 05:40:09 brouard
149: *** empty log message ***
150:
1.331 brouard 151: Revision 1.330 2022/08/06 07:18:25 brouard
152: Summary: last 0.99r31
153:
154: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
155:
1.330 brouard 156: Revision 1.329 2022/08/03 17:29:54 brouard
157: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
158:
1.329 brouard 159: Revision 1.328 2022/07/27 17:40:48 brouard
160: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
161:
1.328 brouard 162: Revision 1.327 2022/07/27 14:47:35 brouard
163: Summary: Still a problem for one-step probabilities in case of quantitative variables
164:
1.327 brouard 165: Revision 1.326 2022/07/26 17:33:55 brouard
166: Summary: some test with nres=1
167:
1.326 brouard 168: Revision 1.325 2022/07/25 14:27:23 brouard
169: Summary: r30
170:
171: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
172: coredumped, revealed by Feiuno, thank you.
173:
1.325 brouard 174: Revision 1.324 2022/07/23 17:44:26 brouard
175: *** empty log message ***
176:
1.324 brouard 177: Revision 1.323 2022/07/22 12:30:08 brouard
178: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
179:
1.323 brouard 180: Revision 1.322 2022/07/22 12:27:48 brouard
181: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
182:
1.322 brouard 183: Revision 1.321 2022/07/22 12:04:24 brouard
184: Summary: r28
185:
186: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
187:
1.321 brouard 188: Revision 1.320 2022/06/02 05:10:11 brouard
189: *** empty log message ***
190:
1.320 brouard 191: Revision 1.319 2022/06/02 04:45:11 brouard
192: * imach.c (Module): Adding the Wald tests from the log to the main
193: htm for better display of the maximum likelihood estimators.
194:
1.319 brouard 195: Revision 1.318 2022/05/24 08:10:59 brouard
196: * imach.c (Module): Some attempts to find a bug of wrong estimates
197: of confidencce intervals with product in the equation modelC
198:
1.318 brouard 199: Revision 1.317 2022/05/15 15:06:23 brouard
200: * imach.c (Module): Some minor improvements
201:
1.317 brouard 202: Revision 1.316 2022/05/11 15:11:31 brouard
203: Summary: r27
204:
1.316 brouard 205: Revision 1.315 2022/05/11 15:06:32 brouard
206: *** empty log message ***
207:
1.315 brouard 208: Revision 1.314 2022/04/13 17:43:09 brouard
209: * imach.c (Module): Adding link to text data files
210:
1.314 brouard 211: Revision 1.313 2022/04/11 15:57:42 brouard
212: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
213:
1.313 brouard 214: Revision 1.312 2022/04/05 21:24:39 brouard
215: *** empty log message ***
216:
1.312 brouard 217: Revision 1.311 2022/04/05 21:03:51 brouard
218: Summary: Fixed quantitative covariates
219:
220: Fixed covariates (dummy or quantitative)
221: with missing values have never been allowed but are ERRORS and
222: program quits. Standard deviations of fixed covariates were
223: wrongly computed. Mean and standard deviations of time varying
224: covariates are still not computed.
225:
1.311 brouard 226: Revision 1.310 2022/03/17 08:45:53 brouard
227: Summary: 99r25
228:
229: Improving detection of errors: result lines should be compatible with
230: the model.
231:
1.310 brouard 232: Revision 1.309 2021/05/20 12:39:14 brouard
233: Summary: Version 0.99r24
234:
1.309 brouard 235: Revision 1.308 2021/03/31 13:11:57 brouard
236: Summary: Version 0.99r23
237:
238:
239: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
240:
1.308 brouard 241: Revision 1.307 2021/03/08 18:11:32 brouard
242: Summary: 0.99r22 fixed bug on result:
243:
1.307 brouard 244: Revision 1.306 2021/02/20 15:44:02 brouard
245: Summary: Version 0.99r21
246:
247: * imach.c (Module): Fix bug on quitting after result lines!
248: (Module): Version 0.99r21
249:
1.306 brouard 250: Revision 1.305 2021/02/20 15:28:30 brouard
251: * imach.c (Module): Fix bug on quitting after result lines!
252:
1.305 brouard 253: Revision 1.304 2021/02/12 11:34:20 brouard
254: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
255:
1.304 brouard 256: Revision 1.303 2021/02/11 19:50:15 brouard
257: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
258:
1.303 brouard 259: Revision 1.302 2020/02/22 21:00:05 brouard
260: * (Module): imach.c Update mle=-3 (for computing Life expectancy
261: and life table from the data without any state)
262:
1.302 brouard 263: Revision 1.301 2019/06/04 13:51:20 brouard
264: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
265:
1.301 brouard 266: Revision 1.300 2019/05/22 19:09:45 brouard
267: Summary: version 0.99r19 of May 2019
268:
1.300 brouard 269: Revision 1.299 2019/05/22 18:37:08 brouard
270: Summary: Cleaned 0.99r19
271:
1.299 brouard 272: Revision 1.298 2019/05/22 18:19:56 brouard
273: *** empty log message ***
274:
1.298 brouard 275: Revision 1.297 2019/05/22 17:56:10 brouard
276: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
277:
1.297 brouard 278: Revision 1.296 2019/05/20 13:03:18 brouard
279: Summary: Projection syntax simplified
280:
281:
282: We can now start projections, forward or backward, from the mean date
283: of inteviews up to or down to a number of years of projection:
284: prevforecast=1 yearsfproj=15.3 mobil_average=0
285: or
286: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
287: or
288: prevbackcast=1 yearsbproj=12.3 mobil_average=1
289: or
290: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
291:
1.296 brouard 292: Revision 1.295 2019/05/18 09:52:50 brouard
293: Summary: doxygen tex bug
294:
1.295 brouard 295: Revision 1.294 2019/05/16 14:54:33 brouard
296: Summary: There was some wrong lines added
297:
1.294 brouard 298: Revision 1.293 2019/05/09 15:17:34 brouard
299: *** empty log message ***
300:
1.293 brouard 301: Revision 1.292 2019/05/09 14:17:20 brouard
302: Summary: Some updates
303:
1.292 brouard 304: Revision 1.291 2019/05/09 13:44:18 brouard
305: Summary: Before ncovmax
306:
1.291 brouard 307: Revision 1.290 2019/05/09 13:39:37 brouard
308: Summary: 0.99r18 unlimited number of individuals
309:
310: 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.
311:
1.290 brouard 312: Revision 1.289 2018/12/13 09:16:26 brouard
313: Summary: Bug for young ages (<-30) will be in r17
314:
1.289 brouard 315: Revision 1.288 2018/05/02 20:58:27 brouard
316: Summary: Some bugs fixed
317:
1.288 brouard 318: Revision 1.287 2018/05/01 17:57:25 brouard
319: Summary: Bug fixed by providing frequencies only for non missing covariates
320:
1.287 brouard 321: Revision 1.286 2018/04/27 14:27:04 brouard
322: Summary: some minor bugs
323:
1.286 brouard 324: Revision 1.285 2018/04/21 21:02:16 brouard
325: Summary: Some bugs fixed, valgrind tested
326:
1.285 brouard 327: Revision 1.284 2018/04/20 05:22:13 brouard
328: Summary: Computing mean and stdeviation of fixed quantitative variables
329:
1.284 brouard 330: Revision 1.283 2018/04/19 14:49:16 brouard
331: Summary: Some minor bugs fixed
332:
1.283 brouard 333: Revision 1.282 2018/02/27 22:50:02 brouard
334: *** empty log message ***
335:
1.282 brouard 336: Revision 1.281 2018/02/27 19:25:23 brouard
337: Summary: Adding second argument for quitting
338:
1.281 brouard 339: Revision 1.280 2018/02/21 07:58:13 brouard
340: Summary: 0.99r15
341:
342: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
343:
1.280 brouard 344: Revision 1.279 2017/07/20 13:35:01 brouard
345: Summary: temporary working
346:
1.279 brouard 347: Revision 1.278 2017/07/19 14:09:02 brouard
348: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
349:
1.278 brouard 350: Revision 1.277 2017/07/17 08:53:49 brouard
351: Summary: BOM files can be read now
352:
1.277 brouard 353: Revision 1.276 2017/06/30 15:48:31 brouard
354: Summary: Graphs improvements
355:
1.276 brouard 356: Revision 1.275 2017/06/30 13:39:33 brouard
357: Summary: Saito's color
358:
1.275 brouard 359: Revision 1.274 2017/06/29 09:47:08 brouard
360: Summary: Version 0.99r14
361:
1.274 brouard 362: Revision 1.273 2017/06/27 11:06:02 brouard
363: Summary: More documentation on projections
364:
1.273 brouard 365: Revision 1.272 2017/06/27 10:22:40 brouard
366: Summary: Color of backprojection changed from 6 to 5(yellow)
367:
1.272 brouard 368: Revision 1.271 2017/06/27 10:17:50 brouard
369: Summary: Some bug with rint
370:
1.271 brouard 371: Revision 1.270 2017/05/24 05:45:29 brouard
372: *** empty log message ***
373:
1.270 brouard 374: Revision 1.269 2017/05/23 08:39:25 brouard
375: Summary: Code into subroutine, cleanings
376:
1.269 brouard 377: Revision 1.268 2017/05/18 20:09:32 brouard
378: Summary: backprojection and confidence intervals of backprevalence
379:
1.268 brouard 380: Revision 1.267 2017/05/13 10:25:05 brouard
381: Summary: temporary save for backprojection
382:
1.267 brouard 383: Revision 1.266 2017/05/13 07:26:12 brouard
384: Summary: Version 0.99r13 (improvements and bugs fixed)
385:
1.266 brouard 386: Revision 1.265 2017/04/26 16:22:11 brouard
387: Summary: imach 0.99r13 Some bugs fixed
388:
1.265 brouard 389: Revision 1.264 2017/04/26 06:01:29 brouard
390: Summary: Labels in graphs
391:
1.264 brouard 392: Revision 1.263 2017/04/24 15:23:15 brouard
393: Summary: to save
394:
1.263 brouard 395: Revision 1.262 2017/04/18 16:48:12 brouard
396: *** empty log message ***
397:
1.262 brouard 398: Revision 1.261 2017/04/05 10:14:09 brouard
399: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
400:
1.261 brouard 401: Revision 1.260 2017/04/04 17:46:59 brouard
402: Summary: Gnuplot indexations fixed (humm)
403:
1.260 brouard 404: Revision 1.259 2017/04/04 13:01:16 brouard
405: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
406:
1.259 brouard 407: Revision 1.258 2017/04/03 10:17:47 brouard
408: Summary: Version 0.99r12
409:
410: Some cleanings, conformed with updated documentation.
411:
1.258 brouard 412: Revision 1.257 2017/03/29 16:53:30 brouard
413: Summary: Temp
414:
1.257 brouard 415: Revision 1.256 2017/03/27 05:50:23 brouard
416: Summary: Temporary
417:
1.256 brouard 418: Revision 1.255 2017/03/08 16:02:28 brouard
419: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
420:
1.255 brouard 421: Revision 1.254 2017/03/08 07:13:00 brouard
422: Summary: Fixing data parameter line
423:
1.254 brouard 424: Revision 1.253 2016/12/15 11:59:41 brouard
425: Summary: 0.99 in progress
426:
1.253 brouard 427: Revision 1.252 2016/09/15 21:15:37 brouard
428: *** empty log message ***
429:
1.252 brouard 430: Revision 1.251 2016/09/15 15:01:13 brouard
431: Summary: not working
432:
1.251 brouard 433: Revision 1.250 2016/09/08 16:07:27 brouard
434: Summary: continue
435:
1.250 brouard 436: Revision 1.249 2016/09/07 17:14:18 brouard
437: Summary: Starting values from frequencies
438:
1.249 brouard 439: Revision 1.248 2016/09/07 14:10:18 brouard
440: *** empty log message ***
441:
1.248 brouard 442: Revision 1.247 2016/09/02 11:11:21 brouard
443: *** empty log message ***
444:
1.247 brouard 445: Revision 1.246 2016/09/02 08:49:22 brouard
446: *** empty log message ***
447:
1.246 brouard 448: Revision 1.245 2016/09/02 07:25:01 brouard
449: *** empty log message ***
450:
1.245 brouard 451: Revision 1.244 2016/09/02 07:17:34 brouard
452: *** empty log message ***
453:
1.244 brouard 454: Revision 1.243 2016/09/02 06:45:35 brouard
455: *** empty log message ***
456:
1.243 brouard 457: Revision 1.242 2016/08/30 15:01:20 brouard
458: Summary: Fixing a lots
459:
1.242 brouard 460: Revision 1.241 2016/08/29 17:17:25 brouard
461: Summary: gnuplot problem in Back projection to fix
462:
1.241 brouard 463: Revision 1.240 2016/08/29 07:53:18 brouard
464: Summary: Better
465:
1.240 brouard 466: Revision 1.239 2016/08/26 15:51:03 brouard
467: Summary: Improvement in Powell output in order to copy and paste
468:
469: Author:
470:
1.239 brouard 471: Revision 1.238 2016/08/26 14:23:35 brouard
472: Summary: Starting tests of 0.99
473:
1.238 brouard 474: Revision 1.237 2016/08/26 09:20:19 brouard
475: Summary: to valgrind
476:
1.237 brouard 477: Revision 1.236 2016/08/25 10:50:18 brouard
478: *** empty log message ***
479:
1.236 brouard 480: Revision 1.235 2016/08/25 06:59:23 brouard
481: *** empty log message ***
482:
1.235 brouard 483: Revision 1.234 2016/08/23 16:51:20 brouard
484: *** empty log message ***
485:
1.234 brouard 486: Revision 1.233 2016/08/23 07:40:50 brouard
487: Summary: not working
488:
1.233 brouard 489: Revision 1.232 2016/08/22 14:20:21 brouard
490: Summary: not working
491:
1.232 brouard 492: Revision 1.231 2016/08/22 07:17:15 brouard
493: Summary: not working
494:
1.231 brouard 495: Revision 1.230 2016/08/22 06:55:53 brouard
496: Summary: Not working
497:
1.230 brouard 498: Revision 1.229 2016/07/23 09:45:53 brouard
499: Summary: Completing for func too
500:
1.229 brouard 501: Revision 1.228 2016/07/22 17:45:30 brouard
502: Summary: Fixing some arrays, still debugging
503:
1.227 brouard 504: Revision 1.226 2016/07/12 18:42:34 brouard
505: Summary: temp
506:
1.226 brouard 507: Revision 1.225 2016/07/12 08:40:03 brouard
508: Summary: saving but not running
509:
1.225 brouard 510: Revision 1.224 2016/07/01 13:16:01 brouard
511: Summary: Fixes
512:
1.224 brouard 513: Revision 1.223 2016/02/19 09:23:35 brouard
514: Summary: temporary
515:
1.223 brouard 516: Revision 1.222 2016/02/17 08:14:50 brouard
517: Summary: Probably last 0.98 stable version 0.98r6
518:
1.222 brouard 519: Revision 1.221 2016/02/15 23:35:36 brouard
520: Summary: minor bug
521:
1.220 brouard 522: Revision 1.219 2016/02/15 00:48:12 brouard
523: *** empty log message ***
524:
1.219 brouard 525: Revision 1.218 2016/02/12 11:29:23 brouard
526: Summary: 0.99 Back projections
527:
1.218 brouard 528: Revision 1.217 2015/12/23 17:18:31 brouard
529: Summary: Experimental backcast
530:
1.217 brouard 531: Revision 1.216 2015/12/18 17:32:11 brouard
532: Summary: 0.98r4 Warning and status=-2
533:
534: Version 0.98r4 is now:
535: - displaying an error when status is -1, date of interview unknown and date of death known;
536: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
537: Older changes concerning s=-2, dating from 2005 have been supersed.
538:
1.216 brouard 539: Revision 1.215 2015/12/16 08:52:24 brouard
540: Summary: 0.98r4 working
541:
1.215 brouard 542: Revision 1.214 2015/12/16 06:57:54 brouard
543: Summary: temporary not working
544:
1.214 brouard 545: Revision 1.213 2015/12/11 18:22:17 brouard
546: Summary: 0.98r4
547:
1.213 brouard 548: Revision 1.212 2015/11/21 12:47:24 brouard
549: Summary: minor typo
550:
1.212 brouard 551: Revision 1.211 2015/11/21 12:41:11 brouard
552: Summary: 0.98r3 with some graph of projected cross-sectional
553:
554: Author: Nicolas Brouard
555:
1.211 brouard 556: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 557: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 558: Summary: Adding ftolpl parameter
559: Author: N Brouard
560:
561: We had difficulties to get smoothed confidence intervals. It was due
562: to the period prevalence which wasn't computed accurately. The inner
563: parameter ftolpl is now an outer parameter of the .imach parameter
564: file after estepm. If ftolpl is small 1.e-4 and estepm too,
565: computation are long.
566:
1.209 brouard 567: Revision 1.208 2015/11/17 14:31:57 brouard
568: Summary: temporary
569:
1.208 brouard 570: Revision 1.207 2015/10/27 17:36:57 brouard
571: *** empty log message ***
572:
1.207 brouard 573: Revision 1.206 2015/10/24 07:14:11 brouard
574: *** empty log message ***
575:
1.206 brouard 576: Revision 1.205 2015/10/23 15:50:53 brouard
577: Summary: 0.98r3 some clarification for graphs on likelihood contributions
578:
1.205 brouard 579: Revision 1.204 2015/10/01 16:20:26 brouard
580: Summary: Some new graphs of contribution to likelihood
581:
1.204 brouard 582: Revision 1.203 2015/09/30 17:45:14 brouard
583: Summary: looking at better estimation of the hessian
584:
585: Also a better criteria for convergence to the period prevalence And
586: therefore adding the number of years needed to converge. (The
587: prevalence in any alive state shold sum to one
588:
1.203 brouard 589: Revision 1.202 2015/09/22 19:45:16 brouard
590: Summary: Adding some overall graph on contribution to likelihood. Might change
591:
1.202 brouard 592: Revision 1.201 2015/09/15 17:34:58 brouard
593: Summary: 0.98r0
594:
595: - Some new graphs like suvival functions
596: - Some bugs fixed like model=1+age+V2.
597:
1.201 brouard 598: Revision 1.200 2015/09/09 16:53:55 brouard
599: Summary: Big bug thanks to Flavia
600:
601: Even model=1+age+V2. did not work anymore
602:
1.200 brouard 603: Revision 1.199 2015/09/07 14:09:23 brouard
604: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
605:
1.199 brouard 606: Revision 1.198 2015/09/03 07:14:39 brouard
607: Summary: 0.98q5 Flavia
608:
1.198 brouard 609: Revision 1.197 2015/09/01 18:24:39 brouard
610: *** empty log message ***
611:
1.197 brouard 612: Revision 1.196 2015/08/18 23:17:52 brouard
613: Summary: 0.98q5
614:
1.196 brouard 615: Revision 1.195 2015/08/18 16:28:39 brouard
616: Summary: Adding a hack for testing purpose
617:
618: After reading the title, ftol and model lines, if the comment line has
619: a q, starting with #q, the answer at the end of the run is quit. It
620: permits to run test files in batch with ctest. The former workaround was
621: $ echo q | imach foo.imach
622:
1.195 brouard 623: Revision 1.194 2015/08/18 13:32:00 brouard
624: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
625:
1.194 brouard 626: Revision 1.193 2015/08/04 07:17:42 brouard
627: Summary: 0.98q4
628:
1.193 brouard 629: Revision 1.192 2015/07/16 16:49:02 brouard
630: Summary: Fixing some outputs
631:
1.192 brouard 632: Revision 1.191 2015/07/14 10:00:33 brouard
633: Summary: Some fixes
634:
1.191 brouard 635: Revision 1.190 2015/05/05 08:51:13 brouard
636: Summary: Adding digits in output parameters (7 digits instead of 6)
637:
638: Fix 1+age+.
639:
1.190 brouard 640: Revision 1.189 2015/04/30 14:45:16 brouard
641: Summary: 0.98q2
642:
1.189 brouard 643: Revision 1.188 2015/04/30 08:27:53 brouard
644: *** empty log message ***
645:
1.188 brouard 646: Revision 1.187 2015/04/29 09:11:15 brouard
647: *** empty log message ***
648:
1.187 brouard 649: Revision 1.186 2015/04/23 12:01:52 brouard
650: Summary: V1*age is working now, version 0.98q1
651:
652: Some codes had been disabled in order to simplify and Vn*age was
653: working in the optimization phase, ie, giving correct MLE parameters,
654: but, as usual, outputs were not correct and program core dumped.
655:
1.186 brouard 656: Revision 1.185 2015/03/11 13:26:42 brouard
657: Summary: Inclusion of compile and links command line for Intel Compiler
658:
1.185 brouard 659: Revision 1.184 2015/03/11 11:52:39 brouard
660: Summary: Back from Windows 8. Intel Compiler
661:
1.184 brouard 662: Revision 1.183 2015/03/10 20:34:32 brouard
663: Summary: 0.98q0, trying with directest, mnbrak fixed
664:
665: We use directest instead of original Powell test; probably no
666: incidence on the results, but better justifications;
667: We fixed Numerical Recipes mnbrak routine which was wrong and gave
668: wrong results.
669:
1.183 brouard 670: Revision 1.182 2015/02/12 08:19:57 brouard
671: Summary: Trying to keep directest which seems simpler and more general
672: Author: Nicolas Brouard
673:
1.182 brouard 674: Revision 1.181 2015/02/11 23:22:24 brouard
675: Summary: Comments on Powell added
676:
677: Author:
678:
1.181 brouard 679: Revision 1.180 2015/02/11 17:33:45 brouard
680: Summary: Finishing move from main to function (hpijx and prevalence_limit)
681:
1.180 brouard 682: Revision 1.179 2015/01/04 09:57:06 brouard
683: Summary: back to OS/X
684:
1.179 brouard 685: Revision 1.178 2015/01/04 09:35:48 brouard
686: *** empty log message ***
687:
1.178 brouard 688: Revision 1.177 2015/01/03 18:40:56 brouard
689: Summary: Still testing ilc32 on OSX
690:
1.177 brouard 691: Revision 1.176 2015/01/03 16:45:04 brouard
692: *** empty log message ***
693:
1.176 brouard 694: Revision 1.175 2015/01/03 16:33:42 brouard
695: *** empty log message ***
696:
1.175 brouard 697: Revision 1.174 2015/01/03 16:15:49 brouard
698: Summary: Still in cross-compilation
699:
1.174 brouard 700: Revision 1.173 2015/01/03 12:06:26 brouard
701: Summary: trying to detect cross-compilation
702:
1.173 brouard 703: Revision 1.172 2014/12/27 12:07:47 brouard
704: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
705:
1.172 brouard 706: Revision 1.171 2014/12/23 13:26:59 brouard
707: Summary: Back from Visual C
708:
709: Still problem with utsname.h on Windows
710:
1.171 brouard 711: Revision 1.170 2014/12/23 11:17:12 brouard
712: Summary: Cleaning some \%% back to %%
713:
714: The escape was mandatory for a specific compiler (which one?), but too many warnings.
715:
1.170 brouard 716: Revision 1.169 2014/12/22 23:08:31 brouard
717: Summary: 0.98p
718:
719: Outputs some informations on compiler used, OS etc. Testing on different platforms.
720:
1.169 brouard 721: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 722: Summary: update
1.169 brouard 723:
1.168 brouard 724: Revision 1.167 2014/12/22 13:50:56 brouard
725: Summary: Testing uname and compiler version and if compiled 32 or 64
726:
727: Testing on Linux 64
728:
1.167 brouard 729: Revision 1.166 2014/12/22 11:40:47 brouard
730: *** empty log message ***
731:
1.166 brouard 732: Revision 1.165 2014/12/16 11:20:36 brouard
733: Summary: After compiling on Visual C
734:
735: * imach.c (Module): Merging 1.61 to 1.162
736:
1.165 brouard 737: Revision 1.164 2014/12/16 10:52:11 brouard
738: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
739:
740: * imach.c (Module): Merging 1.61 to 1.162
741:
1.164 brouard 742: Revision 1.163 2014/12/16 10:30:11 brouard
743: * imach.c (Module): Merging 1.61 to 1.162
744:
1.163 brouard 745: Revision 1.162 2014/09/25 11:43:39 brouard
746: Summary: temporary backup 0.99!
747:
1.162 brouard 748: Revision 1.1 2014/09/16 11:06:58 brouard
749: Summary: With some code (wrong) for nlopt
750:
751: Author:
752:
753: Revision 1.161 2014/09/15 20:41:41 brouard
754: Summary: Problem with macro SQR on Intel compiler
755:
1.161 brouard 756: Revision 1.160 2014/09/02 09:24:05 brouard
757: *** empty log message ***
758:
1.160 brouard 759: Revision 1.159 2014/09/01 10:34:10 brouard
760: Summary: WIN32
761: Author: Brouard
762:
1.159 brouard 763: Revision 1.158 2014/08/27 17:11:51 brouard
764: *** empty log message ***
765:
1.158 brouard 766: Revision 1.157 2014/08/27 16:26:55 brouard
767: Summary: Preparing windows Visual studio version
768: Author: Brouard
769:
770: In order to compile on Visual studio, time.h is now correct and time_t
771: and tm struct should be used. difftime should be used but sometimes I
772: just make the differences in raw time format (time(&now).
773: Trying to suppress #ifdef LINUX
774: Add xdg-open for __linux in order to open default browser.
775:
1.157 brouard 776: Revision 1.156 2014/08/25 20:10:10 brouard
777: *** empty log message ***
778:
1.156 brouard 779: Revision 1.155 2014/08/25 18:32:34 brouard
780: Summary: New compile, minor changes
781: Author: Brouard
782:
1.155 brouard 783: Revision 1.154 2014/06/20 17:32:08 brouard
784: Summary: Outputs now all graphs of convergence to period prevalence
785:
1.154 brouard 786: Revision 1.153 2014/06/20 16:45:46 brouard
787: Summary: If 3 live state, convergence to period prevalence on same graph
788: Author: Brouard
789:
1.153 brouard 790: Revision 1.152 2014/06/18 17:54:09 brouard
791: Summary: open browser, use gnuplot on same dir than imach if not found in the path
792:
1.152 brouard 793: Revision 1.151 2014/06/18 16:43:30 brouard
794: *** empty log message ***
795:
1.151 brouard 796: Revision 1.150 2014/06/18 16:42:35 brouard
797: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
798: Author: brouard
799:
1.150 brouard 800: Revision 1.149 2014/06/18 15:51:14 brouard
801: Summary: Some fixes in parameter files errors
802: Author: Nicolas Brouard
803:
1.149 brouard 804: Revision 1.148 2014/06/17 17:38:48 brouard
805: Summary: Nothing new
806: Author: Brouard
807:
808: Just a new packaging for OS/X version 0.98nS
809:
1.148 brouard 810: Revision 1.147 2014/06/16 10:33:11 brouard
811: *** empty log message ***
812:
1.147 brouard 813: Revision 1.146 2014/06/16 10:20:28 brouard
814: Summary: Merge
815: Author: Brouard
816:
817: Merge, before building revised version.
818:
1.146 brouard 819: Revision 1.145 2014/06/10 21:23:15 brouard
820: Summary: Debugging with valgrind
821: Author: Nicolas Brouard
822:
823: Lot of changes in order to output the results with some covariates
824: After the Edimburgh REVES conference 2014, it seems mandatory to
825: improve the code.
826: No more memory valgrind error but a lot has to be done in order to
827: continue the work of splitting the code into subroutines.
828: Also, decodemodel has been improved. Tricode is still not
829: optimal. nbcode should be improved. Documentation has been added in
830: the source code.
831:
1.144 brouard 832: Revision 1.143 2014/01/26 09:45:38 brouard
833: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
834:
835: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
836: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
837:
1.143 brouard 838: Revision 1.142 2014/01/26 03:57:36 brouard
839: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
840:
841: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
842:
1.142 brouard 843: Revision 1.141 2014/01/26 02:42:01 brouard
844: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
845:
1.141 brouard 846: Revision 1.140 2011/09/02 10:37:54 brouard
847: Summary: times.h is ok with mingw32 now.
848:
1.140 brouard 849: Revision 1.139 2010/06/14 07:50:17 brouard
850: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
851: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
852:
1.139 brouard 853: Revision 1.138 2010/04/30 18:19:40 brouard
854: *** empty log message ***
855:
1.138 brouard 856: Revision 1.137 2010/04/29 18:11:38 brouard
857: (Module): Checking covariates for more complex models
858: than V1+V2. A lot of change to be done. Unstable.
859:
1.137 brouard 860: Revision 1.136 2010/04/26 20:30:53 brouard
861: (Module): merging some libgsl code. Fixing computation
862: of likelione (using inter/intrapolation if mle = 0) in order to
863: get same likelihood as if mle=1.
864: Some cleaning of code and comments added.
865:
1.136 brouard 866: Revision 1.135 2009/10/29 15:33:14 brouard
867: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
868:
1.135 brouard 869: Revision 1.134 2009/10/29 13:18:53 brouard
870: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
871:
1.134 brouard 872: Revision 1.133 2009/07/06 10:21:25 brouard
873: just nforces
874:
1.133 brouard 875: Revision 1.132 2009/07/06 08:22:05 brouard
876: Many tings
877:
1.132 brouard 878: Revision 1.131 2009/06/20 16:22:47 brouard
879: Some dimensions resccaled
880:
1.131 brouard 881: Revision 1.130 2009/05/26 06:44:34 brouard
882: (Module): Max Covariate is now set to 20 instead of 8. A
883: lot of cleaning with variables initialized to 0. Trying to make
884: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
885:
1.130 brouard 886: Revision 1.129 2007/08/31 13:49:27 lievre
887: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
888:
1.129 lievre 889: Revision 1.128 2006/06/30 13:02:05 brouard
890: (Module): Clarifications on computing e.j
891:
1.128 brouard 892: Revision 1.127 2006/04/28 18:11:50 brouard
893: (Module): Yes the sum of survivors was wrong since
894: imach-114 because nhstepm was no more computed in the age
895: loop. Now we define nhstepma in the age loop.
896: (Module): In order to speed up (in case of numerous covariates) we
897: compute health expectancies (without variances) in a first step
898: and then all the health expectancies with variances or standard
899: deviation (needs data from the Hessian matrices) which slows the
900: computation.
901: In the future we should be able to stop the program is only health
902: expectancies and graph are needed without standard deviations.
903:
1.127 brouard 904: Revision 1.126 2006/04/28 17:23:28 brouard
905: (Module): Yes the sum of survivors was wrong since
906: imach-114 because nhstepm was no more computed in the age
907: loop. Now we define nhstepma in the age loop.
908: Version 0.98h
909:
1.126 brouard 910: Revision 1.125 2006/04/04 15:20:31 lievre
911: Errors in calculation of health expectancies. Age was not initialized.
912: Forecasting file added.
913:
914: Revision 1.124 2006/03/22 17:13:53 lievre
915: Parameters are printed with %lf instead of %f (more numbers after the comma).
916: The log-likelihood is printed in the log file
917:
918: Revision 1.123 2006/03/20 10:52:43 brouard
919: * imach.c (Module): <title> changed, corresponds to .htm file
920: name. <head> headers where missing.
921:
922: * imach.c (Module): Weights can have a decimal point as for
923: English (a comma might work with a correct LC_NUMERIC environment,
924: otherwise the weight is truncated).
925: Modification of warning when the covariates values are not 0 or
926: 1.
927: Version 0.98g
928:
929: Revision 1.122 2006/03/20 09:45:41 brouard
930: (Module): Weights can have a decimal point as for
931: English (a comma might work with a correct LC_NUMERIC environment,
932: otherwise the weight is truncated).
933: Modification of warning when the covariates values are not 0 or
934: 1.
935: Version 0.98g
936:
937: Revision 1.121 2006/03/16 17:45:01 lievre
938: * imach.c (Module): Comments concerning covariates added
939:
940: * imach.c (Module): refinements in the computation of lli if
941: status=-2 in order to have more reliable computation if stepm is
942: not 1 month. Version 0.98f
943:
944: Revision 1.120 2006/03/16 15:10:38 lievre
945: (Module): refinements in the computation of lli if
946: status=-2 in order to have more reliable computation if stepm is
947: not 1 month. Version 0.98f
948:
949: Revision 1.119 2006/03/15 17:42:26 brouard
950: (Module): Bug if status = -2, the loglikelihood was
951: computed as likelihood omitting the logarithm. Version O.98e
952:
953: Revision 1.118 2006/03/14 18:20:07 brouard
954: (Module): varevsij Comments added explaining the second
955: table of variances if popbased=1 .
956: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
957: (Module): Function pstamp added
958: (Module): Version 0.98d
959:
960: Revision 1.117 2006/03/14 17:16:22 brouard
961: (Module): varevsij Comments added explaining the second
962: table of variances if popbased=1 .
963: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
964: (Module): Function pstamp added
965: (Module): Version 0.98d
966:
967: Revision 1.116 2006/03/06 10:29:27 brouard
968: (Module): Variance-covariance wrong links and
969: varian-covariance of ej. is needed (Saito).
970:
971: Revision 1.115 2006/02/27 12:17:45 brouard
972: (Module): One freematrix added in mlikeli! 0.98c
973:
974: Revision 1.114 2006/02/26 12:57:58 brouard
975: (Module): Some improvements in processing parameter
976: filename with strsep.
977:
978: Revision 1.113 2006/02/24 14:20:24 brouard
979: (Module): Memory leaks checks with valgrind and:
980: datafile was not closed, some imatrix were not freed and on matrix
981: allocation too.
982:
983: Revision 1.112 2006/01/30 09:55:26 brouard
984: (Module): Back to gnuplot.exe instead of wgnuplot.exe
985:
986: Revision 1.111 2006/01/25 20:38:18 brouard
987: (Module): Lots of cleaning and bugs added (Gompertz)
988: (Module): Comments can be added in data file. Missing date values
989: can be a simple dot '.'.
990:
991: Revision 1.110 2006/01/25 00:51:50 brouard
992: (Module): Lots of cleaning and bugs added (Gompertz)
993:
994: Revision 1.109 2006/01/24 19:37:15 brouard
995: (Module): Comments (lines starting with a #) are allowed in data.
996:
997: Revision 1.108 2006/01/19 18:05:42 lievre
998: Gnuplot problem appeared...
999: To be fixed
1000:
1001: Revision 1.107 2006/01/19 16:20:37 brouard
1002: Test existence of gnuplot in imach path
1003:
1004: Revision 1.106 2006/01/19 13:24:36 brouard
1005: Some cleaning and links added in html output
1006:
1007: Revision 1.105 2006/01/05 20:23:19 lievre
1008: *** empty log message ***
1009:
1010: Revision 1.104 2005/09/30 16:11:43 lievre
1011: (Module): sump fixed, loop imx fixed, and simplifications.
1012: (Module): If the status is missing at the last wave but we know
1013: that the person is alive, then we can code his/her status as -2
1014: (instead of missing=-1 in earlier versions) and his/her
1015: contributions to the likelihood is 1 - Prob of dying from last
1016: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1017: the healthy state at last known wave). Version is 0.98
1018:
1019: Revision 1.103 2005/09/30 15:54:49 lievre
1020: (Module): sump fixed, loop imx fixed, and simplifications.
1021:
1022: Revision 1.102 2004/09/15 17:31:30 brouard
1023: Add the possibility to read data file including tab characters.
1024:
1025: Revision 1.101 2004/09/15 10:38:38 brouard
1026: Fix on curr_time
1027:
1028: Revision 1.100 2004/07/12 18:29:06 brouard
1029: Add version for Mac OS X. Just define UNIX in Makefile
1030:
1031: Revision 1.99 2004/06/05 08:57:40 brouard
1032: *** empty log message ***
1033:
1034: Revision 1.98 2004/05/16 15:05:56 brouard
1035: New version 0.97 . First attempt to estimate force of mortality
1036: directly from the data i.e. without the need of knowing the health
1037: state at each age, but using a Gompertz model: log u =a + b*age .
1038: This is the basic analysis of mortality and should be done before any
1039: other analysis, in order to test if the mortality estimated from the
1040: cross-longitudinal survey is different from the mortality estimated
1041: from other sources like vital statistic data.
1042:
1043: The same imach parameter file can be used but the option for mle should be -3.
1044:
1.324 brouard 1045: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1046: former routines in order to include the new code within the former code.
1047:
1048: The output is very simple: only an estimate of the intercept and of
1049: the slope with 95% confident intervals.
1050:
1051: Current limitations:
1052: A) Even if you enter covariates, i.e. with the
1053: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1054: B) There is no computation of Life Expectancy nor Life Table.
1055:
1056: Revision 1.97 2004/02/20 13:25:42 lievre
1057: Version 0.96d. Population forecasting command line is (temporarily)
1058: suppressed.
1059:
1060: Revision 1.96 2003/07/15 15:38:55 brouard
1061: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1062: rewritten within the same printf. Workaround: many printfs.
1063:
1064: Revision 1.95 2003/07/08 07:54:34 brouard
1065: * imach.c (Repository):
1066: (Repository): Using imachwizard code to output a more meaningful covariance
1067: matrix (cov(a12,c31) instead of numbers.
1068:
1069: Revision 1.94 2003/06/27 13:00:02 brouard
1070: Just cleaning
1071:
1072: Revision 1.93 2003/06/25 16:33:55 brouard
1073: (Module): On windows (cygwin) function asctime_r doesn't
1074: exist so I changed back to asctime which exists.
1075: (Module): Version 0.96b
1076:
1077: Revision 1.92 2003/06/25 16:30:45 brouard
1078: (Module): On windows (cygwin) function asctime_r doesn't
1079: exist so I changed back to asctime which exists.
1080:
1081: Revision 1.91 2003/06/25 15:30:29 brouard
1082: * imach.c (Repository): Duplicated warning errors corrected.
1083: (Repository): Elapsed time after each iteration is now output. It
1084: helps to forecast when convergence will be reached. Elapsed time
1085: is stamped in powell. We created a new html file for the graphs
1086: concerning matrix of covariance. It has extension -cov.htm.
1087:
1088: Revision 1.90 2003/06/24 12:34:15 brouard
1089: (Module): Some bugs corrected for windows. Also, when
1090: mle=-1 a template is output in file "or"mypar.txt with the design
1091: of the covariance matrix to be input.
1092:
1093: Revision 1.89 2003/06/24 12:30:52 brouard
1094: (Module): Some bugs corrected for windows. Also, when
1095: mle=-1 a template is output in file "or"mypar.txt with the design
1096: of the covariance matrix to be input.
1097:
1098: Revision 1.88 2003/06/23 17:54:56 brouard
1099: * 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.
1100:
1101: Revision 1.87 2003/06/18 12:26:01 brouard
1102: Version 0.96
1103:
1104: Revision 1.86 2003/06/17 20:04:08 brouard
1105: (Module): Change position of html and gnuplot routines and added
1106: routine fileappend.
1107:
1108: Revision 1.85 2003/06/17 13:12:43 brouard
1109: * imach.c (Repository): Check when date of death was earlier that
1110: current date of interview. It may happen when the death was just
1111: prior to the death. In this case, dh was negative and likelihood
1112: was wrong (infinity). We still send an "Error" but patch by
1113: assuming that the date of death was just one stepm after the
1114: interview.
1115: (Repository): Because some people have very long ID (first column)
1116: we changed int to long in num[] and we added a new lvector for
1117: memory allocation. But we also truncated to 8 characters (left
1118: truncation)
1119: (Repository): No more line truncation errors.
1120:
1121: Revision 1.84 2003/06/13 21:44:43 brouard
1122: * imach.c (Repository): Replace "freqsummary" at a correct
1123: place. It differs from routine "prevalence" which may be called
1124: many times. Probs is memory consuming and must be used with
1125: parcimony.
1126: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1127:
1128: Revision 1.83 2003/06/10 13:39:11 lievre
1129: *** empty log message ***
1130:
1131: Revision 1.82 2003/06/05 15:57:20 brouard
1132: Add log in imach.c and fullversion number is now printed.
1133:
1134: */
1135: /*
1136: Interpolated Markov Chain
1137:
1138: Short summary of the programme:
1139:
1.227 brouard 1140: This program computes Healthy Life Expectancies or State-specific
1141: (if states aren't health statuses) Expectancies from
1142: cross-longitudinal data. Cross-longitudinal data consist in:
1143:
1144: -1- a first survey ("cross") where individuals from different ages
1145: are interviewed on their health status or degree of disability (in
1146: the case of a health survey which is our main interest)
1147:
1148: -2- at least a second wave of interviews ("longitudinal") which
1149: measure each change (if any) in individual health status. Health
1150: expectancies are computed from the time spent in each health state
1151: according to a model. More health states you consider, more time is
1152: necessary to reach the Maximum Likelihood of the parameters involved
1153: in the model. The simplest model is the multinomial logistic model
1154: where pij is the probability to be observed in state j at the second
1155: wave conditional to be observed in state i at the first
1156: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1157: etc , where 'age' is age and 'sex' is a covariate. If you want to
1158: have a more complex model than "constant and age", you should modify
1159: the program where the markup *Covariates have to be included here
1160: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1161: convergence.
1162:
1163: The advantage of this computer programme, compared to a simple
1164: multinomial logistic model, is clear when the delay between waves is not
1165: identical for each individual. Also, if a individual missed an
1166: intermediate interview, the information is lost, but taken into
1167: account using an interpolation or extrapolation.
1168:
1169: hPijx is the probability to be observed in state i at age x+h
1170: conditional to the observed state i at age x. The delay 'h' can be
1171: split into an exact number (nh*stepm) of unobserved intermediate
1172: states. This elementary transition (by month, quarter,
1173: semester or year) is modelled as a multinomial logistic. The hPx
1174: matrix is simply the matrix product of nh*stepm elementary matrices
1175: and the contribution of each individual to the likelihood is simply
1176: hPijx.
1177:
1178: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1179: of the life expectancies. It also computes the period (stable) prevalence.
1180:
1181: Back prevalence and projections:
1.227 brouard 1182:
1183: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1184: double agemaxpar, double ftolpl, int *ncvyearp, double
1185: dateprev1,double dateprev2, int firstpass, int lastpass, int
1186: mobilavproj)
1187:
1188: Computes the back prevalence limit for any combination of
1189: covariate values k at any age between ageminpar and agemaxpar and
1190: returns it in **bprlim. In the loops,
1191:
1192: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1193: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1194:
1195: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1196: Computes for any combination of covariates k and any age between bage and fage
1197: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1198: oldm=oldms;savm=savms;
1.227 brouard 1199:
1.267 brouard 1200: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1201: Computes the transition matrix starting at age 'age' over
1202: 'nhstepm*hstepm*stepm' months (i.e. until
1203: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1204: nhstepm*hstepm matrices.
1205:
1206: Returns p3mat[i][j][h] after calling
1207: p3mat[i][j][h]=matprod2(newm,
1208: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1209: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1210: oldm);
1.226 brouard 1211:
1212: Important routines
1213:
1214: - func (or funcone), computes logit (pij) distinguishing
1215: o fixed variables (single or product dummies or quantitative);
1216: o varying variables by:
1217: (1) wave (single, product dummies, quantitative),
1218: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1219: % fixed dummy (treated) or quantitative (not done because time-consuming);
1220: % varying dummy (not done) or quantitative (not done);
1221: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1222: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1223: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1224: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1225: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1226:
1.226 brouard 1227:
1228:
1.324 brouard 1229: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1230: Institut national d'études démographiques, Paris.
1.126 brouard 1231: This software have been partly granted by Euro-REVES, a concerted action
1232: from the European Union.
1233: It is copyrighted identically to a GNU software product, ie programme and
1234: software can be distributed freely for non commercial use. Latest version
1235: can be accessed at http://euroreves.ined.fr/imach .
1236:
1237: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1238: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1239:
1240: **********************************************************************/
1241: /*
1242: main
1243: read parameterfile
1244: read datafile
1245: concatwav
1246: freqsummary
1247: if (mle >= 1)
1248: mlikeli
1249: print results files
1250: if mle==1
1251: computes hessian
1252: read end of parameter file: agemin, agemax, bage, fage, estepm
1253: begin-prev-date,...
1254: open gnuplot file
1255: open html file
1.145 brouard 1256: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1257: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1258: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1259: freexexit2 possible for memory heap.
1260:
1261: h Pij x | pij_nom ficrestpij
1262: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1263: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1264: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1265:
1266: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1267: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1268: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1269: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1270: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1271:
1.126 brouard 1272: forecasting if prevfcast==1 prevforecast call prevalence()
1273: health expectancies
1274: Variance-covariance of DFLE
1275: prevalence()
1276: movingaverage()
1277: varevsij()
1278: if popbased==1 varevsij(,popbased)
1279: total life expectancies
1280: Variance of period (stable) prevalence
1281: end
1282: */
1283:
1.187 brouard 1284: /* #define DEBUG */
1285: /* #define DEBUGBRENT */
1.203 brouard 1286: /* #define DEBUGLINMIN */
1287: /* #define DEBUGHESS */
1288: #define DEBUGHESSIJ
1.224 brouard 1289: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1290: #define POWELL /* Instead of NLOPT */
1.224 brouard 1291: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1292: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1293: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1294: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.357 ! brouard 1295: #define POWELLORIGINCONJUGATE /* Don't use conjugate but biggest decrease if valuable */
1.126 brouard 1296:
1297: #include <math.h>
1298: #include <stdio.h>
1299: #include <stdlib.h>
1300: #include <string.h>
1.226 brouard 1301: #include <ctype.h>
1.159 brouard 1302:
1303: #ifdef _WIN32
1304: #include <io.h>
1.172 brouard 1305: #include <windows.h>
1306: #include <tchar.h>
1.159 brouard 1307: #else
1.126 brouard 1308: #include <unistd.h>
1.159 brouard 1309: #endif
1.126 brouard 1310:
1311: #include <limits.h>
1312: #include <sys/types.h>
1.171 brouard 1313:
1314: #if defined(__GNUC__)
1315: #include <sys/utsname.h> /* Doesn't work on Windows */
1316: #endif
1317:
1.126 brouard 1318: #include <sys/stat.h>
1319: #include <errno.h>
1.159 brouard 1320: /* extern int errno; */
1.126 brouard 1321:
1.157 brouard 1322: /* #ifdef LINUX */
1323: /* #include <time.h> */
1324: /* #include "timeval.h" */
1325: /* #else */
1326: /* #include <sys/time.h> */
1327: /* #endif */
1328:
1.126 brouard 1329: #include <time.h>
1330:
1.136 brouard 1331: #ifdef GSL
1332: #include <gsl/gsl_errno.h>
1333: #include <gsl/gsl_multimin.h>
1334: #endif
1335:
1.167 brouard 1336:
1.162 brouard 1337: #ifdef NLOPT
1338: #include <nlopt.h>
1339: typedef struct {
1340: double (* function)(double [] );
1341: } myfunc_data ;
1342: #endif
1343:
1.126 brouard 1344: /* #include <libintl.h> */
1345: /* #define _(String) gettext (String) */
1346:
1.349 brouard 1347: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1348:
1349: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1350: #define GNUPLOTVERSION 5.1
1351: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1352: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1353: #define FILENAMELENGTH 256
1.126 brouard 1354:
1355: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1356: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1357:
1.349 brouard 1358: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1359: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1360:
1361: #define NINTERVMAX 8
1.144 brouard 1362: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1363: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1364: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1365: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1366: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1367: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1368: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1369: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1370: /* #define AGESUP 130 */
1.288 brouard 1371: /* #define AGESUP 150 */
1372: #define AGESUP 200
1.268 brouard 1373: #define AGEINF 0
1.218 brouard 1374: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1375: #define AGEBASE 40
1.194 brouard 1376: #define AGEOVERFLOW 1.e20
1.164 brouard 1377: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1378: #ifdef _WIN32
1379: #define DIRSEPARATOR '\\'
1380: #define CHARSEPARATOR "\\"
1381: #define ODIRSEPARATOR '/'
1382: #else
1.126 brouard 1383: #define DIRSEPARATOR '/'
1384: #define CHARSEPARATOR "/"
1385: #define ODIRSEPARATOR '\\'
1386: #endif
1387:
1.357 ! brouard 1388: /* $Id: imach.c,v 1.356 2023/05/23 12:08:43 brouard Exp $ */
1.126 brouard 1389: /* $State: Exp $ */
1.196 brouard 1390: #include "version.h"
1391: char version[]=__IMACH_VERSION__;
1.352 brouard 1392: char copyright[]="April 2023,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
1.357 ! brouard 1393: char fullversion[]="$Revision: 1.356 $ $Date: 2023/05/23 12:08:43 $";
1.126 brouard 1394: char strstart[80];
1395: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1396: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1397: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1398: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1399: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1400: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1401: 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 1402: 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 1403: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1404: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1405: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1406: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1407: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1408: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1409: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1410: 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 1411: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1412: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1413: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1414: int ncovvta=0; /* +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1415: int ncovta=0; /*age*V3*V2 +age*V2+agev3+ageV4 +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1416: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1417: int ncovva=0; /* +age*V6 + age*V7+ge*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1.234 brouard 1418: int nsd=0; /**< Total number of single dummy variables (output) */
1419: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1420: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1421: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1422: int ntveff=0; /**< ntveff number of effective time varying variables */
1423: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1424: int cptcov=0; /* Working variable */
1.334 brouard 1425: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1426: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1427: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1428: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1429: int nlstate=2; /* Number of live states */
1430: int ndeath=1; /* Number of dead states */
1.130 brouard 1431: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1432: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1433: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1434: int popbased=0;
1435:
1436: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1437: int maxwav=0; /* Maxim number of waves */
1438: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1439: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1440: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1441: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1442: int mle=1, weightopt=0;
1.126 brouard 1443: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1444: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1445: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1446: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1447: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1448: int selected(int kvar); /* Is covariate kvar selected for printing results */
1449:
1.130 brouard 1450: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1451: double **matprod2(); /* test */
1.126 brouard 1452: double **oldm, **newm, **savm; /* Working pointers to matrices */
1453: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1454: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1455:
1.136 brouard 1456: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1457: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1458: FILE *ficlog, *ficrespow;
1.130 brouard 1459: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1460: double fretone; /* Only one call to likelihood */
1.130 brouard 1461: long ipmx=0; /* Number of contributions */
1.126 brouard 1462: double sw; /* Sum of weights */
1463: char filerespow[FILENAMELENGTH];
1464: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1465: FILE *ficresilk;
1466: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1467: FILE *ficresprobmorprev;
1468: FILE *fichtm, *fichtmcov; /* Html File */
1469: FILE *ficreseij;
1470: char filerese[FILENAMELENGTH];
1471: FILE *ficresstdeij;
1472: char fileresstde[FILENAMELENGTH];
1473: FILE *ficrescveij;
1474: char filerescve[FILENAMELENGTH];
1475: FILE *ficresvij;
1476: char fileresv[FILENAMELENGTH];
1.269 brouard 1477:
1.126 brouard 1478: char title[MAXLINE];
1.234 brouard 1479: char model[MAXLINE]; /**< The model line */
1.217 brouard 1480: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1481: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1482: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1483: char command[FILENAMELENGTH];
1484: int outcmd=0;
1485:
1.217 brouard 1486: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1487: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1488: char filelog[FILENAMELENGTH]; /* Log file */
1489: char filerest[FILENAMELENGTH];
1490: char fileregp[FILENAMELENGTH];
1491: char popfile[FILENAMELENGTH];
1492:
1493: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1494:
1.157 brouard 1495: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1496: /* struct timezone tzp; */
1497: /* extern int gettimeofday(); */
1498: struct tm tml, *gmtime(), *localtime();
1499:
1500: extern time_t time();
1501:
1502: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1503: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1504: time_t rlast_btime; /* raw time */
1.157 brouard 1505: struct tm tm;
1506:
1.126 brouard 1507: char strcurr[80], strfor[80];
1508:
1509: char *endptr;
1510: long lval;
1511: double dval;
1512:
1513: #define NR_END 1
1514: #define FREE_ARG char*
1515: #define FTOL 1.0e-10
1516:
1517: #define NRANSI
1.240 brouard 1518: #define ITMAX 200
1519: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1520:
1521: #define TOL 2.0e-4
1522:
1523: #define CGOLD 0.3819660
1524: #define ZEPS 1.0e-10
1525: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1526:
1527: #define GOLD 1.618034
1528: #define GLIMIT 100.0
1529: #define TINY 1.0e-20
1530:
1531: static double maxarg1,maxarg2;
1532: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1533: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1534:
1535: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1536: #define rint(a) floor(a+0.5)
1.166 brouard 1537: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1538: #define mytinydouble 1.0e-16
1.166 brouard 1539: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1540: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1541: /* static double dsqrarg; */
1542: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1543: static double sqrarg;
1544: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1545: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1546: int agegomp= AGEGOMP;
1547:
1548: int imx;
1549: int stepm=1;
1550: /* Stepm, step in month: minimum step interpolation*/
1551:
1552: int estepm;
1553: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1554:
1555: int m,nb;
1556: long *num;
1.197 brouard 1557: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1558: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1559: covariate for which somebody answered excluding
1560: undefined. Usually 2: 0 and 1. */
1561: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1562: covariate for which somebody answered including
1563: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1564: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1565: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1566: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1567: 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 1568: double *ageexmed,*agecens;
1569: double dateintmean=0;
1.296 brouard 1570: double anprojd, mprojd, jprojd; /* For eventual projections */
1571: double anprojf, mprojf, jprojf;
1.126 brouard 1572:
1.296 brouard 1573: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1574: double anbackf, mbackf, jbackf;
1575: double jintmean,mintmean,aintmean;
1.126 brouard 1576: double *weight;
1577: int **s; /* Status */
1.141 brouard 1578: double *agedc;
1.145 brouard 1579: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1580: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1581: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1582: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1583: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1584: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1585: double idx;
1586: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1587: /* Some documentation */
1588: /* Design original data
1589: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1590: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1591: * ntv=3 nqtv=1
1.330 brouard 1592: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1593: * For time varying covariate, quanti or dummies
1594: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1595: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1596: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1597: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1598: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1599: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1600: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1601: * k= 1 2 3 4 5 6 7 8 9 10 11
1602: */
1603: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1604: /* 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
1605: # States 1=Coresidence, 2 Living alone, 3 Institution
1606: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1607: */
1.349 brouard 1608: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1609: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1610: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1611: /* fixed or varying), 1 for age product, 2 for*/
1612: /* product without age, 3 for age and double product */
1613: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1614: /*(single or product without age), 2 dummy*/
1615: /* with age product, 3 quant with age product*/
1616: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1617: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1618: /*TnsdVar[Tvar] 1 2 3 */
1619: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1620: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1621: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1622: /* nsq 1 2 */ /* Counting single quantit tv */
1623: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1624: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1625: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1626: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1627: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1628: /* model="V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
1629: /* p Tvard[1][1]@21 = {6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0}*/
1.354 brouard 1630: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>} */
1.350 brouard 1631: /* p Tvardk[1][1]@24 = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0}*/
1632: /* p Tvardk[1][1]@22 = {0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0} */
1.349 brouard 1633: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1634: /* 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 1635: /* 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 1636: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1637: /* Type */
1638: /* V 1 2 3 4 5 */
1639: /* F F V V V */
1640: /* D Q D D Q */
1641: /* */
1642: int *TvarsD;
1.330 brouard 1643: int *TnsdVar;
1.234 brouard 1644: int *TvarsDind;
1645: int *TvarsQ;
1646: int *TvarsQind;
1647:
1.318 brouard 1648: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1649: int nresult=0;
1.258 brouard 1650: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1651: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1652: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1653: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1654: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1655: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1656: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1657: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1658: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1659: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1660: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1661:
1662: /* 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
1663: # States 1=Coresidence, 2 Living alone, 3 Institution
1664: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1665: */
1.234 brouard 1666: /* 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 1667: 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 */
1668: 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 */
1669: 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 */
1670: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1671: 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 */
1672: 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 1673: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1674: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1675: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1676: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1677: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1678: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1679: 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 */
1680: 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 1681: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1682: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1683: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1684: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1685: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1686: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1687: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1688: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1689: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1690: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1691: /* TvarVVind={2,5,5,6,6}, for V3 and then the product V1*V3 is decomposed into V1 and V3 and V1*V3*age into 6,6 */
1.230 brouard 1692: int *Tvarsel; /**< Selected covariates for output */
1693: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1694: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 age*Vn*Vm */
1.227 brouard 1695: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1696: 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 1697: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1698: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1699: int *Tage;
1.227 brouard 1700: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1701: 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 1702: 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*/
1703: 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 1704: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1705: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1706: int **Tvard;
1.330 brouard 1707: int **Tvardk;
1.227 brouard 1708: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1709: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1710: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1711: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1712: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1713: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1714: double *lsurv, *lpop, *tpop;
1715:
1.231 brouard 1716: #define FD 1; /* Fixed dummy covariate */
1717: #define FQ 2; /* Fixed quantitative covariate */
1718: #define FP 3; /* Fixed product covariate */
1719: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1720: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1721: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1722: #define VD 10; /* Varying dummy covariate */
1723: #define VQ 11; /* Varying quantitative covariate */
1724: #define VP 12; /* Varying product covariate */
1725: #define VPDD 13; /* Varying product dummy*dummy covariate */
1726: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1727: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1728: #define APFD 16; /* Age product * fixed dummy covariate */
1729: #define APFQ 17; /* Age product * fixed quantitative covariate */
1730: #define APVD 18; /* Age product * varying dummy covariate */
1731: #define APVQ 19; /* Age product * varying quantitative covariate */
1732:
1733: #define FTYPE 1; /* Fixed covariate */
1734: #define VTYPE 2; /* Varying covariate (loop in wave) */
1735: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1736:
1737: struct kmodel{
1738: int maintype; /* main type */
1739: int subtype; /* subtype */
1740: };
1741: struct kmodel modell[NCOVMAX];
1742:
1.143 brouard 1743: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1744: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1745:
1746: /**************** split *************************/
1747: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1748: {
1749: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1750: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1751: */
1752: char *ss; /* pointer */
1.186 brouard 1753: int l1=0, l2=0; /* length counters */
1.126 brouard 1754:
1755: l1 = strlen(path ); /* length of path */
1756: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1757: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1758: if ( ss == NULL ) { /* no directory, so determine current directory */
1759: strcpy( name, path ); /* we got the fullname name because no directory */
1760: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1761: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1762: /* get current working directory */
1763: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1764: #ifdef WIN32
1765: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1766: #else
1767: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1768: #endif
1.126 brouard 1769: return( GLOCK_ERROR_GETCWD );
1770: }
1771: /* got dirc from getcwd*/
1772: printf(" DIRC = %s \n",dirc);
1.205 brouard 1773: } else { /* strip directory from path */
1.126 brouard 1774: ss++; /* after this, the filename */
1775: l2 = strlen( ss ); /* length of filename */
1776: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1777: strcpy( name, ss ); /* save file name */
1778: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1779: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1780: printf(" DIRC2 = %s \n",dirc);
1781: }
1782: /* We add a separator at the end of dirc if not exists */
1783: l1 = strlen( dirc ); /* length of directory */
1784: if( dirc[l1-1] != DIRSEPARATOR ){
1785: dirc[l1] = DIRSEPARATOR;
1786: dirc[l1+1] = 0;
1787: printf(" DIRC3 = %s \n",dirc);
1788: }
1789: ss = strrchr( name, '.' ); /* find last / */
1790: if (ss >0){
1791: ss++;
1792: strcpy(ext,ss); /* save extension */
1793: l1= strlen( name);
1794: l2= strlen(ss)+1;
1795: strncpy( finame, name, l1-l2);
1796: finame[l1-l2]= 0;
1797: }
1798:
1799: return( 0 ); /* we're done */
1800: }
1801:
1802:
1803: /******************************************/
1804:
1805: void replace_back_to_slash(char *s, char*t)
1806: {
1807: int i;
1808: int lg=0;
1809: i=0;
1810: lg=strlen(t);
1811: for(i=0; i<= lg; i++) {
1812: (s[i] = t[i]);
1813: if (t[i]== '\\') s[i]='/';
1814: }
1815: }
1816:
1.132 brouard 1817: char *trimbb(char *out, char *in)
1.137 brouard 1818: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1819: char *s;
1820: s=out;
1821: while (*in != '\0'){
1.137 brouard 1822: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1823: in++;
1824: }
1825: *out++ = *in++;
1826: }
1827: *out='\0';
1828: return s;
1829: }
1830:
1.351 brouard 1831: char *trimbtab(char *out, char *in)
1832: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1833: char *s;
1834: s=out;
1835: while (*in != '\0'){
1836: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1837: in++;
1838: }
1839: *out++ = *in++;
1840: }
1841: *out='\0';
1842: return s;
1843: }
1844:
1.187 brouard 1845: /* char *substrchaine(char *out, char *in, char *chain) */
1846: /* { */
1847: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1848: /* char *s, *t; */
1849: /* t=in;s=out; */
1850: /* while ((*in != *chain) && (*in != '\0')){ */
1851: /* *out++ = *in++; */
1852: /* } */
1853:
1854: /* /\* *in matches *chain *\/ */
1855: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1856: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1857: /* } */
1858: /* in--; chain--; */
1859: /* while ( (*in != '\0')){ */
1860: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1861: /* *out++ = *in++; */
1862: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1863: /* } */
1864: /* *out='\0'; */
1865: /* out=s; */
1866: /* return out; */
1867: /* } */
1868: char *substrchaine(char *out, char *in, char *chain)
1869: {
1870: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1871: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1872:
1873: char *strloc;
1874:
1.349 brouard 1875: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1876: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1877: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out); /* strloc=+age*age+V2 chain="+age*age", out="V1+V1*age+age*age+V2" */
1.187 brouard 1878: if(strloc != NULL){
1.349 brouard 1879: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1880: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1); /* move number of bytes corresponding to the length of "+V2" which is 3, plus one is 4 (including the null)*/
1881: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1882: }
1.349 brouard 1883: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); /* strloc=+V2 chain="+age*age", in="V1+V1*age+age*age+V2", out="V1+V1*age+V2" */
1.187 brouard 1884: return out;
1885: }
1886:
1887:
1.145 brouard 1888: char *cutl(char *blocc, char *alocc, char *in, char occ)
1889: {
1.187 brouard 1890: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1891: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1892: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1893: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1894: */
1.160 brouard 1895: char *s, *t;
1.145 brouard 1896: t=in;s=in;
1897: while ((*in != occ) && (*in != '\0')){
1898: *alocc++ = *in++;
1899: }
1900: if( *in == occ){
1901: *(alocc)='\0';
1902: s=++in;
1903: }
1904:
1905: if (s == t) {/* occ not found */
1906: *(alocc-(in-s))='\0';
1907: in=s;
1908: }
1909: while ( *in != '\0'){
1910: *blocc++ = *in++;
1911: }
1912:
1913: *blocc='\0';
1914: return t;
1915: }
1.137 brouard 1916: char *cutv(char *blocc, char *alocc, char *in, char occ)
1917: {
1.187 brouard 1918: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1919: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1920: gives blocc="abcdef2ghi" and alocc="j".
1921: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1922: */
1923: char *s, *t;
1924: t=in;s=in;
1925: while (*in != '\0'){
1926: while( *in == occ){
1927: *blocc++ = *in++;
1928: s=in;
1929: }
1930: *blocc++ = *in++;
1931: }
1932: if (s == t) /* occ not found */
1933: *(blocc-(in-s))='\0';
1934: else
1935: *(blocc-(in-s)-1)='\0';
1936: in=s;
1937: while ( *in != '\0'){
1938: *alocc++ = *in++;
1939: }
1940:
1941: *alocc='\0';
1942: return s;
1943: }
1944:
1.126 brouard 1945: int nbocc(char *s, char occ)
1946: {
1947: int i,j=0;
1948: int lg=20;
1949: i=0;
1950: lg=strlen(s);
1951: for(i=0; i<= lg; i++) {
1.234 brouard 1952: if (s[i] == occ ) j++;
1.126 brouard 1953: }
1954: return j;
1955: }
1956:
1.349 brouard 1957: int nboccstr(char *textin, char *chain)
1958: {
1959: /* Counts the number of occurence of "chain" in string textin */
1960: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1961: char *strloc;
1962:
1963: int i,j=0;
1964:
1965: i=0;
1966:
1967: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1968: for(;;) {
1969: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1970: if(strloc != NULL){
1971: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1972: j++;
1973: }else
1974: break;
1975: }
1976: return j;
1977:
1978: }
1.137 brouard 1979: /* void cutv(char *u,char *v, char*t, char occ) */
1980: /* { */
1981: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1982: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1983: /* gives u="abcdef2ghi" and v="j" *\/ */
1984: /* int i,lg,j,p=0; */
1985: /* i=0; */
1986: /* lg=strlen(t); */
1987: /* for(j=0; j<=lg-1; j++) { */
1988: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1989: /* } */
1.126 brouard 1990:
1.137 brouard 1991: /* for(j=0; j<p; j++) { */
1992: /* (u[j] = t[j]); */
1993: /* } */
1994: /* u[p]='\0'; */
1.126 brouard 1995:
1.137 brouard 1996: /* for(j=0; j<= lg; j++) { */
1997: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1998: /* } */
1999: /* } */
1.126 brouard 2000:
1.160 brouard 2001: #ifdef _WIN32
2002: char * strsep(char **pp, const char *delim)
2003: {
2004: char *p, *q;
2005:
2006: if ((p = *pp) == NULL)
2007: return 0;
2008: if ((q = strpbrk (p, delim)) != NULL)
2009: {
2010: *pp = q + 1;
2011: *q = '\0';
2012: }
2013: else
2014: *pp = 0;
2015: return p;
2016: }
2017: #endif
2018:
1.126 brouard 2019: /********************** nrerror ********************/
2020:
2021: void nrerror(char error_text[])
2022: {
2023: fprintf(stderr,"ERREUR ...\n");
2024: fprintf(stderr,"%s\n",error_text);
2025: exit(EXIT_FAILURE);
2026: }
2027: /*********************** vector *******************/
2028: double *vector(int nl, int nh)
2029: {
2030: double *v;
2031: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2032: if (!v) nrerror("allocation failure in vector");
2033: return v-nl+NR_END;
2034: }
2035:
2036: /************************ free vector ******************/
2037: void free_vector(double*v, int nl, int nh)
2038: {
2039: free((FREE_ARG)(v+nl-NR_END));
2040: }
2041:
2042: /************************ivector *******************************/
2043: int *ivector(long nl,long nh)
2044: {
2045: int *v;
2046: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2047: if (!v) nrerror("allocation failure in ivector");
2048: return v-nl+NR_END;
2049: }
2050:
2051: /******************free ivector **************************/
2052: void free_ivector(int *v, long nl, long nh)
2053: {
2054: free((FREE_ARG)(v+nl-NR_END));
2055: }
2056:
2057: /************************lvector *******************************/
2058: long *lvector(long nl,long nh)
2059: {
2060: long *v;
2061: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2062: if (!v) nrerror("allocation failure in ivector");
2063: return v-nl+NR_END;
2064: }
2065:
2066: /******************free lvector **************************/
2067: void free_lvector(long *v, long nl, long nh)
2068: {
2069: free((FREE_ARG)(v+nl-NR_END));
2070: }
2071:
2072: /******************* imatrix *******************************/
2073: int **imatrix(long nrl, long nrh, long ncl, long nch)
2074: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2075: {
2076: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2077: int **m;
2078:
2079: /* allocate pointers to rows */
2080: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2081: if (!m) nrerror("allocation failure 1 in matrix()");
2082: m += NR_END;
2083: m -= nrl;
2084:
2085:
2086: /* allocate rows and set pointers to them */
2087: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2088: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2089: m[nrl] += NR_END;
2090: m[nrl] -= ncl;
2091:
2092: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2093:
2094: /* return pointer to array of pointers to rows */
2095: return m;
2096: }
2097:
2098: /****************** free_imatrix *************************/
2099: void free_imatrix(m,nrl,nrh,ncl,nch)
2100: int **m;
2101: long nch,ncl,nrh,nrl;
2102: /* free an int matrix allocated by imatrix() */
2103: {
2104: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2105: free((FREE_ARG) (m+nrl-NR_END));
2106: }
2107:
2108: /******************* matrix *******************************/
2109: double **matrix(long nrl, long nrh, long ncl, long nch)
2110: {
2111: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2112: double **m;
2113:
2114: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2115: if (!m) nrerror("allocation failure 1 in matrix()");
2116: m += NR_END;
2117: m -= nrl;
2118:
2119: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2120: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2121: m[nrl] += NR_END;
2122: m[nrl] -= ncl;
2123:
2124: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2125: return m;
1.145 brouard 2126: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2127: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2128: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2129: */
2130: }
2131:
2132: /*************************free matrix ************************/
2133: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2134: {
2135: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2136: free((FREE_ARG)(m+nrl-NR_END));
2137: }
2138:
2139: /******************* ma3x *******************************/
2140: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2141: {
2142: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2143: double ***m;
2144:
2145: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2146: if (!m) nrerror("allocation failure 1 in matrix()");
2147: m += NR_END;
2148: m -= nrl;
2149:
2150: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2151: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2152: m[nrl] += NR_END;
2153: m[nrl] -= ncl;
2154:
2155: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2156:
2157: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2158: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2159: m[nrl][ncl] += NR_END;
2160: m[nrl][ncl] -= nll;
2161: for (j=ncl+1; j<=nch; j++)
2162: m[nrl][j]=m[nrl][j-1]+nlay;
2163:
2164: for (i=nrl+1; i<=nrh; i++) {
2165: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2166: for (j=ncl+1; j<=nch; j++)
2167: m[i][j]=m[i][j-1]+nlay;
2168: }
2169: return m;
2170: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2171: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2172: */
2173: }
2174:
2175: /*************************free ma3x ************************/
2176: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2177: {
2178: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2179: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2180: free((FREE_ARG)(m+nrl-NR_END));
2181: }
2182:
2183: /*************** function subdirf ***********/
2184: char *subdirf(char fileres[])
2185: {
2186: /* Caution optionfilefiname is hidden */
2187: strcpy(tmpout,optionfilefiname);
2188: strcat(tmpout,"/"); /* Add to the right */
2189: strcat(tmpout,fileres);
2190: return tmpout;
2191: }
2192:
2193: /*************** function subdirf2 ***********/
2194: char *subdirf2(char fileres[], char *preop)
2195: {
1.314 brouard 2196: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2197: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2198: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2199: /* Caution optionfilefiname is hidden */
2200: strcpy(tmpout,optionfilefiname);
2201: strcat(tmpout,"/");
2202: strcat(tmpout,preop);
2203: strcat(tmpout,fileres);
2204: return tmpout;
2205: }
2206:
2207: /*************** function subdirf3 ***********/
2208: char *subdirf3(char fileres[], char *preop, char *preop2)
2209: {
2210:
2211: /* Caution optionfilefiname is hidden */
2212: strcpy(tmpout,optionfilefiname);
2213: strcat(tmpout,"/");
2214: strcat(tmpout,preop);
2215: strcat(tmpout,preop2);
2216: strcat(tmpout,fileres);
2217: return tmpout;
2218: }
1.213 brouard 2219:
2220: /*************** function subdirfext ***********/
2221: char *subdirfext(char fileres[], char *preop, char *postop)
2222: {
2223:
2224: strcpy(tmpout,preop);
2225: strcat(tmpout,fileres);
2226: strcat(tmpout,postop);
2227: return tmpout;
2228: }
1.126 brouard 2229:
1.213 brouard 2230: /*************** function subdirfext3 ***********/
2231: char *subdirfext3(char fileres[], char *preop, char *postop)
2232: {
2233:
2234: /* Caution optionfilefiname is hidden */
2235: strcpy(tmpout,optionfilefiname);
2236: strcat(tmpout,"/");
2237: strcat(tmpout,preop);
2238: strcat(tmpout,fileres);
2239: strcat(tmpout,postop);
2240: return tmpout;
2241: }
2242:
1.162 brouard 2243: char *asc_diff_time(long time_sec, char ascdiff[])
2244: {
2245: long sec_left, days, hours, minutes;
2246: days = (time_sec) / (60*60*24);
2247: sec_left = (time_sec) % (60*60*24);
2248: hours = (sec_left) / (60*60) ;
2249: sec_left = (sec_left) %(60*60);
2250: minutes = (sec_left) /60;
2251: sec_left = (sec_left) % (60);
2252: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2253: return ascdiff;
2254: }
2255:
1.126 brouard 2256: /***************** f1dim *************************/
2257: extern int ncom;
2258: extern double *pcom,*xicom;
2259: extern double (*nrfunc)(double []);
2260:
2261: double f1dim(double x)
2262: {
2263: int j;
2264: double f;
2265: double *xt;
2266:
2267: xt=vector(1,ncom);
2268: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2269: f=(*nrfunc)(xt);
2270: free_vector(xt,1,ncom);
2271: return f;
2272: }
2273:
2274: /*****************brent *************************/
2275: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2276: {
2277: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2278: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2279: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2280: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2281: * returned function value.
2282: */
1.126 brouard 2283: int iter;
2284: double a,b,d,etemp;
1.159 brouard 2285: double fu=0,fv,fw,fx;
1.164 brouard 2286: double ftemp=0.;
1.126 brouard 2287: double p,q,r,tol1,tol2,u,v,w,x,xm;
2288: double e=0.0;
2289:
2290: a=(ax < cx ? ax : cx);
2291: b=(ax > cx ? ax : cx);
2292: x=w=v=bx;
2293: fw=fv=fx=(*f)(x);
2294: for (iter=1;iter<=ITMAX;iter++) {
2295: xm=0.5*(a+b);
2296: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2297: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2298: printf(".");fflush(stdout);
2299: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2300: #ifdef DEBUGBRENT
1.126 brouard 2301: 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);
2302: 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);
2303: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2304: #endif
2305: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2306: *xmin=x;
2307: return fx;
2308: }
2309: ftemp=fu;
2310: if (fabs(e) > tol1) {
2311: r=(x-w)*(fx-fv);
2312: q=(x-v)*(fx-fw);
2313: p=(x-v)*q-(x-w)*r;
2314: q=2.0*(q-r);
2315: if (q > 0.0) p = -p;
2316: q=fabs(q);
2317: etemp=e;
2318: e=d;
2319: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2320: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2321: else {
1.224 brouard 2322: d=p/q;
2323: u=x+d;
2324: if (u-a < tol2 || b-u < tol2)
2325: d=SIGN(tol1,xm-x);
1.126 brouard 2326: }
2327: } else {
2328: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2329: }
2330: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2331: fu=(*f)(u);
2332: if (fu <= fx) {
2333: if (u >= x) a=x; else b=x;
2334: SHFT(v,w,x,u)
1.183 brouard 2335: SHFT(fv,fw,fx,fu)
2336: } else {
2337: if (u < x) a=u; else b=u;
2338: if (fu <= fw || w == x) {
1.224 brouard 2339: v=w;
2340: w=u;
2341: fv=fw;
2342: fw=fu;
1.183 brouard 2343: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2344: v=u;
2345: fv=fu;
1.183 brouard 2346: }
2347: }
1.126 brouard 2348: }
2349: nrerror("Too many iterations in brent");
2350: *xmin=x;
2351: return fx;
2352: }
2353:
2354: /****************** mnbrak ***********************/
2355:
2356: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2357: double (*func)(double))
1.183 brouard 2358: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2359: the downhill direction (defined by the function as evaluated at the initial points) and returns
2360: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2361: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2362: */
1.126 brouard 2363: double ulim,u,r,q, dum;
2364: double fu;
1.187 brouard 2365:
2366: double scale=10.;
2367: int iterscale=0;
2368:
2369: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2370: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2371:
2372:
2373: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2374: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2375: /* *bx = *ax - (*ax - *bx)/scale; */
2376: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2377: /* } */
2378:
1.126 brouard 2379: if (*fb > *fa) {
2380: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2381: SHFT(dum,*fb,*fa,dum)
2382: }
1.126 brouard 2383: *cx=(*bx)+GOLD*(*bx-*ax);
2384: *fc=(*func)(*cx);
1.183 brouard 2385: #ifdef DEBUG
1.224 brouard 2386: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2387: 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 2388: #endif
1.224 brouard 2389: 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 2390: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2391: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2392: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2393: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2394: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2395: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2396: fu=(*func)(u);
1.163 brouard 2397: #ifdef DEBUG
2398: /* f(x)=A(x-u)**2+f(u) */
2399: double A, fparabu;
2400: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2401: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2402: 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);
2403: 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 2404: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2405: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2406: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2407: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2408: #endif
1.184 brouard 2409: #ifdef MNBRAKORIGINAL
1.183 brouard 2410: #else
1.191 brouard 2411: /* if (fu > *fc) { */
2412: /* #ifdef DEBUG */
2413: /* printf("mnbrak4 fu > fc \n"); */
2414: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2415: /* #endif */
2416: /* /\* 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 *\\/ *\/ */
2417: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2418: /* dum=u; /\* Shifting c and u *\/ */
2419: /* u = *cx; */
2420: /* *cx = dum; */
2421: /* dum = fu; */
2422: /* fu = *fc; */
2423: /* *fc =dum; */
2424: /* } else { /\* end *\/ */
2425: /* #ifdef DEBUG */
2426: /* printf("mnbrak3 fu < fc \n"); */
2427: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2428: /* #endif */
2429: /* dum=u; /\* Shifting c and u *\/ */
2430: /* u = *cx; */
2431: /* *cx = dum; */
2432: /* dum = fu; */
2433: /* fu = *fc; */
2434: /* *fc =dum; */
2435: /* } */
1.224 brouard 2436: #ifdef DEBUGMNBRAK
2437: double A, fparabu;
2438: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2439: fparabu= *fa - A*(*ax-u)*(*ax-u);
2440: 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);
2441: 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 2442: #endif
1.191 brouard 2443: dum=u; /* Shifting c and u */
2444: u = *cx;
2445: *cx = dum;
2446: dum = fu;
2447: fu = *fc;
2448: *fc =dum;
1.183 brouard 2449: #endif
1.162 brouard 2450: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2451: #ifdef DEBUG
1.224 brouard 2452: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2453: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2454: #endif
1.126 brouard 2455: fu=(*func)(u);
2456: if (fu < *fc) {
1.183 brouard 2457: #ifdef DEBUG
1.224 brouard 2458: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2459: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2460: #endif
2461: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2462: SHFT(*fb,*fc,fu,(*func)(u))
2463: #ifdef DEBUG
2464: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2465: #endif
2466: }
1.162 brouard 2467: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2468: #ifdef DEBUG
1.224 brouard 2469: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2470: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2471: #endif
1.126 brouard 2472: u=ulim;
2473: fu=(*func)(u);
1.183 brouard 2474: } else { /* u could be left to b (if r > q parabola has a maximum) */
2475: #ifdef DEBUG
1.224 brouard 2476: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2477: 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 2478: #endif
1.126 brouard 2479: u=(*cx)+GOLD*(*cx-*bx);
2480: fu=(*func)(u);
1.224 brouard 2481: #ifdef DEBUG
2482: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2483: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2484: #endif
1.183 brouard 2485: } /* end tests */
1.126 brouard 2486: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2487: SHFT(*fa,*fb,*fc,fu)
2488: #ifdef DEBUG
1.224 brouard 2489: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2490: 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 2491: #endif
2492: } /* 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 2493: }
2494:
2495: /*************** linmin ************************/
1.162 brouard 2496: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2497: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2498: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2499: the value of func at the returned location p . This is actually all accomplished by calling the
2500: routines mnbrak and brent .*/
1.126 brouard 2501: int ncom;
2502: double *pcom,*xicom;
2503: double (*nrfunc)(double []);
2504:
1.224 brouard 2505: #ifdef LINMINORIGINAL
1.126 brouard 2506: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2507: #else
2508: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2509: #endif
1.126 brouard 2510: {
2511: double brent(double ax, double bx, double cx,
2512: double (*f)(double), double tol, double *xmin);
2513: double f1dim(double x);
2514: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2515: double *fc, double (*func)(double));
2516: int j;
2517: double xx,xmin,bx,ax;
2518: double fx,fb,fa;
1.187 brouard 2519:
1.203 brouard 2520: #ifdef LINMINORIGINAL
2521: #else
2522: double scale=10., axs, xxs; /* Scale added for infinity */
2523: #endif
2524:
1.126 brouard 2525: ncom=n;
2526: pcom=vector(1,n);
2527: xicom=vector(1,n);
2528: nrfunc=func;
2529: for (j=1;j<=n;j++) {
2530: pcom[j]=p[j];
1.202 brouard 2531: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2532: }
1.187 brouard 2533:
1.203 brouard 2534: #ifdef LINMINORIGINAL
2535: xx=1.;
2536: #else
2537: axs=0.0;
2538: xxs=1.;
2539: do{
2540: xx= xxs;
2541: #endif
1.187 brouard 2542: ax=0.;
2543: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2544: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2545: /* 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)) */
2546: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2547: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2548: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2549: /* 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 2550: #ifdef LINMINORIGINAL
2551: #else
2552: if (fx != fx){
1.224 brouard 2553: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2554: printf("|");
2555: fprintf(ficlog,"|");
1.203 brouard 2556: #ifdef DEBUGLINMIN
1.224 brouard 2557: 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 2558: #endif
2559: }
1.224 brouard 2560: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2561: #endif
2562:
1.191 brouard 2563: #ifdef DEBUGLINMIN
2564: 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 2565: 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 2566: #endif
1.224 brouard 2567: #ifdef LINMINORIGINAL
2568: #else
1.317 brouard 2569: if(fb == fx){ /* Flat function in the direction */
2570: xmin=xx;
1.224 brouard 2571: *flat=1;
1.317 brouard 2572: }else{
1.224 brouard 2573: *flat=0;
2574: #endif
2575: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2576: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2577: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2578: /* fmin = f(p[j] + xmin * xi[j]) */
2579: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2580: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2581: #ifdef DEBUG
1.224 brouard 2582: 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);
2583: 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);
2584: #endif
2585: #ifdef LINMINORIGINAL
2586: #else
2587: }
1.126 brouard 2588: #endif
1.191 brouard 2589: #ifdef DEBUGLINMIN
2590: printf("linmin end ");
1.202 brouard 2591: fprintf(ficlog,"linmin end ");
1.191 brouard 2592: #endif
1.126 brouard 2593: for (j=1;j<=n;j++) {
1.203 brouard 2594: #ifdef LINMINORIGINAL
2595: xi[j] *= xmin;
2596: #else
2597: #ifdef DEBUGLINMIN
2598: if(xxs <1.0)
2599: printf(" before xi[%d]=%12.8f", j,xi[j]);
2600: #endif
2601: 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) */
2602: #ifdef DEBUGLINMIN
2603: if(xxs <1.0)
2604: 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 );
2605: #endif
2606: #endif
1.187 brouard 2607: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2608: }
1.191 brouard 2609: #ifdef DEBUGLINMIN
1.203 brouard 2610: printf("\n");
1.191 brouard 2611: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2612: 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 2613: for (j=1;j<=n;j++) {
1.202 brouard 2614: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2615: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2616: if(j % ncovmodel == 0){
1.191 brouard 2617: printf("\n");
1.202 brouard 2618: fprintf(ficlog,"\n");
2619: }
1.191 brouard 2620: }
1.203 brouard 2621: #else
1.191 brouard 2622: #endif
1.126 brouard 2623: free_vector(xicom,1,n);
2624: free_vector(pcom,1,n);
2625: }
2626:
2627:
2628: /*************** powell ************************/
1.162 brouard 2629: /*
1.317 brouard 2630: Minimization of a function func of n variables. Input consists in an initial starting point
2631: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2632: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2633: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2634: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2635: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2636: */
1.224 brouard 2637: #ifdef LINMINORIGINAL
2638: #else
2639: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2640: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2641: #endif
1.126 brouard 2642: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2643: double (*func)(double []))
2644: {
1.224 brouard 2645: #ifdef LINMINORIGINAL
2646: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2647: double (*func)(double []));
1.224 brouard 2648: #else
1.241 brouard 2649: void linmin(double p[], double xi[], int n, double *fret,
2650: double (*func)(double []),int *flat);
1.224 brouard 2651: #endif
1.239 brouard 2652: int i,ibig,j,jk,k;
1.126 brouard 2653: double del,t,*pt,*ptt,*xit;
1.181 brouard 2654: double directest;
1.126 brouard 2655: double fp,fptt;
2656: double *xits;
2657: int niterf, itmp;
1.349 brouard 2658: int Bigter=0, nBigterf=1;
2659:
1.126 brouard 2660: pt=vector(1,n);
2661: ptt=vector(1,n);
2662: xit=vector(1,n);
2663: xits=vector(1,n);
2664: *fret=(*func)(p);
2665: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2666: rcurr_time = time(NULL);
2667: fp=(*fret); /* Initialisation */
1.126 brouard 2668: for (*iter=1;;++(*iter)) {
2669: ibig=0;
2670: del=0.0;
1.157 brouard 2671: rlast_time=rcurr_time;
1.349 brouard 2672: rlast_btime=rcurr_time;
1.157 brouard 2673: /* (void) gettimeofday(&curr_time,&tzp); */
2674: rcurr_time = time(NULL);
2675: curr_time = *localtime(&rcurr_time);
1.337 brouard 2676: /* 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); */
2677: /* fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); */
1.349 brouard 2678: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
2679: printf("\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2680: fprintf(ficlog,"\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2681: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2682: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2683: for (i=1;i<=n;i++) {
1.126 brouard 2684: fprintf(ficrespow," %.12lf", p[i]);
2685: }
1.239 brouard 2686: fprintf(ficrespow,"\n");fflush(ficrespow);
2687: printf("\n#model= 1 + age ");
2688: fprintf(ficlog,"\n#model= 1 + age ");
2689: if(nagesqr==1){
1.241 brouard 2690: printf(" + age*age ");
2691: fprintf(ficlog," + age*age ");
1.239 brouard 2692: }
2693: for(j=1;j <=ncovmodel-2;j++){
2694: if(Typevar[j]==0) {
2695: printf(" + V%d ",Tvar[j]);
2696: fprintf(ficlog," + V%d ",Tvar[j]);
2697: }else if(Typevar[j]==1) {
2698: printf(" + V%d*age ",Tvar[j]);
2699: fprintf(ficlog," + V%d*age ",Tvar[j]);
2700: }else if(Typevar[j]==2) {
2701: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2702: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 2703: }else if(Typevar[j]==3) {
2704: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2705: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2706: }
2707: }
1.126 brouard 2708: printf("\n");
1.239 brouard 2709: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2710: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2711: fprintf(ficlog,"\n");
1.239 brouard 2712: for(i=1,jk=1; i <=nlstate; i++){
2713: for(k=1; k <=(nlstate+ndeath); k++){
2714: if (k != i) {
2715: printf("%d%d ",i,k);
2716: fprintf(ficlog,"%d%d ",i,k);
2717: for(j=1; j <=ncovmodel; j++){
2718: printf("%12.7f ",p[jk]);
2719: fprintf(ficlog,"%12.7f ",p[jk]);
2720: jk++;
2721: }
2722: printf("\n");
2723: fprintf(ficlog,"\n");
2724: }
2725: }
2726: }
1.241 brouard 2727: if(*iter <=3 && *iter >1){
1.157 brouard 2728: tml = *localtime(&rcurr_time);
2729: strcpy(strcurr,asctime(&tml));
2730: rforecast_time=rcurr_time;
1.126 brouard 2731: itmp = strlen(strcurr);
2732: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2733: strcurr[itmp-1]='\0';
1.162 brouard 2734: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2735: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 2736: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
2737: niterf=nBigterf*ncovmodel;
2738: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2739: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2740: forecast_time = *localtime(&rforecast_time);
2741: strcpy(strfor,asctime(&forecast_time));
2742: itmp = strlen(strfor);
2743: if(strfor[itmp-1]=='\n')
2744: strfor[itmp-1]='\0';
1.349 brouard 2745: printf(" - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
2746: fprintf(ficlog," - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2747: }
2748: }
1.187 brouard 2749: for (i=1;i<=n;i++) { /* For each direction i */
2750: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2751: fptt=(*fret);
2752: #ifdef DEBUG
1.203 brouard 2753: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2754: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2755: #endif
1.203 brouard 2756: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2757: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2758: #ifdef LINMINORIGINAL
1.357 ! brouard 2759: linmin(p,xit,n,fret,func); /* New point i minimizing in direction i has coordinates p[j].*/
! 2760: /* xit[j] gives the n coordinates of direction i as input.*/
! 2761: /* *fret gives the maximum value on direction xit */
1.224 brouard 2762: #else
2763: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2764: flatdir[i]=flat; /* Function is vanishing in that direction i */
2765: #endif
2766: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2767: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2768: /* because that direction will be replaced unless the gain del is small */
2769: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2770: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2771: /* with the new direction. */
2772: del=fabs(fptt-(*fret));
2773: ibig=i;
1.126 brouard 2774: }
2775: #ifdef DEBUG
2776: printf("%d %.12e",i,(*fret));
2777: fprintf(ficlog,"%d %.12e",i,(*fret));
2778: for (j=1;j<=n;j++) {
1.224 brouard 2779: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2780: printf(" x(%d)=%.12e",j,xit[j]);
2781: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2782: }
2783: for(j=1;j<=n;j++) {
1.225 brouard 2784: printf(" p(%d)=%.12e",j,p[j]);
2785: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2786: }
2787: printf("\n");
2788: fprintf(ficlog,"\n");
2789: #endif
1.187 brouard 2790: } /* end loop on each direction i */
1.357 ! brouard 2791: /* Convergence test will use last linmin estimation (fret) and compare to former iteration (fp) */
1.188 brouard 2792: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.319 brouard 2793: for(j=1;j<=n;j++) {
2794: if(flatdir[j] >0){
2795: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2796: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2797: }
1.319 brouard 2798: /* printf("\n"); */
2799: /* fprintf(ficlog,"\n"); */
2800: }
1.243 brouard 2801: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2802: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2803: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2804: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2805: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2806: /* decreased of more than 3.84 */
2807: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2808: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2809: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2810:
1.188 brouard 2811: /* Starting the program with initial values given by a former maximization will simply change */
2812: /* the scales of the directions and the directions, because the are reset to canonical directions */
2813: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2814: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2815: #ifdef DEBUG
2816: int k[2],l;
2817: k[0]=1;
2818: k[1]=-1;
2819: printf("Max: %.12e",(*func)(p));
2820: fprintf(ficlog,"Max: %.12e",(*func)(p));
2821: for (j=1;j<=n;j++) {
2822: printf(" %.12e",p[j]);
2823: fprintf(ficlog," %.12e",p[j]);
2824: }
2825: printf("\n");
2826: fprintf(ficlog,"\n");
2827: for(l=0;l<=1;l++) {
2828: for (j=1;j<=n;j++) {
2829: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2830: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2831: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2832: }
2833: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2834: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2835: }
2836: #endif
2837:
2838: free_vector(xit,1,n);
2839: free_vector(xits,1,n);
2840: free_vector(ptt,1,n);
2841: free_vector(pt,1,n);
2842: return;
1.192 brouard 2843: } /* enough precision */
1.240 brouard 2844: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2845: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2846: ptt[j]=2.0*p[j]-pt[j];
2847: xit[j]=p[j]-pt[j];
2848: pt[j]=p[j];
2849: }
1.181 brouard 2850: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2851: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2852: if (*iter <=4) {
1.225 brouard 2853: #else
2854: #endif
1.224 brouard 2855: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2856: #else
1.161 brouard 2857: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2858: #endif
1.162 brouard 2859: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2860: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2861: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2862: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2863: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2864: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2865: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2866: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2867: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2868: /* Even if f3 <f1, directest can be negative and t >0 */
2869: /* mu² and del² are equal when f3=f1 */
2870: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2871: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2872: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2873: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2874: #ifdef NRCORIGINAL
2875: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2876: #else
2877: 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 2878: t= t- del*SQR(fp-fptt);
1.183 brouard 2879: #endif
1.202 brouard 2880: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2881: #ifdef DEBUG
1.181 brouard 2882: 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);
2883: 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 2884: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2885: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2886: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2887: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2888: 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);
2889: 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);
2890: #endif
1.183 brouard 2891: #ifdef POWELLORIGINAL
2892: if (t < 0.0) { /* Then we use it for new direction */
2893: #else
1.182 brouard 2894: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2895: 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 2896: 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 2897: 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 2898: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2899: }
1.181 brouard 2900: if (directest < 0.0) { /* Then we use it for new direction */
2901: #endif
1.191 brouard 2902: #ifdef DEBUGLINMIN
1.234 brouard 2903: printf("Before linmin in direction P%d-P0\n",n);
2904: for (j=1;j<=n;j++) {
2905: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2906: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2907: if(j % ncovmodel == 0){
2908: printf("\n");
2909: fprintf(ficlog,"\n");
2910: }
2911: }
1.224 brouard 2912: #endif
2913: #ifdef LINMINORIGINAL
1.234 brouard 2914: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2915: #else
1.234 brouard 2916: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2917: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2918: #endif
1.234 brouard 2919:
1.191 brouard 2920: #ifdef DEBUGLINMIN
1.234 brouard 2921: for (j=1;j<=n;j++) {
2922: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2923: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2924: if(j % ncovmodel == 0){
2925: printf("\n");
2926: fprintf(ficlog,"\n");
2927: }
2928: }
1.224 brouard 2929: #endif
1.357 ! brouard 2930: #ifdef POWELLORIGINCONJUGATE
1.234 brouard 2931: for (j=1;j<=n;j++) {
2932: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2933: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2934: }
1.357 ! brouard 2935: #else
! 2936: for (j=1;j<=n-1;j++) {
! 2937: xi[j][1]=xi[j][j+1]; /* Standard method of conjugate directions */
! 2938: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
! 2939: }
! 2940: #endif
1.224 brouard 2941: #ifdef LINMINORIGINAL
2942: #else
1.234 brouard 2943: for (j=1, flatd=0;j<=n;j++) {
2944: if(flatdir[j]>0)
2945: flatd++;
2946: }
2947: if(flatd >0){
1.255 brouard 2948: printf("%d flat directions: ",flatd);
2949: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2950: for (j=1;j<=n;j++) {
2951: if(flatdir[j]>0){
2952: printf("%d ",j);
2953: fprintf(ficlog,"%d ",j);
2954: }
2955: }
2956: printf("\n");
2957: fprintf(ficlog,"\n");
1.319 brouard 2958: #ifdef FLATSUP
2959: free_vector(xit,1,n);
2960: free_vector(xits,1,n);
2961: free_vector(ptt,1,n);
2962: free_vector(pt,1,n);
2963: return;
2964: #endif
1.234 brouard 2965: }
1.191 brouard 2966: #endif
1.234 brouard 2967: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2968: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
1.357 ! brouard 2969: /* The minimization in direction $\xi_1$ gives $P_1$. From $P_1$ minimization in direction $\xi_2$ gives */
! 2970: /* $P_2$. Minimization of line $P_2-P_1$ gives new starting point $P^{(1)}_0$ and direction $\xi_1$ is dropped and replaced by second */
! 2971: /* direction $\xi_1^{(1)}=\xi_2$. Also second direction is replaced by new direction $\xi^{(1)}_2=P_2-P_0$. */
! 2972:
! 2973: /* At the second iteration, starting from $P_0^{(1)}$, minimization amongst $\xi^{(1)}_1$ gives point $P^{(1)}_1$. */
! 2974: /* Minimization amongst $\xi^{(1)}_2=(P_2-P_0)$ gives point $P^{(1)}_2$. As $P^{(2)}_1$ and */
! 2975: /* $P^{(1)}_0$ are minimizing in the same direction $P^{(1)}_2 - P^{(1)}_1= P_2-P_0$, directions $P^{(1)}_2-P^{(1)}_0$ */
! 2976: /* and $P_2-P_0$ (parallel to $\xi$ and $\xi^c$) are conjugate. } */
! 2977:
1.234 brouard 2978:
1.126 brouard 2979: #ifdef DEBUG
1.234 brouard 2980: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2981: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2982: for(j=1;j<=n;j++){
2983: printf(" %lf",xit[j]);
2984: fprintf(ficlog," %lf",xit[j]);
2985: }
2986: printf("\n");
2987: fprintf(ficlog,"\n");
1.126 brouard 2988: #endif
1.192 brouard 2989: } /* end of t or directest negative */
1.224 brouard 2990: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2991: #else
1.234 brouard 2992: } /* end if (fptt < fp) */
1.192 brouard 2993: #endif
1.225 brouard 2994: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2995: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2996: #else
1.224 brouard 2997: #endif
1.234 brouard 2998: } /* loop iteration */
1.126 brouard 2999: }
1.234 brouard 3000:
1.126 brouard 3001: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 3002:
1.235 brouard 3003: 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 3004: {
1.338 brouard 3005: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 3006: * (and selected quantitative values in nres)
3007: * by left multiplying the unit
3008: * matrix by transitions matrix until convergence is reached with precision ftolpl
3009: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
3010: * Wx is row vector: population in state 1, population in state 2, population dead
3011: * or prevalence in state 1, prevalence in state 2, 0
3012: * newm is the matrix after multiplications, its rows are identical at a factor.
3013: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
3014: * Output is prlim.
3015: * Initial matrix pimij
3016: */
1.206 brouard 3017: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3018: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3019: /* 0, 0 , 1} */
3020: /*
3021: * and after some iteration: */
3022: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3023: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3024: /* 0, 0 , 1} */
3025: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3026: /* {0.51571254859325999, 0.4842874514067399, */
3027: /* 0.51326036147820708, 0.48673963852179264} */
3028: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 3029:
1.332 brouard 3030: int i, ii,j,k, k1;
1.209 brouard 3031: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 3032: /* double **matprod2(); */ /* test */
1.218 brouard 3033: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 3034: double **newm;
1.209 brouard 3035: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 3036: int ncvloop=0;
1.288 brouard 3037: int first=0;
1.169 brouard 3038:
1.209 brouard 3039: min=vector(1,nlstate);
3040: max=vector(1,nlstate);
3041: meandiff=vector(1,nlstate);
3042:
1.218 brouard 3043: /* Starting with matrix unity */
1.126 brouard 3044: for (ii=1;ii<=nlstate+ndeath;ii++)
3045: for (j=1;j<=nlstate+ndeath;j++){
3046: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3047: }
1.169 brouard 3048:
3049: cov[1]=1.;
3050:
3051: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 3052: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 3053: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 3054: ncvloop++;
1.126 brouard 3055: newm=savm;
3056: /* Covariates have to be included here again */
1.138 brouard 3057: cov[2]=agefin;
1.319 brouard 3058: if(nagesqr==1){
3059: cov[3]= agefin*agefin;
3060: }
1.332 brouard 3061: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3062: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3063: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3064: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3065: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3066: }else{
3067: cov[2+nagesqr+k1]=precov[nres][k1];
3068: }
3069: }/* End of loop on model equation */
3070:
3071: /* Start of old code (replaced by a loop on position in the model equation */
3072: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3073: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3074: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3075: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3076: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3077: /* * k 1 2 3 4 5 6 7 8 */
3078: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3079: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3080: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3081: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3082: /* *nsd=3 (1) (2) (3) */
3083: /* *TvarsD[nsd] [1]=2 1 3 */
3084: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3085: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3086: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3087: /* *Tvard[] [1][1]=1 [2][1]=1 */
3088: /* * [1][2]=3 [2][2]=2 */
3089: /* *Tprod[](=k) [1]=1 [2]=8 */
3090: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3091: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3092: /* *TvarsDpType */
3093: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3094: /* * nsd=1 (1) (2) */
3095: /* *TvarsD[nsd] 3 2 */
3096: /* *TnsdVar (3)=1 (2)=2 */
3097: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3098: /* *Tage[] [1]=2 [2]= 3 */
3099: /* *\/ */
3100: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3101: /* /\* 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)); *\/ */
3102: /* } */
3103: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3104: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3105: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3106: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3107: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3108: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3109: /* /\* 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]); *\/ */
3110: /* } */
3111: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3112: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3113: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3114: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3115: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3116: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3117: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3118: /* } */
3119: /* /\* 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]); *\/ */
3120: /* } */
3121: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3122: /* /\* 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]); *\/ */
3123: /* if(Dummy[Tvard[k][1]]==0){ */
3124: /* if(Dummy[Tvard[k][2]]==0){ */
3125: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3126: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3127: /* }else{ */
3128: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3129: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3130: /* } */
3131: /* }else{ */
3132: /* if(Dummy[Tvard[k][2]]==0){ */
3133: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3134: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3135: /* }else{ */
3136: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3137: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3138: /* } */
3139: /* } */
3140: /* } /\* End product without age *\/ */
3141: /* ENd of old code */
1.138 brouard 3142: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3143: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3144: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3145: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3146: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3147: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3148: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3149:
1.126 brouard 3150: savm=oldm;
3151: oldm=newm;
1.209 brouard 3152:
3153: for(j=1; j<=nlstate; j++){
3154: max[j]=0.;
3155: min[j]=1.;
3156: }
3157: for(i=1;i<=nlstate;i++){
3158: sumnew=0;
3159: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3160: for(j=1; j<=nlstate; j++){
3161: prlim[i][j]= newm[i][j]/(1-sumnew);
3162: max[j]=FMAX(max[j],prlim[i][j]);
3163: min[j]=FMIN(min[j],prlim[i][j]);
3164: }
3165: }
3166:
1.126 brouard 3167: maxmax=0.;
1.209 brouard 3168: for(j=1; j<=nlstate; j++){
3169: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3170: maxmax=FMAX(maxmax,meandiff[j]);
3171: /* 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 3172: } /* j loop */
1.203 brouard 3173: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3174: /* 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 3175: if(maxmax < ftolpl){
1.209 brouard 3176: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3177: free_vector(min,1,nlstate);
3178: free_vector(max,1,nlstate);
3179: free_vector(meandiff,1,nlstate);
1.126 brouard 3180: return prlim;
3181: }
1.288 brouard 3182: } /* agefin loop */
1.208 brouard 3183: /* After some age loop it doesn't converge */
1.288 brouard 3184: if(!first){
3185: first=1;
3186: 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 3187: 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);
3188: }else if (first >=1 && first <10){
3189: 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);
3190: first++;
3191: }else if (first ==10){
3192: 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);
3193: 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");
3194: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3195: first++;
1.288 brouard 3196: }
3197:
1.209 brouard 3198: /* 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); */
3199: free_vector(min,1,nlstate);
3200: free_vector(max,1,nlstate);
3201: free_vector(meandiff,1,nlstate);
1.208 brouard 3202:
1.169 brouard 3203: return prlim; /* should not reach here */
1.126 brouard 3204: }
3205:
1.217 brouard 3206:
3207: /**** Back Prevalence limit (stable or period prevalence) ****************/
3208:
1.218 brouard 3209: /* 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) */
3210: /* 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 3211: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3212: {
1.264 brouard 3213: /* 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 3214: matrix by transitions matrix until convergence is reached with precision ftolpl */
3215: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3216: /* Wx is row vector: population in state 1, population in state 2, population dead */
3217: /* or prevalence in state 1, prevalence in state 2, 0 */
3218: /* newm is the matrix after multiplications, its rows are identical at a factor */
3219: /* Initial matrix pimij */
3220: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3221: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3222: /* 0, 0 , 1} */
3223: /*
3224: * and after some iteration: */
3225: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3226: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3227: /* 0, 0 , 1} */
3228: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3229: /* {0.51571254859325999, 0.4842874514067399, */
3230: /* 0.51326036147820708, 0.48673963852179264} */
3231: /* If we start from prlim again, prlim tends to a constant matrix */
3232:
1.332 brouard 3233: int i, ii,j,k, k1;
1.247 brouard 3234: int first=0;
1.217 brouard 3235: double *min, *max, *meandiff, maxmax,sumnew=0.;
3236: /* double **matprod2(); */ /* test */
3237: double **out, cov[NCOVMAX+1], **bmij();
3238: double **newm;
1.218 brouard 3239: double **dnewm, **doldm, **dsavm; /* for use */
3240: double **oldm, **savm; /* for use */
3241:
1.217 brouard 3242: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3243: int ncvloop=0;
3244:
3245: min=vector(1,nlstate);
3246: max=vector(1,nlstate);
3247: meandiff=vector(1,nlstate);
3248:
1.266 brouard 3249: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3250: oldm=oldms; savm=savms;
3251:
3252: /* Starting with matrix unity */
3253: for (ii=1;ii<=nlstate+ndeath;ii++)
3254: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3255: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3256: }
3257:
3258: cov[1]=1.;
3259:
3260: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3261: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3262: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3263: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3264: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3265: ncvloop++;
1.218 brouard 3266: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3267: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3268: /* Covariates have to be included here again */
3269: cov[2]=agefin;
1.319 brouard 3270: if(nagesqr==1){
1.217 brouard 3271: cov[3]= agefin*agefin;;
1.319 brouard 3272: }
1.332 brouard 3273: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3274: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3275: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3276: }else{
1.332 brouard 3277: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3278: }
1.332 brouard 3279: }/* End of loop on model equation */
3280:
3281: /* Old code */
3282:
3283: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3284: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3285: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3286: /* /\* 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)); *\/ */
3287: /* } */
3288: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3289: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3290: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3291: /* /\* /\\* 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])]); *\\/ *\/ */
3292: /* /\* } *\/ */
3293: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3294: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3295: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3296: /* /\* 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]); *\/ */
3297: /* } */
3298: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3299: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3300: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3301: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3302: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3303: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3304: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3305: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3306: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3307: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3308: /* } */
3309: /* /\* 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]); *\/ */
3310: /* } */
3311: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3312: /* /\* 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]); *\/ */
3313: /* if(Dummy[Tvard[k][1]]==0){ */
3314: /* if(Dummy[Tvard[k][2]]==0){ */
3315: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3316: /* }else{ */
3317: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3318: /* } */
3319: /* }else{ */
3320: /* if(Dummy[Tvard[k][2]]==0){ */
3321: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3322: /* }else{ */
3323: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3324: /* } */
3325: /* } */
3326: /* } */
1.217 brouard 3327:
3328: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3329: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3330: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3331: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3332: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3333: /* ij should be linked to the correct index of cov */
3334: /* age and covariate values ij are in 'cov', but we need to pass
3335: * ij for the observed prevalence at age and status and covariate
3336: * number: prevacurrent[(int)agefin][ii][ij]
3337: */
3338: /* 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 *\/ */
3339: /* 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 *\/ */
3340: 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 3341: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3342: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3343: /* for(i=1; i<=nlstate+ndeath; i++) { */
3344: /* printf("%d newm= ",i); */
3345: /* for(j=1;j<=nlstate+ndeath;j++) { */
3346: /* printf("%f ",newm[i][j]); */
3347: /* } */
3348: /* printf("oldm * "); */
3349: /* for(j=1;j<=nlstate+ndeath;j++) { */
3350: /* printf("%f ",oldm[i][j]); */
3351: /* } */
1.268 brouard 3352: /* printf(" bmmij "); */
1.266 brouard 3353: /* for(j=1;j<=nlstate+ndeath;j++) { */
3354: /* printf("%f ",pmmij[i][j]); */
3355: /* } */
3356: /* printf("\n"); */
3357: /* } */
3358: /* } */
1.217 brouard 3359: savm=oldm;
3360: oldm=newm;
1.266 brouard 3361:
1.217 brouard 3362: for(j=1; j<=nlstate; j++){
3363: max[j]=0.;
3364: min[j]=1.;
3365: }
3366: for(j=1; j<=nlstate; j++){
3367: for(i=1;i<=nlstate;i++){
1.234 brouard 3368: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3369: bprlim[i][j]= newm[i][j];
3370: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3371: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3372: }
3373: }
1.218 brouard 3374:
1.217 brouard 3375: maxmax=0.;
3376: for(i=1; i<=nlstate; i++){
1.318 brouard 3377: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3378: maxmax=FMAX(maxmax,meandiff[i]);
3379: /* 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 3380: } /* i loop */
1.217 brouard 3381: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3382: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3383: if(maxmax < ftolpl){
1.220 brouard 3384: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3385: free_vector(min,1,nlstate);
3386: free_vector(max,1,nlstate);
3387: free_vector(meandiff,1,nlstate);
3388: return bprlim;
3389: }
1.288 brouard 3390: } /* agefin loop */
1.217 brouard 3391: /* After some age loop it doesn't converge */
1.288 brouard 3392: if(!first){
1.247 brouard 3393: first=1;
3394: 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\
3395: 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);
3396: }
3397: 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 3398: 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);
3399: /* 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); */
3400: free_vector(min,1,nlstate);
3401: free_vector(max,1,nlstate);
3402: free_vector(meandiff,1,nlstate);
3403:
3404: return bprlim; /* should not reach here */
3405: }
3406:
1.126 brouard 3407: /*************** transition probabilities ***************/
3408:
3409: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3410: {
1.138 brouard 3411: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3412: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3413: model to the ncovmodel covariates (including constant and age).
3414: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3415: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3416: ncth covariate in the global vector x is given by the formula:
3417: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3418: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3419: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3420: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3421: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3422: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3423: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3424: */
3425: double s1, lnpijopii;
1.126 brouard 3426: /*double t34;*/
1.164 brouard 3427: int i,j, nc, ii, jj;
1.126 brouard 3428:
1.223 brouard 3429: for(i=1; i<= nlstate; i++){
3430: for(j=1; j<i;j++){
3431: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3432: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3433: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3434: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3435: }
3436: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3437: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3438: }
3439: for(j=i+1; j<=nlstate+ndeath;j++){
3440: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3441: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3442: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3443: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3444: }
3445: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3446: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3447: }
3448: }
1.218 brouard 3449:
1.223 brouard 3450: for(i=1; i<= nlstate; i++){
3451: s1=0;
3452: for(j=1; j<i; j++){
1.339 brouard 3453: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3454: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3455: }
3456: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3457: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3458: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3459: }
3460: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3461: ps[i][i]=1./(s1+1.);
3462: /* Computing other pijs */
3463: for(j=1; j<i; j++)
1.325 brouard 3464: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3465: for(j=i+1; j<=nlstate+ndeath; j++)
3466: ps[i][j]= exp(ps[i][j])*ps[i][i];
3467: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3468: } /* end i */
1.218 brouard 3469:
1.223 brouard 3470: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3471: for(jj=1; jj<= nlstate+ndeath; jj++){
3472: ps[ii][jj]=0;
3473: ps[ii][ii]=1;
3474: }
3475: }
1.294 brouard 3476:
3477:
1.223 brouard 3478: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3479: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3480: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3481: /* } */
3482: /* printf("\n "); */
3483: /* } */
3484: /* printf("\n ");printf("%lf ",cov[2]);*/
3485: /*
3486: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3487: goto end;*/
1.266 brouard 3488: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3489: }
3490:
1.218 brouard 3491: /*************** backward transition probabilities ***************/
3492:
3493: /* 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 ) */
3494: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3495: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3496: {
1.302 brouard 3497: /* 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 3498: * 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 3499: */
1.218 brouard 3500: int i, ii, j,k;
1.222 brouard 3501:
3502: double **out, **pmij();
3503: double sumnew=0.;
1.218 brouard 3504: double agefin;
1.292 brouard 3505: 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 3506: double **dnewm, **dsavm, **doldm;
3507: double **bbmij;
3508:
1.218 brouard 3509: doldm=ddoldms; /* global pointers */
1.222 brouard 3510: dnewm=ddnewms;
3511: dsavm=ddsavms;
1.318 brouard 3512:
3513: /* Debug */
3514: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3515: agefin=cov[2];
1.268 brouard 3516: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3517: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3518: the observed prevalence (with this covariate ij) at beginning of transition */
3519: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3520:
3521: /* P_x */
1.325 brouard 3522: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3523: /* outputs pmmij which is a stochastic matrix in row */
3524:
3525: /* Diag(w_x) */
1.292 brouard 3526: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3527: sumnew=0.;
1.269 brouard 3528: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3529: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3530: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3531: sumnew+=prevacurrent[(int)agefin][ii][ij];
3532: }
3533: if(sumnew >0.01){ /* At least some value in the prevalence */
3534: for (ii=1;ii<=nlstate+ndeath;ii++){
3535: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3536: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3537: }
3538: }else{
3539: for (ii=1;ii<=nlstate+ndeath;ii++){
3540: for (j=1;j<=nlstate+ndeath;j++)
3541: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3542: }
3543: /* if(sumnew <0.9){ */
3544: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3545: /* } */
3546: }
3547: k3=0.0; /* We put the last diagonal to 0 */
3548: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3549: doldm[ii][ii]= k3;
3550: }
3551: /* End doldm, At the end doldm is diag[(w_i)] */
3552:
1.292 brouard 3553: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3554: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3555:
1.292 brouard 3556: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3557: /* 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 3558: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3559: sumnew=0.;
1.222 brouard 3560: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3561: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3562: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3563: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3564: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3565: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3566: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3567: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3568: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3569: /* }else */
1.268 brouard 3570: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3571: } /*End ii */
3572: } /* 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 */
3573:
1.292 brouard 3574: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3575: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3576: /* end bmij */
1.266 brouard 3577: return ps; /*pointer is unchanged */
1.218 brouard 3578: }
1.217 brouard 3579: /*************** transition probabilities ***************/
3580:
1.218 brouard 3581: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3582: {
3583: /* According to parameters values stored in x and the covariate's values stored in cov,
3584: computes the probability to be observed in state j being in state i by appying the
3585: model to the ncovmodel covariates (including constant and age).
3586: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3587: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3588: ncth covariate in the global vector x is given by the formula:
3589: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3590: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3591: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3592: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3593: Outputs ps[i][j] the probability to be observed in j being in j according to
3594: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3595: */
3596: double s1, lnpijopii;
3597: /*double t34;*/
3598: int i,j, nc, ii, jj;
3599:
1.234 brouard 3600: for(i=1; i<= nlstate; i++){
3601: for(j=1; j<i;j++){
3602: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3603: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3604: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3605: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3606: }
3607: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3608: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3609: }
3610: for(j=i+1; j<=nlstate+ndeath;j++){
3611: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3612: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3613: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3614: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3615: }
3616: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3617: }
3618: }
3619:
3620: for(i=1; i<= nlstate; i++){
3621: s1=0;
3622: for(j=1; j<i; j++){
3623: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3624: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3625: }
3626: for(j=i+1; j<=nlstate+ndeath; j++){
3627: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3628: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3629: }
3630: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3631: ps[i][i]=1./(s1+1.);
3632: /* Computing other pijs */
3633: for(j=1; j<i; j++)
3634: ps[i][j]= exp(ps[i][j])*ps[i][i];
3635: for(j=i+1; j<=nlstate+ndeath; j++)
3636: ps[i][j]= exp(ps[i][j])*ps[i][i];
3637: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3638: } /* end i */
3639:
3640: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3641: for(jj=1; jj<= nlstate+ndeath; jj++){
3642: ps[ii][jj]=0;
3643: ps[ii][ii]=1;
3644: }
3645: }
1.296 brouard 3646: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3647: for(jj=1; jj<= nlstate+ndeath; jj++){
3648: s1=0.;
3649: for(ii=1; ii<= nlstate+ndeath; ii++){
3650: s1+=ps[ii][jj];
3651: }
3652: for(ii=1; ii<= nlstate; ii++){
3653: ps[ii][jj]=ps[ii][jj]/s1;
3654: }
3655: }
3656: /* Transposition */
3657: for(jj=1; jj<= nlstate+ndeath; jj++){
3658: for(ii=jj; ii<= nlstate+ndeath; ii++){
3659: s1=ps[ii][jj];
3660: ps[ii][jj]=ps[jj][ii];
3661: ps[jj][ii]=s1;
3662: }
3663: }
3664: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3665: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3666: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3667: /* } */
3668: /* printf("\n "); */
3669: /* } */
3670: /* printf("\n ");printf("%lf ",cov[2]);*/
3671: /*
3672: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3673: goto end;*/
3674: return ps;
1.217 brouard 3675: }
3676:
3677:
1.126 brouard 3678: /**************** Product of 2 matrices ******************/
3679:
1.145 brouard 3680: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3681: {
3682: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3683: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3684: /* in, b, out are matrice of pointers which should have been initialized
3685: before: only the contents of out is modified. The function returns
3686: a pointer to pointers identical to out */
1.145 brouard 3687: int i, j, k;
1.126 brouard 3688: for(i=nrl; i<= nrh; i++)
1.145 brouard 3689: for(k=ncolol; k<=ncoloh; k++){
3690: out[i][k]=0.;
3691: for(j=ncl; j<=nch; j++)
3692: out[i][k] +=in[i][j]*b[j][k];
3693: }
1.126 brouard 3694: return out;
3695: }
3696:
3697:
3698: /************* Higher Matrix Product ***************/
3699:
1.235 brouard 3700: 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 3701: {
1.336 brouard 3702: /* Already optimized with precov.
3703: 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 3704: 'nhstepm*hstepm*stepm' months (i.e. until
3705: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3706: nhstepm*hstepm matrices.
3707: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3708: (typically every 2 years instead of every month which is too big
3709: for the memory).
3710: Model is determined by parameters x and covariates have to be
3711: included manually here.
3712:
3713: */
3714:
1.330 brouard 3715: int i, j, d, h, k, k1;
1.131 brouard 3716: double **out, cov[NCOVMAX+1];
1.126 brouard 3717: double **newm;
1.187 brouard 3718: double agexact;
1.214 brouard 3719: double agebegin, ageend;
1.126 brouard 3720:
3721: /* Hstepm could be zero and should return the unit matrix */
3722: for (i=1;i<=nlstate+ndeath;i++)
3723: for (j=1;j<=nlstate+ndeath;j++){
3724: oldm[i][j]=(i==j ? 1.0 : 0.0);
3725: po[i][j][0]=(i==j ? 1.0 : 0.0);
3726: }
3727: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3728: for(h=1; h <=nhstepm; h++){
3729: for(d=1; d <=hstepm; d++){
3730: newm=savm;
3731: /* Covariates have to be included here again */
3732: cov[1]=1.;
1.214 brouard 3733: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3734: cov[2]=agexact;
1.319 brouard 3735: if(nagesqr==1){
1.227 brouard 3736: cov[3]= agexact*agexact;
1.319 brouard 3737: }
1.330 brouard 3738: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3739: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3740: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3741: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3742: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3743: }else{
3744: cov[2+nagesqr+k1]=precov[nres][k1];
3745: }
3746: }/* End of loop on model equation */
3747: /* Old code */
3748: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3749: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3750: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3751: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3752: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3753: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3754: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3755: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3756: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3757: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3758: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3759: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3760: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3761: /* /\* 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]])); *\/ */
3762: /* 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); */
3763: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3764: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3765: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3766: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3767: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3768: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3769: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3770: /* 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]]); */
3771: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3772: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3773: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3774: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3775: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3776: /* 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]); */
3777: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3778:
3779: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3780: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3781: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3782: /* /\* *\/ */
1.330 brouard 3783: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3784: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3785: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3786: /* /\*cptcovage=2 1 2 *\/ */
3787: /* /\*Tage[k]= 5 8 *\/ */
3788: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3789: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3790: /* 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]]); */
3791: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3792: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3793: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3794: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3795: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3796: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3797: /* /\* 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); *\/ */
3798: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3799: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3800: /* /\* } *\/ */
3801: /* /\* 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]); *\/ */
3802: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3803: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3804: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3805: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3806: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3807: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3808: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3809: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3810: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3811:
1.332 brouard 3812: /* /\* 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])]); *\/ */
3813: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3814: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3815: /* 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]]); */
3816: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3817:
3818: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3819: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3820: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3821: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3822: /* /\* 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]])]; *\/ */
3823: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3824: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3825: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3826: /* /\* } *\/ */
3827: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3828: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3829: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3830: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3831: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3832: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3833: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3834: /* /\* } *\/ */
3835: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3836: /* }/\*end of products *\/ */
3837: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3838: /* for (k=1; k<=cptcovn;k++) */
3839: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3840: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3841: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3842: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3843: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3844:
3845:
1.126 brouard 3846: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3847: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3848: /* right multiplication of oldm by the current matrix */
1.126 brouard 3849: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3850: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3851: /* if((int)age == 70){ */
3852: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3853: /* for(i=1; i<=nlstate+ndeath; i++) { */
3854: /* printf("%d pmmij ",i); */
3855: /* for(j=1;j<=nlstate+ndeath;j++) { */
3856: /* printf("%f ",pmmij[i][j]); */
3857: /* } */
3858: /* printf(" oldm "); */
3859: /* for(j=1;j<=nlstate+ndeath;j++) { */
3860: /* printf("%f ",oldm[i][j]); */
3861: /* } */
3862: /* printf("\n"); */
3863: /* } */
3864: /* } */
1.126 brouard 3865: savm=oldm;
3866: oldm=newm;
3867: }
3868: for(i=1; i<=nlstate+ndeath; i++)
3869: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3870: po[i][j][h]=newm[i][j];
3871: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3872: }
1.128 brouard 3873: /*printf("h=%d ",h);*/
1.126 brouard 3874: } /* end h */
1.267 brouard 3875: /* printf("\n H=%d \n",h); */
1.126 brouard 3876: return po;
3877: }
3878:
1.217 brouard 3879: /************* Higher Back Matrix Product ***************/
1.218 brouard 3880: /* 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 3881: 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 3882: {
1.332 brouard 3883: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3884: computes the transition matrix starting at age 'age' over
1.217 brouard 3885: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3886: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3887: nhstepm*hstepm matrices.
3888: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3889: (typically every 2 years instead of every month which is too big
1.217 brouard 3890: for the memory).
1.218 brouard 3891: Model is determined by parameters x and covariates have to be
1.266 brouard 3892: included manually here. Then we use a call to bmij(x and cov)
3893: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3894: */
1.217 brouard 3895:
1.332 brouard 3896: int i, j, d, h, k, k1;
1.266 brouard 3897: double **out, cov[NCOVMAX+1], **bmij();
3898: double **newm, ***newmm;
1.217 brouard 3899: double agexact;
3900: double agebegin, ageend;
1.222 brouard 3901: double **oldm, **savm;
1.217 brouard 3902:
1.266 brouard 3903: newmm=po; /* To be saved */
3904: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3905: /* Hstepm could be zero and should return the unit matrix */
3906: for (i=1;i<=nlstate+ndeath;i++)
3907: for (j=1;j<=nlstate+ndeath;j++){
3908: oldm[i][j]=(i==j ? 1.0 : 0.0);
3909: po[i][j][0]=(i==j ? 1.0 : 0.0);
3910: }
3911: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3912: for(h=1; h <=nhstepm; h++){
3913: for(d=1; d <=hstepm; d++){
3914: newm=savm;
3915: /* Covariates have to be included here again */
3916: cov[1]=1.;
1.271 brouard 3917: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3918: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3919: /* Debug */
3920: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3921: cov[2]=agexact;
1.332 brouard 3922: if(nagesqr==1){
1.222 brouard 3923: cov[3]= agexact*agexact;
1.332 brouard 3924: }
3925: /** New code */
3926: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3927: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3928: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3929: }else{
1.332 brouard 3930: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3931: }
1.332 brouard 3932: }/* End of loop on model equation */
3933: /** End of new code */
3934: /** This was old code */
3935: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3936: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3937: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3938: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3939: /* /\* 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)); *\/ */
3940: /* } */
3941: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3942: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3943: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3944: /* /\* 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]); *\/ */
3945: /* } */
3946: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3947: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3948: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3949: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3950: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3951: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3952: /* } */
3953: /* /\* 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]); *\/ */
3954: /* } */
3955: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3956: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3957: /* if(Dummy[Tvard[k][1]]==0){ */
3958: /* if(Dummy[Tvard[k][2]]==0){ */
3959: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3960: /* }else{ */
3961: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3962: /* } */
3963: /* }else{ */
3964: /* if(Dummy[Tvard[k][2]]==0){ */
3965: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3966: /* }else{ */
3967: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3968: /* } */
3969: /* } */
3970: /* } */
3971: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3972: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3973: /** End of old code */
3974:
1.218 brouard 3975: /* Careful transposed matrix */
1.266 brouard 3976: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3977: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3978: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3979: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3980: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3981: /* if((int)age == 70){ */
3982: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3983: /* for(i=1; i<=nlstate+ndeath; i++) { */
3984: /* printf("%d pmmij ",i); */
3985: /* for(j=1;j<=nlstate+ndeath;j++) { */
3986: /* printf("%f ",pmmij[i][j]); */
3987: /* } */
3988: /* printf(" oldm "); */
3989: /* for(j=1;j<=nlstate+ndeath;j++) { */
3990: /* printf("%f ",oldm[i][j]); */
3991: /* } */
3992: /* printf("\n"); */
3993: /* } */
3994: /* } */
3995: savm=oldm;
3996: oldm=newm;
3997: }
3998: for(i=1; i<=nlstate+ndeath; i++)
3999: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 4000: po[i][j][h]=newm[i][j];
1.268 brouard 4001: /* if(h==nhstepm) */
4002: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 4003: }
1.268 brouard 4004: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 4005: } /* end h */
1.268 brouard 4006: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 4007: return po;
4008: }
4009:
4010:
1.162 brouard 4011: #ifdef NLOPT
4012: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
4013: double fret;
4014: double *xt;
4015: int j;
4016: myfunc_data *d2 = (myfunc_data *) pd;
4017: /* xt = (p1-1); */
4018: xt=vector(1,n);
4019: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
4020:
4021: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
4022: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
4023: printf("Function = %.12lf ",fret);
4024: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
4025: printf("\n");
4026: free_vector(xt,1,n);
4027: return fret;
4028: }
4029: #endif
1.126 brouard 4030:
4031: /*************** log-likelihood *************/
4032: double func( double *x)
4033: {
1.336 brouard 4034: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 4035: int ioffset=0;
1.339 brouard 4036: int ipos=0,iposold=0,ncovv=0;
4037:
1.340 brouard 4038: double cotvarv, cotvarvold;
1.226 brouard 4039: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
4040: double **out;
4041: double lli; /* Individual log likelihood */
4042: int s1, s2;
1.228 brouard 4043: 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 4044:
1.226 brouard 4045: double bbh, survp;
4046: double agexact;
1.336 brouard 4047: double agebegin, ageend;
1.226 brouard 4048: /*extern weight */
4049: /* We are differentiating ll according to initial status */
4050: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4051: /*for(i=1;i<imx;i++)
4052: printf(" %d\n",s[4][i]);
4053: */
1.162 brouard 4054:
1.226 brouard 4055: ++countcallfunc;
1.162 brouard 4056:
1.226 brouard 4057: cov[1]=1.;
1.126 brouard 4058:
1.226 brouard 4059: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4060: ioffset=0;
1.226 brouard 4061: if(mle==1){
4062: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4063: /* Computes the values of the ncovmodel covariates of the model
4064: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4065: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4066: to be observed in j being in i according to the model.
4067: */
1.243 brouard 4068: ioffset=2+nagesqr ;
1.233 brouard 4069: /* Fixed */
1.345 brouard 4070: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4071: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4072: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4073: /* 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 4074: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4075: 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 4076: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4077: }
1.226 brouard 4078: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4079: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4080: has been calculated etc */
4081: /* For an individual i, wav[i] gives the number of effective waves */
4082: /* We compute the contribution to Likelihood of each effective transition
4083: mw[mi][i] is real wave of the mi th effectve wave */
4084: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4085: s2=s[mw[mi+1][i]][i];
1.341 brouard 4086: 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 4087: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4088: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4089: */
1.336 brouard 4090: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4091: /* Wave varying (but not age varying) */
1.339 brouard 4092: /* 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*\/ */
4093: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4094: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4095: /* } */
1.340 brouard 4096: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4097: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4098: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4099: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4100: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4101: }else{ /* fixed covariate */
1.345 brouard 4102: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
1.340 brouard 4103: }
1.339 brouard 4104: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4105: cotvarvold=cotvarv;
4106: }else{ /* A second product */
4107: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4108: }
4109: iposold=ipos;
1.340 brouard 4110: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4111: }
1.339 brouard 4112: /* for products of time varying to be done */
1.234 brouard 4113: for (ii=1;ii<=nlstate+ndeath;ii++)
4114: for (j=1;j<=nlstate+ndeath;j++){
4115: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4116: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4117: }
1.336 brouard 4118:
4119: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4120: 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 4121: for(d=0; d<dh[mi][i]; d++){
4122: newm=savm;
4123: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4124: cov[2]=agexact;
4125: if(nagesqr==1)
4126: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 4127: /* for (kk=1; kk<=cptcovage;kk++) { */
4128: /* if(!FixedV[Tvar[Tage[kk]]]) */
4129: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
4130: /* else */
4131: /* 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) *\/ */
4132: /* } */
4133: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4134: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4135: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4136: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4137: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4138: }else{ /* fixed covariate */
4139: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4140: }
4141: if(ipos!=iposold){ /* Not a product or first of a product */
4142: cotvarvold=cotvarv;
4143: }else{ /* A second product */
4144: cotvarv=cotvarv*cotvarvold;
4145: }
4146: iposold=ipos;
4147: cov[ioffset+ipos]=cotvarv*agexact;
4148: /* For products */
1.234 brouard 4149: }
1.349 brouard 4150:
1.234 brouard 4151: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4152: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4153: savm=oldm;
4154: oldm=newm;
4155: } /* end mult */
4156:
4157: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4158: /* But now since version 0.9 we anticipate for bias at large stepm.
4159: * If stepm is larger than one month (smallest stepm) and if the exact delay
4160: * (in months) between two waves is not a multiple of stepm, we rounded to
4161: * the nearest (and in case of equal distance, to the lowest) interval but now
4162: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4163: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4164: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4165: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4166: * -stepm/2 to stepm/2 .
4167: * For stepm=1 the results are the same as for previous versions of Imach.
4168: * For stepm > 1 the results are less biased than in previous versions.
4169: */
1.234 brouard 4170: s1=s[mw[mi][i]][i];
4171: s2=s[mw[mi+1][i]][i];
4172: bbh=(double)bh[mi][i]/(double)stepm;
4173: /* bias bh is positive if real duration
4174: * is higher than the multiple of stepm and negative otherwise.
4175: */
4176: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4177: if( s2 > nlstate){
4178: /* i.e. if s2 is a death state and if the date of death is known
4179: then the contribution to the likelihood is the probability to
4180: die between last step unit time and current step unit time,
4181: which is also equal to probability to die before dh
4182: minus probability to die before dh-stepm .
4183: In version up to 0.92 likelihood was computed
4184: as if date of death was unknown. Death was treated as any other
4185: health state: the date of the interview describes the actual state
4186: and not the date of a change in health state. The former idea was
4187: to consider that at each interview the state was recorded
4188: (healthy, disable or death) and IMaCh was corrected; but when we
4189: introduced the exact date of death then we should have modified
4190: the contribution of an exact death to the likelihood. This new
4191: contribution is smaller and very dependent of the step unit
4192: stepm. It is no more the probability to die between last interview
4193: and month of death but the probability to survive from last
4194: interview up to one month before death multiplied by the
4195: probability to die within a month. Thanks to Chris
4196: Jackson for correcting this bug. Former versions increased
4197: mortality artificially. The bad side is that we add another loop
4198: which slows down the processing. The difference can be up to 10%
4199: lower mortality.
4200: */
4201: /* If, at the beginning of the maximization mostly, the
4202: cumulative probability or probability to be dead is
4203: constant (ie = 1) over time d, the difference is equal to
4204: 0. out[s1][3] = savm[s1][3]: probability, being at state
4205: s1 at precedent wave, to be dead a month before current
4206: wave is equal to probability, being at state s1 at
4207: precedent wave, to be dead at mont of the current
4208: wave. Then the observed probability (that this person died)
4209: is null according to current estimated parameter. In fact,
4210: it should be very low but not zero otherwise the log go to
4211: infinity.
4212: */
1.183 brouard 4213: /* #ifdef INFINITYORIGINAL */
4214: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4215: /* #else */
4216: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4217: /* lli=log(mytinydouble); */
4218: /* else */
4219: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4220: /* #endif */
1.226 brouard 4221: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4222:
1.226 brouard 4223: } else if ( s2==-1 ) { /* alive */
4224: for (j=1,survp=0. ; j<=nlstate; j++)
4225: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4226: /*survp += out[s1][j]; */
4227: lli= log(survp);
4228: }
1.336 brouard 4229: /* else if (s2==-4) { */
4230: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4231: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4232: /* lli= log(survp); */
4233: /* } */
4234: /* else if (s2==-5) { */
4235: /* for (j=1,survp=0. ; j<=2; j++) */
4236: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4237: /* lli= log(survp); */
4238: /* } */
1.226 brouard 4239: else{
4240: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4241: /* 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 */
4242: }
4243: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4244: /*if(lli ==000.0)*/
1.340 brouard 4245: /* 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 4246: ipmx +=1;
4247: sw += weight[i];
4248: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4249: /* if (lli < log(mytinydouble)){ */
4250: /* 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); */
4251: /* 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]); */
4252: /* } */
4253: } /* end of wave */
4254: } /* end of individual */
4255: } else if(mle==2){
4256: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4257: ioffset=2+nagesqr ;
4258: for (k=1; k<=ncovf;k++)
4259: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4260: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4261: for(k=1; k <= ncovv ; k++){
1.341 brouard 4262: 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 4263: }
1.226 brouard 4264: for (ii=1;ii<=nlstate+ndeath;ii++)
4265: for (j=1;j<=nlstate+ndeath;j++){
4266: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4267: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4268: }
4269: for(d=0; d<=dh[mi][i]; d++){
4270: newm=savm;
4271: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4272: cov[2]=agexact;
4273: if(nagesqr==1)
4274: cov[3]= agexact*agexact;
4275: for (kk=1; kk<=cptcovage;kk++) {
4276: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4277: }
4278: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4279: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4280: savm=oldm;
4281: oldm=newm;
4282: } /* end mult */
4283:
4284: s1=s[mw[mi][i]][i];
4285: s2=s[mw[mi+1][i]][i];
4286: bbh=(double)bh[mi][i]/(double)stepm;
4287: 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 */
4288: ipmx +=1;
4289: sw += weight[i];
4290: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4291: } /* end of wave */
4292: } /* end of individual */
4293: } else if(mle==3){ /* exponential inter-extrapolation */
4294: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4295: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4296: for(mi=1; mi<= wav[i]-1; mi++){
4297: for (ii=1;ii<=nlstate+ndeath;ii++)
4298: for (j=1;j<=nlstate+ndeath;j++){
4299: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4300: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4301: }
4302: for(d=0; d<dh[mi][i]; d++){
4303: newm=savm;
4304: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4305: cov[2]=agexact;
4306: if(nagesqr==1)
4307: cov[3]= agexact*agexact;
4308: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4309: if(!FixedV[Tvar[Tage[kk]]])
4310: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4311: else
1.341 brouard 4312: 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 4313: }
4314: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4315: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4316: savm=oldm;
4317: oldm=newm;
4318: } /* end mult */
4319:
4320: s1=s[mw[mi][i]][i];
4321: s2=s[mw[mi+1][i]][i];
4322: bbh=(double)bh[mi][i]/(double)stepm;
4323: 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 */
4324: ipmx +=1;
4325: sw += weight[i];
4326: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4327: } /* end of wave */
4328: } /* end of individual */
4329: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4330: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4331: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4332: for(mi=1; mi<= wav[i]-1; mi++){
4333: for (ii=1;ii<=nlstate+ndeath;ii++)
4334: for (j=1;j<=nlstate+ndeath;j++){
4335: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4336: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4337: }
4338: for(d=0; d<dh[mi][i]; d++){
4339: newm=savm;
4340: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4341: cov[2]=agexact;
4342: if(nagesqr==1)
4343: cov[3]= agexact*agexact;
4344: for (kk=1; kk<=cptcovage;kk++) {
4345: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4346: }
1.126 brouard 4347:
1.226 brouard 4348: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4349: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4350: savm=oldm;
4351: oldm=newm;
4352: } /* end mult */
4353:
4354: s1=s[mw[mi][i]][i];
4355: s2=s[mw[mi+1][i]][i];
4356: if( s2 > nlstate){
4357: lli=log(out[s1][s2] - savm[s1][s2]);
4358: } else if ( s2==-1 ) { /* alive */
4359: for (j=1,survp=0. ; j<=nlstate; j++)
4360: survp += out[s1][j];
4361: lli= log(survp);
4362: }else{
4363: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4364: }
4365: ipmx +=1;
4366: sw += weight[i];
4367: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4368: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.226 brouard 4369: } /* end of wave */
4370: } /* end of individual */
4371: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4372: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4373: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4374: for(mi=1; mi<= wav[i]-1; mi++){
4375: for (ii=1;ii<=nlstate+ndeath;ii++)
4376: for (j=1;j<=nlstate+ndeath;j++){
4377: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4378: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4379: }
4380: for(d=0; d<dh[mi][i]; d++){
4381: newm=savm;
4382: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4383: cov[2]=agexact;
4384: if(nagesqr==1)
4385: cov[3]= agexact*agexact;
4386: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4387: if(!FixedV[Tvar[Tage[kk]]])
4388: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4389: else
1.341 brouard 4390: 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 4391: }
1.126 brouard 4392:
1.226 brouard 4393: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4394: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4395: savm=oldm;
4396: oldm=newm;
4397: } /* end mult */
4398:
4399: s1=s[mw[mi][i]][i];
4400: s2=s[mw[mi+1][i]][i];
4401: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4402: ipmx +=1;
4403: sw += weight[i];
4404: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4405: /*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]);*/
4406: } /* end of wave */
4407: } /* end of individual */
4408: } /* End of if */
4409: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4410: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4411: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4412: return -l;
1.126 brouard 4413: }
4414:
4415: /*************** log-likelihood *************/
4416: double funcone( double *x)
4417: {
1.228 brouard 4418: /* Same as func but slower because of a lot of printf and if */
1.349 brouard 4419: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4420: int ioffset=0;
1.339 brouard 4421: int ipos=0,iposold=0,ncovv=0;
4422:
1.340 brouard 4423: double cotvarv, cotvarvold;
1.131 brouard 4424: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4425: double **out;
4426: double lli; /* Individual log likelihood */
4427: double llt;
4428: int s1, s2;
1.228 brouard 4429: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4430:
1.126 brouard 4431: double bbh, survp;
1.187 brouard 4432: double agexact;
1.214 brouard 4433: double agebegin, ageend;
1.126 brouard 4434: /*extern weight */
4435: /* We are differentiating ll according to initial status */
4436: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4437: /*for(i=1;i<imx;i++)
4438: printf(" %d\n",s[4][i]);
4439: */
4440: cov[1]=1.;
4441:
4442: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4443: ioffset=0;
4444: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4445: /* Computes the values of the ncovmodel covariates of the model
4446: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4447: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4448: to be observed in j being in i according to the model.
4449: */
1.243 brouard 4450: /* ioffset=2+nagesqr+cptcovage; */
4451: ioffset=2+nagesqr;
1.232 brouard 4452: /* Fixed */
1.224 brouard 4453: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4454: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 4455: for (kf=1; kf<=ncovf;kf++){ /* V2 + V3 + V4 Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 brouard 4456: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4457: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4458: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4459: 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 4460: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4461: /* cov[2+6]=covar[Tvar[6]][i]; */
4462: /* cov[2+6]=covar[2][i]; V2 */
4463: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4464: /* cov[2+7]=covar[Tvar[7]][i]; */
4465: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4466: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4467: /* cov[2+9]=covar[Tvar[9]][i]; */
4468: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4469: }
1.336 brouard 4470: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4471: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4472: has been calculated etc */
4473: /* For an individual i, wav[i] gives the number of effective waves */
4474: /* We compute the contribution to Likelihood of each effective transition
4475: mw[mi][i] is real wave of the mi th effectve wave */
4476: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4477: s2=s[mw[mi+1][i]][i];
1.341 brouard 4478: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4479: */
4480: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4481: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4482: /* 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?)*\/ */
4483: /* } */
1.231 brouard 4484: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4485: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4486: /* } */
1.225 brouard 4487:
1.233 brouard 4488:
4489: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4490: /* 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 */
4491: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4492: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4493: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4494: /* } */
4495:
4496: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4497: /* model V1+V3+age*V1+age*V3+V1*V3 */
4498: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4499: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4500: /* We need the position of the time varying or product in the model */
4501: /* 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 */
4502: /* TvarVV gives the variable name */
1.340 brouard 4503: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4504: * k= 1 2 3 4 5 6 7 8 9
4505: * varying 1 2 3 4 5
4506: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4507: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4508: * TvarVVind 2 3 7 7 8 8 9 9
4509: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4510: */
1.345 brouard 4511: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 4512: * V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[(v6*V2)6]=9
1.345 brouard 4513: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 4514: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4515: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
4516: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
4517: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4518: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4519: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4520: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4521: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4522: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4523: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4524: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4525: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4526: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4527: * 12 13 14 15 16
4528: * 17 18 19 20 21
4529: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
4530: * 2 3 4 6 7
4531: * 9 11 12 13 14
4532: * cptcovage=5+5 total of covariates with age
4533: * Tage[cptcovage] age*V2=12 13 14 15 16
4534: *1 17 18 19 20 21 gives the position in model of covariates associated with age
4535: *3 Tage[cptcovage] age*V3*V2=6
4536: *3 age*V2=12 13 14 15 16
4537: *3 age*V6*V3=18 19 20 21
4538: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4539: * Tvar[17]age*V6*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4540: * 2 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4541: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4542: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4543: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
4544: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
4545: * 3 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4546: * Tvar= {2, 3, 4, 6, 7,
4547: * 9, 10, 11, 12, 13, 14,
4548: * Tvar[12]=2, 3, 4, 6, 7,
4549: * Tvar[17]=9, 11, 12, 13, 14}
4550: * Typevar[1]@21 = {0, 0, 0, 0, 0,
4551: * 2, 2, 2, 2, 2, 2,
4552: * 3 3, 2, 2, 2, 2, 2,
4553: * 1, 1, 1, 1, 1,
4554: * 3, 3, 3, 3, 3}
4555: * 3 2, 3, 3, 3, 3}
4556: * p Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6} Id of the prod at position k in the model
4557: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4558: * 3 Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6}
4559: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4560: * cptcovprod=11 (6+5)
4561: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
4562: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
4563: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
4564: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
4565: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4566: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4567: * cptcovdageprod=5 for gnuplot printing
4568: * cptcovprodvage=6
4569: * ncova=15 1 2 3 4 5
4570: * 6 7 8 9 10 11 12 13 14 15
4571: * TvarA 2 3 4 6 7
4572: * 6 2 6 7 7 3 6 4 7 4
4573: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4574: * ncovf 1 2 3
1.349 brouard 4575: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4576: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4577: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4578: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4579: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4580: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4581: * 3 1 2 3 4 5 6 7 8 9 10 11 12
4582: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
4583: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
4584: * 3 cptcovprodvage=6
4585: * 3 ncovta=15 +age*V3*V2+age*V2+agev3+ageV4 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4586: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
4587: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.354 brouard 4588: *?TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
1.349 brouard 4589: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
4590: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4591: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
4592: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
4593: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
4594: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
4595: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
4596: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4597: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 4598: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
4599: * 2, 3, 4, 6, 7,
4600: * 6, 8, 9, 10, 11}
1.345 brouard 4601: * TvarFind[itv] 0 0 0
4602: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
1.354 brouard 4603: *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0
1.345 brouard 4604: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4605: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4606: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 4607: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4608: */
4609:
1.349 brouard 4610: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 Time varying covariates (single and extended product but no age) including individual from products, product is computed dynamically */
4611: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, or fixed covariate of a varying product after exploding product Vn*Vm into Vn and then Vm */
1.340 brouard 4612: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4613: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4614: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
1.354 brouard 4615: /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.345 brouard 4616: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.354 brouard 4617: /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4618: }else{ /* fixed covariate */
1.345 brouard 4619: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
1.354 brouard 4620: /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.349 brouard 4621: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.354 brouard 4622: /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4623: }
1.339 brouard 4624: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4625: cotvarvold=cotvarv;
4626: }else{ /* A second product */
4627: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4628: }
4629: iposold=ipos;
1.340 brouard 4630: cov[ioffset+ipos]=cotvarv;
1.354 brouard 4631: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
1.339 brouard 4632: /* For products */
4633: }
4634: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4635: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4636: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4637: /* /\* 1 2 3 4 5 *\/ */
4638: /* /\*itv 1 *\/ */
4639: /* /\* TvarVInd[1]= 2 *\/ */
4640: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4641: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4642: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4643: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4644: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4645: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4646: /* /\* 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]); *\/ */
4647: /* } */
1.232 brouard 4648: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4649: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4650: /* /\* 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]); *\/ */
4651: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4652: /* } */
1.126 brouard 4653: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4654: for (j=1;j<=nlstate+ndeath;j++){
4655: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4656: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4657: }
1.214 brouard 4658:
4659: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4660: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4661: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4662: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4663: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4664: and mw[mi+1][i]. dh depends on stepm.*/
4665: newm=savm;
1.247 brouard 4666: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4667: cov[2]=agexact;
4668: if(nagesqr==1)
4669: cov[3]= agexact*agexact;
1.349 brouard 4670: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4671: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4672: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4673: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4674: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4675: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4676: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4677: }else{ /* fixed covariate */
4678: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4679: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4680: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4681: }
4682: if(ipos!=iposold){ /* Not a product or first of a product */
4683: cotvarvold=cotvarv;
4684: }else{ /* A second product */
4685: /* printf("DEBUG * \n"); */
4686: cotvarv=cotvarv*cotvarvold;
4687: }
4688: iposold=ipos;
4689: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4690: cov[ioffset+ipos]=cotvarv*agexact;
4691: /* For products */
1.242 brouard 4692: }
1.349 brouard 4693:
1.242 brouard 4694: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4695: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4696: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4697: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4698: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4699: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4700: savm=oldm;
4701: oldm=newm;
1.126 brouard 4702: } /* end mult */
1.336 brouard 4703: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4704: /* But now since version 0.9 we anticipate for bias at large stepm.
4705: * If stepm is larger than one month (smallest stepm) and if the exact delay
4706: * (in months) between two waves is not a multiple of stepm, we rounded to
4707: * the nearest (and in case of equal distance, to the lowest) interval but now
4708: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4709: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4710: * probability in order to take into account the bias as a fraction of the way
4711: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4712: * -stepm/2 to stepm/2 .
4713: * For stepm=1 the results are the same as for previous versions of Imach.
4714: * For stepm > 1 the results are less biased than in previous versions.
4715: */
1.126 brouard 4716: s1=s[mw[mi][i]][i];
4717: s2=s[mw[mi+1][i]][i];
1.217 brouard 4718: /* if(s2==-1){ */
1.268 brouard 4719: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4720: /* /\* exit(1); *\/ */
4721: /* } */
1.126 brouard 4722: bbh=(double)bh[mi][i]/(double)stepm;
4723: /* bias is positive if real duration
4724: * is higher than the multiple of stepm and negative otherwise.
4725: */
4726: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4727: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4728: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4729: for (j=1,survp=0. ; j<=nlstate; j++)
4730: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4731: lli= log(survp);
1.126 brouard 4732: }else if (mle==1){
1.242 brouard 4733: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4734: } else if(mle==2){
1.242 brouard 4735: 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 4736: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4737: 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 4738: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4739: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4740: } else{ /* mle=0 back to 1 */
1.242 brouard 4741: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4742: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4743: } /* End of if */
4744: ipmx +=1;
4745: sw += weight[i];
4746: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4747: /* Printing covariates values for each contribution for checking */
1.343 brouard 4748: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.126 brouard 4749: if(globpr){
1.246 brouard 4750: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4751: %11.6f %11.6f %11.6f ", \
1.242 brouard 4752: 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 4753: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4754: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4755: /* %11.6f %11.6f %11.6f ", \ */
4756: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4757: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4758: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4759: llt +=ll[k]*gipmx/gsw;
4760: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4761: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4762: }
1.343 brouard 4763: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4764: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4765: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4766: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4767: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4768: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4769: }
4770: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4771: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4772: if(ipos!=iposold){ /* Not a product or first of a product */
4773: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4774: /* printf(" %g",cov[ioffset+ipos]); */
4775: }else{
4776: fprintf(ficresilk,"*");
4777: /* printf("*"); */
1.342 brouard 4778: }
1.343 brouard 4779: iposold=ipos;
4780: }
1.349 brouard 4781: /* for (kk=1; kk<=cptcovage;kk++) { */
4782: /* if(!FixedV[Tvar[Tage[kk]]]){ */
4783: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
4784: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
4785: /* }else{ */
4786: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4787: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
4788: /* } */
4789: /* } */
4790: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4791: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4792: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4793: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4794: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4795: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4796: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4797: }else{ /* fixed covariate */
4798: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4799: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4800: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4801: }
4802: if(ipos!=iposold){ /* Not a product or first of a product */
4803: cotvarvold=cotvarv;
4804: }else{ /* A second product */
4805: /* printf("DEBUG * \n"); */
4806: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4807: }
1.349 brouard 4808: cotvarv=cotvarv*agexact;
4809: fprintf(ficresilk," %g*age",cotvarv);
4810: iposold=ipos;
4811: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4812: cov[ioffset+ipos]=cotvarv;
4813: /* For products */
1.343 brouard 4814: }
4815: /* printf("\n"); */
1.342 brouard 4816: /* } /\* End debugILK *\/ */
4817: fprintf(ficresilk,"\n");
4818: } /* End if globpr */
1.335 brouard 4819: } /* end of wave */
4820: } /* end of individual */
4821: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4822: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4823: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4824: if(globpr==0){ /* First time we count the contributions and weights */
4825: gipmx=ipmx;
4826: gsw=sw;
4827: }
1.343 brouard 4828: return -l;
1.126 brouard 4829: }
4830:
4831:
4832: /*************** function likelione ***********/
1.292 brouard 4833: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4834: {
4835: /* This routine should help understanding what is done with
4836: the selection of individuals/waves and
4837: to check the exact contribution to the likelihood.
4838: Plotting could be done.
1.342 brouard 4839: */
4840: void pstamp(FILE *ficres);
1.343 brouard 4841: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4842:
4843: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4844: strcpy(fileresilk,"ILK_");
1.202 brouard 4845: strcat(fileresilk,fileresu);
1.126 brouard 4846: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4847: printf("Problem with resultfile: %s\n", fileresilk);
4848: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4849: }
1.342 brouard 4850: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4851: 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");
4852: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4853: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4854: for(k=1; k<=nlstate; k++)
4855: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4856: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4857:
4858: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4859: for(kf=1;kf <= ncovf; kf++){
4860: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4861: /* printf("V%d",Tvar[TvarFind[kf]]); */
4862: }
4863: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4864: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4865: if(ipos!=iposold){ /* Not a product or first of a product */
4866: /* printf(" %d",ipos); */
4867: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4868: }else{
4869: /* printf("*"); */
4870: fprintf(ficresilk,"*");
1.343 brouard 4871: }
1.342 brouard 4872: iposold=ipos;
4873: }
4874: for (kk=1; kk<=cptcovage;kk++) {
4875: if(!FixedV[Tvar[Tage[kk]]]){
4876: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4877: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4878: }else{
4879: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4880: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4881: }
4882: }
4883: /* } /\* End if debugILK *\/ */
4884: /* printf("\n"); */
4885: fprintf(ficresilk,"\n");
4886: } /* End glogpri */
1.126 brouard 4887:
1.292 brouard 4888: *fretone=(*func)(p);
1.126 brouard 4889: if(*globpri !=0){
4890: fclose(ficresilk);
1.205 brouard 4891: if (mle ==0)
4892: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4893: else if(mle >=1)
4894: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4895: 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 4896: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4897:
1.207 brouard 4898: fprintf(fichtm,"<br>- The function drawn is -2Log(L) in Log scale: by state of origin <a href=\"%s-ori.png\">%s-ori.png</a><br> \
1.343 brouard 4899: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4900: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4901: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4902:
4903: for (k=1; k<= nlstate ; k++) {
4904: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Dot's sizes are related to corresponding weight: <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br>\n \
4905: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4906: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 4907: kvar=Tvar[TvarFind[kf]]; /* variable */
4908: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): ",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]]);
4909: fprintf(fichtm,"<a href=\"%s-p%dj-%d.png\">%s-p%dj-%d.png</a><br>",subdirf2(optionfilefiname,"ILK_"),k,kvar,subdirf2(optionfilefiname,"ILK_"),k,kvar);
4910: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 4911: }
4912: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4913: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4914: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4915: /* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
4916: if(ipos!=iposold){ /* Not a product or first of a product */
4917: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4918: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4919: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
4920: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored time varying dummy covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \
4921: <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar);
4922: } /* End only for dummies time varying (single?) */
4923: }else{ /* Useless product */
4924: /* printf("*"); */
4925: /* fprintf(ficresilk,"*"); */
4926: }
4927: iposold=ipos;
4928: } /* For each time varying covariate */
4929: } /* End loop on states */
4930:
4931: /* if(debugILK){ */
4932: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4933: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4934: /* for (k=1; k<= nlstate ; k++) { */
4935: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
4936: /* <img src=\"%s-p%dj-%d.png\">",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]); */
4937: /* } */
4938: /* } */
4939: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4940: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4941: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4942: /* /\* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); *\/ */
4943: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4944: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4945: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4946: /* if(Dummy[ipos]==0 && Typevar[ipos]==0){ /\* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) *\/ */
4947: /* for (k=1; k<= nlstate ; k++) { */
4948: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
4949: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4950: /* } /\* End state *\/ */
4951: /* } /\* End only for dummies time varying (single?) *\/ */
4952: /* }else{ /\* Useless product *\/ */
4953: /* /\* printf("*"); *\/ */
4954: /* /\* fprintf(ficresilk,"*"); *\/ */
4955: /* } */
4956: /* iposold=ipos; */
4957: /* } /\* For each time varying covariate *\/ */
4958: /* }/\* End debugILK *\/ */
1.207 brouard 4959: fflush(fichtm);
1.343 brouard 4960: }/* End globpri */
1.126 brouard 4961: return;
4962: }
4963:
4964:
4965: /*********** Maximum Likelihood Estimation ***************/
4966:
4967: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4968: {
1.319 brouard 4969: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4970: double **xi;
4971: double fret;
4972: double fretone; /* Only one call to likelihood */
4973: /* char filerespow[FILENAMELENGTH];*/
1.354 brouard 4974:
4975: double * p1; /* Shifted parameters from 0 instead of 1 */
1.162 brouard 4976: #ifdef NLOPT
4977: int creturn;
4978: nlopt_opt opt;
4979: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4980: double *lb;
4981: double minf; /* the minimum objective value, upon return */
1.354 brouard 4982:
1.162 brouard 4983: myfunc_data dinst, *d = &dinst;
4984: #endif
4985:
4986:
1.126 brouard 4987: xi=matrix(1,npar,1,npar);
1.357 ! brouard 4988: for (i=1;i<=npar;i++) /* Starting with canonical directions j=1,n xi[i=1,n][j] */
1.126 brouard 4989: for (j=1;j<=npar;j++)
4990: xi[i][j]=(i==j ? 1.0 : 0.0);
4991: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4992: strcpy(filerespow,"POW_");
1.126 brouard 4993: strcat(filerespow,fileres);
4994: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4995: printf("Problem with resultfile: %s\n", filerespow);
4996: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4997: }
4998: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4999: for (i=1;i<=nlstate;i++)
5000: for(j=1;j<=nlstate+ndeath;j++)
5001: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
5002: fprintf(ficrespow,"\n");
1.162 brouard 5003: #ifdef POWELL
1.319 brouard 5004: #ifdef LINMINORIGINAL
5005: #else /* LINMINORIGINAL */
5006:
5007: flatdir=ivector(1,npar);
5008: for (j=1;j<=npar;j++) flatdir[j]=0;
5009: #endif /*LINMINORIGINAL */
5010:
5011: #ifdef FLATSUP
5012: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5013: /* reorganizing p by suppressing flat directions */
5014: for(i=1, jk=1; i <=nlstate; i++){
5015: for(k=1; k <=(nlstate+ndeath); k++){
5016: if (k != i) {
5017: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
5018: if(flatdir[jk]==1){
5019: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
5020: }
5021: for(j=1; j <=ncovmodel; j++){
5022: printf("%12.7f ",p[jk]);
5023: jk++;
5024: }
5025: printf("\n");
5026: }
5027: }
5028: }
5029: /* skipping */
5030: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
5031: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
5032: for(k=1; k <=(nlstate+ndeath); k++){
5033: if (k != i) {
5034: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
5035: if(flatdir[jk]==1){
5036: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
5037: for(j=1; j <=ncovmodel; jk++,j++){
5038: printf(" p[%d]=%12.7f",jk, p[jk]);
5039: /*q[jjk]=p[jk];*/
5040: }
5041: }else{
5042: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
5043: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
5044: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
5045: /*q[jjk]=p[jk];*/
5046: }
5047: }
5048: printf("\n");
5049: }
5050: fflush(stdout);
5051: }
5052: }
5053: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5054: #else /* FLATSUP */
1.126 brouard 5055: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 5056: #endif /* FLATSUP */
5057:
5058: #ifdef LINMINORIGINAL
5059: #else
5060: free_ivector(flatdir,1,npar);
5061: #endif /* LINMINORIGINAL*/
5062: #endif /* POWELL */
1.126 brouard 5063:
1.162 brouard 5064: #ifdef NLOPT
5065: #ifdef NEWUOA
5066: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
5067: #else
5068: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
5069: #endif
5070: lb=vector(0,npar-1);
5071: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
5072: nlopt_set_lower_bounds(opt, lb);
5073: nlopt_set_initial_step1(opt, 0.1);
5074:
5075: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5076: d->function = func;
5077: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5078: nlopt_set_min_objective(opt, myfunc, d);
5079: nlopt_set_xtol_rel(opt, ftol);
5080: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5081: printf("nlopt failed! %d\n",creturn);
5082: }
5083: else {
5084: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5085: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5086: iter=1; /* not equal */
5087: }
5088: nlopt_destroy(opt);
5089: #endif
1.319 brouard 5090: #ifdef FLATSUP
5091: /* npared = npar -flatd/ncovmodel; */
5092: /* xired= matrix(1,npared,1,npared); */
5093: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5094: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5095: /* free_matrix(xire,1,npared,1,npared); */
5096: #else /* FLATSUP */
5097: #endif /* FLATSUP */
1.126 brouard 5098: free_matrix(xi,1,npar,1,npar);
5099: fclose(ficrespow);
1.203 brouard 5100: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5101: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5102: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5103:
5104: }
5105:
5106: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5107: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5108: {
5109: double **a,**y,*x,pd;
1.203 brouard 5110: /* double **hess; */
1.164 brouard 5111: int i, j;
1.126 brouard 5112: int *indx;
5113:
5114: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5115: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5116: void lubksb(double **a, int npar, int *indx, double b[]) ;
5117: void ludcmp(double **a, int npar, int *indx, double *d) ;
5118: double gompertz(double p[]);
1.203 brouard 5119: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5120:
5121: printf("\nCalculation of the hessian matrix. Wait...\n");
5122: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5123: for (i=1;i<=npar;i++){
1.203 brouard 5124: printf("%d-",i);fflush(stdout);
5125: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5126:
5127: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5128:
5129: /* printf(" %f ",p[i]);
5130: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5131: }
5132:
5133: for (i=1;i<=npar;i++) {
5134: for (j=1;j<=npar;j++) {
5135: if (j>i) {
1.203 brouard 5136: printf(".%d-%d",i,j);fflush(stdout);
5137: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5138: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5139:
5140: hess[j][i]=hess[i][j];
5141: /*printf(" %lf ",hess[i][j]);*/
5142: }
5143: }
5144: }
5145: printf("\n");
5146: fprintf(ficlog,"\n");
5147:
5148: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5149: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5150:
5151: a=matrix(1,npar,1,npar);
5152: y=matrix(1,npar,1,npar);
5153: x=vector(1,npar);
5154: indx=ivector(1,npar);
5155: for (i=1;i<=npar;i++)
5156: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5157: ludcmp(a,npar,indx,&pd);
5158:
5159: for (j=1;j<=npar;j++) {
5160: for (i=1;i<=npar;i++) x[i]=0;
5161: x[j]=1;
5162: lubksb(a,npar,indx,x);
5163: for (i=1;i<=npar;i++){
5164: matcov[i][j]=x[i];
5165: }
5166: }
5167:
5168: printf("\n#Hessian matrix#\n");
5169: fprintf(ficlog,"\n#Hessian matrix#\n");
5170: for (i=1;i<=npar;i++) {
5171: for (j=1;j<=npar;j++) {
1.203 brouard 5172: printf("%.6e ",hess[i][j]);
5173: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5174: }
5175: printf("\n");
5176: fprintf(ficlog,"\n");
5177: }
5178:
1.203 brouard 5179: /* printf("\n#Covariance matrix#\n"); */
5180: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5181: /* for (i=1;i<=npar;i++) { */
5182: /* for (j=1;j<=npar;j++) { */
5183: /* printf("%.6e ",matcov[i][j]); */
5184: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5185: /* } */
5186: /* printf("\n"); */
5187: /* fprintf(ficlog,"\n"); */
5188: /* } */
5189:
1.126 brouard 5190: /* Recompute Inverse */
1.203 brouard 5191: /* for (i=1;i<=npar;i++) */
5192: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5193: /* ludcmp(a,npar,indx,&pd); */
5194:
5195: /* printf("\n#Hessian matrix recomputed#\n"); */
5196:
5197: /* for (j=1;j<=npar;j++) { */
5198: /* for (i=1;i<=npar;i++) x[i]=0; */
5199: /* x[j]=1; */
5200: /* lubksb(a,npar,indx,x); */
5201: /* for (i=1;i<=npar;i++){ */
5202: /* y[i][j]=x[i]; */
5203: /* printf("%.3e ",y[i][j]); */
5204: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5205: /* } */
5206: /* printf("\n"); */
5207: /* fprintf(ficlog,"\n"); */
5208: /* } */
5209:
5210: /* Verifying the inverse matrix */
5211: #ifdef DEBUGHESS
5212: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5213:
1.203 brouard 5214: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5215: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5216:
5217: for (j=1;j<=npar;j++) {
5218: for (i=1;i<=npar;i++){
1.203 brouard 5219: printf("%.2f ",y[i][j]);
5220: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5221: }
5222: printf("\n");
5223: fprintf(ficlog,"\n");
5224: }
1.203 brouard 5225: #endif
1.126 brouard 5226:
5227: free_matrix(a,1,npar,1,npar);
5228: free_matrix(y,1,npar,1,npar);
5229: free_vector(x,1,npar);
5230: free_ivector(indx,1,npar);
1.203 brouard 5231: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5232:
5233:
5234: }
5235:
5236: /*************** hessian matrix ****************/
5237: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5238: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5239: int i;
5240: int l=1, lmax=20;
1.203 brouard 5241: double k1,k2, res, fx;
1.132 brouard 5242: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5243: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5244: int k=0,kmax=10;
5245: double l1;
5246:
5247: fx=func(x);
5248: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5249: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5250: l1=pow(10,l);
5251: delts=delt;
5252: for(k=1 ; k <kmax; k=k+1){
5253: delt = delta*(l1*k);
5254: p2[theta]=x[theta] +delt;
1.145 brouard 5255: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5256: p2[theta]=x[theta]-delt;
5257: k2=func(p2)-fx;
5258: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5259: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5260:
1.203 brouard 5261: #ifdef DEBUGHESSII
1.126 brouard 5262: 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);
5263: 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);
5264: #endif
5265: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5266: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5267: k=kmax;
5268: }
5269: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5270: k=kmax; l=lmax*10;
1.126 brouard 5271: }
5272: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5273: delts=delt;
5274: }
1.203 brouard 5275: } /* End loop k */
1.126 brouard 5276: }
5277: delti[theta]=delts;
5278: return res;
5279:
5280: }
5281:
1.203 brouard 5282: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5283: {
5284: int i;
1.164 brouard 5285: int l=1, lmax=20;
1.126 brouard 5286: double k1,k2,k3,k4,res,fx;
1.132 brouard 5287: double p2[MAXPARM+1];
1.203 brouard 5288: int k, kmax=1;
5289: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5290:
5291: int firstime=0;
1.203 brouard 5292:
1.126 brouard 5293: fx=func(x);
1.203 brouard 5294: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5295: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5296: p2[thetai]=x[thetai]+delti[thetai]*k;
5297: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5298: k1=func(p2)-fx;
5299:
1.203 brouard 5300: p2[thetai]=x[thetai]+delti[thetai]*k;
5301: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5302: k2=func(p2)-fx;
5303:
1.203 brouard 5304: p2[thetai]=x[thetai]-delti[thetai]*k;
5305: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5306: k3=func(p2)-fx;
5307:
1.203 brouard 5308: p2[thetai]=x[thetai]-delti[thetai]*k;
5309: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5310: k4=func(p2)-fx;
1.203 brouard 5311: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5312: if(k1*k2*k3*k4 <0.){
1.208 brouard 5313: firstime=1;
1.203 brouard 5314: kmax=kmax+10;
1.208 brouard 5315: }
5316: if(kmax >=10 || firstime ==1){
1.354 brouard 5317: /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */
1.246 brouard 5318: 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);
5319: 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 5320: 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);
5321: 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);
5322: }
5323: #ifdef DEBUGHESSIJ
5324: v1=hess[thetai][thetai];
5325: v2=hess[thetaj][thetaj];
5326: cv12=res;
5327: /* Computing eigen value of Hessian matrix */
5328: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5329: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5330: if ((lc2 <0) || (lc1 <0) ){
5331: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5332: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5333: printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
5334: fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
5335: }
1.126 brouard 5336: #endif
5337: }
5338: return res;
5339: }
5340:
1.203 brouard 5341: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5342: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5343: /* { */
5344: /* int i; */
5345: /* int l=1, lmax=20; */
5346: /* double k1,k2,k3,k4,res,fx; */
5347: /* double p2[MAXPARM+1]; */
5348: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5349: /* int k=0,kmax=10; */
5350: /* double l1; */
5351:
5352: /* fx=func(x); */
5353: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5354: /* l1=pow(10,l); */
5355: /* delts=delt; */
5356: /* for(k=1 ; k <kmax; k=k+1){ */
5357: /* delt = delti*(l1*k); */
5358: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5359: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5360: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5361: /* k1=func(p2)-fx; */
5362:
5363: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5364: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5365: /* k2=func(p2)-fx; */
5366:
5367: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5368: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5369: /* k3=func(p2)-fx; */
5370:
5371: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5372: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5373: /* k4=func(p2)-fx; */
5374: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5375: /* #ifdef DEBUGHESSIJ */
5376: /* 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); */
5377: /* 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); */
5378: /* #endif */
5379: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5380: /* k=kmax; */
5381: /* } */
5382: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5383: /* k=kmax; l=lmax*10; */
5384: /* } */
5385: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5386: /* delts=delt; */
5387: /* } */
5388: /* } /\* End loop k *\/ */
5389: /* } */
5390: /* delti[theta]=delts; */
5391: /* return res; */
5392: /* } */
5393:
5394:
1.126 brouard 5395: /************** Inverse of matrix **************/
5396: void ludcmp(double **a, int n, int *indx, double *d)
5397: {
5398: int i,imax,j,k;
5399: double big,dum,sum,temp;
5400: double *vv;
5401:
5402: vv=vector(1,n);
5403: *d=1.0;
5404: for (i=1;i<=n;i++) {
5405: big=0.0;
5406: for (j=1;j<=n;j++)
5407: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5408: if (big == 0.0){
5409: printf(" Singular Hessian matrix at row %d:\n",i);
5410: for (j=1;j<=n;j++) {
5411: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5412: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5413: }
5414: fflush(ficlog);
5415: fclose(ficlog);
5416: nrerror("Singular matrix in routine ludcmp");
5417: }
1.126 brouard 5418: vv[i]=1.0/big;
5419: }
5420: for (j=1;j<=n;j++) {
5421: for (i=1;i<j;i++) {
5422: sum=a[i][j];
5423: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5424: a[i][j]=sum;
5425: }
5426: big=0.0;
5427: for (i=j;i<=n;i++) {
5428: sum=a[i][j];
5429: for (k=1;k<j;k++)
5430: sum -= a[i][k]*a[k][j];
5431: a[i][j]=sum;
5432: if ( (dum=vv[i]*fabs(sum)) >= big) {
5433: big=dum;
5434: imax=i;
5435: }
5436: }
5437: if (j != imax) {
5438: for (k=1;k<=n;k++) {
5439: dum=a[imax][k];
5440: a[imax][k]=a[j][k];
5441: a[j][k]=dum;
5442: }
5443: *d = -(*d);
5444: vv[imax]=vv[j];
5445: }
5446: indx[j]=imax;
5447: if (a[j][j] == 0.0) a[j][j]=TINY;
5448: if (j != n) {
5449: dum=1.0/(a[j][j]);
5450: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5451: }
5452: }
5453: free_vector(vv,1,n); /* Doesn't work */
5454: ;
5455: }
5456:
5457: void lubksb(double **a, int n, int *indx, double b[])
5458: {
5459: int i,ii=0,ip,j;
5460: double sum;
5461:
5462: for (i=1;i<=n;i++) {
5463: ip=indx[i];
5464: sum=b[ip];
5465: b[ip]=b[i];
5466: if (ii)
5467: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5468: else if (sum) ii=i;
5469: b[i]=sum;
5470: }
5471: for (i=n;i>=1;i--) {
5472: sum=b[i];
5473: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5474: b[i]=sum/a[i][i];
5475: }
5476: }
5477:
5478: void pstamp(FILE *fichier)
5479: {
1.196 brouard 5480: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5481: }
5482:
1.297 brouard 5483: void date2dmy(double date,double *day, double *month, double *year){
5484: double yp=0., yp1=0., yp2=0.;
5485:
5486: yp1=modf(date,&yp);/* extracts integral of date in yp and
5487: fractional in yp1 */
5488: *year=yp;
5489: yp2=modf((yp1*12),&yp);
5490: *month=yp;
5491: yp1=modf((yp2*30.5),&yp);
5492: *day=yp;
5493: if(*day==0) *day=1;
5494: if(*month==0) *month=1;
5495: }
5496:
1.253 brouard 5497:
5498:
1.126 brouard 5499: /************ Frequencies ********************/
1.251 brouard 5500: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5501: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5502: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5503: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5504: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5505: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5506: int iind=0, iage=0;
5507: int mi; /* Effective wave */
5508: int first;
5509: double ***freq; /* Frequencies */
1.268 brouard 5510: 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 */
5511: 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 5512: double *meanq, *stdq, *idq;
1.226 brouard 5513: double **meanqt;
5514: double *pp, **prop, *posprop, *pospropt;
5515: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5516: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5517: double agebegin, ageend;
5518:
5519: pp=vector(1,nlstate);
1.251 brouard 5520: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5521: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5522: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5523: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5524: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5525: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5526: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5527: meanqt=matrix(1,lastpass,1,nqtveff);
5528: strcpy(fileresp,"P_");
5529: strcat(fileresp,fileresu);
5530: /*strcat(fileresphtm,fileresu);*/
5531: if((ficresp=fopen(fileresp,"w"))==NULL) {
5532: printf("Problem with prevalence resultfile: %s\n", fileresp);
5533: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5534: exit(0);
5535: }
1.240 brouard 5536:
1.226 brouard 5537: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5538: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5539: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5540: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5541: fflush(ficlog);
5542: exit(70);
5543: }
5544: else{
5545: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5546: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5547: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5548: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5549: }
1.319 brouard 5550: 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 5551:
1.226 brouard 5552: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5553: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5554: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5555: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5556: fflush(ficlog);
5557: exit(70);
1.240 brouard 5558: } else{
1.226 brouard 5559: 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 5560: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5561: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5562: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5563: }
1.319 brouard 5564: 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 5565:
1.253 brouard 5566: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5567: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5568: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5569: j1=0;
1.126 brouard 5570:
1.227 brouard 5571: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5572: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5573: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5574: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5575:
5576:
1.226 brouard 5577: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5578: reference=low_education V1=0,V2=0
5579: med_educ V1=1 V2=0,
5580: high_educ V1=0 V2=1
1.330 brouard 5581: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5582: */
1.249 brouard 5583: dateintsum=0;
5584: k2cpt=0;
5585:
1.253 brouard 5586: if(cptcoveff == 0 )
1.265 brouard 5587: nl=1; /* Constant and age model only */
1.253 brouard 5588: else
5589: nl=2;
1.265 brouard 5590:
5591: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5592: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5593: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5594: * freq[s1][s2][iage] =0.
5595: * Loop on iind
5596: * ++freq[s1][s2][iage] weighted
5597: * end iind
5598: * if covariate and j!0
5599: * headers Variable on one line
5600: * endif cov j!=0
5601: * header of frequency table by age
5602: * Loop on age
5603: * pp[s1]+=freq[s1][s2][iage] weighted
5604: * pos+=freq[s1][s2][iage] weighted
5605: * Loop on s1 initial state
5606: * fprintf(ficresp
5607: * end s1
5608: * end age
5609: * if j!=0 computes starting values
5610: * end compute starting values
5611: * end j1
5612: * end nl
5613: */
1.253 brouard 5614: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5615: if(nj==1)
5616: j=0; /* First pass for the constant */
1.265 brouard 5617: else{
1.335 brouard 5618: 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 5619: }
1.251 brouard 5620: first=1;
1.332 brouard 5621: 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 5622: posproptt=0.;
1.330 brouard 5623: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5624: scanf("%d", i);*/
5625: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5626: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5627: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5628: freq[i][s2][m]=0;
1.251 brouard 5629:
5630: for (i=1; i<=nlstate; i++) {
1.240 brouard 5631: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5632: prop[i][m]=0;
5633: posprop[i]=0;
5634: pospropt[i]=0;
5635: }
1.283 brouard 5636: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5637: idq[z1]=0.;
5638: meanq[z1]=0.;
5639: stdq[z1]=0.;
1.283 brouard 5640: }
5641: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5642: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5643: /* meanqt[m][z1]=0.; */
5644: /* } */
5645: /* } */
1.251 brouard 5646: /* dateintsum=0; */
5647: /* k2cpt=0; */
5648:
1.265 brouard 5649: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5650: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5651: bool=1;
5652: if(j !=0){
5653: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5654: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5655: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5656: /* if(Tvaraff[z1] ==-20){ */
5657: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5658: /* }else if(Tvaraff[z1] ==-10){ */
5659: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5660: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5661: /* 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); */
5662: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5663: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5664: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5665: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5666: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5667: /* 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", */
5668: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5669: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5670: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5671: } /* Onlyf fixed */
5672: } /* end z1 */
1.335 brouard 5673: } /* cptcoveff > 0 */
1.251 brouard 5674: } /* end any */
5675: }/* end j==0 */
1.265 brouard 5676: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5677: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5678: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5679: m=mw[mi][iind];
5680: if(j!=0){
5681: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5682: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5683: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5684: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5685: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5686: 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 5687: value is -1, we don't select. It differs from the
5688: constant and age model which counts them. */
5689: bool=0; /* not selected */
5690: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5691: /* i1=Tvaraff[z1]; */
5692: /* i2=TnsdVar[i1]; */
5693: /* i3=nbcode[i1][i2]; */
5694: /* i4=covar[i1][iind]; */
5695: /* if(i4 != i3){ */
5696: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5697: bool=0;
5698: }
5699: }
5700: }
5701: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5702: } /* end j==0 */
5703: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5704: if(bool==1){ /*Selected */
1.251 brouard 5705: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5706: and mw[mi+1][iind]. dh depends on stepm. */
5707: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5708: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5709: if(m >=firstpass && m <=lastpass){
5710: k2=anint[m][iind]+(mint[m][iind]/12.);
5711: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5712: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5713: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5714: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5715: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5716: if (m<lastpass) {
5717: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5718: /* 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]); */
5719: if(s[m][iind]==-1)
5720: 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.));
5721: 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 5722: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5723: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5724: idq[z1]=idq[z1]+weight[iind];
5725: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5726: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5727: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5728: }
1.284 brouard 5729: }
1.251 brouard 5730: /* if((int)agev[m][iind] == 55) */
5731: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5732: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5733: 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 5734: }
1.251 brouard 5735: } /* end if between passes */
5736: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5737: dateintsum=dateintsum+k2; /* on all covariates ?*/
5738: k2cpt++;
5739: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5740: }
1.251 brouard 5741: }else{
5742: bool=1;
5743: }/* end bool 2 */
5744: } /* end m */
1.284 brouard 5745: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5746: /* idq[z1]=idq[z1]+weight[iind]; */
5747: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5748: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5749: /* } */
1.251 brouard 5750: } /* end bool */
5751: } /* end iind = 1 to imx */
1.319 brouard 5752: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5753: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5754:
5755:
5756: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5757: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5758: pstamp(ficresp);
1.335 brouard 5759: if (cptcoveff>0 && j!=0){
1.265 brouard 5760: pstamp(ficresp);
1.251 brouard 5761: printf( "\n#********** Variable ");
5762: fprintf(ficresp, "\n#********** Variable ");
5763: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5764: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5765: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5766: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5767: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5768: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5769: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5770: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5771: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5772: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5773: }else{
1.330 brouard 5774: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5775: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5776: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5777: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5778: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5779: }
5780: }
5781: printf( "**********\n#");
5782: fprintf(ficresp, "**********\n#");
5783: fprintf(ficresphtm, "**********</h3>\n");
5784: fprintf(ficresphtmfr, "**********</h3>\n");
5785: fprintf(ficlog, "**********\n");
5786: }
1.284 brouard 5787: /*
5788: Printing means of quantitative variables if any
5789: */
5790: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5791: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5792: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5793: if(weightopt==1){
5794: printf(" Weighted mean and standard deviation of");
5795: fprintf(ficlog," Weighted mean and standard deviation of");
5796: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5797: }
1.311 brouard 5798: /* mu = \frac{w x}{\sum w}
5799: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5800: */
5801: 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]));
5802: 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]));
5803: 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 5804: }
5805: /* for (z1=1; z1<= nqtveff; z1++) { */
5806: /* for(m=1;m<=lastpass;m++){ */
5807: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5808: /* } */
5809: /* } */
1.283 brouard 5810:
1.251 brouard 5811: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5812: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5813: fprintf(ficresp, " Age");
1.335 brouard 5814: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5815: 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]]);
5816: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5817: }
1.251 brouard 5818: for(i=1; i<=nlstate;i++) {
1.335 brouard 5819: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5820: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5821: }
1.335 brouard 5822: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5823: fprintf(ficresphtm, "\n");
5824:
5825: /* Header of frequency table by age */
5826: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5827: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5828: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5829: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5830: if(s2!=0 && m!=0)
5831: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5832: }
1.226 brouard 5833: }
1.251 brouard 5834: fprintf(ficresphtmfr, "\n");
5835:
5836: /* For each age */
5837: for(iage=iagemin; iage <= iagemax+3; iage++){
5838: fprintf(ficresphtm,"<tr>");
5839: if(iage==iagemax+1){
5840: fprintf(ficlog,"1");
5841: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5842: }else if(iage==iagemax+2){
5843: fprintf(ficlog,"0");
5844: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5845: }else if(iage==iagemax+3){
5846: fprintf(ficlog,"Total");
5847: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5848: }else{
1.240 brouard 5849: if(first==1){
1.251 brouard 5850: first=0;
5851: printf("See log file for details...\n");
5852: }
5853: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5854: fprintf(ficlog,"Age %d", iage);
5855: }
1.265 brouard 5856: for(s1=1; s1 <=nlstate ; s1++){
5857: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5858: pp[s1] += freq[s1][m][iage];
1.251 brouard 5859: }
1.265 brouard 5860: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5861: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5862: pos += freq[s1][m][iage];
5863: if(pp[s1]>=1.e-10){
1.251 brouard 5864: if(first==1){
1.265 brouard 5865: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5866: }
1.265 brouard 5867: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5868: }else{
5869: if(first==1)
1.265 brouard 5870: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5871: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5872: }
5873: }
5874:
1.265 brouard 5875: for(s1=1; s1 <=nlstate ; s1++){
5876: /* posprop[s1]=0; */
5877: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5878: pp[s1] += freq[s1][m][iage];
5879: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5880:
5881: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5882: pos += pp[s1]; /* pos is the total number of transitions until this age */
5883: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5884: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5885: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5886: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5887: }
5888:
5889: /* Writing ficresp */
1.335 brouard 5890: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5891: if( iage <= iagemax){
5892: fprintf(ficresp," %d",iage);
5893: }
5894: }else if( nj==2){
5895: if( iage <= iagemax){
5896: fprintf(ficresp," %d",iage);
1.335 brouard 5897: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5898: }
1.240 brouard 5899: }
1.265 brouard 5900: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5901: if(pos>=1.e-5){
1.251 brouard 5902: if(first==1)
1.265 brouard 5903: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5904: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5905: }else{
5906: if(first==1)
1.265 brouard 5907: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5908: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5909: }
5910: if( iage <= iagemax){
5911: if(pos>=1.e-5){
1.335 brouard 5912: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5913: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5914: }else if( nj==2){
5915: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5916: }
5917: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5918: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5919: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5920: } else{
1.335 brouard 5921: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5922: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5923: }
1.240 brouard 5924: }
1.265 brouard 5925: pospropt[s1] +=posprop[s1];
5926: } /* end loop s1 */
1.251 brouard 5927: /* pospropt=0.; */
1.265 brouard 5928: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5929: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5930: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5931: if(first==1){
1.265 brouard 5932: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5933: }
1.265 brouard 5934: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5935: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5936: }
1.265 brouard 5937: if(s1!=0 && m!=0)
5938: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5939: }
1.265 brouard 5940: } /* end loop s1 */
1.251 brouard 5941: posproptt=0.;
1.265 brouard 5942: for(s1=1; s1 <=nlstate; s1++){
5943: posproptt += pospropt[s1];
1.251 brouard 5944: }
5945: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5946: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5947: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5948: if(iage <= iagemax)
5949: fprintf(ficresp,"\n");
1.240 brouard 5950: }
1.251 brouard 5951: if(first==1)
5952: printf("Others in log...\n");
5953: fprintf(ficlog,"\n");
5954: } /* end loop age iage */
1.265 brouard 5955:
1.251 brouard 5956: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5957: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5958: if(posproptt < 1.e-5){
1.265 brouard 5959: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5960: }else{
1.265 brouard 5961: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5962: }
1.226 brouard 5963: }
1.251 brouard 5964: fprintf(ficresphtm,"</tr>\n");
5965: fprintf(ficresphtm,"</table>\n");
5966: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5967: if(posproptt < 1.e-5){
1.251 brouard 5968: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5969: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5970: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5971: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5972: invalidvarcomb[j1]=1;
1.226 brouard 5973: }else{
1.338 brouard 5974: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5975: invalidvarcomb[j1]=0;
1.226 brouard 5976: }
1.251 brouard 5977: fprintf(ficresphtmfr,"</table>\n");
5978: fprintf(ficlog,"\n");
5979: if(j!=0){
5980: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5981: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5982: for(k=1; k <=(nlstate+ndeath); k++){
5983: if (k != i) {
1.265 brouard 5984: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5985: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5986: if(j1==1){ /* All dummy covariates to zero */
5987: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5988: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5989: printf("%d%d ",i,k);
5990: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5991: 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]));
5992: 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]));
5993: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5994: }
1.253 brouard 5995: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5996: for(iage=iagemin; iage <= iagemax+3; iage++){
5997: x[iage]= (double)iage;
5998: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5999: /* 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 6000: }
1.268 brouard 6001: /* Some are not finite, but linreg will ignore these ages */
6002: no=0;
1.253 brouard 6003: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 6004: pstart[s1]=b;
6005: pstart[s1-1]=a;
1.252 brouard 6006: }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 */
6007: 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]);
6008: 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 6009: 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 6010: printf("%d%d ",i,k);
6011: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 6012: 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 6013: }else{ /* Other cases, like quantitative fixed or varying covariates */
6014: ;
6015: }
6016: /* printf("%12.7f )", param[i][jj][k]); */
6017: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 6018: s1++;
1.251 brouard 6019: } /* end jj */
6020: } /* end k!= i */
6021: } /* end k */
1.265 brouard 6022: } /* end i, s1 */
1.251 brouard 6023: } /* end j !=0 */
6024: } /* end selected combination of covariate j1 */
6025: if(j==0){ /* We can estimate starting values from the occurences in each case */
6026: printf("#Freqsummary: Starting values for the constants:\n");
6027: fprintf(ficlog,"\n");
1.265 brouard 6028: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 6029: for(k=1; k <=(nlstate+ndeath); k++){
6030: if (k != i) {
6031: printf("%d%d ",i,k);
6032: fprintf(ficlog,"%d%d ",i,k);
6033: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 6034: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 6035: if(jj==1){ /* Age has to be done */
1.265 brouard 6036: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
6037: 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]));
6038: 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 6039: }
6040: /* printf("%12.7f )", param[i][jj][k]); */
6041: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 6042: s1++;
1.250 brouard 6043: }
1.251 brouard 6044: printf("\n");
6045: fprintf(ficlog,"\n");
1.250 brouard 6046: }
6047: }
1.284 brouard 6048: } /* end of state i */
1.251 brouard 6049: printf("#Freqsummary\n");
6050: fprintf(ficlog,"\n");
1.265 brouard 6051: for(s1=-1; s1 <=nlstate+ndeath; s1++){
6052: for(s2=-1; s2 <=nlstate+ndeath; s2++){
6053: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
6054: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6055: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6056: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
6057: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
6058: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 6059: /* } */
6060: }
1.265 brouard 6061: } /* end loop s1 */
1.251 brouard 6062:
6063: printf("\n");
6064: fprintf(ficlog,"\n");
6065: } /* end j=0 */
1.249 brouard 6066: } /* end j */
1.252 brouard 6067:
1.253 brouard 6068: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 6069: for(i=1, jk=1; i <=nlstate; i++){
6070: for(j=1; j <=nlstate+ndeath; j++){
6071: if(j!=i){
6072: /*ca[0]= k+'a'-1;ca[1]='\0';*/
6073: printf("%1d%1d",i,j);
6074: fprintf(ficparo,"%1d%1d",i,j);
6075: for(k=1; k<=ncovmodel;k++){
6076: /* printf(" %lf",param[i][j][k]); */
6077: /* fprintf(ficparo," %lf",param[i][j][k]); */
6078: p[jk]=pstart[jk];
6079: printf(" %f ",pstart[jk]);
6080: fprintf(ficparo," %f ",pstart[jk]);
6081: jk++;
6082: }
6083: printf("\n");
6084: fprintf(ficparo,"\n");
6085: }
6086: }
6087: }
6088: } /* end mle=-2 */
1.226 brouard 6089: dateintmean=dateintsum/k2cpt;
1.296 brouard 6090: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6091:
1.226 brouard 6092: fclose(ficresp);
6093: fclose(ficresphtm);
6094: fclose(ficresphtmfr);
1.283 brouard 6095: free_vector(idq,1,nqfveff);
1.226 brouard 6096: free_vector(meanq,1,nqfveff);
1.284 brouard 6097: free_vector(stdq,1,nqfveff);
1.226 brouard 6098: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6099: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6100: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6101: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6102: free_vector(pospropt,1,nlstate);
6103: free_vector(posprop,1,nlstate);
1.251 brouard 6104: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6105: free_vector(pp,1,nlstate);
6106: /* End of freqsummary */
6107: }
1.126 brouard 6108:
1.268 brouard 6109: /* Simple linear regression */
6110: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6111:
6112: /* y=a+bx regression */
6113: double sumx = 0.0; /* sum of x */
6114: double sumx2 = 0.0; /* sum of x**2 */
6115: double sumxy = 0.0; /* sum of x * y */
6116: double sumy = 0.0; /* sum of y */
6117: double sumy2 = 0.0; /* sum of y**2 */
6118: double sume2 = 0.0; /* sum of square or residuals */
6119: double yhat;
6120:
6121: double denom=0;
6122: int i;
6123: int ne=*no;
6124:
6125: for ( i=ifi, ne=0;i<=ila;i++) {
6126: if(!isfinite(x[i]) || !isfinite(y[i])){
6127: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6128: continue;
6129: }
6130: ne=ne+1;
6131: sumx += x[i];
6132: sumx2 += x[i]*x[i];
6133: sumxy += x[i] * y[i];
6134: sumy += y[i];
6135: sumy2 += y[i]*y[i];
6136: denom = (ne * sumx2 - sumx*sumx);
6137: /* 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); */
6138: }
6139:
6140: denom = (ne * sumx2 - sumx*sumx);
6141: if (denom == 0) {
6142: // vertical, slope m is infinity
6143: *b = INFINITY;
6144: *a = 0;
6145: if (r) *r = 0;
6146: return 1;
6147: }
6148:
6149: *b = (ne * sumxy - sumx * sumy) / denom;
6150: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6151: if (r!=NULL) {
6152: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6153: sqrt((sumx2 - sumx*sumx/ne) *
6154: (sumy2 - sumy*sumy/ne));
6155: }
6156: *no=ne;
6157: for ( i=ifi, ne=0;i<=ila;i++) {
6158: if(!isfinite(x[i]) || !isfinite(y[i])){
6159: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6160: continue;
6161: }
6162: ne=ne+1;
6163: yhat = y[i] - *a -*b* x[i];
6164: sume2 += yhat * yhat ;
6165:
6166: denom = (ne * sumx2 - sumx*sumx);
6167: /* 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); */
6168: }
6169: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6170: *sa= *sb * sqrt(sumx2/ne);
6171:
6172: return 0;
6173: }
6174:
1.126 brouard 6175: /************ Prevalence ********************/
1.227 brouard 6176: 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)
6177: {
6178: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6179: in each health status at the date of interview (if between dateprev1 and dateprev2).
6180: We still use firstpass and lastpass as another selection.
6181: */
1.126 brouard 6182:
1.227 brouard 6183: int i, m, jk, j1, bool, z1,j, iv;
6184: int mi; /* Effective wave */
6185: int iage;
6186: double agebegin, ageend;
6187:
6188: double **prop;
6189: double posprop;
6190: double y2; /* in fractional years */
6191: int iagemin, iagemax;
6192: int first; /** to stop verbosity which is redirected to log file */
6193:
6194: iagemin= (int) agemin;
6195: iagemax= (int) agemax;
6196: /*pp=vector(1,nlstate);*/
1.251 brouard 6197: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6198: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6199: j1=0;
1.222 brouard 6200:
1.227 brouard 6201: /*j=cptcoveff;*/
6202: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6203:
1.288 brouard 6204: first=0;
1.335 brouard 6205: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6206: for (i=1; i<=nlstate; i++)
1.251 brouard 6207: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6208: prop[i][iage]=0.0;
6209: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6210: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6211: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6212:
6213: for (i=1; i<=imx; i++) { /* Each individual */
6214: bool=1;
6215: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6216: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6217: m=mw[mi][i];
6218: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6219: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6220: for (z1=1; z1<=cptcoveff; z1++){
6221: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6222: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6223: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6224: bool=0;
6225: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6226: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6227: bool=0;
6228: }
6229: }
6230: if(bool==1){ /* Otherwise we skip that wave/person */
6231: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6232: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6233: if(m >=firstpass && m <=lastpass){
6234: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6235: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6236: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6237: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6238: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6239: 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);
6240: exit(1);
6241: }
6242: if (s[m][i]>0 && s[m][i]<=nlstate) {
6243: /*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]]);*/
6244: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6245: prop[s[m][i]][iagemax+3] += weight[i];
6246: } /* end valid statuses */
6247: } /* end selection of dates */
6248: } /* end selection of waves */
6249: } /* end bool */
6250: } /* end wave */
6251: } /* end individual */
6252: for(i=iagemin; i <= iagemax+3; i++){
6253: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6254: posprop += prop[jk][i];
6255: }
6256:
6257: for(jk=1; jk <=nlstate ; jk++){
6258: if( i <= iagemax){
6259: if(posprop>=1.e-5){
6260: probs[i][jk][j1]= prop[jk][i]/posprop;
6261: } else{
1.288 brouard 6262: if(!first){
6263: first=1;
1.266 brouard 6264: 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]);
6265: }else{
1.288 brouard 6266: 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 6267: }
6268: }
6269: }
6270: }/* end jk */
6271: }/* end i */
1.222 brouard 6272: /*} *//* end i1 */
1.227 brouard 6273: } /* end j1 */
1.222 brouard 6274:
1.227 brouard 6275: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6276: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6277: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6278: } /* End of prevalence */
1.126 brouard 6279:
6280: /************* Waves Concatenation ***************/
6281:
6282: 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)
6283: {
1.298 brouard 6284: /* 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 6285: Death is a valid wave (if date is known).
6286: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6287: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6288: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6289: */
1.126 brouard 6290:
1.224 brouard 6291: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6292: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6293: double sum=0., jmean=0.;*/
1.224 brouard 6294: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6295: int j, k=0,jk, ju, jl;
6296: double sum=0.;
6297: first=0;
1.214 brouard 6298: firstwo=0;
1.217 brouard 6299: firsthree=0;
1.218 brouard 6300: firstfour=0;
1.164 brouard 6301: jmin=100000;
1.126 brouard 6302: jmax=-1;
6303: jmean=0.;
1.224 brouard 6304:
6305: /* Treating live states */
1.214 brouard 6306: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6307: mi=0; /* First valid wave */
1.227 brouard 6308: mli=0; /* Last valid wave */
1.309 brouard 6309: m=firstpass; /* Loop on waves */
6310: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6311: 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 */
6312: mli=m-1;/* mw[++mi][i]=m-1; */
6313: }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 6314: 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 6315: mli=m;
1.224 brouard 6316: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6317: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6318: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6319: }
1.309 brouard 6320: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6321: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6322: break;
1.224 brouard 6323: #else
1.317 brouard 6324: 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 6325: if(firsthree == 0){
1.302 brouard 6326: 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 6327: firsthree=1;
1.317 brouard 6328: }else if(firsthree >=1 && firsthree < 10){
6329: 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);
6330: firsthree++;
6331: }else if(firsthree == 10){
6332: printf("Information, too many Information flags: no more reported to log either\n");
6333: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6334: firsthree++;
6335: }else{
6336: firsthree++;
1.227 brouard 6337: }
1.309 brouard 6338: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6339: mli=m;
6340: }
6341: if(s[m][i]==-2){ /* Vital status is really unknown */
6342: nbwarn++;
1.309 brouard 6343: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6344: 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);
6345: 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);
6346: }
6347: break;
6348: }
6349: break;
1.224 brouard 6350: #endif
1.227 brouard 6351: }/* End m >= lastpass */
1.126 brouard 6352: }/* end while */
1.224 brouard 6353:
1.227 brouard 6354: /* 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 6355: /* After last pass */
1.224 brouard 6356: /* Treating death states */
1.214 brouard 6357: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6358: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6359: /* } */
1.126 brouard 6360: mi++; /* Death is another wave */
6361: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6362: /* Only death is a correct wave */
1.126 brouard 6363: mw[mi][i]=m;
1.257 brouard 6364: } /* else not in a death state */
1.224 brouard 6365: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6366: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6367: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6368: 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 6369: nbwarn++;
6370: if(firstfiv==0){
1.309 brouard 6371: 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 6372: firstfiv=1;
6373: }else{
1.309 brouard 6374: 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 6375: }
1.309 brouard 6376: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6377: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6378: nberr++;
6379: if(firstwo==0){
1.309 brouard 6380: 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 6381: firstwo=1;
6382: }
1.309 brouard 6383: 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 6384: }
1.257 brouard 6385: }else{ /* if date of interview is unknown */
1.227 brouard 6386: /* death is known but not confirmed by death status at any wave */
6387: if(firstfour==0){
1.309 brouard 6388: 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 6389: firstfour=1;
6390: }
1.309 brouard 6391: 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 6392: }
1.224 brouard 6393: } /* end if date of death is known */
6394: #endif
1.309 brouard 6395: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6396: /* wav[i]=mw[mi][i]; */
1.126 brouard 6397: if(mi==0){
6398: nbwarn++;
6399: if(first==0){
1.227 brouard 6400: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6401: first=1;
1.126 brouard 6402: }
6403: if(first==1){
1.227 brouard 6404: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6405: }
6406: } /* end mi==0 */
6407: } /* End individuals */
1.214 brouard 6408: /* wav and mw are no more changed */
1.223 brouard 6409:
1.317 brouard 6410: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6411: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6412:
6413:
1.126 brouard 6414: for(i=1; i<=imx; i++){
6415: for(mi=1; mi<wav[i];mi++){
6416: if (stepm <=0)
1.227 brouard 6417: dh[mi][i]=1;
1.126 brouard 6418: else{
1.260 brouard 6419: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6420: if (agedc[i] < 2*AGESUP) {
6421: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6422: if(j==0) j=1; /* Survives at least one month after exam */
6423: else if(j<0){
6424: nberr++;
6425: 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]);
6426: j=1; /* Temporary Dangerous patch */
6427: 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);
6428: 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]);
6429: 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);
6430: }
6431: k=k+1;
6432: if (j >= jmax){
6433: jmax=j;
6434: ijmax=i;
6435: }
6436: if (j <= jmin){
6437: jmin=j;
6438: ijmin=i;
6439: }
6440: sum=sum+j;
6441: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6442: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6443: }
6444: }
6445: else{
6446: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6447: /* 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 6448:
1.227 brouard 6449: k=k+1;
6450: if (j >= jmax) {
6451: jmax=j;
6452: ijmax=i;
6453: }
6454: else if (j <= jmin){
6455: jmin=j;
6456: ijmin=i;
6457: }
6458: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6459: /*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]);*/
6460: if(j<0){
6461: nberr++;
6462: 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]);
6463: 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]);
6464: }
6465: sum=sum+j;
6466: }
6467: jk= j/stepm;
6468: jl= j -jk*stepm;
6469: ju= j -(jk+1)*stepm;
6470: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6471: if(jl==0){
6472: dh[mi][i]=jk;
6473: bh[mi][i]=0;
6474: }else{ /* We want a negative bias in order to only have interpolation ie
6475: * to avoid the price of an extra matrix product in likelihood */
6476: dh[mi][i]=jk+1;
6477: bh[mi][i]=ju;
6478: }
6479: }else{
6480: if(jl <= -ju){
6481: dh[mi][i]=jk;
6482: bh[mi][i]=jl; /* bias is positive if real duration
6483: * is higher than the multiple of stepm and negative otherwise.
6484: */
6485: }
6486: else{
6487: dh[mi][i]=jk+1;
6488: bh[mi][i]=ju;
6489: }
6490: if(dh[mi][i]==0){
6491: dh[mi][i]=1; /* At least one step */
6492: bh[mi][i]=ju; /* At least one step */
6493: /* 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);*/
6494: }
6495: } /* end if mle */
1.126 brouard 6496: }
6497: } /* end wave */
6498: }
6499: jmean=sum/k;
6500: 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 6501: 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 6502: }
1.126 brouard 6503:
6504: /*********** Tricode ****************************/
1.220 brouard 6505: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6506: {
6507: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6508: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6509: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6510: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6511: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6512: */
1.130 brouard 6513:
1.242 brouard 6514: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6515: int modmaxcovj=0; /* Modality max of covariates j */
6516: int cptcode=0; /* Modality max of covariates j */
6517: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6518:
6519:
1.242 brouard 6520: /* cptcoveff=0; */
6521: /* *cptcov=0; */
1.126 brouard 6522:
1.242 brouard 6523: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6524: for (k=1; k <= maxncov; k++)
6525: for(j=1; j<=2; j++)
6526: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6527:
1.242 brouard 6528: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6529: 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 6530: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6531: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 6532: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 3 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 6533: switch(Fixed[k]) {
6534: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6535: modmaxcovj=0;
6536: modmincovj=0;
1.242 brouard 6537: 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 6538: /* 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 6539: ij=(int)(covar[Tvar[k]][i]);
6540: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6541: * If product of Vn*Vm, still boolean *:
6542: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6543: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6544: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6545: modality of the nth covariate of individual i. */
6546: if (ij > modmaxcovj)
6547: modmaxcovj=ij;
6548: else if (ij < modmincovj)
6549: modmincovj=ij;
1.287 brouard 6550: if (ij <0 || ij >1 ){
1.311 brouard 6551: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6552: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6553: fflush(ficlog);
6554: exit(1);
1.287 brouard 6555: }
6556: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6557: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6558: exit(1);
6559: }else
6560: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6561: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6562: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6563: /* getting the maximum value of the modality of the covariate
6564: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6565: female ies 1, then modmaxcovj=1.
6566: */
6567: } /* end for loop on individuals i */
6568: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6569: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6570: cptcode=modmaxcovj;
6571: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6572: /*for (i=0; i<=cptcode; i++) {*/
6573: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6574: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6575: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6576: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6577: if( j != -1){
6578: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6579: covariate for which somebody answered excluding
6580: undefined. Usually 2: 0 and 1. */
6581: }
6582: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6583: covariate for which somebody answered including
6584: undefined. Usually 3: -1, 0 and 1. */
6585: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6586: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6587: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6588:
1.242 brouard 6589: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6590: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6591: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6592: /* modmincovj=3; modmaxcovj = 7; */
6593: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6594: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6595: /* defining two dummy variables: variables V1_1 and V1_2.*/
6596: /* nbcode[Tvar[j]][ij]=k; */
6597: /* nbcode[Tvar[j]][1]=0; */
6598: /* nbcode[Tvar[j]][2]=1; */
6599: /* nbcode[Tvar[j]][3]=2; */
6600: /* To be continued (not working yet). */
6601: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6602:
6603: /* 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*/
6604: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6605: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6606: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6607: /*, could be restored in the future */
6608: 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 6609: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6610: break;
6611: }
6612: ij++;
1.287 brouard 6613: 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 6614: cptcode = ij; /* New max modality for covar j */
6615: } /* end of loop on modality i=-1 to 1 or more */
6616: break;
6617: case 1: /* Testing on varying covariate, could be simple and
6618: * should look at waves or product of fixed *
6619: * varying. No time to test -1, assuming 0 and 1 only */
6620: ij=0;
6621: for(i=0; i<=1;i++){
6622: nbcode[Tvar[k]][++ij]=i;
6623: }
6624: break;
6625: default:
6626: break;
6627: } /* end switch */
6628: } /* end dummy test */
1.349 brouard 6629: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6630: 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 6631: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6632: printf("Error k=%d \n",k);
6633: exit(1);
6634: }
1.311 brouard 6635: if(isnan(covar[Tvar[k]][i])){
6636: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6637: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6638: fflush(ficlog);
6639: exit(1);
6640: }
6641: }
1.335 brouard 6642: } /* end Quanti */
1.287 brouard 6643: } /* 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 6644:
6645: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6646: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6647: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6648: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6649: 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 */
6650: 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 */
6651: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6652: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6653:
6654: ij=0;
6655: /* 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 6656: 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 */
6657: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6658: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6659: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6660: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6661: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6662: /* 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 6663: /* If product not in single variable we don't print results */
6664: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6665: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6666: /* k= 1 2 3 4 5 6 7 8 9 */
6667: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6668: /* ij 1 2 3 */
6669: /* Tvaraff[ij]= 4 3 1 */
6670: /* Tmodelind[ij]=2 3 9 */
6671: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6672: 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*/
6673: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6674: 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 */
6675: if(Fixed[k]!=0)
6676: anyvaryingduminmodel=1;
6677: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6678: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6679: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6680: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6681: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6682: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6683: }
6684: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6685: /* ij--; */
6686: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6687: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6688: * because they can be excluded from the model and real
6689: * if in the model but excluded because missing values, but how to get k from ij?*/
6690: for(j=ij+1; j<= cptcovt; j++){
6691: Tvaraff[j]=0;
6692: Tmodelind[j]=0;
6693: }
6694: for(j=ntveff+1; j<= cptcovt; j++){
6695: TmodelInvind[j]=0;
6696: }
6697: /* To be sorted */
6698: ;
6699: }
1.126 brouard 6700:
1.145 brouard 6701:
1.126 brouard 6702: /*********** Health Expectancies ****************/
6703:
1.235 brouard 6704: 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 6705:
6706: {
6707: /* Health expectancies, no variances */
1.329 brouard 6708: /* cij is the combination in the list of combination of dummy covariates */
6709: /* strstart is a string of time at start of computing */
1.164 brouard 6710: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6711: int nhstepma, nstepma; /* Decreasing with age */
6712: double age, agelim, hf;
6713: double ***p3mat;
6714: double eip;
6715:
1.238 brouard 6716: /* pstamp(ficreseij); */
1.126 brouard 6717: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6718: fprintf(ficreseij,"# Age");
6719: for(i=1; i<=nlstate;i++){
6720: for(j=1; j<=nlstate;j++){
6721: fprintf(ficreseij," e%1d%1d ",i,j);
6722: }
6723: fprintf(ficreseij," e%1d. ",i);
6724: }
6725: fprintf(ficreseij,"\n");
6726:
6727:
6728: if(estepm < stepm){
6729: printf ("Problem %d lower than %d\n",estepm, stepm);
6730: }
6731: else hstepm=estepm;
6732: /* We compute the life expectancy from trapezoids spaced every estepm months
6733: * This is mainly to measure the difference between two models: for example
6734: * if stepm=24 months pijx are given only every 2 years and by summing them
6735: * we are calculating an estimate of the Life Expectancy assuming a linear
6736: * progression in between and thus overestimating or underestimating according
6737: * to the curvature of the survival function. If, for the same date, we
6738: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6739: * to compare the new estimate of Life expectancy with the same linear
6740: * hypothesis. A more precise result, taking into account a more precise
6741: * curvature will be obtained if estepm is as small as stepm. */
6742:
6743: /* For example we decided to compute the life expectancy with the smallest unit */
6744: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6745: nhstepm is the number of hstepm from age to agelim
6746: nstepm is the number of stepm from age to agelin.
1.270 brouard 6747: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6748: and note for a fixed period like estepm months */
6749: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6750: survival function given by stepm (the optimization length). Unfortunately it
6751: means that if the survival funtion is printed only each two years of age and if
6752: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6753: results. So we changed our mind and took the option of the best precision.
6754: */
6755: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6756:
6757: agelim=AGESUP;
6758: /* If stepm=6 months */
6759: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6760: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6761:
6762: /* nhstepm age range expressed in number of stepm */
6763: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6764: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6765: /* if (stepm >= YEARM) hstepm=1;*/
6766: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6767: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6768:
6769: for (age=bage; age<=fage; age ++){
6770: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6771: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6772: /* if (stepm >= YEARM) hstepm=1;*/
6773: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6774:
6775: /* If stepm=6 months */
6776: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6777: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6778: /* 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 6779: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6780:
6781: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6782:
6783: printf("%d|",(int)age);fflush(stdout);
6784: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6785:
6786: /* Computing expectancies */
6787: for(i=1; i<=nlstate;i++)
6788: for(j=1; j<=nlstate;j++)
6789: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6790: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6791:
6792: /* 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]);*/
6793:
6794: }
6795:
6796: fprintf(ficreseij,"%3.0f",age );
6797: for(i=1; i<=nlstate;i++){
6798: eip=0;
6799: for(j=1; j<=nlstate;j++){
6800: eip +=eij[i][j][(int)age];
6801: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6802: }
6803: fprintf(ficreseij,"%9.4f", eip );
6804: }
6805: fprintf(ficreseij,"\n");
6806:
6807: }
6808: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6809: printf("\n");
6810: fprintf(ficlog,"\n");
6811:
6812: }
6813:
1.235 brouard 6814: 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 6815:
6816: {
6817: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6818: to initial status i, ei. .
1.126 brouard 6819: */
1.336 brouard 6820: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6821: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6822: int nhstepma, nstepma; /* Decreasing with age */
6823: double age, agelim, hf;
6824: double ***p3matp, ***p3matm, ***varhe;
6825: double **dnewm,**doldm;
6826: double *xp, *xm;
6827: double **gp, **gm;
6828: double ***gradg, ***trgradg;
6829: int theta;
6830:
6831: double eip, vip;
6832:
6833: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6834: xp=vector(1,npar);
6835: xm=vector(1,npar);
6836: dnewm=matrix(1,nlstate*nlstate,1,npar);
6837: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6838:
6839: pstamp(ficresstdeij);
6840: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6841: fprintf(ficresstdeij,"# Age");
6842: for(i=1; i<=nlstate;i++){
6843: for(j=1; j<=nlstate;j++)
6844: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6845: fprintf(ficresstdeij," e%1d. ",i);
6846: }
6847: fprintf(ficresstdeij,"\n");
6848:
6849: pstamp(ficrescveij);
6850: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6851: fprintf(ficrescveij,"# Age");
6852: for(i=1; i<=nlstate;i++)
6853: for(j=1; j<=nlstate;j++){
6854: cptj= (j-1)*nlstate+i;
6855: for(i2=1; i2<=nlstate;i2++)
6856: for(j2=1; j2<=nlstate;j2++){
6857: cptj2= (j2-1)*nlstate+i2;
6858: if(cptj2 <= cptj)
6859: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6860: }
6861: }
6862: fprintf(ficrescveij,"\n");
6863:
6864: if(estepm < stepm){
6865: printf ("Problem %d lower than %d\n",estepm, stepm);
6866: }
6867: else hstepm=estepm;
6868: /* We compute the life expectancy from trapezoids spaced every estepm months
6869: * This is mainly to measure the difference between two models: for example
6870: * if stepm=24 months pijx are given only every 2 years and by summing them
6871: * we are calculating an estimate of the Life Expectancy assuming a linear
6872: * progression in between and thus overestimating or underestimating according
6873: * to the curvature of the survival function. If, for the same date, we
6874: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6875: * to compare the new estimate of Life expectancy with the same linear
6876: * hypothesis. A more precise result, taking into account a more precise
6877: * curvature will be obtained if estepm is as small as stepm. */
6878:
6879: /* For example we decided to compute the life expectancy with the smallest unit */
6880: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6881: nhstepm is the number of hstepm from age to agelim
6882: nstepm is the number of stepm from age to agelin.
6883: Look at hpijx to understand the reason of that which relies in memory size
6884: and note for a fixed period like estepm months */
6885: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6886: survival function given by stepm (the optimization length). Unfortunately it
6887: means that if the survival funtion is printed only each two years of age and if
6888: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6889: results. So we changed our mind and took the option of the best precision.
6890: */
6891: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6892:
6893: /* If stepm=6 months */
6894: /* nhstepm age range expressed in number of stepm */
6895: agelim=AGESUP;
6896: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6897: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6898: /* if (stepm >= YEARM) hstepm=1;*/
6899: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6900:
6901: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6902: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6903: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6904: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6905: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6906: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6907:
6908: for (age=bage; age<=fage; age ++){
6909: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6910: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6911: /* if (stepm >= YEARM) hstepm=1;*/
6912: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6913:
1.126 brouard 6914: /* If stepm=6 months */
6915: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6916: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6917:
6918: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6919:
1.126 brouard 6920: /* Computing Variances of health expectancies */
6921: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6922: decrease memory allocation */
6923: for(theta=1; theta <=npar; theta++){
6924: for(i=1; i<=npar; i++){
1.222 brouard 6925: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6926: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6927: }
1.235 brouard 6928: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6929: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6930:
1.126 brouard 6931: for(j=1; j<= nlstate; j++){
1.222 brouard 6932: for(i=1; i<=nlstate; i++){
6933: for(h=0; h<=nhstepm-1; h++){
6934: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6935: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6936: }
6937: }
1.126 brouard 6938: }
1.218 brouard 6939:
1.126 brouard 6940: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6941: for(h=0; h<=nhstepm-1; h++){
6942: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6943: }
1.126 brouard 6944: }/* End theta */
6945:
6946:
6947: for(h=0; h<=nhstepm-1; h++)
6948: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6949: for(theta=1; theta <=npar; theta++)
6950: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6951:
1.218 brouard 6952:
1.222 brouard 6953: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6954: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6955: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6956:
1.222 brouard 6957: printf("%d|",(int)age);fflush(stdout);
6958: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6959: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6960: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6961: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6962: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6963: for(ij=1;ij<=nlstate*nlstate;ij++)
6964: for(ji=1;ji<=nlstate*nlstate;ji++)
6965: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6966: }
6967: }
1.320 brouard 6968: /* if((int)age ==50){ */
6969: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6970: /* } */
1.126 brouard 6971: /* Computing expectancies */
1.235 brouard 6972: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6973: for(i=1; i<=nlstate;i++)
6974: for(j=1; j<=nlstate;j++)
1.222 brouard 6975: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6976: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6977:
1.222 brouard 6978: /* 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 6979:
1.222 brouard 6980: }
1.269 brouard 6981:
6982: /* Standard deviation of expectancies ij */
1.126 brouard 6983: fprintf(ficresstdeij,"%3.0f",age );
6984: for(i=1; i<=nlstate;i++){
6985: eip=0.;
6986: vip=0.;
6987: for(j=1; j<=nlstate;j++){
1.222 brouard 6988: eip += eij[i][j][(int)age];
6989: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6990: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6991: 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 6992: }
6993: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6994: }
6995: fprintf(ficresstdeij,"\n");
1.218 brouard 6996:
1.269 brouard 6997: /* Variance of expectancies ij */
1.126 brouard 6998: fprintf(ficrescveij,"%3.0f",age );
6999: for(i=1; i<=nlstate;i++)
7000: for(j=1; j<=nlstate;j++){
1.222 brouard 7001: cptj= (j-1)*nlstate+i;
7002: for(i2=1; i2<=nlstate;i2++)
7003: for(j2=1; j2<=nlstate;j2++){
7004: cptj2= (j2-1)*nlstate+i2;
7005: if(cptj2 <= cptj)
7006: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
7007: }
1.126 brouard 7008: }
7009: fprintf(ficrescveij,"\n");
1.218 brouard 7010:
1.126 brouard 7011: }
7012: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
7013: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
7014: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
7015: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
7016: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7017: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7018: printf("\n");
7019: fprintf(ficlog,"\n");
1.218 brouard 7020:
1.126 brouard 7021: free_vector(xm,1,npar);
7022: free_vector(xp,1,npar);
7023: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
7024: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
7025: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
7026: }
1.218 brouard 7027:
1.126 brouard 7028: /************ Variance ******************/
1.235 brouard 7029: 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 7030: {
1.279 brouard 7031: /** Variance of health expectancies
7032: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
7033: * double **newm;
7034: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
7035: */
1.218 brouard 7036:
7037: /* int movingaverage(); */
7038: double **dnewm,**doldm;
7039: double **dnewmp,**doldmp;
7040: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 7041: int first=0;
1.218 brouard 7042: int k;
7043: double *xp;
1.279 brouard 7044: double **gp, **gm; /**< for var eij */
7045: double ***gradg, ***trgradg; /**< for var eij */
7046: double **gradgp, **trgradgp; /**< for var p point j */
7047: double *gpp, *gmp; /**< for var p point j */
7048: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 7049: double ***p3mat;
7050: double age,agelim, hf;
7051: /* double ***mobaverage; */
7052: int theta;
7053: char digit[4];
7054: char digitp[25];
7055:
7056: char fileresprobmorprev[FILENAMELENGTH];
7057:
7058: if(popbased==1){
7059: if(mobilav!=0)
7060: strcpy(digitp,"-POPULBASED-MOBILAV_");
7061: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
7062: }
7063: else
7064: strcpy(digitp,"-STABLBASED_");
1.126 brouard 7065:
1.218 brouard 7066: /* if (mobilav!=0) { */
7067: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7068: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
7069: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
7070: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
7071: /* } */
7072: /* } */
7073:
7074: strcpy(fileresprobmorprev,"PRMORPREV-");
7075: sprintf(digit,"%-d",ij);
7076: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7077: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7078: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7079: strcat(fileresprobmorprev,fileresu);
7080: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7081: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7082: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7083: }
7084: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7085: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7086: pstamp(ficresprobmorprev);
7087: 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 7088: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7089:
7090: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7091: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7092: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7093: /* } */
7094: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7095: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7096: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7097: }
1.337 brouard 7098: /* for(j=1;j<=cptcoveff;j++) */
7099: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7100: fprintf(ficresprobmorprev,"\n");
7101:
1.218 brouard 7102: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7103: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7104: fprintf(ficresprobmorprev," p.%-d SE",j);
7105: for(i=1; i<=nlstate;i++)
7106: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7107: }
7108: fprintf(ficresprobmorprev,"\n");
7109:
7110: fprintf(ficgp,"\n# Routine varevsij");
7111: fprintf(ficgp,"\nunset title \n");
7112: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7113: 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");
7114: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7115:
1.218 brouard 7116: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7117: pstamp(ficresvij);
7118: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7119: if(popbased==1)
7120: 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);
7121: else
7122: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7123: fprintf(ficresvij,"# Age");
7124: for(i=1; i<=nlstate;i++)
7125: for(j=1; j<=nlstate;j++)
7126: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7127: fprintf(ficresvij,"\n");
7128:
7129: xp=vector(1,npar);
7130: dnewm=matrix(1,nlstate,1,npar);
7131: doldm=matrix(1,nlstate,1,nlstate);
7132: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7133: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7134:
7135: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7136: gpp=vector(nlstate+1,nlstate+ndeath);
7137: gmp=vector(nlstate+1,nlstate+ndeath);
7138: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7139:
1.218 brouard 7140: if(estepm < stepm){
7141: printf ("Problem %d lower than %d\n",estepm, stepm);
7142: }
7143: else hstepm=estepm;
7144: /* For example we decided to compute the life expectancy with the smallest unit */
7145: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7146: nhstepm is the number of hstepm from age to agelim
7147: nstepm is the number of stepm from age to agelim.
7148: Look at function hpijx to understand why because of memory size limitations,
7149: we decided (b) to get a life expectancy respecting the most precise curvature of the
7150: survival function given by stepm (the optimization length). Unfortunately it
7151: means that if the survival funtion is printed every two years of age and if
7152: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7153: results. So we changed our mind and took the option of the best precision.
7154: */
7155: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7156: agelim = AGESUP;
7157: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7158: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7159: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7160: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7161: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7162: gp=matrix(0,nhstepm,1,nlstate);
7163: gm=matrix(0,nhstepm,1,nlstate);
7164:
7165:
7166: for(theta=1; theta <=npar; theta++){
7167: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7168: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7169: }
1.279 brouard 7170: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7171: * returns into prlim .
1.288 brouard 7172: */
1.242 brouard 7173: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7174:
7175: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7176: if (popbased==1) {
7177: if(mobilav ==0){
7178: for(i=1; i<=nlstate;i++)
7179: prlim[i][i]=probs[(int)age][i][ij];
7180: }else{ /* mobilav */
7181: for(i=1; i<=nlstate;i++)
7182: prlim[i][i]=mobaverage[(int)age][i][ij];
7183: }
7184: }
1.295 brouard 7185: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7186: */
7187: 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 7188: /**< 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 7189: * at horizon h in state j including mortality.
7190: */
1.218 brouard 7191: for(j=1; j<= nlstate; j++){
7192: for(h=0; h<=nhstepm; h++){
7193: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7194: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7195: }
7196: }
1.279 brouard 7197: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7198: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7199: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7200: */
7201: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7202: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7203: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7204: }
7205:
7206: /* Again with minus shift */
1.218 brouard 7207:
7208: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7209: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7210:
1.242 brouard 7211: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7212:
7213: if (popbased==1) {
7214: if(mobilav ==0){
7215: for(i=1; i<=nlstate;i++)
7216: prlim[i][i]=probs[(int)age][i][ij];
7217: }else{ /* mobilav */
7218: for(i=1; i<=nlstate;i++)
7219: prlim[i][i]=mobaverage[(int)age][i][ij];
7220: }
7221: }
7222:
1.235 brouard 7223: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7224:
7225: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7226: for(h=0; h<=nhstepm; h++){
7227: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7228: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7229: }
7230: }
7231: /* This for computing probability of death (h=1 means
7232: computed over hstepm matrices product = hstepm*stepm months)
7233: as a weighted average of prlim.
7234: */
7235: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7236: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7237: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7238: }
1.279 brouard 7239: /* end shifting computations */
7240:
7241: /**< Computing gradient matrix at horizon h
7242: */
1.218 brouard 7243: for(j=1; j<= nlstate; j++) /* vareij */
7244: for(h=0; h<=nhstepm; h++){
7245: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7246: }
1.279 brouard 7247: /**< Gradient of overall mortality p.3 (or p.j)
7248: */
7249: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7250: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7251: }
7252:
7253: } /* End theta */
1.279 brouard 7254:
7255: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7256: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7257:
7258: for(h=0; h<=nhstepm; h++) /* veij */
7259: for(j=1; j<=nlstate;j++)
7260: for(theta=1; theta <=npar; theta++)
7261: trgradg[h][j][theta]=gradg[h][theta][j];
7262:
7263: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7264: for(theta=1; theta <=npar; theta++)
7265: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7266: /**< as well as its transposed matrix
7267: */
1.218 brouard 7268:
7269: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7270: for(i=1;i<=nlstate;i++)
7271: for(j=1;j<=nlstate;j++)
7272: vareij[i][j][(int)age] =0.;
1.279 brouard 7273:
7274: /* Computing trgradg by matcov by gradg at age and summing over h
7275: * and k (nhstepm) formula 15 of article
7276: * Lievre-Brouard-Heathcote
7277: */
7278:
1.218 brouard 7279: for(h=0;h<=nhstepm;h++){
7280: for(k=0;k<=nhstepm;k++){
7281: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7282: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7283: for(i=1;i<=nlstate;i++)
7284: for(j=1;j<=nlstate;j++)
7285: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7286: }
7287: }
7288:
1.279 brouard 7289: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7290: * p.j overall mortality formula 49 but computed directly because
7291: * we compute the grad (wix pijx) instead of grad (pijx),even if
7292: * wix is independent of theta.
7293: */
1.218 brouard 7294: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7295: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7296: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7297: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7298: varppt[j][i]=doldmp[j][i];
7299: /* end ppptj */
7300: /* x centered again */
7301:
1.242 brouard 7302: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7303:
7304: if (popbased==1) {
7305: if(mobilav ==0){
7306: for(i=1; i<=nlstate;i++)
7307: prlim[i][i]=probs[(int)age][i][ij];
7308: }else{ /* mobilav */
7309: for(i=1; i<=nlstate;i++)
7310: prlim[i][i]=mobaverage[(int)age][i][ij];
7311: }
7312: }
7313:
7314: /* This for computing probability of death (h=1 means
7315: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7316: as a weighted average of prlim.
7317: */
1.235 brouard 7318: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7319: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7320: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7321: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7322: }
7323: /* end probability of death */
7324:
7325: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7326: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7327: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7328: for(i=1; i<=nlstate;i++){
7329: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7330: }
7331: }
7332: fprintf(ficresprobmorprev,"\n");
7333:
7334: fprintf(ficresvij,"%.0f ",age );
7335: for(i=1; i<=nlstate;i++)
7336: for(j=1; j<=nlstate;j++){
7337: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7338: }
7339: fprintf(ficresvij,"\n");
7340: free_matrix(gp,0,nhstepm,1,nlstate);
7341: free_matrix(gm,0,nhstepm,1,nlstate);
7342: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7343: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7344: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7345: } /* End age */
7346: free_vector(gpp,nlstate+1,nlstate+ndeath);
7347: free_vector(gmp,nlstate+1,nlstate+ndeath);
7348: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7349: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7350: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7351: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7352: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7353: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7354: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7355: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7356: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7357: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7358: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7359: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7360: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7361: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7362: 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);
7363: /* 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 7364: */
1.218 brouard 7365: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7366: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7367:
1.218 brouard 7368: free_vector(xp,1,npar);
7369: free_matrix(doldm,1,nlstate,1,nlstate);
7370: free_matrix(dnewm,1,nlstate,1,npar);
7371: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7372: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7373: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7374: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7375: fclose(ficresprobmorprev);
7376: fflush(ficgp);
7377: fflush(fichtm);
7378: } /* end varevsij */
1.126 brouard 7379:
7380: /************ Variance of prevlim ******************/
1.269 brouard 7381: 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 7382: {
1.205 brouard 7383: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7384: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7385:
1.268 brouard 7386: double **dnewmpar,**doldm;
1.126 brouard 7387: int i, j, nhstepm, hstepm;
7388: double *xp;
7389: double *gp, *gm;
7390: double **gradg, **trgradg;
1.208 brouard 7391: double **mgm, **mgp;
1.126 brouard 7392: double age,agelim;
7393: int theta;
7394:
7395: pstamp(ficresvpl);
1.288 brouard 7396: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7397: fprintf(ficresvpl,"# Age ");
7398: if(nresult >=1)
7399: fprintf(ficresvpl," Result# ");
1.126 brouard 7400: for(i=1; i<=nlstate;i++)
7401: fprintf(ficresvpl," %1d-%1d",i,i);
7402: fprintf(ficresvpl,"\n");
7403:
7404: xp=vector(1,npar);
1.268 brouard 7405: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7406: doldm=matrix(1,nlstate,1,nlstate);
7407:
7408: hstepm=1*YEARM; /* Every year of age */
7409: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7410: agelim = AGESUP;
7411: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7412: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7413: if (stepm >= YEARM) hstepm=1;
7414: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7415: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7416: mgp=matrix(1,npar,1,nlstate);
7417: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7418: gp=vector(1,nlstate);
7419: gm=vector(1,nlstate);
7420:
7421: for(theta=1; theta <=npar; theta++){
7422: for(i=1; i<=npar; i++){ /* Computes gradient */
7423: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7424: }
1.288 brouard 7425: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7426: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7427: /* else */
7428: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7429: for(i=1;i<=nlstate;i++){
1.126 brouard 7430: gp[i] = prlim[i][i];
1.208 brouard 7431: mgp[theta][i] = prlim[i][i];
7432: }
1.126 brouard 7433: for(i=1; i<=npar; i++) /* Computes gradient */
7434: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7435: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7436: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7437: /* else */
7438: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7439: for(i=1;i<=nlstate;i++){
1.126 brouard 7440: gm[i] = prlim[i][i];
1.208 brouard 7441: mgm[theta][i] = prlim[i][i];
7442: }
1.126 brouard 7443: for(i=1;i<=nlstate;i++)
7444: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7445: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7446: } /* End theta */
7447:
7448: trgradg =matrix(1,nlstate,1,npar);
7449:
7450: for(j=1; j<=nlstate;j++)
7451: for(theta=1; theta <=npar; theta++)
7452: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7453: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7454: /* printf("\nmgm mgp %d ",(int)age); */
7455: /* for(j=1; j<=nlstate;j++){ */
7456: /* printf(" %d ",j); */
7457: /* for(theta=1; theta <=npar; theta++) */
7458: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7459: /* printf("\n "); */
7460: /* } */
7461: /* } */
7462: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7463: /* printf("\n gradg %d ",(int)age); */
7464: /* for(j=1; j<=nlstate;j++){ */
7465: /* printf("%d ",j); */
7466: /* for(theta=1; theta <=npar; theta++) */
7467: /* printf("%d %lf ",theta,gradg[theta][j]); */
7468: /* printf("\n "); */
7469: /* } */
7470: /* } */
1.126 brouard 7471:
7472: for(i=1;i<=nlstate;i++)
7473: varpl[i][(int)age] =0.;
1.209 brouard 7474: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7475: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7476: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7477: }else{
1.268 brouard 7478: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7479: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7480: }
1.126 brouard 7481: for(i=1;i<=nlstate;i++)
7482: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7483:
7484: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7485: if(nresult >=1)
7486: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7487: for(i=1; i<=nlstate;i++){
1.126 brouard 7488: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7489: /* for(j=1;j<=nlstate;j++) */
7490: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7491: }
1.126 brouard 7492: fprintf(ficresvpl,"\n");
7493: free_vector(gp,1,nlstate);
7494: free_vector(gm,1,nlstate);
1.208 brouard 7495: free_matrix(mgm,1,npar,1,nlstate);
7496: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7497: free_matrix(gradg,1,npar,1,nlstate);
7498: free_matrix(trgradg,1,nlstate,1,npar);
7499: } /* End age */
7500:
7501: free_vector(xp,1,npar);
7502: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7503: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7504:
7505: }
7506:
7507:
7508: /************ Variance of backprevalence limit ******************/
1.269 brouard 7509: 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 7510: {
7511: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7512: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7513:
7514: double **dnewmpar,**doldm;
7515: int i, j, nhstepm, hstepm;
7516: double *xp;
7517: double *gp, *gm;
7518: double **gradg, **trgradg;
7519: double **mgm, **mgp;
7520: double age,agelim;
7521: int theta;
7522:
7523: pstamp(ficresvbl);
7524: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7525: fprintf(ficresvbl,"# Age ");
7526: if(nresult >=1)
7527: fprintf(ficresvbl," Result# ");
7528: for(i=1; i<=nlstate;i++)
7529: fprintf(ficresvbl," %1d-%1d",i,i);
7530: fprintf(ficresvbl,"\n");
7531:
7532: xp=vector(1,npar);
7533: dnewmpar=matrix(1,nlstate,1,npar);
7534: doldm=matrix(1,nlstate,1,nlstate);
7535:
7536: hstepm=1*YEARM; /* Every year of age */
7537: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7538: agelim = AGEINF;
7539: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7540: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7541: if (stepm >= YEARM) hstepm=1;
7542: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7543: gradg=matrix(1,npar,1,nlstate);
7544: mgp=matrix(1,npar,1,nlstate);
7545: mgm=matrix(1,npar,1,nlstate);
7546: gp=vector(1,nlstate);
7547: gm=vector(1,nlstate);
7548:
7549: for(theta=1; theta <=npar; theta++){
7550: for(i=1; i<=npar; i++){ /* Computes gradient */
7551: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7552: }
7553: if(mobilavproj > 0 )
7554: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7555: else
7556: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7557: for(i=1;i<=nlstate;i++){
7558: gp[i] = bprlim[i][i];
7559: mgp[theta][i] = bprlim[i][i];
7560: }
7561: for(i=1; i<=npar; i++) /* Computes gradient */
7562: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7563: if(mobilavproj > 0 )
7564: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7565: else
7566: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7567: for(i=1;i<=nlstate;i++){
7568: gm[i] = bprlim[i][i];
7569: mgm[theta][i] = bprlim[i][i];
7570: }
7571: for(i=1;i<=nlstate;i++)
7572: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7573: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7574: } /* End theta */
7575:
7576: trgradg =matrix(1,nlstate,1,npar);
7577:
7578: for(j=1; j<=nlstate;j++)
7579: for(theta=1; theta <=npar; theta++)
7580: trgradg[j][theta]=gradg[theta][j];
7581: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7582: /* printf("\nmgm mgp %d ",(int)age); */
7583: /* for(j=1; j<=nlstate;j++){ */
7584: /* printf(" %d ",j); */
7585: /* for(theta=1; theta <=npar; theta++) */
7586: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7587: /* printf("\n "); */
7588: /* } */
7589: /* } */
7590: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7591: /* printf("\n gradg %d ",(int)age); */
7592: /* for(j=1; j<=nlstate;j++){ */
7593: /* printf("%d ",j); */
7594: /* for(theta=1; theta <=npar; theta++) */
7595: /* printf("%d %lf ",theta,gradg[theta][j]); */
7596: /* printf("\n "); */
7597: /* } */
7598: /* } */
7599:
7600: for(i=1;i<=nlstate;i++)
7601: varbpl[i][(int)age] =0.;
7602: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7603: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7604: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7605: }else{
7606: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7607: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7608: }
7609: for(i=1;i<=nlstate;i++)
7610: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7611:
7612: fprintf(ficresvbl,"%.0f ",age );
7613: if(nresult >=1)
7614: fprintf(ficresvbl,"%d ",nres );
7615: for(i=1; i<=nlstate;i++)
7616: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7617: fprintf(ficresvbl,"\n");
7618: free_vector(gp,1,nlstate);
7619: free_vector(gm,1,nlstate);
7620: free_matrix(mgm,1,npar,1,nlstate);
7621: free_matrix(mgp,1,npar,1,nlstate);
7622: free_matrix(gradg,1,npar,1,nlstate);
7623: free_matrix(trgradg,1,nlstate,1,npar);
7624: } /* End age */
7625:
7626: free_vector(xp,1,npar);
7627: free_matrix(doldm,1,nlstate,1,npar);
7628: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7629:
7630: }
7631:
7632: /************ Variance of one-step probabilities ******************/
7633: 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 7634: {
7635: int i, j=0, k1, l1, tj;
7636: int k2, l2, j1, z1;
7637: int k=0, l;
7638: int first=1, first1, first2;
1.326 brouard 7639: int nres=0; /* New */
1.222 brouard 7640: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7641: double **dnewm,**doldm;
7642: double *xp;
7643: double *gp, *gm;
7644: double **gradg, **trgradg;
7645: double **mu;
7646: double age, cov[NCOVMAX+1];
7647: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7648: int theta;
7649: char fileresprob[FILENAMELENGTH];
7650: char fileresprobcov[FILENAMELENGTH];
7651: char fileresprobcor[FILENAMELENGTH];
7652: double ***varpij;
7653:
7654: strcpy(fileresprob,"PROB_");
1.356 brouard 7655: strcat(fileresprob,fileresu);
1.222 brouard 7656: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7657: printf("Problem with resultfile: %s\n", fileresprob);
7658: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7659: }
7660: strcpy(fileresprobcov,"PROBCOV_");
7661: strcat(fileresprobcov,fileresu);
7662: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7663: printf("Problem with resultfile: %s\n", fileresprobcov);
7664: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7665: }
7666: strcpy(fileresprobcor,"PROBCOR_");
7667: strcat(fileresprobcor,fileresu);
7668: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7669: printf("Problem with resultfile: %s\n", fileresprobcor);
7670: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7671: }
7672: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7673: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7674: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7675: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7676: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7677: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7678: pstamp(ficresprob);
7679: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7680: fprintf(ficresprob,"# Age");
7681: pstamp(ficresprobcov);
7682: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7683: fprintf(ficresprobcov,"# Age");
7684: pstamp(ficresprobcor);
7685: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7686: fprintf(ficresprobcor,"# Age");
1.126 brouard 7687:
7688:
1.222 brouard 7689: for(i=1; i<=nlstate;i++)
7690: for(j=1; j<=(nlstate+ndeath);j++){
7691: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7692: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7693: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7694: }
7695: /* fprintf(ficresprob,"\n");
7696: fprintf(ficresprobcov,"\n");
7697: fprintf(ficresprobcor,"\n");
7698: */
7699: xp=vector(1,npar);
7700: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7701: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7702: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7703: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7704: first=1;
7705: fprintf(ficgp,"\n# Routine varprob");
7706: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7707: fprintf(fichtm,"\n");
7708:
1.288 brouard 7709: 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 7710: 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);
7711: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7712: and drawn. It helps understanding how is the covariance between two incidences.\
7713: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7714: 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 7715: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7716: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7717: standard deviations wide on each axis. <br>\
7718: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7719: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7720: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7721:
1.222 brouard 7722: cov[1]=1;
7723: /* tj=cptcoveff; */
1.225 brouard 7724: tj = (int) pow(2,cptcoveff);
1.222 brouard 7725: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7726: j1=0;
1.332 brouard 7727:
7728: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7729: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7730: /* 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 7731: if(tj != 1 && TKresult[nres]!= j1)
7732: continue;
7733:
7734: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7735: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7736: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7737: if (cptcovn>0) {
1.334 brouard 7738: fprintf(ficresprob, "\n#********** Variable ");
7739: fprintf(ficresprobcov, "\n#********** Variable ");
7740: fprintf(ficgp, "\n#********** Variable ");
7741: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7742: fprintf(ficresprobcor, "\n#********** Variable ");
7743:
7744: /* Including quantitative variables of the resultline to be done */
7745: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7746: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7747: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7748: /* 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 7749: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7750: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7751: 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 */
7752: 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 */
7753: 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 */
7754: 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 */
7755: 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 */
7756: fprintf(ficresprob,"fixed ");
7757: fprintf(ficresprobcov,"fixed ");
7758: fprintf(ficgp,"fixed ");
7759: fprintf(fichtmcov,"fixed ");
7760: fprintf(ficresprobcor,"fixed ");
7761: }else{
7762: fprintf(ficresprob,"varyi ");
7763: fprintf(ficresprobcov,"varyi ");
7764: fprintf(ficgp,"varyi ");
7765: fprintf(fichtmcov,"varyi ");
7766: fprintf(ficresprobcor,"varyi ");
7767: }
7768: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7769: /* For each selected (single) quantitative value */
1.337 brouard 7770: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7771: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7772: fprintf(ficresprob,"fixed ");
7773: fprintf(ficresprobcov,"fixed ");
7774: fprintf(ficgp,"fixed ");
7775: fprintf(fichtmcov,"fixed ");
7776: fprintf(ficresprobcor,"fixed ");
7777: }else{
7778: fprintf(ficresprob,"varyi ");
7779: fprintf(ficresprobcov,"varyi ");
7780: fprintf(ficgp,"varyi ");
7781: fprintf(fichtmcov,"varyi ");
7782: fprintf(ficresprobcor,"varyi ");
7783: }
7784: }else{
7785: 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 */
7786: 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 */
7787: exit(1);
7788: }
7789: } /* End loop on variable of this resultline */
7790: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7791: fprintf(ficresprob, "**********\n#\n");
7792: fprintf(ficresprobcov, "**********\n#\n");
7793: fprintf(ficgp, "**********\n#\n");
7794: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7795: fprintf(ficresprobcor, "**********\n#");
7796: if(invalidvarcomb[j1]){
7797: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7798: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7799: continue;
7800: }
7801: }
7802: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7803: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7804: gp=vector(1,(nlstate)*(nlstate+ndeath));
7805: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7806: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7807: cov[2]=age;
7808: if(nagesqr==1)
7809: cov[3]= age*age;
1.334 brouard 7810: /* New code end of combination but for each resultline */
7811: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 7812: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7813: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7814: }else{
1.334 brouard 7815: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7816: }
1.334 brouard 7817: }/* End of loop on model equation */
7818: /* Old code */
7819: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7820: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7821: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7822: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7823: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7824: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7825: /* * 1 1 1 1 1 */
7826: /* * 2 2 1 1 1 */
7827: /* * 3 1 2 1 1 */
7828: /* *\/ */
7829: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7830: /* } */
7831: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7832: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7833: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7834: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7835: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7836: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7837: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7838: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7839: /* 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]); */
7840: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7841: /* /\* exit(1); *\/ */
7842: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7843: /* } */
7844: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7845: /* } */
7846: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7847: /* if(Dummy[Tvard[k][1]]==0){ */
7848: /* if(Dummy[Tvard[k][2]]==0){ */
7849: /* 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]])]; */
7850: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7851: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7852: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7853: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7854: /* } */
7855: /* }else{ */
7856: /* if(Dummy[Tvard[k][2]]==0){ */
7857: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7858: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7859: /* }else{ */
7860: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7861: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7862: /* } */
7863: /* } */
7864: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7865: /* } */
1.326 brouard 7866: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7867: for(theta=1; theta <=npar; theta++){
7868: for(i=1; i<=npar; i++)
7869: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7870:
1.222 brouard 7871: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7872:
1.222 brouard 7873: k=0;
7874: for(i=1; i<= (nlstate); i++){
7875: for(j=1; j<=(nlstate+ndeath);j++){
7876: k=k+1;
7877: gp[k]=pmmij[i][j];
7878: }
7879: }
1.220 brouard 7880:
1.222 brouard 7881: for(i=1; i<=npar; i++)
7882: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7883:
1.222 brouard 7884: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7885: k=0;
7886: for(i=1; i<=(nlstate); i++){
7887: for(j=1; j<=(nlstate+ndeath);j++){
7888: k=k+1;
7889: gm[k]=pmmij[i][j];
7890: }
7891: }
1.220 brouard 7892:
1.222 brouard 7893: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7894: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7895: }
1.126 brouard 7896:
1.222 brouard 7897: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7898: for(theta=1; theta <=npar; theta++)
7899: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7900:
1.222 brouard 7901: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7902: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7903:
1.222 brouard 7904: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7905:
1.222 brouard 7906: k=0;
7907: for(i=1; i<=(nlstate); i++){
7908: for(j=1; j<=(nlstate+ndeath);j++){
7909: k=k+1;
7910: mu[k][(int) age]=pmmij[i][j];
7911: }
7912: }
7913: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7914: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7915: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7916:
1.222 brouard 7917: /*printf("\n%d ",(int)age);
7918: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7919: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7920: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7921: }*/
1.220 brouard 7922:
1.222 brouard 7923: fprintf(ficresprob,"\n%d ",(int)age);
7924: fprintf(ficresprobcov,"\n%d ",(int)age);
7925: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7926:
1.222 brouard 7927: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7928: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7929: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7930: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7931: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7932: }
7933: i=0;
7934: for (k=1; k<=(nlstate);k++){
7935: for (l=1; l<=(nlstate+ndeath);l++){
7936: i++;
7937: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7938: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7939: for (j=1; j<=i;j++){
7940: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7941: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7942: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7943: }
7944: }
7945: }/* end of loop for state */
7946: } /* end of loop for age */
7947: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7948: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7949: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7950: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7951:
7952: /* Confidence intervalle of pij */
7953: /*
7954: fprintf(ficgp,"\nunset parametric;unset label");
7955: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7956: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7957: 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);
7958: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7959: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7960: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7961: */
7962:
7963: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7964: first1=1;first2=2;
7965: for (k2=1; k2<=(nlstate);k2++){
7966: for (l2=1; l2<=(nlstate+ndeath);l2++){
7967: if(l2==k2) continue;
7968: j=(k2-1)*(nlstate+ndeath)+l2;
7969: for (k1=1; k1<=(nlstate);k1++){
7970: for (l1=1; l1<=(nlstate+ndeath);l1++){
7971: if(l1==k1) continue;
7972: i=(k1-1)*(nlstate+ndeath)+l1;
7973: if(i<=j) continue;
7974: for (age=bage; age<=fage; age ++){
7975: if ((int)age %5==0){
7976: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7977: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7978: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7979: mu1=mu[i][(int) age]/stepm*YEARM ;
7980: mu2=mu[j][(int) age]/stepm*YEARM;
7981: c12=cv12/sqrt(v1*v2);
7982: /* Computing eigen value of matrix of covariance */
7983: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7984: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7985: if ((lc2 <0) || (lc1 <0) ){
7986: if(first2==1){
7987: first1=0;
7988: 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);
7989: }
7990: 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);
7991: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7992: /* lc2=fabs(lc2); */
7993: }
1.220 brouard 7994:
1.222 brouard 7995: /* Eigen vectors */
1.280 brouard 7996: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7997: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7998: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7999: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
8000: }else
8001: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 8002: /*v21=sqrt(1.-v11*v11); *//* error */
8003: v21=(lc1-v1)/cv12*v11;
8004: v12=-v21;
8005: v22=v11;
8006: tnalp=v21/v11;
8007: if(first1==1){
8008: first1=0;
8009: 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);
8010: }
8011: 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);
8012: /*printf(fignu*/
8013: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
8014: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
8015: if(first==1){
8016: first=0;
8017: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
8018: fprintf(ficgp,"\nset parametric;unset label");
8019: 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);
8020: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 8021: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 8022: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 8023: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 8024: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
8025: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8026: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8027: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
8028: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8029: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
8030: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
8031: 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 8032: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
8033: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 8034: }else{
8035: first=0;
8036: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
8037: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
8038: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
8039: 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 8040: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
8041: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 8042: }/* if first */
8043: } /* age mod 5 */
8044: } /* end loop age */
8045: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8046: first=1;
8047: } /*l12 */
8048: } /* k12 */
8049: } /*l1 */
8050: }/* k1 */
1.332 brouard 8051: } /* loop on combination of covariates j1 */
1.326 brouard 8052: } /* loop on nres */
1.222 brouard 8053: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
8054: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
8055: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
8056: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
8057: free_vector(xp,1,npar);
8058: fclose(ficresprob);
8059: fclose(ficresprobcov);
8060: fclose(ficresprobcor);
8061: fflush(ficgp);
8062: fflush(fichtmcov);
8063: }
1.126 brouard 8064:
8065:
8066: /******************* Printing html file ***********/
1.201 brouard 8067: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8068: int lastpass, int stepm, int weightopt, char model[],\
8069: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 8070: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
8071: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
8072: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 8073: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 8074: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8075: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8076: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8077: </ul>");
1.319 brouard 8078: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8079: /* </ul>", model); */
1.214 brouard 8080: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8081: 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",
8082: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8083: 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 8084: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8085: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8086: fprintf(fichtm,"\
8087: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8088: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8089: fprintf(fichtm,"\
1.217 brouard 8090: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8091: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8092: fprintf(fichtm,"\
1.288 brouard 8093: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8094: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8095: fprintf(fichtm,"\
1.288 brouard 8096: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8097: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8098: fprintf(fichtm,"\
1.211 brouard 8099: - (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 8100: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8101: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8102: if(prevfcast==1){
8103: fprintf(fichtm,"\
8104: - Prevalence projections by age and states: \
1.201 brouard 8105: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8106: }
1.126 brouard 8107:
8108:
1.225 brouard 8109: m=pow(2,cptcoveff);
1.222 brouard 8110: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8111:
1.317 brouard 8112: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8113:
8114: jj1=0;
8115:
8116: fprintf(fichtm," \n<ul>");
1.337 brouard 8117: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8118: /* k1=nres; */
1.338 brouard 8119: k1=TKresult[nres];
8120: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8121: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8122: /* if(m != 1 && TKresult[nres]!= k1) */
8123: /* continue; */
1.264 brouard 8124: jj1++;
8125: if (cptcovn > 0) {
8126: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8127: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8128: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8129: }
1.337 brouard 8130: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8131: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8132: /* } */
8133: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8134: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8135: /* } */
1.264 brouard 8136: fprintf(fichtm,"\">");
8137:
8138: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8139: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8140: for (cpt=1; cpt<=cptcovs;cpt++){
8141: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8142: }
1.337 brouard 8143: /* fprintf(fichtm,"************ Results for covariates"); */
8144: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8145: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8146: /* } */
8147: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8148: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8149: /* } */
1.264 brouard 8150: if(invalidvarcomb[k1]){
8151: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8152: continue;
8153: }
8154: fprintf(fichtm,"</a></li>");
8155: } /* cptcovn >0 */
8156: }
1.317 brouard 8157: fprintf(fichtm," \n</ul>");
1.264 brouard 8158:
1.222 brouard 8159: jj1=0;
1.237 brouard 8160:
1.337 brouard 8161: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8162: /* k1=nres; */
1.338 brouard 8163: k1=TKresult[nres];
8164: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8165: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8166: /* if(m != 1 && TKresult[nres]!= k1) */
8167: /* continue; */
1.220 brouard 8168:
1.222 brouard 8169: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8170: jj1++;
8171: if (cptcovn > 0) {
1.264 brouard 8172: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8173: for (cpt=1; cpt<=cptcovs;cpt++){
8174: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8175: }
1.337 brouard 8176: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8177: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8178: /* } */
1.264 brouard 8179: fprintf(fichtm,"\"</a>");
8180:
1.222 brouard 8181: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8182: for (cpt=1; cpt<=cptcovs;cpt++){
8183: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8184: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8185: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8186: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8187: }
1.230 brouard 8188: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8189: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8190: if(invalidvarcomb[k1]){
8191: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8192: printf("\nCombination (%d) ignored because no cases \n",k1);
8193: continue;
8194: }
8195: }
8196: /* aij, bij */
1.259 brouard 8197: 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 8198: <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 8199: /* Pij */
1.241 brouard 8200: 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> \
8201: <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 8202: /* Quasi-incidences */
8203: 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 8204: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8205: 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 8206: 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> \
8207: <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 8208: /* Survival functions (period) in state j */
8209: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8210: 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);
8211: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8212: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8213: }
8214: /* State specific survival functions (period) */
8215: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8216: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8217: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8218: <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);
8219: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8220: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8221: }
1.288 brouard 8222: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8223: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8224: 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 8225: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8226: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8227: }
1.296 brouard 8228: if(prevbcast==1){
1.288 brouard 8229: /* Backward prevalence in each health state */
1.222 brouard 8230: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8231: 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);
8232: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8233: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8234: }
1.217 brouard 8235: }
1.222 brouard 8236: if(prevfcast==1){
1.288 brouard 8237: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8238: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8239: 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);
8240: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8241: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8242: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8243: }
8244: }
1.296 brouard 8245: if(prevbcast==1){
1.268 brouard 8246: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8247: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8248: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8249: 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 \
8250: 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 8251: 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);
8252: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8253: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8254: }
8255: }
1.220 brouard 8256:
1.222 brouard 8257: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8258: 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);
8259: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8260: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8261: }
8262: /* } /\* end i1 *\/ */
1.337 brouard 8263: }/* End k1=nres */
1.222 brouard 8264: fprintf(fichtm,"</ul>");
1.126 brouard 8265:
1.222 brouard 8266: fprintf(fichtm,"\
1.126 brouard 8267: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8268: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8269: - 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 8270: But because parameters are usually highly correlated (a higher incidence of disability \
8271: and a higher incidence of recovery can give very close observed transition) it might \
8272: be very useful to look not only at linear confidence intervals estimated from the \
8273: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8274: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8275: covariance matrix of the one-step probabilities. \
8276: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8277:
1.222 brouard 8278: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8279: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8280: fprintf(fichtm,"\
1.126 brouard 8281: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8282: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8283:
1.222 brouard 8284: fprintf(fichtm,"\
1.126 brouard 8285: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8286: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8287: fprintf(fichtm,"\
1.126 brouard 8288: - 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): \
8289: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8290: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8291: fprintf(fichtm,"\
1.126 brouard 8292: - (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): \
8293: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8294: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8295: fprintf(fichtm,"\
1.288 brouard 8296: - 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 8297: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8298: fprintf(fichtm,"\
1.128 brouard 8299: - 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 8300: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8301: fprintf(fichtm,"\
1.288 brouard 8302: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8303: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8304:
8305: /* if(popforecast==1) fprintf(fichtm,"\n */
8306: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8307: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8308: /* <br>",fileres,fileres,fileres,fileres); */
8309: /* else */
1.338 brouard 8310: /* 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 8311: fflush(fichtm);
1.126 brouard 8312:
1.225 brouard 8313: m=pow(2,cptcoveff);
1.222 brouard 8314: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8315:
1.317 brouard 8316: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8317:
8318: jj1=0;
8319:
8320: fprintf(fichtm," \n<ul>");
1.337 brouard 8321: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8322: /* k1=nres; */
1.338 brouard 8323: k1=TKresult[nres];
1.337 brouard 8324: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8325: /* if(m != 1 && TKresult[nres]!= k1) */
8326: /* continue; */
1.317 brouard 8327: jj1++;
8328: if (cptcovn > 0) {
8329: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8330: for (cpt=1; cpt<=cptcovs;cpt++){
8331: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8332: }
8333: fprintf(fichtm,"\">");
8334:
8335: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8336: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8337: for (cpt=1; cpt<=cptcovs;cpt++){
8338: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8339: }
8340: if(invalidvarcomb[k1]){
8341: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8342: continue;
8343: }
8344: fprintf(fichtm,"</a></li>");
8345: } /* cptcovn >0 */
1.337 brouard 8346: } /* End nres */
1.317 brouard 8347: fprintf(fichtm," \n</ul>");
8348:
1.222 brouard 8349: jj1=0;
1.237 brouard 8350:
1.241 brouard 8351: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8352: /* k1=nres; */
1.338 brouard 8353: k1=TKresult[nres];
8354: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8355: /* for(k1=1; k1<=m;k1++){ */
8356: /* if(m != 1 && TKresult[nres]!= k1) */
8357: /* continue; */
1.222 brouard 8358: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8359: jj1++;
1.126 brouard 8360: if (cptcovn > 0) {
1.317 brouard 8361: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8362: for (cpt=1; cpt<=cptcovs;cpt++){
8363: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8364: }
8365: fprintf(fichtm,"\"</a>");
8366:
1.126 brouard 8367: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8368: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8369: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8370: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8371: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8372: }
1.237 brouard 8373:
1.338 brouard 8374: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8375:
1.222 brouard 8376: if(invalidvarcomb[k1]){
8377: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8378: continue;
8379: }
1.337 brouard 8380: } /* If cptcovn >0 */
1.126 brouard 8381: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8382: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8383: 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);
8384: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8385: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8386: }
8387: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8388: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8389: true period expectancies (those weighted with period prevalences are also\
8390: drawn in addition to the population based expectancies computed using\
1.314 brouard 8391: 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);
8392: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8393: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8394: /* } /\* end i1 *\/ */
1.241 brouard 8395: }/* End nres */
1.222 brouard 8396: fprintf(fichtm,"</ul>");
8397: fflush(fichtm);
1.126 brouard 8398: }
8399:
8400: /******************* Gnuplot file **************/
1.296 brouard 8401: 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 8402:
1.354 brouard 8403: char dirfileres[256],optfileres[256];
8404: char gplotcondition[256], gplotlabel[256];
1.343 brouard 8405: int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,kf=0,kvar=0,kk=0,ipos=0,iposold=0,ij=0, ijp=0, l=0;
1.211 brouard 8406: int lv=0, vlv=0, kl=0;
1.130 brouard 8407: int ng=0;
1.201 brouard 8408: int vpopbased;
1.223 brouard 8409: int ioffset; /* variable offset for columns */
1.270 brouard 8410: int iyearc=1; /* variable column for year of projection */
8411: int iagec=1; /* variable column for age of projection */
1.235 brouard 8412: int nres=0; /* Index of resultline */
1.266 brouard 8413: int istart=1; /* For starting graphs in projections */
1.219 brouard 8414:
1.126 brouard 8415: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8416: /* printf("Problem with file %s",optionfilegnuplot); */
8417: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8418: /* } */
8419:
8420: /*#ifdef windows */
8421: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8422: /*#endif */
1.225 brouard 8423: m=pow(2,cptcoveff);
1.126 brouard 8424:
1.274 brouard 8425: /* diagram of the model */
8426: fprintf(ficgp,"\n#Diagram of the model \n");
8427: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8428: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8429: 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);
8430:
1.343 brouard 8431: fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=1:%d] for [j=1:%d] arrow (%d+1)*10+i from cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.80*(cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) ), -0.80*(sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) + yoff ) ls 4\n",nlstate, nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
1.274 brouard 8432: fprintf(ficgp,"\n#show arrow\nunset label\n");
8433: 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);
8434: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8435: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8436: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8437: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8438:
1.202 brouard 8439: /* Contribution to likelihood */
8440: /* Plot the probability implied in the likelihood */
1.223 brouard 8441: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8442: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8443: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8444: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8445: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8446: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8447: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8448: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8449: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8450: 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));
8451: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8452: 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));
8453: for (i=1; i<= nlstate ; i ++) {
8454: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8455: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8456: 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);
8457: for (j=2; j<= nlstate+ndeath ; j ++) {
8458: 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);
8459: }
8460: fprintf(ficgp,";\nset out; unset ylabel;\n");
8461: }
8462: /* 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 */
8463: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8464: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8465: fprintf(ficgp,"\nset out;unset log\n");
8466: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8467:
1.343 brouard 8468: /* Plot the probability implied in the likelihood by covariate value */
8469: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8470: /* if(debugILK==1){ */
8471: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8472: kvar=Tvar[TvarFind[kf]]; /* variable name */
8473: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 8474: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
1.356 brouard 8475: /* k=19+kf;/\*offset because there are 19 columns in the ILK_ file *\/ */
1.355 brouard 8476: k=16+nlstate+kf;/*offset because there are 19 columns in the ILK_ file, first cov Vn on col 21 with 4 living states */
1.343 brouard 8477: for (i=1; i<= nlstate ; i ++) {
8478: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8479: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8480: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8481: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
8482: for (j=2; j<= nlstate+ndeath ; j ++) {
8483: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
8484: }
8485: }else{
8486: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar);
8487: for (j=2; j<= nlstate+ndeath ; j ++) {
8488: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar);
8489: }
1.343 brouard 8490: }
8491: fprintf(ficgp,";\nset out; unset ylabel;\n");
8492: }
8493: } /* End of each covariate dummy */
8494: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8495: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8496: * kmodel = 1 2 3 4 5 6 7 8 9
8497: * varying 1 2 3 4 5
8498: * ncovv 1 2 3 4 5 6 7 8
8499: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8500: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8501: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8502: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8503: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8504: */
8505: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8506: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8507: /* printf("DebugILK ficgp ncovv=%d, kvar=TvarVV[ncovv]=%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
8508: if(ipos!=iposold){ /* Not a product or first of a product */
8509: /* printf(" %d",ipos); */
8510: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8511: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8512: kk++; /* Position of the ncovv column in ILK_ */
8513: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8514: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
8515: for (i=1; i<= nlstate ; i ++) {
8516: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8517: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8518:
1.348 brouard 8519: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8520: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8521: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8522: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
8523: for (j=2; j<= nlstate+ndeath ; j ++) {
8524: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
8525: }
8526: }else{
8527: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8528: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar);
8529: for (j=2; j<= nlstate+ndeath ; j ++) {
8530: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar);
8531: }
8532: }
8533: fprintf(ficgp,";\nset out; unset ylabel;\n");
8534: }
8535: }/* End if dummy varying */
8536: }else{ /*Product */
8537: /* printf("*"); */
8538: /* fprintf(ficresilk,"*"); */
8539: }
8540: iposold=ipos;
8541: } /* For each time varying covariate */
8542: /* } /\* debugILK==1 *\/ */
8543: /* 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 */
8544: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8545: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8546: fprintf(ficgp,"\nset out;unset log\n");
8547: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8548:
8549:
8550:
1.126 brouard 8551: strcpy(dirfileres,optionfilefiname);
8552: strcpy(optfileres,"vpl");
1.223 brouard 8553: /* 1eme*/
1.238 brouard 8554: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8555: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8556: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8557: k1=TKresult[nres];
1.338 brouard 8558: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8559: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8560: /* if(m != 1 && TKresult[nres]!= k1) */
8561: /* continue; */
1.238 brouard 8562: /* We are interested in selected combination by the resultline */
1.246 brouard 8563: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8564: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8565: strcpy(gplotlabel,"(");
1.337 brouard 8566: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8567: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8568: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8569:
8570: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8571: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8572: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8573: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8574: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8575: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8576: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8577: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8578: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8579: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8580: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8581: /* } */
8582: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8583: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8584: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8585: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8586: }
8587: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8588: /* printf("\n#\n"); */
1.238 brouard 8589: fprintf(ficgp,"\n#\n");
8590: if(invalidvarcomb[k1]){
1.260 brouard 8591: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8592: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8593: continue;
8594: }
1.235 brouard 8595:
1.241 brouard 8596: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8597: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8598: /* 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 8599: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8600: 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);
8601: /* 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); */
8602: /* k1-1 error should be nres-1*/
1.238 brouard 8603: for (i=1; i<= nlstate ; i ++) {
8604: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8605: else fprintf(ficgp," %%*lf (%%*lf)");
8606: }
1.288 brouard 8607: 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 8608: for (i=1; i<= nlstate ; i ++) {
8609: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8610: else fprintf(ficgp," %%*lf (%%*lf)");
8611: }
1.260 brouard 8612: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8613: for (i=1; i<= nlstate ; i ++) {
8614: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8615: else fprintf(ficgp," %%*lf (%%*lf)");
8616: }
1.265 brouard 8617: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8618:
8619: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8620: if(cptcoveff ==0){
1.271 brouard 8621: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8622: }else{
8623: kl=0;
8624: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8625: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8626: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8627: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8628: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8629: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8630: vlv= nbcode[Tvaraff[k]][lv];
8631: kl++;
8632: /* 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 *\/ */
8633: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8634: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8635: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8636: if(k==cptcoveff){
8637: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8638: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8639: }else{
8640: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8641: kl++;
8642: }
8643: } /* end covariate */
8644: } /* end if no covariate */
8645:
1.296 brouard 8646: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8647: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8648: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8649: if(cptcoveff ==0){
1.245 brouard 8650: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8651: }else{
8652: kl=0;
8653: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8654: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8655: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8656: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8657: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8658: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8659: /* vlv= nbcode[Tvaraff[k]][lv]; */
8660: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8661: kl++;
1.238 brouard 8662: /* 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 *\/ */
8663: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8664: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8665: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8666: if(k==cptcoveff){
1.245 brouard 8667: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8668: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8669: }else{
1.332 brouard 8670: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8671: kl++;
8672: }
8673: } /* end covariate */
8674: } /* end if no covariate */
1.296 brouard 8675: if(prevbcast == 1){
1.268 brouard 8676: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8677: /* k1-1 error should be nres-1*/
8678: for (i=1; i<= nlstate ; i ++) {
8679: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8680: else fprintf(ficgp," %%*lf (%%*lf)");
8681: }
1.271 brouard 8682: 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 8683: for (i=1; i<= nlstate ; i ++) {
8684: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8685: else fprintf(ficgp," %%*lf (%%*lf)");
8686: }
1.276 brouard 8687: 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 8688: for (i=1; i<= nlstate ; i ++) {
8689: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8690: else fprintf(ficgp," %%*lf (%%*lf)");
8691: }
1.274 brouard 8692: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8693: } /* end if backprojcast */
1.296 brouard 8694: } /* end if prevbcast */
1.276 brouard 8695: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8696: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8697: } /* nres */
1.337 brouard 8698: /* } /\* k1 *\/ */
1.201 brouard 8699: } /* cpt */
1.235 brouard 8700:
8701:
1.126 brouard 8702: /*2 eme*/
1.337 brouard 8703: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8704: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8705: k1=TKresult[nres];
1.338 brouard 8706: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8707: /* if(m != 1 && TKresult[nres]!= k1) */
8708: /* continue; */
1.238 brouard 8709: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8710: strcpy(gplotlabel,"(");
1.337 brouard 8711: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8712: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8713: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8714: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8715: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8716: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8717: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8718: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8719: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8720: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8721: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8722: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8723: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8724: /* } */
8725: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8726: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8727: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8728: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8729: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8730: }
1.264 brouard 8731: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8732: fprintf(ficgp,"\n#\n");
1.223 brouard 8733: if(invalidvarcomb[k1]){
8734: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8735: continue;
8736: }
1.219 brouard 8737:
1.241 brouard 8738: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8739: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8740: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8741: if(vpopbased==0){
1.238 brouard 8742: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8743: }else
1.238 brouard 8744: fprintf(ficgp,"\nreplot ");
8745: for (i=1; i<= nlstate+1 ; i ++) {
8746: k=2*i;
1.261 brouard 8747: 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 8748: for (j=1; j<= nlstate+1 ; j ++) {
8749: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8750: else fprintf(ficgp," %%*lf (%%*lf)");
8751: }
8752: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8753: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8754: 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 8755: for (j=1; j<= nlstate+1 ; j ++) {
8756: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8757: else fprintf(ficgp," %%*lf (%%*lf)");
8758: }
8759: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8760: 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 8761: for (j=1; j<= nlstate+1 ; j ++) {
8762: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8763: else fprintf(ficgp," %%*lf (%%*lf)");
8764: }
8765: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8766: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8767: } /* state */
8768: } /* vpopbased */
1.264 brouard 8769: 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 8770: } /* end nres */
1.337 brouard 8771: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8772:
8773:
8774: /*3eme*/
1.337 brouard 8775: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8776: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8777: k1=TKresult[nres];
1.338 brouard 8778: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8779: /* if(m != 1 && TKresult[nres]!= k1) */
8780: /* continue; */
1.238 brouard 8781:
1.332 brouard 8782: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8783: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8784: strcpy(gplotlabel,"(");
1.337 brouard 8785: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8786: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8787: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8788: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8789: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8790: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8791: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8792: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8793: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8794: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8795: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8796: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8797: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8798: /* } */
8799: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8800: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8801: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8802: }
1.264 brouard 8803: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8804: fprintf(ficgp,"\n#\n");
8805: if(invalidvarcomb[k1]){
8806: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8807: continue;
8808: }
8809:
8810: /* k=2+nlstate*(2*cpt-2); */
8811: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8812: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8813: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8814: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8815: 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 8816: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8817: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8818: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8819: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8820: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8821: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8822:
1.238 brouard 8823: */
8824: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8825: 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 8826: /* 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 8827:
1.238 brouard 8828: }
1.261 brouard 8829: 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 8830: }
1.264 brouard 8831: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8832: } /* end nres */
1.337 brouard 8833: /* } /\* end kl 3eme *\/ */
1.126 brouard 8834:
1.223 brouard 8835: /* 4eme */
1.201 brouard 8836: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8837: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8838: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8839: k1=TKresult[nres];
1.338 brouard 8840: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8841: /* if(m != 1 && TKresult[nres]!= k1) */
8842: /* continue; */
1.238 brouard 8843: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8844: strcpy(gplotlabel,"(");
1.337 brouard 8845: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8846: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8847: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8848: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8849: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8850: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8851: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8852: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8853: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8854: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8855: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8856: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8857: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8858: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8859: /* } */
8860: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8861: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8862: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8863: }
1.264 brouard 8864: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8865: fprintf(ficgp,"\n#\n");
8866: if(invalidvarcomb[k1]){
8867: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8868: continue;
1.223 brouard 8869: }
1.238 brouard 8870:
1.241 brouard 8871: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8872: 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 8873: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8874: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8875: k=3;
8876: for (i=1; i<= nlstate ; i ++){
8877: if(i==1){
8878: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8879: }else{
8880: fprintf(ficgp,", '' ");
8881: }
8882: l=(nlstate+ndeath)*(i-1)+1;
8883: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8884: for (j=2; j<= nlstate+ndeath ; j ++)
8885: fprintf(ficgp,"+$%d",k+l+j-1);
8886: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8887: } /* nlstate */
1.264 brouard 8888: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8889: } /* end cpt state*/
8890: } /* end nres */
1.337 brouard 8891: /* } /\* end covariate k1 *\/ */
1.238 brouard 8892:
1.220 brouard 8893: /* 5eme */
1.201 brouard 8894: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8895: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8896: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8897: k1=TKresult[nres];
1.338 brouard 8898: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8899: /* if(m != 1 && TKresult[nres]!= k1) */
8900: /* continue; */
1.238 brouard 8901: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8902: strcpy(gplotlabel,"(");
1.238 brouard 8903: 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 8904: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8905: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8906: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8907: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8908: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8909: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8910: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8911: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8912: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8913: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8914: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8915: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8916: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8917: /* } */
8918: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8919: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8920: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8921: }
1.264 brouard 8922: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8923: fprintf(ficgp,"\n#\n");
8924: if(invalidvarcomb[k1]){
8925: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8926: continue;
8927: }
1.227 brouard 8928:
1.241 brouard 8929: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8930: 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 8931: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8932: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8933: k=3;
8934: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8935: if(j==1)
8936: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8937: else
8938: fprintf(ficgp,", '' ");
8939: l=(nlstate+ndeath)*(cpt-1) +j;
8940: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8941: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8942: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8943: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8944: } /* nlstate */
8945: fprintf(ficgp,", '' ");
8946: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8947: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8948: l=(nlstate+ndeath)*(cpt-1) +j;
8949: if(j < nlstate)
8950: fprintf(ficgp,"$%d +",k+l);
8951: else
8952: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8953: }
1.264 brouard 8954: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8955: } /* end cpt state*/
1.337 brouard 8956: /* } /\* end covariate *\/ */
1.238 brouard 8957: } /* end nres */
1.227 brouard 8958:
1.220 brouard 8959: /* 6eme */
1.202 brouard 8960: /* CV preval stable (period) for each covariate */
1.337 brouard 8961: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8962: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8963: k1=TKresult[nres];
1.338 brouard 8964: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8965: /* if(m != 1 && TKresult[nres]!= k1) */
8966: /* continue; */
1.255 brouard 8967: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8968: strcpy(gplotlabel,"(");
1.288 brouard 8969: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8970: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8971: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8972: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8973: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8974: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8975: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8976: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8977: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8978: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8979: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8980: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8981: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8982: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8983: /* } */
8984: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8985: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8986: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8987: }
1.264 brouard 8988: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8989: fprintf(ficgp,"\n#\n");
1.223 brouard 8990: if(invalidvarcomb[k1]){
1.227 brouard 8991: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8992: continue;
1.223 brouard 8993: }
1.227 brouard 8994:
1.241 brouard 8995: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8996: 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 8997: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8998: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8999: k=3; /* Offset */
1.255 brouard 9000: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 9001: if(i==1)
9002: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
9003: else
9004: fprintf(ficgp,", '' ");
1.255 brouard 9005: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 9006: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
9007: for (j=2; j<= nlstate ; j ++)
9008: fprintf(ficgp,"+$%d",k+l+j-1);
9009: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 9010: } /* nlstate */
1.264 brouard 9011: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 9012: } /* end cpt state*/
9013: } /* end covariate */
1.227 brouard 9014:
9015:
1.220 brouard 9016: /* 7eme */
1.296 brouard 9017: if(prevbcast == 1){
1.288 brouard 9018: /* CV backward prevalence for each covariate */
1.337 brouard 9019: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9020: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9021: k1=TKresult[nres];
1.338 brouard 9022: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9023: /* if(m != 1 && TKresult[nres]!= k1) */
9024: /* continue; */
1.268 brouard 9025: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 9026: strcpy(gplotlabel,"(");
1.288 brouard 9027: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9028: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9029: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9030: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9031: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
9032: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
9033: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9034: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9035: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9036: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9037: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9038: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9039: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9040: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9041: /* } */
9042: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9043: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9044: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9045: }
1.264 brouard 9046: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9047: fprintf(ficgp,"\n#\n");
9048: if(invalidvarcomb[k1]){
9049: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9050: continue;
9051: }
9052:
1.241 brouard 9053: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 9054: 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 9055: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 9056: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 9057: k=3; /* Offset */
1.268 brouard 9058: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 9059: if(i==1)
9060: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
9061: else
9062: fprintf(ficgp,", '' ");
9063: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 9064: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 9065: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
9066: /* 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 9067: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 9068: /* for (j=2; j<= nlstate ; j ++) */
9069: /* fprintf(ficgp,"+$%d",k+l+j-1); */
9070: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 9071: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 9072: } /* nlstate */
1.264 brouard 9073: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 9074: } /* end cpt state*/
9075: } /* end covariate */
1.296 brouard 9076: } /* End if prevbcast */
1.218 brouard 9077:
1.223 brouard 9078: /* 8eme */
1.218 brouard 9079: if(prevfcast==1){
1.288 brouard 9080: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9081:
1.337 brouard 9082: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9083: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9084: k1=TKresult[nres];
1.338 brouard 9085: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9086: /* if(m != 1 && TKresult[nres]!= k1) */
9087: /* continue; */
1.211 brouard 9088: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9089: strcpy(gplotlabel,"(");
1.288 brouard 9090: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9091: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9092: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9093: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9094: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9095: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9096: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9097: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9098: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9099: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9100: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9101: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9102: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9103: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9104: /* } */
9105: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9106: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9107: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9108: }
1.264 brouard 9109: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9110: fprintf(ficgp,"\n#\n");
9111: if(invalidvarcomb[k1]){
9112: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9113: continue;
9114: }
9115:
9116: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9117: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9118: 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 9119: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9120: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9121:
9122: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9123: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9124: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9125: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9126: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9127: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9128: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9129: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9130: if(i==istart){
1.227 brouard 9131: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9132: }else{
9133: fprintf(ficgp,",\\\n '' ");
9134: }
9135: if(cptcoveff ==0){ /* No covariate */
9136: ioffset=2; /* Age is in 2 */
9137: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9138: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9139: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9140: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9141: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9142: if(i==nlstate+1){
1.270 brouard 9143: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9144: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9145: fprintf(ficgp,",\\\n '' ");
9146: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9147: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9148: offyear, \
1.268 brouard 9149: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9150: }else
1.227 brouard 9151: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9152: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9153: }else{ /* more than 2 covariates */
1.270 brouard 9154: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9155: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9156: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9157: iyearc=ioffset-1;
9158: iagec=ioffset;
1.227 brouard 9159: fprintf(ficgp," u %d:(",ioffset);
9160: kl=0;
9161: strcpy(gplotcondition,"(");
1.351 brouard 9162: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 9163: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 9164: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9165: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9166: lv=Tvresult[nres][k];
9167: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 9168: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9169: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9170: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9171: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 9172: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 9173: kl++;
1.351 brouard 9174: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9175: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 9176: kl++;
1.351 brouard 9177: if(k <cptcovs && cptcovs>1)
1.227 brouard 9178: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9179: }
9180: strcpy(gplotcondition+strlen(gplotcondition),")");
9181: /* 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 *\/ */
9182: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9183: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9184: /* '' 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*/
9185: if(i==nlstate+1){
1.270 brouard 9186: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9187: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9188: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9189: fprintf(ficgp," u %d:(",iagec);
9190: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9191: iyearc, iagec, offyear, \
9192: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9193: /* '' 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 9194: }else{
9195: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9196: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9197: }
9198: } /* end if covariate */
9199: } /* nlstate */
1.264 brouard 9200: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9201: } /* end cpt state*/
9202: } /* end covariate */
9203: } /* End if prevfcast */
1.227 brouard 9204:
1.296 brouard 9205: if(prevbcast==1){
1.268 brouard 9206: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9207:
1.337 brouard 9208: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9209: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9210: k1=TKresult[nres];
1.338 brouard 9211: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9212: /* if(m != 1 && TKresult[nres]!= k1) */
9213: /* continue; */
1.268 brouard 9214: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9215: strcpy(gplotlabel,"(");
9216: 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 9217: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9218: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9219: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9220: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9221: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9222: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9223: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9224: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9225: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9226: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9227: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9228: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9229: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9230: /* } */
9231: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9232: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9233: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9234: }
9235: strcpy(gplotlabel+strlen(gplotlabel),")");
9236: fprintf(ficgp,"\n#\n");
9237: if(invalidvarcomb[k1]){
9238: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9239: continue;
9240: }
9241:
9242: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9243: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9244: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9245: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9246: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9247:
9248: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9249: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9250: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9251: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9252: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9253: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9254: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9255: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9256: if(i==istart){
9257: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9258: }else{
9259: fprintf(ficgp,",\\\n '' ");
9260: }
1.351 brouard 9261: /* if(cptcoveff ==0){ /\* No covariate *\/ */
9262: if(cptcovs ==0){ /* No covariate */
1.268 brouard 9263: ioffset=2; /* Age is in 2 */
9264: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9265: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9266: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9267: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9268: fprintf(ficgp," u %d:(", ioffset);
9269: if(i==nlstate+1){
1.270 brouard 9270: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9271: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9272: fprintf(ficgp,",\\\n '' ");
9273: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9274: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9275: offbyear, \
9276: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9277: }else
9278: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9279: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9280: }else{ /* more than 2 covariates */
1.270 brouard 9281: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9282: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9283: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9284: iyearc=ioffset-1;
9285: iagec=ioffset;
1.268 brouard 9286: fprintf(ficgp," u %d:(",ioffset);
9287: kl=0;
9288: strcpy(gplotcondition,"(");
1.337 brouard 9289: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9290: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9291: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9292: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9293: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9294: lv=Tvresult[nres][k];
9295: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9296: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9297: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9298: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9299: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9300: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9301: kl++;
9302: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9303: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9304: kl++;
1.338 brouard 9305: if(k <cptcovs && cptcovs>1)
1.337 brouard 9306: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9307: }
1.268 brouard 9308: }
9309: strcpy(gplotcondition+strlen(gplotcondition),")");
9310: /* 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 *\/ */
9311: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9312: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9313: /* '' 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*/
9314: if(i==nlstate+1){
1.270 brouard 9315: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9316: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9317: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9318: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9319: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9320: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9321: iyearc,iagec,offbyear, \
9322: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9323: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9324: }else{
9325: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9326: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9327: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9328: }
9329: } /* end if covariate */
9330: } /* nlstate */
9331: fprintf(ficgp,"\nset out; unset label;\n");
9332: } /* end cpt state*/
9333: } /* end covariate */
1.296 brouard 9334: } /* End if prevbcast */
1.268 brouard 9335:
1.227 brouard 9336:
1.238 brouard 9337: /* 9eme writing MLE parameters */
9338: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9339: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9340: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9341: for(k=1; k <=(nlstate+ndeath); k++){
9342: if (k != i) {
1.227 brouard 9343: fprintf(ficgp,"# current state %d\n",k);
9344: for(j=1; j <=ncovmodel; j++){
9345: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9346: jk++;
9347: }
9348: fprintf(ficgp,"\n");
1.126 brouard 9349: }
9350: }
1.223 brouard 9351: }
1.187 brouard 9352: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9353:
1.145 brouard 9354: /*goto avoid;*/
1.238 brouard 9355: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9356: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9357: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9358: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9359: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9360: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9361: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9362: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9363: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9364: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9365: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9366: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9367: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9368: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9369: fprintf(ficgp,"#\n");
1.223 brouard 9370: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9371: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9372: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9373: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 9374: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
9375: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 9376: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9377: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9378: /* k1=nres; */
1.338 brouard 9379: k1=TKresult[nres];
9380: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9381: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9382: strcpy(gplotlabel,"(");
1.276 brouard 9383: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9384: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9385: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9386: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9387: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9388: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9389: }
9390: /* if(m != 1 && TKresult[nres]!= k1) */
9391: /* continue; */
9392: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9393: /* strcpy(gplotlabel,"("); */
9394: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9395: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9396: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9397: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9398: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9399: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9400: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9401: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9402: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9403: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9404: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9405: /* } */
9406: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9407: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9408: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9409: /* } */
1.264 brouard 9410: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9411: fprintf(ficgp,"\n#\n");
1.264 brouard 9412: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9413: fprintf(ficgp,"\nset key outside ");
9414: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9415: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9416: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9417: if (ng==1){
9418: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9419: fprintf(ficgp,"\nunset log y");
9420: }else if (ng==2){
9421: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9422: fprintf(ficgp,"\nset log y");
9423: }else if (ng==3){
9424: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9425: fprintf(ficgp,"\nset log y");
9426: }else
9427: fprintf(ficgp,"\nunset title ");
9428: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9429: i=1;
9430: for(k2=1; k2<=nlstate; k2++) {
9431: k3=i;
9432: for(k=1; k<=(nlstate+ndeath); k++) {
9433: if (k != k2){
9434: switch( ng) {
9435: case 1:
9436: if(nagesqr==0)
9437: fprintf(ficgp," p%d+p%d*x",i,i+1);
9438: else /* nagesqr =1 */
9439: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9440: break;
9441: case 2: /* ng=2 */
9442: if(nagesqr==0)
9443: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9444: else /* nagesqr =1 */
9445: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9446: break;
9447: case 3:
9448: if(nagesqr==0)
9449: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9450: else /* nagesqr =1 */
9451: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9452: break;
9453: }
9454: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9455: ijp=1; /* product no age */
9456: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9457: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9458: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9459: switch(Typevar[j]){
9460: case 1:
9461: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9462: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9463: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9464: if(DummyV[j]==0){/* Bug valgrind */
9465: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9466: }else{ /* quantitative */
9467: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9468: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9469: }
9470: ij++;
1.268 brouard 9471: }
1.237 brouard 9472: }
1.329 brouard 9473: }
9474: break;
9475: case 2:
9476: if(cptcovprod >0){
9477: if(j==Tprod[ijp]) { /* */
9478: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9479: if(ijp <=cptcovprod) { /* Product */
9480: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9481: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9482: /* 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)]); */
9483: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9484: }else{ /* Vn is dummy and Vm is quanti */
9485: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9486: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9487: }
9488: }else{ /* Vn*Vm Vn is quanti */
9489: if(DummyV[Tvard[ijp][2]]==0){
9490: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9491: }else{ /* Both quanti */
9492: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9493: }
1.268 brouard 9494: }
1.329 brouard 9495: ijp++;
1.237 brouard 9496: }
1.329 brouard 9497: } /* end Tprod */
9498: }
9499: break;
1.349 brouard 9500: case 3:
9501: if(cptcovdageprod >0){
9502: /* if(j==Tprod[ijp]) { */ /* not necessary */
9503: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 9504: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
9505: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9506: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9507: /* 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)]); */
9508: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9509: }else{ /* Vn is dummy and Vm is quanti */
9510: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 9511: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9512: }
1.350 brouard 9513: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 9514: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 9515: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 9516: }else{ /* Both quanti */
1.350 brouard 9517: fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9518: }
9519: }
9520: ijp++;
9521: }
9522: /* } */ /* end Tprod */
9523: }
9524: break;
1.329 brouard 9525: case 0:
9526: /* simple covariate */
1.264 brouard 9527: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9528: if(Dummy[j]==0){
9529: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9530: }else{ /* quantitative */
9531: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9532: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9533: }
1.329 brouard 9534: /* end simple */
9535: break;
9536: default:
9537: break;
9538: } /* end switch */
1.237 brouard 9539: } /* end j */
1.329 brouard 9540: }else{ /* k=k2 */
9541: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9542: fprintf(ficgp," (1.");i=i-ncovmodel;
9543: }else
9544: i=i-ncovmodel;
1.223 brouard 9545: }
1.227 brouard 9546:
1.223 brouard 9547: if(ng != 1){
9548: fprintf(ficgp,")/(1");
1.227 brouard 9549:
1.264 brouard 9550: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9551: if(nagesqr==0)
1.264 brouard 9552: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9553: else /* nagesqr =1 */
1.264 brouard 9554: 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 9555:
1.223 brouard 9556: ij=1;
1.329 brouard 9557: ijp=1;
9558: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9559: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9560: switch(Typevar[j]){
9561: case 1:
9562: if(cptcovage >0){
9563: if(j==Tage[ij]) { /* Bug valgrind */
9564: if(ij <=cptcovage) { /* Bug valgrind */
9565: if(DummyV[j]==0){/* Bug valgrind */
9566: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9567: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9568: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9569: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9570: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9571: }else{ /* quantitative */
9572: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9573: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9574: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9575: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9576: }
9577: ij++;
9578: }
9579: }
9580: }
9581: break;
9582: case 2:
9583: if(cptcovprod >0){
9584: if(j==Tprod[ijp]) { /* */
9585: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9586: if(ijp <=cptcovprod) { /* Product */
9587: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9588: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9589: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
9590: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9591: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9592: }else{ /* Vn is dummy and Vm is quanti */
9593: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9594: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9595: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9596: }
9597: }else{ /* Vn*Vm Vn is quanti */
9598: if(DummyV[Tvard[ijp][2]]==0){
9599: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9600: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9601: }else{ /* Both quanti */
9602: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9603: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9604: }
9605: }
9606: ijp++;
9607: }
9608: } /* end Tprod */
9609: } /* end if */
9610: break;
1.349 brouard 9611: case 3:
9612: if(cptcovdageprod >0){
9613: /* if(j==Tprod[ijp]) { /\* *\/ */
9614: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9615: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 9616: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9617: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9618: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
1.350 brouard 9619: fprintf(ficgp,"+p%d*%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9620: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9621: }else{ /* Vn is dummy and Vm is quanti */
9622: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 9623: fprintf(ficgp,"+p%d*%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9624: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9625: }
9626: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 9627: if(DummyV[Tvardk[ijp][2]]==0){
9628: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 9629: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9630: }else{ /* Both quanti */
1.350 brouard 9631: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9632: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9633: }
9634: }
9635: ijp++;
9636: }
9637: /* } /\* end Tprod *\/ */
9638: } /* end if */
9639: break;
1.329 brouard 9640: case 0:
9641: /* simple covariate */
9642: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9643: if(Dummy[j]==0){
9644: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9645: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9646: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9647: }else{ /* quantitative */
9648: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9649: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9650: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9651: }
9652: /* end simple */
9653: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9654: break;
9655: default:
9656: break;
9657: } /* end switch */
1.223 brouard 9658: }
9659: fprintf(ficgp,")");
9660: }
9661: fprintf(ficgp,")");
9662: if(ng ==2)
1.276 brouard 9663: 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 9664: else /* ng= 3 */
1.276 brouard 9665: 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 9666: }else{ /* end ng <> 1 */
1.223 brouard 9667: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9668: 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 9669: }
9670: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9671: fprintf(ficgp,",");
9672: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9673: fprintf(ficgp,",");
9674: i=i+ncovmodel;
9675: } /* end k */
9676: } /* end k2 */
1.276 brouard 9677: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9678: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9679: } /* end resultline */
1.223 brouard 9680: } /* end ng */
9681: /* avoid: */
9682: fflush(ficgp);
1.126 brouard 9683: } /* end gnuplot */
9684:
9685:
9686: /*************** Moving average **************/
1.219 brouard 9687: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9688: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9689:
1.222 brouard 9690: int i, cpt, cptcod;
9691: int modcovmax =1;
9692: int mobilavrange, mob;
9693: int iage=0;
1.288 brouard 9694: int firstA1=0, firstA2=0;
1.222 brouard 9695:
1.266 brouard 9696: double sum=0., sumr=0.;
1.222 brouard 9697: double age;
1.266 brouard 9698: double *sumnewp, *sumnewm, *sumnewmr;
9699: double *agemingood, *agemaxgood;
9700: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9701:
9702:
1.278 brouard 9703: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9704: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9705:
9706: sumnewp = vector(1,ncovcombmax);
9707: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9708: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9709: agemingood = vector(1,ncovcombmax);
1.266 brouard 9710: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9711: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9712: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9713:
9714: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9715: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9716: sumnewp[cptcod]=0.;
1.266 brouard 9717: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9718: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9719: }
9720: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9721:
1.266 brouard 9722: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9723: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9724: else mobilavrange=mobilav;
9725: for (age=bage; age<=fage; age++)
9726: for (i=1; i<=nlstate;i++)
9727: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9728: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9729: /* We keep the original values on the extreme ages bage, fage and for
9730: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9731: we use a 5 terms etc. until the borders are no more concerned.
9732: */
9733: for (mob=3;mob <=mobilavrange;mob=mob+2){
9734: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9735: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9736: sumnewm[cptcod]=0.;
9737: for (i=1; i<=nlstate;i++){
1.222 brouard 9738: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9739: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9740: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9741: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9742: }
9743: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9744: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9745: } /* end i */
9746: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9747: } /* end cptcod */
1.222 brouard 9748: }/* end age */
9749: }/* end mob */
1.266 brouard 9750: }else{
9751: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9752: return -1;
1.266 brouard 9753: }
9754:
9755: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9756: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9757: if(invalidvarcomb[cptcod]){
9758: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9759: continue;
9760: }
1.219 brouard 9761:
1.266 brouard 9762: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9763: sumnewm[cptcod]=0.;
9764: sumnewmr[cptcod]=0.;
9765: for (i=1; i<=nlstate;i++){
9766: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9767: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9768: }
9769: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9770: agemingoodr[cptcod]=age;
9771: }
9772: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9773: agemingood[cptcod]=age;
9774: }
9775: } /* age */
9776: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9777: sumnewm[cptcod]=0.;
1.266 brouard 9778: sumnewmr[cptcod]=0.;
1.222 brouard 9779: for (i=1; i<=nlstate;i++){
9780: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9781: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9782: }
9783: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9784: agemaxgoodr[cptcod]=age;
1.222 brouard 9785: }
9786: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9787: agemaxgood[cptcod]=age;
9788: }
9789: } /* age */
9790: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9791: /* but they will change */
1.288 brouard 9792: firstA1=0;firstA2=0;
1.266 brouard 9793: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9794: sumnewm[cptcod]=0.;
9795: sumnewmr[cptcod]=0.;
9796: for (i=1; i<=nlstate;i++){
9797: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9798: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9799: }
9800: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9801: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9802: agemaxgoodr[cptcod]=age; /* age min */
9803: for (i=1; i<=nlstate;i++)
9804: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9805: }else{ /* bad we change the value with the values of good ages */
9806: for (i=1; i<=nlstate;i++){
9807: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9808: } /* i */
9809: } /* end bad */
9810: }else{
9811: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9812: agemaxgood[cptcod]=age;
9813: }else{ /* bad we change the value with the values of good ages */
9814: for (i=1; i<=nlstate;i++){
9815: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9816: } /* i */
9817: } /* end bad */
9818: }/* end else */
9819: sum=0.;sumr=0.;
9820: for (i=1; i<=nlstate;i++){
9821: sum+=mobaverage[(int)age][i][cptcod];
9822: sumr+=probs[(int)age][i][cptcod];
9823: }
9824: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9825: if(!firstA1){
9826: firstA1=1;
9827: 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);
9828: }
9829: 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 9830: } /* end bad */
9831: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9832: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9833: if(!firstA2){
9834: firstA2=1;
9835: 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);
9836: }
9837: 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 9838: } /* end bad */
9839: }/* age */
1.266 brouard 9840:
9841: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9842: sumnewm[cptcod]=0.;
1.266 brouard 9843: sumnewmr[cptcod]=0.;
1.222 brouard 9844: for (i=1; i<=nlstate;i++){
9845: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9846: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9847: }
9848: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9849: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9850: agemingoodr[cptcod]=age;
9851: for (i=1; i<=nlstate;i++)
9852: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9853: }else{ /* bad we change the value with the values of good ages */
9854: for (i=1; i<=nlstate;i++){
9855: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9856: } /* i */
9857: } /* end bad */
9858: }else{
9859: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9860: agemingood[cptcod]=age;
9861: }else{ /* bad */
9862: for (i=1; i<=nlstate;i++){
9863: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9864: } /* i */
9865: } /* end bad */
9866: }/* end else */
9867: sum=0.;sumr=0.;
9868: for (i=1; i<=nlstate;i++){
9869: sum+=mobaverage[(int)age][i][cptcod];
9870: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9871: }
1.266 brouard 9872: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9873: 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 9874: } /* end bad */
9875: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9876: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9877: 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 9878: } /* end bad */
9879: }/* age */
1.266 brouard 9880:
1.222 brouard 9881:
9882: for (age=bage; age<=fage; age++){
1.235 brouard 9883: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9884: sumnewp[cptcod]=0.;
9885: sumnewm[cptcod]=0.;
9886: for (i=1; i<=nlstate;i++){
9887: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9888: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9889: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9890: }
9891: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9892: }
9893: /* printf("\n"); */
9894: /* } */
1.266 brouard 9895:
1.222 brouard 9896: /* brutal averaging */
1.266 brouard 9897: /* for (i=1; i<=nlstate;i++){ */
9898: /* for (age=1; age<=bage; age++){ */
9899: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9900: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9901: /* } */
9902: /* for (age=fage; age<=AGESUP; age++){ */
9903: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9904: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9905: /* } */
9906: /* } /\* end i status *\/ */
9907: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9908: /* for (age=1; age<=AGESUP; age++){ */
9909: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9910: /* mobaverage[(int)age][i][cptcod]=0.; */
9911: /* } */
9912: /* } */
1.222 brouard 9913: }/* end cptcod */
1.266 brouard 9914: free_vector(agemaxgoodr,1, ncovcombmax);
9915: free_vector(agemaxgood,1, ncovcombmax);
9916: free_vector(agemingood,1, ncovcombmax);
9917: free_vector(agemingoodr,1, ncovcombmax);
9918: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9919: free_vector(sumnewm,1, ncovcombmax);
9920: free_vector(sumnewp,1, ncovcombmax);
9921: return 0;
9922: }/* End movingaverage */
1.218 brouard 9923:
1.126 brouard 9924:
1.296 brouard 9925:
1.126 brouard 9926: /************** Forecasting ******************/
1.296 brouard 9927: /* 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)*/
9928: 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){
9929: /* dateintemean, mean date of interviews
9930: dateprojd, year, month, day of starting projection
9931: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9932: agemin, agemax range of age
9933: dateprev1 dateprev2 range of dates during which prevalence is computed
9934: */
1.296 brouard 9935: /* double anprojd, mprojd, jprojd; */
9936: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9937: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9938: double agec; /* generic age */
1.296 brouard 9939: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9940: double *popeffectif,*popcount;
9941: double ***p3mat;
1.218 brouard 9942: /* double ***mobaverage; */
1.126 brouard 9943: char fileresf[FILENAMELENGTH];
9944:
9945: agelim=AGESUP;
1.211 brouard 9946: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9947: in each health status at the date of interview (if between dateprev1 and dateprev2).
9948: We still use firstpass and lastpass as another selection.
9949: */
1.214 brouard 9950: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9951: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9952:
1.201 brouard 9953: strcpy(fileresf,"F_");
9954: strcat(fileresf,fileresu);
1.126 brouard 9955: if((ficresf=fopen(fileresf,"w"))==NULL) {
9956: printf("Problem with forecast resultfile: %s\n", fileresf);
9957: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9958: }
1.235 brouard 9959: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9960: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9961:
1.225 brouard 9962: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9963:
9964:
9965: stepsize=(int) (stepm+YEARM-1)/YEARM;
9966: if (stepm<=12) stepsize=1;
9967: if(estepm < stepm){
9968: printf ("Problem %d lower than %d\n",estepm, stepm);
9969: }
1.270 brouard 9970: else{
9971: hstepm=estepm;
9972: }
9973: if(estepm > stepm){ /* Yes every two year */
9974: stepsize=2;
9975: }
1.296 brouard 9976: hstepm=hstepm/stepm;
1.126 brouard 9977:
1.296 brouard 9978:
9979: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9980: /* fractional in yp1 *\/ */
9981: /* aintmean=yp; */
9982: /* yp2=modf((yp1*12),&yp); */
9983: /* mintmean=yp; */
9984: /* yp1=modf((yp2*30.5),&yp); */
9985: /* jintmean=yp; */
9986: /* if(jintmean==0) jintmean=1; */
9987: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9988:
1.296 brouard 9989:
9990: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9991: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9992: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 9993: /* i1=pow(2,cptcoveff); */
9994: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 9995:
1.296 brouard 9996: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9997:
9998: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9999:
1.126 brouard 10000: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 10001: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10002: k=TKresult[nres];
10003: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
10004: /* 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) *\/ */
10005: /* if(i1 != 1 && TKresult[nres]!= k) */
10006: /* continue; */
10007: /* if(invalidvarcomb[k]){ */
10008: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
10009: /* continue; */
10010: /* } */
1.227 brouard 10011: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 10012: for(j=1;j<=cptcovs;j++){
10013: /* for(j=1;j<=cptcoveff;j++) { */
10014: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
10015: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10016: /* } */
10017: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10018: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10019: /* } */
10020: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 10021: }
1.351 brouard 10022:
1.227 brouard 10023: fprintf(ficresf," yearproj age");
10024: for(j=1; j<=nlstate+ndeath;j++){
10025: for(i=1; i<=nlstate;i++)
10026: fprintf(ficresf," p%d%d",i,j);
10027: fprintf(ficresf," wp.%d",j);
10028: }
1.296 brouard 10029: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 10030: fprintf(ficresf,"\n");
1.296 brouard 10031: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 10032: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
10033: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 10034: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
10035: nhstepm = nhstepm/hstepm;
10036: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10037: oldm=oldms;savm=savms;
1.268 brouard 10038: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 10039: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 10040: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 10041: for (h=0; h<=nhstepm; h++){
10042: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 10043: break;
10044: }
10045: }
10046: fprintf(ficresf,"\n");
1.351 brouard 10047: /* for(j=1;j<=cptcoveff;j++) */
10048: for(j=1;j<=cptcovs;j++)
10049: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 10050: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 10051: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 10052: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 10053:
10054: for(j=1; j<=nlstate+ndeath;j++) {
10055: ppij=0.;
10056: for(i=1; i<=nlstate;i++) {
1.278 brouard 10057: if (mobilav>=1)
10058: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
10059: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
10060: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
10061: }
1.268 brouard 10062: fprintf(ficresf," %.3f", p3mat[i][j][h]);
10063: } /* end i */
10064: fprintf(ficresf," %.3f", ppij);
10065: }/* end j */
1.227 brouard 10066: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10067: } /* end agec */
1.266 brouard 10068: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
10069: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 10070: } /* end yearp */
10071: } /* end k */
1.219 brouard 10072:
1.126 brouard 10073: fclose(ficresf);
1.215 brouard 10074: printf("End of Computing forecasting \n");
10075: fprintf(ficlog,"End of Computing forecasting\n");
10076:
1.126 brouard 10077: }
10078:
1.269 brouard 10079: /************** Back Forecasting ******************/
1.296 brouard 10080: /* 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){ */
10081: 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){
10082: /* back1, year, month, day of starting backprojection
1.267 brouard 10083: agemin, agemax range of age
10084: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 10085: anback2 year of end of backprojection (same day and month as back1).
10086: prevacurrent and prev are prevalences.
1.267 brouard 10087: */
10088: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
10089: double agec; /* generic age */
1.302 brouard 10090: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10091: double *popeffectif,*popcount;
10092: double ***p3mat;
10093: /* double ***mobaverage; */
10094: char fileresfb[FILENAMELENGTH];
10095:
1.268 brouard 10096: agelim=AGEINF;
1.267 brouard 10097: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10098: in each health status at the date of interview (if between dateprev1 and dateprev2).
10099: We still use firstpass and lastpass as another selection.
10100: */
10101: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10102: /* firstpass, lastpass, stepm, weightopt, model); */
10103:
10104: /*Do we need to compute prevalence again?*/
10105:
10106: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10107:
10108: strcpy(fileresfb,"FB_");
10109: strcat(fileresfb,fileresu);
10110: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10111: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10112: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10113: }
10114: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10115: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10116:
10117: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10118:
10119:
10120: stepsize=(int) (stepm+YEARM-1)/YEARM;
10121: if (stepm<=12) stepsize=1;
10122: if(estepm < stepm){
10123: printf ("Problem %d lower than %d\n",estepm, stepm);
10124: }
1.270 brouard 10125: else{
10126: hstepm=estepm;
10127: }
10128: if(estepm >= stepm){ /* Yes every two year */
10129: stepsize=2;
10130: }
1.267 brouard 10131:
10132: hstepm=hstepm/stepm;
1.296 brouard 10133: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10134: /* fractional in yp1 *\/ */
10135: /* aintmean=yp; */
10136: /* yp2=modf((yp1*12),&yp); */
10137: /* mintmean=yp; */
10138: /* yp1=modf((yp2*30.5),&yp); */
10139: /* jintmean=yp; */
10140: /* if(jintmean==0) jintmean=1; */
10141: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10142:
1.351 brouard 10143: /* i1=pow(2,cptcoveff); */
10144: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 10145:
1.296 brouard 10146: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10147: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10148:
10149: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10150:
1.351 brouard 10151: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10152: k=TKresult[nres];
10153: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
10154: /* for(k=1; k<=i1;k++){ */
10155: /* if(i1 != 1 && TKresult[nres]!= k) */
10156: /* continue; */
10157: /* if(invalidvarcomb[k]){ */
10158: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
10159: /* continue; */
10160: /* } */
1.268 brouard 10161: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 10162: for(j=1;j<=cptcovs;j++){
10163: /* for(j=1;j<=cptcoveff;j++) { */
10164: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10165: /* } */
10166: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 10167: }
1.351 brouard 10168: /* fprintf(ficrespij,"******\n"); */
10169: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10170: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10171: /* } */
1.267 brouard 10172: fprintf(ficresfb," yearbproj age");
10173: for(j=1; j<=nlstate+ndeath;j++){
10174: for(i=1; i<=nlstate;i++)
1.268 brouard 10175: fprintf(ficresfb," b%d%d",i,j);
10176: fprintf(ficresfb," b.%d",j);
1.267 brouard 10177: }
1.296 brouard 10178: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10179: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10180: fprintf(ficresfb,"\n");
1.296 brouard 10181: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10182: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10183: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10184: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10185: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10186: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10187: nhstepm = nhstepm/hstepm;
10188: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10189: oldm=oldms;savm=savms;
1.268 brouard 10190: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10191: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10192: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10193: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10194: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10195: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10196: for (h=0; h<=nhstepm; h++){
1.268 brouard 10197: if (h*hstepm/YEARM*stepm ==-yearp) {
10198: break;
10199: }
10200: }
10201: fprintf(ficresfb,"\n");
1.351 brouard 10202: /* for(j=1;j<=cptcoveff;j++) */
10203: for(j=1;j<=cptcovs;j++)
10204: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10205: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 10206: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10207: for(i=1; i<=nlstate+ndeath;i++) {
10208: ppij=0.;ppi=0.;
10209: for(j=1; j<=nlstate;j++) {
10210: /* if (mobilav==1) */
1.269 brouard 10211: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10212: ppi=ppi+prevacurrent[(int)agec][j][k];
10213: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10214: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10215: /* else { */
10216: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10217: /* } */
1.268 brouard 10218: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10219: } /* end j */
10220: if(ppi <0.99){
10221: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10222: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10223: }
10224: fprintf(ficresfb," %.3f", ppij);
10225: }/* end j */
1.267 brouard 10226: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10227: } /* end agec */
10228: } /* end yearp */
10229: } /* end k */
1.217 brouard 10230:
1.267 brouard 10231: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10232:
1.267 brouard 10233: fclose(ficresfb);
10234: printf("End of Computing Back forecasting \n");
10235: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10236:
1.267 brouard 10237: }
1.217 brouard 10238:
1.269 brouard 10239: /* Variance of prevalence limit: varprlim */
10240: 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 10241: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10242:
10243: char fileresvpl[FILENAMELENGTH];
10244: FILE *ficresvpl;
10245: double **oldm, **savm;
10246: double **varpl; /* Variances of prevalence limits by age */
10247: int i1, k, nres, j ;
10248:
10249: strcpy(fileresvpl,"VPL_");
10250: strcat(fileresvpl,fileresu);
10251: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10252: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10253: exit(0);
10254: }
1.288 brouard 10255: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10256: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10257:
10258: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10259: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10260:
10261: i1=pow(2,cptcoveff);
10262: if (cptcovn < 1){i1=1;}
10263:
1.337 brouard 10264: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10265: k=TKresult[nres];
1.338 brouard 10266: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10267: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10268: if(i1 != 1 && TKresult[nres]!= k)
10269: continue;
10270: fprintf(ficresvpl,"\n#****** ");
10271: printf("\n#****** ");
10272: fprintf(ficlog,"\n#****** ");
1.337 brouard 10273: for(j=1;j<=cptcovs;j++) {
10274: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10275: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10276: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10277: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10278: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10279: }
1.337 brouard 10280: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10281: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10282: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10283: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10284: /* } */
1.269 brouard 10285: fprintf(ficresvpl,"******\n");
10286: printf("******\n");
10287: fprintf(ficlog,"******\n");
10288:
10289: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10290: oldm=oldms;savm=savms;
10291: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10292: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10293: /*}*/
10294: }
10295:
10296: fclose(ficresvpl);
1.288 brouard 10297: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10298: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10299:
10300: }
10301: /* Variance of back prevalence: varbprlim */
10302: 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){
10303: /*------- Variance of back (stable) prevalence------*/
10304:
10305: char fileresvbl[FILENAMELENGTH];
10306: FILE *ficresvbl;
10307:
10308: double **oldm, **savm;
10309: double **varbpl; /* Variances of back prevalence limits by age */
10310: int i1, k, nres, j ;
10311:
10312: strcpy(fileresvbl,"VBL_");
10313: strcat(fileresvbl,fileresu);
10314: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10315: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10316: exit(0);
10317: }
10318: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10319: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10320:
10321:
10322: i1=pow(2,cptcoveff);
10323: if (cptcovn < 1){i1=1;}
10324:
1.337 brouard 10325: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10326: k=TKresult[nres];
1.338 brouard 10327: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10328: /* for(k=1; k<=i1;k++){ */
10329: /* if(i1 != 1 && TKresult[nres]!= k) */
10330: /* continue; */
1.269 brouard 10331: fprintf(ficresvbl,"\n#****** ");
10332: printf("\n#****** ");
10333: fprintf(ficlog,"\n#****** ");
1.337 brouard 10334: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10335: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10336: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10337: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10338: /* for(j=1;j<=cptcoveff;j++) { */
10339: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10340: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10341: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10342: /* } */
10343: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10344: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10345: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10346: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10347: }
10348: fprintf(ficresvbl,"******\n");
10349: printf("******\n");
10350: fprintf(ficlog,"******\n");
10351:
10352: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10353: oldm=oldms;savm=savms;
10354:
10355: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10356: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10357: /*}*/
10358: }
10359:
10360: fclose(ficresvbl);
10361: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10362: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10363:
10364: } /* End of varbprlim */
10365:
1.126 brouard 10366: /************** Forecasting *****not tested NB*************/
1.227 brouard 10367: /* 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 10368:
1.227 brouard 10369: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10370: /* int *popage; */
10371: /* double calagedatem, agelim, kk1, kk2; */
10372: /* double *popeffectif,*popcount; */
10373: /* double ***p3mat,***tabpop,***tabpopprev; */
10374: /* /\* double ***mobaverage; *\/ */
10375: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10376:
1.227 brouard 10377: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10378: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10379: /* agelim=AGESUP; */
10380: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10381:
1.227 brouard 10382: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10383:
10384:
1.227 brouard 10385: /* strcpy(filerespop,"POP_"); */
10386: /* strcat(filerespop,fileresu); */
10387: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10388: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10389: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10390: /* } */
10391: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10392: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10393:
1.227 brouard 10394: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10395:
1.227 brouard 10396: /* /\* if (mobilav!=0) { *\/ */
10397: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10398: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10399: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10400: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10401: /* /\* } *\/ */
10402: /* /\* } *\/ */
1.126 brouard 10403:
1.227 brouard 10404: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10405: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10406:
1.227 brouard 10407: /* agelim=AGESUP; */
1.126 brouard 10408:
1.227 brouard 10409: /* hstepm=1; */
10410: /* hstepm=hstepm/stepm; */
1.218 brouard 10411:
1.227 brouard 10412: /* if (popforecast==1) { */
10413: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10414: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10415: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10416: /* } */
10417: /* popage=ivector(0,AGESUP); */
10418: /* popeffectif=vector(0,AGESUP); */
10419: /* popcount=vector(0,AGESUP); */
1.126 brouard 10420:
1.227 brouard 10421: /* i=1; */
10422: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10423:
1.227 brouard 10424: /* imx=i; */
10425: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10426: /* } */
1.218 brouard 10427:
1.227 brouard 10428: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10429: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10430: /* k=k+1; */
10431: /* fprintf(ficrespop,"\n#******"); */
10432: /* for(j=1;j<=cptcoveff;j++) { */
10433: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10434: /* } */
10435: /* fprintf(ficrespop,"******\n"); */
10436: /* fprintf(ficrespop,"# Age"); */
10437: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10438: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10439:
1.227 brouard 10440: /* for (cpt=0; cpt<=0;cpt++) { */
10441: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10442:
1.227 brouard 10443: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10444: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10445: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10446:
1.227 brouard 10447: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10448: /* oldm=oldms;savm=savms; */
10449: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10450:
1.227 brouard 10451: /* for (h=0; h<=nhstepm; h++){ */
10452: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10453: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10454: /* } */
10455: /* for(j=1; j<=nlstate+ndeath;j++) { */
10456: /* kk1=0.;kk2=0; */
10457: /* for(i=1; i<=nlstate;i++) { */
10458: /* if (mobilav==1) */
10459: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10460: /* else { */
10461: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10462: /* } */
10463: /* } */
10464: /* if (h==(int)(calagedatem+12*cpt)){ */
10465: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10466: /* /\*fprintf(ficrespop," %.3f", kk1); */
10467: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10468: /* } */
10469: /* } */
10470: /* for(i=1; i<=nlstate;i++){ */
10471: /* kk1=0.; */
10472: /* for(j=1; j<=nlstate;j++){ */
10473: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10474: /* } */
10475: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10476: /* } */
1.218 brouard 10477:
1.227 brouard 10478: /* if (h==(int)(calagedatem+12*cpt)) */
10479: /* for(j=1; j<=nlstate;j++) */
10480: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10481: /* } */
10482: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10483: /* } */
10484: /* } */
1.218 brouard 10485:
1.227 brouard 10486: /* /\******\/ */
1.218 brouard 10487:
1.227 brouard 10488: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10489: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10490: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10491: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10492: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10493:
1.227 brouard 10494: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10495: /* oldm=oldms;savm=savms; */
10496: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10497: /* for (h=0; h<=nhstepm; h++){ */
10498: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10499: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10500: /* } */
10501: /* for(j=1; j<=nlstate+ndeath;j++) { */
10502: /* kk1=0.;kk2=0; */
10503: /* for(i=1; i<=nlstate;i++) { */
10504: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10505: /* } */
10506: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10507: /* } */
10508: /* } */
10509: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10510: /* } */
10511: /* } */
10512: /* } */
10513: /* } */
1.218 brouard 10514:
1.227 brouard 10515: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10516:
1.227 brouard 10517: /* if (popforecast==1) { */
10518: /* free_ivector(popage,0,AGESUP); */
10519: /* free_vector(popeffectif,0,AGESUP); */
10520: /* free_vector(popcount,0,AGESUP); */
10521: /* } */
10522: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10523: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10524: /* fclose(ficrespop); */
10525: /* } /\* End of popforecast *\/ */
1.218 brouard 10526:
1.126 brouard 10527: int fileappend(FILE *fichier, char *optionfich)
10528: {
10529: if((fichier=fopen(optionfich,"a"))==NULL) {
10530: printf("Problem with file: %s\n", optionfich);
10531: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10532: return (0);
10533: }
10534: fflush(fichier);
10535: return (1);
10536: }
10537:
10538:
10539: /**************** function prwizard **********************/
10540: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10541: {
10542:
10543: /* Wizard to print covariance matrix template */
10544:
1.164 brouard 10545: char ca[32], cb[32];
10546: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10547: int numlinepar;
10548:
10549: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10550: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10551: for(i=1; i <=nlstate; i++){
10552: jj=0;
10553: for(j=1; j <=nlstate+ndeath; j++){
10554: if(j==i) continue;
10555: jj++;
10556: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10557: printf("%1d%1d",i,j);
10558: fprintf(ficparo,"%1d%1d",i,j);
10559: for(k=1; k<=ncovmodel;k++){
10560: /* printf(" %lf",param[i][j][k]); */
10561: /* fprintf(ficparo," %lf",param[i][j][k]); */
10562: printf(" 0.");
10563: fprintf(ficparo," 0.");
10564: }
10565: printf("\n");
10566: fprintf(ficparo,"\n");
10567: }
10568: }
10569: printf("# Scales (for hessian or gradient estimation)\n");
10570: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10571: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10572: for(i=1; i <=nlstate; i++){
10573: jj=0;
10574: for(j=1; j <=nlstate+ndeath; j++){
10575: if(j==i) continue;
10576: jj++;
10577: fprintf(ficparo,"%1d%1d",i,j);
10578: printf("%1d%1d",i,j);
10579: fflush(stdout);
10580: for(k=1; k<=ncovmodel;k++){
10581: /* printf(" %le",delti3[i][j][k]); */
10582: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10583: printf(" 0.");
10584: fprintf(ficparo," 0.");
10585: }
10586: numlinepar++;
10587: printf("\n");
10588: fprintf(ficparo,"\n");
10589: }
10590: }
10591: printf("# Covariance matrix\n");
10592: /* # 121 Var(a12)\n\ */
10593: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10594: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10595: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10596: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10597: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10598: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10599: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10600: fflush(stdout);
10601: fprintf(ficparo,"# Covariance matrix\n");
10602: /* # 121 Var(a12)\n\ */
10603: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10604: /* # ...\n\ */
10605: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10606:
10607: for(itimes=1;itimes<=2;itimes++){
10608: jj=0;
10609: for(i=1; i <=nlstate; i++){
10610: for(j=1; j <=nlstate+ndeath; j++){
10611: if(j==i) continue;
10612: for(k=1; k<=ncovmodel;k++){
10613: jj++;
10614: ca[0]= k+'a'-1;ca[1]='\0';
10615: if(itimes==1){
10616: printf("#%1d%1d%d",i,j,k);
10617: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10618: }else{
10619: printf("%1d%1d%d",i,j,k);
10620: fprintf(ficparo,"%1d%1d%d",i,j,k);
10621: /* printf(" %.5le",matcov[i][j]); */
10622: }
10623: ll=0;
10624: for(li=1;li <=nlstate; li++){
10625: for(lj=1;lj <=nlstate+ndeath; lj++){
10626: if(lj==li) continue;
10627: for(lk=1;lk<=ncovmodel;lk++){
10628: ll++;
10629: if(ll<=jj){
10630: cb[0]= lk +'a'-1;cb[1]='\0';
10631: if(ll<jj){
10632: if(itimes==1){
10633: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10634: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10635: }else{
10636: printf(" 0.");
10637: fprintf(ficparo," 0.");
10638: }
10639: }else{
10640: if(itimes==1){
10641: printf(" Var(%s%1d%1d)",ca,i,j);
10642: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10643: }else{
10644: printf(" 0.");
10645: fprintf(ficparo," 0.");
10646: }
10647: }
10648: }
10649: } /* end lk */
10650: } /* end lj */
10651: } /* end li */
10652: printf("\n");
10653: fprintf(ficparo,"\n");
10654: numlinepar++;
10655: } /* end k*/
10656: } /*end j */
10657: } /* end i */
10658: } /* end itimes */
10659:
10660: } /* end of prwizard */
10661: /******************* Gompertz Likelihood ******************************/
10662: double gompertz(double x[])
10663: {
1.302 brouard 10664: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10665: int i,n=0; /* n is the size of the sample */
10666:
1.220 brouard 10667: for (i=1;i<=imx ; i++) {
1.126 brouard 10668: sump=sump+weight[i];
10669: /* sump=sump+1;*/
10670: num=num+1;
10671: }
1.302 brouard 10672: L=0.0;
10673: /* agegomp=AGEGOMP; */
1.126 brouard 10674: /* for (i=0; i<=imx; i++)
10675: 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]);*/
10676:
1.302 brouard 10677: for (i=1;i<=imx ; i++) {
10678: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10679: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10680: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10681: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10682: * +
10683: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10684: */
10685: if (wav[i] > 1 || agedc[i] < AGESUP) {
10686: if (cens[i] == 1){
10687: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10688: } else if (cens[i] == 0){
1.126 brouard 10689: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10690: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10691: } else
10692: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10693: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10694: L=L+A*weight[i];
1.126 brouard 10695: /* 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 10696: }
10697: }
1.126 brouard 10698:
1.302 brouard 10699: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10700:
10701: return -2*L*num/sump;
10702: }
10703:
1.136 brouard 10704: #ifdef GSL
10705: /******************* Gompertz_f Likelihood ******************************/
10706: double gompertz_f(const gsl_vector *v, void *params)
10707: {
1.302 brouard 10708: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10709: double *x= (double *) v->data;
10710: int i,n=0; /* n is the size of the sample */
10711:
10712: for (i=0;i<=imx-1 ; i++) {
10713: sump=sump+weight[i];
10714: /* sump=sump+1;*/
10715: num=num+1;
10716: }
10717:
10718:
10719: /* for (i=0; i<=imx; i++)
10720: 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]);*/
10721: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10722: for (i=1;i<=imx ; i++)
10723: {
10724: if (cens[i] == 1 && wav[i]>1)
10725: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10726:
10727: if (cens[i] == 0 && wav[i]>1)
10728: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10729: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10730:
10731: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10732: if (wav[i] > 1 ) { /* ??? */
10733: LL=LL+A*weight[i];
10734: /* 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]);*/
10735: }
10736: }
10737:
10738: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10739: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10740:
10741: return -2*LL*num/sump;
10742: }
10743: #endif
10744:
1.126 brouard 10745: /******************* Printing html file ***********/
1.201 brouard 10746: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10747: int lastpass, int stepm, int weightopt, char model[],\
10748: int imx, double p[],double **matcov,double agemortsup){
10749: int i,k;
10750:
10751: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10752: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10753: for (i=1;i<=2;i++)
10754: 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 10755: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10756: fprintf(fichtm,"</ul>");
10757:
10758: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10759:
10760: 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>");
10761:
10762: for (k=agegomp;k<(agemortsup-2);k++)
10763: 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]);
10764:
10765:
10766: fflush(fichtm);
10767: }
10768:
10769: /******************* Gnuplot file **************/
1.201 brouard 10770: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10771:
10772: char dirfileres[132],optfileres[132];
1.164 brouard 10773:
1.126 brouard 10774: int ng;
10775:
10776:
10777: /*#ifdef windows */
10778: fprintf(ficgp,"cd \"%s\" \n",pathc);
10779: /*#endif */
10780:
10781:
10782: strcpy(dirfileres,optionfilefiname);
10783: strcpy(optfileres,"vpl");
1.199 brouard 10784: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10785: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10786: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10787: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10788: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10789:
10790: }
10791:
1.136 brouard 10792: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10793: {
1.126 brouard 10794:
1.136 brouard 10795: /*-------- data file ----------*/
10796: FILE *fic;
10797: char dummy[]=" ";
1.240 brouard 10798: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10799: int lstra;
1.136 brouard 10800: int linei, month, year,iout;
1.302 brouard 10801: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10802: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10803: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10804: char *stratrunc;
1.223 brouard 10805:
1.349 brouard 10806: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
10807: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10808:
10809: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10810:
1.136 brouard 10811: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10812: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10813: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10814: }
1.126 brouard 10815:
1.302 brouard 10816: /* Is it a BOM UTF-8 Windows file? */
10817: /* First data line */
10818: linei=0;
10819: while(fgets(line, MAXLINE, fic)) {
10820: noffset=0;
10821: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10822: {
10823: noffset=noffset+3;
10824: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10825: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10826: fflush(ficlog); return 1;
10827: }
10828: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10829: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10830: {
10831: noffset=noffset+2;
1.304 brouard 10832: 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);
10833: 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 10834: fflush(ficlog); return 1;
10835: }
10836: else if( line[0] == 0 && line[1] == 0)
10837: {
10838: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10839: noffset=noffset+4;
1.304 brouard 10840: 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);
10841: 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 10842: fflush(ficlog); return 1;
10843: }
10844: } else{
10845: ;/*printf(" Not a BOM file\n");*/
10846: }
10847: /* If line starts with a # it is a comment */
10848: if (line[noffset] == '#') {
10849: linei=linei+1;
10850: break;
10851: }else{
10852: break;
10853: }
10854: }
10855: fclose(fic);
10856: if((fic=fopen(datafile,"r"))==NULL) {
10857: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10858: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10859: }
10860: /* Not a Bom file */
10861:
1.136 brouard 10862: i=1;
10863: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10864: linei=linei+1;
10865: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10866: if(line[j] == '\t')
10867: line[j] = ' ';
10868: }
10869: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10870: ;
10871: };
10872: line[j+1]=0; /* Trims blanks at end of line */
10873: if(line[0]=='#'){
10874: fprintf(ficlog,"Comment line\n%s\n",line);
10875: printf("Comment line\n%s\n",line);
10876: continue;
10877: }
10878: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10879: strcpy(line, linetmp);
1.223 brouard 10880:
10881: /* Loops on waves */
10882: for (j=maxwav;j>=1;j--){
10883: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10884: cutv(stra, strb, line, ' ');
10885: if(strb[0]=='.') { /* Missing value */
10886: lval=-1;
10887: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10888: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10889: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10890: 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);
10891: 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);
10892: return 1;
10893: }
10894: }else{
10895: errno=0;
10896: /* what_kind_of_number(strb); */
10897: dval=strtod(strb,&endptr);
10898: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10899: /* if(strb != endptr && *endptr == '\0') */
10900: /* dval=dlval; */
10901: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10902: if( strb[0]=='\0' || (*endptr != '\0')){
10903: 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);
10904: 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);
10905: return 1;
10906: }
10907: cotqvar[j][iv][i]=dval;
1.341 brouard 10908: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10909: }
10910: strcpy(line,stra);
1.223 brouard 10911: }/* end loop ntqv */
1.225 brouard 10912:
1.223 brouard 10913: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10914: cutv(stra, strb, line, ' ');
10915: if(strb[0]=='.') { /* Missing value */
10916: lval=-1;
10917: }else{
10918: errno=0;
10919: lval=strtol(strb,&endptr,10);
10920: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10921: if( strb[0]=='\0' || (*endptr != '\0')){
10922: 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);
10923: 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);
10924: return 1;
10925: }
10926: }
10927: if(lval <-1 || lval >1){
10928: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10929: 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 10930: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10931: For example, for multinomial values like 1, 2 and 3,\n \
10932: build V1=0 V2=0 for the reference value (1),\n \
10933: V1=1 V2=0 for (2) \n \
1.223 brouard 10934: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10935: output of IMaCh is often meaningless.\n \
1.319 brouard 10936: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10937: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10938: 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 10939: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10940: For example, for multinomial values like 1, 2 and 3,\n \
10941: build V1=0 V2=0 for the reference value (1),\n \
10942: V1=1 V2=0 for (2) \n \
1.223 brouard 10943: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10944: output of IMaCh is often meaningless.\n \
1.319 brouard 10945: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10946: return 1;
10947: }
1.341 brouard 10948: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10949: strcpy(line,stra);
1.223 brouard 10950: }/* end loop ntv */
1.225 brouard 10951:
1.223 brouard 10952: /* Statuses at wave */
1.137 brouard 10953: cutv(stra, strb, line, ' ');
1.223 brouard 10954: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10955: lval=-1;
1.136 brouard 10956: }else{
1.238 brouard 10957: errno=0;
10958: lval=strtol(strb,&endptr,10);
10959: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10960: if( strb[0]=='\0' || (*endptr != '\0' )){
10961: 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);
10962: 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);
10963: return 1;
10964: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10965: printf("Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile);fflush(stdout);
10966: fprintf(ficlog,"Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile); fflush(ficlog);
1.238 brouard 10967: return 1;
10968: }
1.136 brouard 10969: }
1.225 brouard 10970:
1.136 brouard 10971: s[j][i]=lval;
1.225 brouard 10972:
1.223 brouard 10973: /* Date of Interview */
1.136 brouard 10974: strcpy(line,stra);
10975: cutv(stra, strb,line,' ');
1.169 brouard 10976: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10977: }
1.169 brouard 10978: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10979: month=99;
10980: year=9999;
1.136 brouard 10981: }else{
1.225 brouard 10982: 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);
10983: 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);
10984: return 1;
1.136 brouard 10985: }
10986: anint[j][i]= (double) year;
1.302 brouard 10987: mint[j][i]= (double)month;
10988: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10989: /* printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
10990: /* fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
10991: /* } */
1.136 brouard 10992: strcpy(line,stra);
1.223 brouard 10993: } /* End loop on waves */
1.225 brouard 10994:
1.223 brouard 10995: /* Date of death */
1.136 brouard 10996: cutv(stra, strb,line,' ');
1.169 brouard 10997: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10998: }
1.169 brouard 10999: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 11000: month=99;
11001: year=9999;
11002: }else{
1.141 brouard 11003: 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 11004: 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);
11005: return 1;
1.136 brouard 11006: }
11007: andc[i]=(double) year;
11008: moisdc[i]=(double) month;
11009: strcpy(line,stra);
11010:
1.223 brouard 11011: /* Date of birth */
1.136 brouard 11012: cutv(stra, strb,line,' ');
1.169 brouard 11013: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 11014: }
1.169 brouard 11015: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 11016: month=99;
11017: year=9999;
11018: }else{
1.141 brouard 11019: 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);
11020: 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 11021: return 1;
1.136 brouard 11022: }
11023: if (year==9999) {
1.141 brouard 11024: 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);
11025: 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 11026: return 1;
11027:
1.136 brouard 11028: }
11029: annais[i]=(double)(year);
1.302 brouard 11030: moisnais[i]=(double)(month);
11031: for (j=1;j<=maxwav;j++){
11032: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
11033: 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]);
11034: 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]);
11035: }
11036: }
11037:
1.136 brouard 11038: strcpy(line,stra);
1.225 brouard 11039:
1.223 brouard 11040: /* Sample weight */
1.136 brouard 11041: cutv(stra, strb,line,' ');
11042: errno=0;
11043: dval=strtod(strb,&endptr);
11044: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 11045: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
11046: 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 11047: fflush(ficlog);
11048: return 1;
11049: }
11050: weight[i]=dval;
11051: strcpy(line,stra);
1.225 brouard 11052:
1.223 brouard 11053: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
11054: cutv(stra, strb, line, ' ');
11055: if(strb[0]=='.') { /* Missing value */
1.225 brouard 11056: lval=-1;
1.311 brouard 11057: coqvar[iv][i]=NAN;
11058: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 11059: }else{
1.225 brouard 11060: errno=0;
11061: /* what_kind_of_number(strb); */
11062: dval=strtod(strb,&endptr);
11063: /* if(strb != endptr && *endptr == '\0') */
11064: /* dval=dlval; */
11065: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
11066: if( strb[0]=='\0' || (*endptr != '\0')){
11067: 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);
11068: 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);
11069: return 1;
11070: }
11071: coqvar[iv][i]=dval;
1.226 brouard 11072: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 11073: }
11074: strcpy(line,stra);
11075: }/* end loop nqv */
1.136 brouard 11076:
1.223 brouard 11077: /* Covariate values */
1.136 brouard 11078: for (j=ncovcol;j>=1;j--){
11079: cutv(stra, strb,line,' ');
1.223 brouard 11080: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 11081: lval=-1;
1.136 brouard 11082: }else{
1.225 brouard 11083: errno=0;
11084: lval=strtol(strb,&endptr,10);
11085: if( strb[0]=='\0' || (*endptr != '\0')){
11086: 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);
11087: 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);
11088: return 1;
11089: }
1.136 brouard 11090: }
11091: if(lval <-1 || lval >1){
1.225 brouard 11092: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11093: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11094: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11095: For example, for multinomial values like 1, 2 and 3,\n \
11096: build V1=0 V2=0 for the reference value (1),\n \
11097: V1=1 V2=0 for (2) \n \
1.136 brouard 11098: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11099: output of IMaCh is often meaningless.\n \
1.136 brouard 11100: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11101: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11102: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11103: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11104: For example, for multinomial values like 1, 2 and 3,\n \
11105: build V1=0 V2=0 for the reference value (1),\n \
11106: V1=1 V2=0 for (2) \n \
1.136 brouard 11107: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11108: output of IMaCh is often meaningless.\n \
1.136 brouard 11109: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11110: return 1;
1.136 brouard 11111: }
11112: covar[j][i]=(double)(lval);
11113: strcpy(line,stra);
11114: }
11115: lstra=strlen(stra);
1.225 brouard 11116:
1.136 brouard 11117: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11118: stratrunc = &(stra[lstra-9]);
11119: num[i]=atol(stratrunc);
11120: }
11121: else
11122: num[i]=atol(stra);
11123: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11124: 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;}*/
11125:
11126: i=i+1;
11127: } /* End loop reading data */
1.225 brouard 11128:
1.136 brouard 11129: *imax=i-1; /* Number of individuals */
11130: fclose(fic);
1.225 brouard 11131:
1.136 brouard 11132: return (0);
1.164 brouard 11133: /* endread: */
1.225 brouard 11134: printf("Exiting readdata: ");
11135: fclose(fic);
11136: return (1);
1.223 brouard 11137: }
1.126 brouard 11138:
1.234 brouard 11139: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11140: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11141: while (*p2 == ' ')
1.234 brouard 11142: p2++;
11143: /* while ((*p1++ = *p2++) !=0) */
11144: /* ; */
11145: /* do */
11146: /* while (*p2 == ' ') */
11147: /* p2++; */
11148: /* while (*p1++ == *p2++); */
11149: *stri=p2;
1.145 brouard 11150: }
11151:
1.330 brouard 11152: int decoderesult( char resultline[], int nres)
1.230 brouard 11153: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11154: {
1.235 brouard 11155: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11156: char resultsav[MAXLINE];
1.330 brouard 11157: /* int resultmodel[MAXLINE]; */
1.334 brouard 11158: /* int modelresult[MAXLINE]; */
1.230 brouard 11159: char stra[80], strb[80], strc[80], strd[80],stre[80];
11160:
1.234 brouard 11161: removefirstspace(&resultline);
1.332 brouard 11162: printf("decoderesult:%s\n",resultline);
1.230 brouard 11163:
1.332 brouard 11164: strcpy(resultsav,resultline);
1.342 brouard 11165: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11166: if (strlen(resultsav) >1){
1.334 brouard 11167: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11168: }
1.353 brouard 11169: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 11170: TKresult[nres]=0; /* Combination for the nresult and the model */
11171: return (0);
11172: }
1.234 brouard 11173: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 brouard 11174: fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(ficlog);
11175: printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(stdout);
11176: if(j==0)
11177: return 1;
1.234 brouard 11178: }
1.334 brouard 11179: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11180: if(nbocc(resultsav,'=') >1){
1.318 brouard 11181: 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 11182: /* 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 11183: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11184: /* If a blank, then strc="V4=" and strd='\0' */
11185: if(strc[0]=='\0'){
11186: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11187: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11188: return 1;
11189: }
1.234 brouard 11190: }else
11191: cutl(strc,strd,resultsav,'=');
1.318 brouard 11192: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11193:
1.230 brouard 11194: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11195: 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 11196: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11197: /* cptcovsel++; */
11198: if (nbocc(stra,'=') >0)
11199: strcpy(resultsav,stra); /* and analyzes it */
11200: }
1.235 brouard 11201: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11202: /* 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 11203: 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 11204: if(Typevar[k1]==0){ /* Single covariate in model */
11205: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11206: match=0;
1.318 brouard 11207: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11208: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11209: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11210: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11211: break;
11212: }
11213: }
11214: if(match == 0){
1.338 brouard 11215: 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]);
11216: 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 11217: return 1;
1.234 brouard 11218: }
1.332 brouard 11219: }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*/
11220: /* We feed resultmodel[k1]=k2; */
11221: match=0;
11222: 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 */
11223: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11224: 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 11225: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11226: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11227: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11228: break;
11229: }
11230: }
11231: if(match == 0){
1.338 brouard 11232: 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]);
11233: 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 11234: return 1;
11235: }
1.349 brouard 11236: }else if(Typevar[k1]==2 || Typevar[k1]==3){ /* Product with or without age. We want to get the position in the resultline of the product in the model line*/
1.332 brouard 11237: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11238: match=0;
1.342 brouard 11239: /* printf("Decoderesult very first Product Tvardk[k1=%d][1]=%d Tvardk[k1=%d][2]=%d V%d * V%d\n",k1,Tvardk[k1][1],k1,Tvardk[k1][2],Tvardk[k1][1],Tvardk[k1][2]); */
1.332 brouard 11240: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11241: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11242: /* modelresult[k2]=k1; */
1.342 brouard 11243: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11244: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11245: }
11246: }
11247: if(match == 0){
1.349 brouard 11248: printf("Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
11249: fprintf(ficlog,"Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 11250: return 1;
11251: }
11252: match=0;
11253: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11254: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11255: /* modelresult[k2]=k1;*/
1.342 brouard 11256: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11257: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11258: break;
11259: }
11260: }
11261: if(match == 0){
1.349 brouard 11262: printf("Error in result line (Product without age second variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
11263: fprintf(ficlog,"Error in result line (Product without age second variable or double product with age): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 11264: return 1;
11265: }
11266: }/* End of testing */
1.333 brouard 11267: }/* End loop cptcovt */
1.235 brouard 11268: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11269: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11270: 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)
11271: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11272: match=0;
1.318 brouard 11273: 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 11274: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 11275: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11276: 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 11277: 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 11278: ++match;
11279: }
11280: }
11281: }
11282: if(match == 0){
1.338 brouard 11283: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11284: 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 11285: return 1;
1.234 brouard 11286: }else if(match > 1){
1.338 brouard 11287: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11288: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11289: return 1;
1.234 brouard 11290: }
11291: }
1.334 brouard 11292: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11293: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11294: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11295: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11296: /* 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*/
11297: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11298: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11299: /* 1 0 0 0 */
11300: /* 2 1 0 0 */
11301: /* 3 0 1 0 */
1.330 brouard 11302: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11303: /* 5 0 0 1 */
1.330 brouard 11304: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11305: /* 7 0 1 1 */
11306: /* 8 1 1 1 */
1.237 brouard 11307: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11308: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11309: /* V5*age V5 known which value for nres? */
11310: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11311: 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.
11312: * loop on position k1 in the MODEL LINE */
1.331 brouard 11313: /* k counting number of combination of single dummies in the equation model */
11314: /* k4 counting single dummies in the equation model */
11315: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11316: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, fixed or timevarying, k1 is sorting according to MODEL, but k3 to resultline */
1.334 brouard 11317: /* 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 11318: /* 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 11319: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11320: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11321: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11322: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11323: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11324: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11325: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11326: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11327: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11328: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11329: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11330: 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 11331: 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 11332: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11333: /* Tinvresult[nres][4]=1 */
1.334 brouard 11334: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11335: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11336: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11337: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11338: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11339: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11340: /* 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 11341: k4++;;
1.331 brouard 11342: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11343: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11344: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11345: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11346: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11347: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11348: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11349: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11350: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11351: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11352: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11353: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11354: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11355: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11356: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11357: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11358: /* 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 11359: k4q++;;
1.350 brouard 11360: }else if( Dummy[k1]==2 ){ /* For dummy with age product "V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
11361: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 11362: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 11363: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11364: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11365: /* 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]]); */
11366: }else{
11367: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11368: 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)*/
11369: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
11370: precov[nres][k1]=Tvalsel[k3];
11371: }
1.342 brouard 11372: /* 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 11373: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 11374: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11375: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11376: /* 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]]); */
11377: }else{
11378: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
11379: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
11380: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
11381: precov[nres][k1]=Tvalsel[k3q];
11382: }
1.342 brouard 11383: /* printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.349 brouard 11384: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11385: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11386: /* 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 11387: }else{
1.332 brouard 11388: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11389: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11390: }
11391: }
1.234 brouard 11392:
1.334 brouard 11393: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11394: return (0);
11395: }
1.235 brouard 11396:
1.230 brouard 11397: int decodemodel( char model[], int lastobs)
11398: /**< This routine decodes the model and returns:
1.224 brouard 11399: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11400: * - nagesqr = 1 if age*age in the model, otherwise 0.
11401: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11402: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11403: * - cptcovage number of covariates with age*products =2
11404: * - cptcovs number of simple covariates
1.339 brouard 11405: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11406: * - 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 11407: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11408: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11409: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11410: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11411: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11412: */
1.319 brouard 11413: /* 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 11414: {
1.238 brouard 11415: int i, j, k, ks, v;
1.349 brouard 11416: int n,m;
11417: int j1, k1, k11, k12, k2, k3, k4;
11418: char modelsav[300];
11419: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11420: char *strpt;
1.349 brouard 11421: int **existcomb;
11422:
11423: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
11424: for(i=1;i<=NCOVMAX;i++)
11425: for(j=1;j<=NCOVMAX;j++)
11426: existcomb[i][j]=0;
11427:
1.145 brouard 11428: /*removespace(model);*/
1.136 brouard 11429: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 11430: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11431: if (strstr(model,"AGE") !=0){
1.192 brouard 11432: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11433: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11434: return 1;
11435: }
1.141 brouard 11436: if (strstr(model,"v") !=0){
1.338 brouard 11437: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11438: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11439: return 1;
11440: }
1.187 brouard 11441: strcpy(modelsav,model);
11442: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11443: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11444: if(strpt != model){
1.338 brouard 11445: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11446: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11447: corresponding column of parameters.\n",model);
1.338 brouard 11448: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11449: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11450: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11451: return 1;
1.225 brouard 11452: }
1.187 brouard 11453: nagesqr=1;
11454: if (strstr(model,"+age*age") !=0)
1.234 brouard 11455: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11456: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11457: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11458: else
1.234 brouard 11459: substrchaine(modelsav, model, "age*age");
1.187 brouard 11460: }else
11461: nagesqr=0;
1.349 brouard 11462: if (strlen(modelsav) >1){ /* V2 +V3 +V4 +V6 +V7 +V6*V2 +V7*V2 +V6*V3 +V7*V3 +V6*V4 +V7*V4 +age*V2 +age*V3 +age*V4 +age*V6 +age*V7 +age*V6*V2 +V7*V2 +age*V6*V3 +age*V7*V3 +age*V6*V4 +age*V7*V4 */
1.187 brouard 11463: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11464: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 11465: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 11466: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11467: * cst, age and age*age
11468: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11469: /* including age products which are counted in cptcovage.
11470: * but the covariates which are products must be treated
11471: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 11472: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
11473: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11474: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 11475: cptcovprodage=0;
11476: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11477:
1.187 brouard 11478: /* Design
11479: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11480: * < ncovcol=8 >
11481: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11482: * k= 1 2 3 4 5 6 7 8
11483: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11484: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11485: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11486: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11487: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11488: * Tage[++cptcovage]=k
1.345 brouard 11489: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11490: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11491: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11492: * 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
11493: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11494: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11495: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11496: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11497: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11498: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11499: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11500: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11501: * p Tprod[1]@2={ 6, 5}
11502: *p Tvard[1][1]@4= {7, 8, 5, 6}
11503: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11504: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11505: *How to reorganize? Tvars(orted)
1.187 brouard 11506: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11507: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11508: * {2, 1, 4, 8, 5, 6, 3, 7}
11509: * Struct []
11510: */
1.225 brouard 11511:
1.187 brouard 11512: /* This loop fills the array Tvar from the string 'model'.*/
11513: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11514: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11515: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11516: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11517: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11518: /* k=1 Tvar[1]=2 (from V2) */
11519: /* k=5 Tvar[5] */
11520: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11521: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11522: /* } */
1.198 brouard 11523: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11524: /*
11525: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11526: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11527: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11528: }
1.187 brouard 11529: cptcovage=0;
1.351 brouard 11530:
11531: /* First loop in order to calculate */
11532: /* for age*VN*Vm
11533: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
11534: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
11535: */
11536: /* Needs FixedV[Tvardk[k][1]] */
11537: /* For others:
11538: * Sets Typevar[k];
11539: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11540: * Tposprod[k]=k11;
11541: * Tprod[k11]=k;
11542: * Tvardk[k][1] =m;
11543: * Needs FixedV[Tvardk[k][1]] == 0
11544: */
11545:
1.319 brouard 11546: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11547: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11548: 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" */
11549: if (nbocc(modelsav,'+')==0)
11550: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11551: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11552: /*scanf("%d",i);*/
1.349 brouard 11553: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age OR double product with age strb=age*V6*V2 or V6*V2*age or V6*age*V2 */
11554: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 OR strb=age*V6*V2 strc=V6*V2 strd=age OR c=V2*age OR c=age*V2 */
11555: if(strchr(strc,'*')) { /**< Model with age and DOUBLE product: allowed since 0.99r44, strc=V6*V2 or V2*age or age*V2, strd=age or V6 or V6 */
11556: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
11557: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
11558: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
11559: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
11560: /* We want strb=Vn*Vm */
11561: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
11562: strcpy(strb,strd);
11563: strcat(strb,"*");
11564: strcat(strb,stre);
11565: }else{ /* strf=Vm If strf=V6 then stre=V2 */
11566: strcpy(strb,strf);
11567: strcat(strb,"*");
11568: strcat(strb,stre);
11569: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
11570: }
1.351 brouard 11571: /* printf("DEBUG FIXED k=%d, Tage[k]=%d, Tvar[Tage[k]=%d,FixedV[Tvar[Tage[k]]]=%d\n",k,Tage[k],Tvar[Tage[k]],FixedV[Tvar[Tage[k]]]); */
11572: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 11573: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
11574: strcpy(stre,strb); /* save full b in stre */
11575: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
11576: strcpy(strf,strc); /* save short c in new short f */
11577: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
11578: /* strcpy(strc,stre);*/ /* save full e in c for future */
11579: }
11580: cptcovdageprod++; /* double product with age Which product is it? */
11581: /* strcpy(strb,strc); /\* strb was age*V6*V2 or V6*V2*age or V6*age*V2 IS now V6*V2 or V2*age or age*V2 *\/ */
11582: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11583: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 11584: n=atoi(stre);
1.234 brouard 11585: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 11586: m=atoi(strc);
11587: cptcovage++; /* Counts the number of covariates which include age as a product */
11588: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
11589: if(existcomb[n][m] == 0){
11590: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
11591: printf("Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
11592: fprintf(ficlog,"Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
11593: fflush(ficlog);
11594: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
11595: k12++;
11596: existcomb[n][m]=k1;
11597: existcomb[m][n]=k1;
11598: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
11599: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2+ age*V6*V3 Gives the k position of the k1 double product Vn*Vm or age*Vn*Vm*/
11600: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
11601: Tvard[k1][1] =m; /* m 1 for V1*/
11602: Tvardk[k][1] =m; /* m 1 for V1*/
11603: Tvard[k1][2] =n; /* n 4 for V4*/
11604: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 11605: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 11606: 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 */
11607: for (i=1; i<=lastobs;i++){/* For fixed product */
11608: /* Computes the new covariate which is a product of
11609: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11610: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11611: }
11612: cptcovprodage++; /* Counting the number of fixed covariate with age */
11613: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11614: k12++;
11615: FixedV[ncovcolt+k12]=0;
11616: }else{ /*End of FixedV */
11617: cptcovprodvage++; /* Counting the number of varying covariate with age */
11618: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11619: k12++;
11620: FixedV[ncovcolt+k12]=1;
11621: }
11622: }else{ /* k1 Vn*Vm already exists */
11623: k11=existcomb[n][m];
11624: Tposprod[k]=k11; /* OK */
11625: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
11626: Tvardk[k][1]=m;
11627: Tvardk[k][2]=n;
11628: 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 */
11629: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11630: cptcovprodage++; /* Counting the number of fixed covariate with age */
11631: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11632: Tvar[Tage[cptcovage]]=k1;
11633: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11634: k12++;
11635: FixedV[ncovcolt+k12]=0;
11636: }else{ /* Already exists but time varying (and age) */
11637: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11638: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11639: /* Tvar[Tage[cptcovage]]=k1; */
11640: cptcovprodvage++;
11641: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11642: k12++;
11643: FixedV[ncovcolt+k12]=1;
11644: }
11645: }
11646: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
11647: /* Tvar[k]=k11; /\* HERY *\/ */
11648: } else {/* simple product strb=age*Vn so that c=Vn and d=age, or strb=Vn*age so that c=age and d=Vn, or b=Vn*Vm so that c=Vm and d=Vn */
11649: cptcovprod++;
11650: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
11651: /* covar is not filled and then is empty */
11652: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
11653: 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 */
11654: Typevar[k]=1; /* 1 for age product */
11655: cptcovage++; /* Counts the number of covariates which include age as a product */
11656: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
11657: if( FixedV[Tvar[k]] == 0){
11658: cptcovprodage++; /* Counting the number of fixed covariate with age */
11659: }else{
11660: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
11661: }
11662: /*printf("stre=%s ", stre);*/
11663: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
11664: cutl(stre,strb,strc,'V');
11665: Tvar[k]=atoi(stre);
11666: Typevar[k]=1; /* 1 for age product */
11667: cptcovage++;
11668: Tage[cptcovage]=k;
11669: if( FixedV[Tvar[k]] == 0){
11670: cptcovprodage++; /* Counting the number of fixed covariate with age */
11671: }else{
11672: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11673: }
1.349 brouard 11674: }else{ /* for product Vn*Vm */
11675: Typevar[k]=2; /* 2 for product Vn*Vm */
11676: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
11677: n=atoi(stre);
11678: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11679: m=atoi(strc);
11680: k1++;
11681: cptcovprodnoage++;
11682: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
11683: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11684: fprintf(ficlog,"Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11685: fflush(ficlog);
11686: k11=existcomb[n][m];
11687: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11688: Tposprod[k]=k11;
11689: Tprod[k11]=k;
11690: Tvardk[k][1] =m; /* m 1 for V1*/
11691: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
11692: Tvardk[k][2] =n; /* n 4 for V4*/
11693: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
11694: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
11695: existcomb[n][m]=k1;
11696: existcomb[m][n]=k1;
11697: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
11698: because this model-covariate is a construction we invent a new column
11699: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
11700: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
11701: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
11702: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
11703: /* Please remark that the new variables are model dependent */
11704: /* If we have 4 variable but the model uses only 3, like in
11705: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11706: * k= 1 2 3 4 5 6 7 8
11707: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11708: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11709: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11710: */
11711: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
11712: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
11713: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
11714: Tvard[k1][1] =m; /* m 1 for V1*/
11715: Tvardk[k][1] =m; /* m 1 for V1*/
11716: Tvard[k1][2] =n; /* n 4 for V4*/
11717: Tvardk[k][2] =n; /* n 4 for V4*/
11718: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11719: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11720: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
11721: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
11722: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
11723: 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 */
11724: for (i=1; i<=lastobs;i++){/* For fixed product */
11725: /* Computes the new covariate which is a product of
11726: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11727: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11728: }
11729: /* TvarVV[k2]=n; */
11730: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11731: /* TvarVV[k2+1]=m; */
11732: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11733: }else{ /* not FixedV */
11734: /* TvarVV[k2]=n; */
11735: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11736: /* TvarVV[k2+1]=m; */
11737: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11738: }
11739: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
11740: } /* End of product Vn*Vm */
11741: } /* End of age*double product or simple product */
11742: }else { /* not a product */
1.234 brouard 11743: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11744: /* scanf("%d",i);*/
11745: cutl(strd,strc,strb,'V');
11746: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11747: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11748: Tvar[k]=atoi(strd);
11749: Typevar[k]=0; /* 0 for simple covariates */
11750: }
11751: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11752: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11753: scanf("%d",i);*/
1.187 brouard 11754: } /* end of loop + on total covariates */
1.351 brouard 11755:
11756:
1.187 brouard 11757: } /* end if strlen(modelsave == 0) age*age might exist */
11758: } /* end if strlen(model == 0) */
1.349 brouard 11759: cptcovs=cptcovt - cptcovdageprod - cptcovprod;/**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age + age*v4*V3=> V1 + V3 =4+1-3=2 */
11760:
1.136 brouard 11761: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11762: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11763:
1.136 brouard 11764: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11765: printf("cptcovprod=%d ", cptcovprod);
11766: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11767: scanf("%d ",i);*/
11768:
11769:
1.230 brouard 11770: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11771: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11772: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11773: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11774: k = 1 2 3 4 5 6 7 8 9
11775: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11776: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11777: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11778: Dummy[k] 1 0 0 0 3 1 1 2 3
11779: Tmodelind[combination of covar]=k;
1.225 brouard 11780: */
11781: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11782: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11783: /* 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 11784: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11785: printf("Model=1+age+%s\n\
1.349 brouard 11786: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 11787: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11788: 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 11789: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 11790: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 11791: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11792: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.342 brouard 11793: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11794: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 11795:
11796:
11797: /* Second loop for calculating Fixed[k], Dummy[k]*/
11798:
11799:
1.349 brouard 11800: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0,ncovva=0,ncovvta=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt loop on k from model */
1.234 brouard 11801: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11802: Fixed[k]= 0;
11803: Dummy[k]= 0;
1.225 brouard 11804: ncoveff++;
1.232 brouard 11805: ncovf++;
1.234 brouard 11806: nsd++;
11807: modell[k].maintype= FTYPE;
11808: TvarsD[nsd]=Tvar[k];
11809: TvarsDind[nsd]=k;
1.330 brouard 11810: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11811: TvarF[ncovf]=Tvar[k];
11812: TvarFind[ncovf]=k;
11813: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11814: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11815: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
1.240 brouard 11816: }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 11817: Fixed[k]= 0;
11818: Dummy[k]= 1;
1.230 brouard 11819: nqfveff++;
1.234 brouard 11820: modell[k].maintype= FTYPE;
11821: modell[k].subtype= FQ;
11822: nsq++;
1.334 brouard 11823: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11824: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11825: ncovf++;
1.234 brouard 11826: TvarF[ncovf]=Tvar[k];
11827: TvarFind[ncovf]=k;
1.231 brouard 11828: 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 11829: 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 11830: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11831: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11832: /* model V1+V3+age*V1+age*V3+V1*V3 */
11833: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11834: ncovvt++;
11835: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11836: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11837:
1.227 brouard 11838: Fixed[k]= 1;
11839: Dummy[k]= 0;
1.225 brouard 11840: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11841: modell[k].maintype= VTYPE;
11842: modell[k].subtype= VD;
11843: nsd++;
11844: TvarsD[nsd]=Tvar[k];
11845: TvarsDind[nsd]=k;
1.330 brouard 11846: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11847: ncovv++; /* Only simple time varying variables */
11848: TvarV[ncovv]=Tvar[k];
1.242 brouard 11849: 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 11850: 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 */
11851: 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 11852: 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);
11853: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11854: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11855: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11856: /* model V1+V3+age*V1+age*V3+V1*V3 */
11857: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11858: ncovvt++;
11859: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11860: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11861:
1.234 brouard 11862: Fixed[k]= 1;
11863: Dummy[k]= 1;
11864: nqtveff++;
11865: modell[k].maintype= VTYPE;
11866: modell[k].subtype= VQ;
11867: ncovv++; /* Only simple time varying variables */
11868: nsq++;
1.334 brouard 11869: 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) */
11870: 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 11871: TvarV[ncovv]=Tvar[k];
1.242 brouard 11872: 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 11873: 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 */
11874: 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 11875: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11876: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 11877: /* printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%Ad,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv); */
1.342 brouard 11878: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11879: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11880: ncova++;
11881: TvarA[ncova]=Tvar[k];
11882: TvarAind[ncova]=k;
1.349 brouard 11883: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11884: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.231 brouard 11885: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11886: Fixed[k]= 2;
11887: Dummy[k]= 2;
11888: modell[k].maintype= ATYPE;
11889: modell[k].subtype= APFD;
1.349 brouard 11890: ncovta++;
11891: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
11892: TvarAVVAind[ncovta]=k;
1.240 brouard 11893: /* ncoveff++; */
1.227 brouard 11894: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11895: Fixed[k]= 2;
11896: Dummy[k]= 3;
11897: modell[k].maintype= ATYPE;
11898: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 11899: ncovta++;
11900: TvarAVVA[ncovta]=Tvar[k]; /* */
11901: TvarAVVAind[ncovta]=k;
1.240 brouard 11902: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11903: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11904: Fixed[k]= 3;
11905: Dummy[k]= 2;
11906: modell[k].maintype= ATYPE;
11907: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 11908: ncovva++;
11909: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11910: TvarVVAind[ncovva]=k;
11911: ncovta++;
11912: TvarAVVA[ncovta]=Tvar[k]; /* */
11913: TvarAVVAind[ncovta]=k;
1.240 brouard 11914: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11915: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11916: Fixed[k]= 3;
11917: Dummy[k]= 3;
11918: modell[k].maintype= ATYPE;
11919: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 11920: ncovva++;
11921: TvarVVA[ncovva]=Tvar[k]; /* */
11922: TvarVVAind[ncovva]=k;
11923: ncovta++;
11924: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11925: TvarAVVAind[ncovta]=k;
1.240 brouard 11926: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11927: }
1.349 brouard 11928: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
11929: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
11930: if(FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol V3*V2 */
11931: printf("MEMORY ERRORR k=%d Tvardk[k][1]=%d, Tvardk[k][2]=%d, FixedV[Tvardk[k][1]]=%d,FixedV[Tvardk[k][2]]=%d\n ",k,Tvardk[k][1],Tvardk[k][2],FixedV[Tvardk[k][1]],FixedV[Tvardk[k][2]]);
11932: Fixed[k]= 0;
11933: Dummy[k]= 0;
11934: ncoveff++;
11935: ncovf++;
11936: /* ncovv++; */
11937: /* TvarVV[ncovv]=Tvardk[k][1]; */
11938: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11939: /* ncovv++; */
11940: /* TvarVV[ncovv]=Tvardk[k][2]; */
11941: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11942: modell[k].maintype= FTYPE;
11943: TvarF[ncovf]=Tvar[k];
11944: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
11945: TvarFind[ncovf]=k;
11946: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11947: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11948: }else{/* product varying Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
11949: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11950: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11951: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11952: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
11953: ncovvt++;
11954: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11955: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11956: ncovvt++;
11957: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11958: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11959:
11960: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11961: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
11962:
11963: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11964: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
11965: Fixed[k]= 1;
11966: Dummy[k]= 0;
11967: modell[k].maintype= FTYPE;
11968: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11969: ncovf++; /* Fixed variables without age */
11970: TvarF[ncovf]=Tvar[k];
11971: TvarFind[ncovf]=k;
11972: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11973: Fixed[k]= 0; /* Fixed product */
11974: Dummy[k]= 1;
11975: modell[k].maintype= FTYPE;
11976: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11977: ncovf++; /* Varying variables without age */
11978: TvarF[ncovf]=Tvar[k];
11979: TvarFind[ncovf]=k;
11980: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
11981: Fixed[k]= 1;
11982: Dummy[k]= 0;
11983: modell[k].maintype= VTYPE;
11984: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11985: ncovv++; /* Varying variables without age */
11986: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11987: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11988: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
11989: Fixed[k]= 1;
11990: Dummy[k]= 1;
11991: modell[k].maintype= VTYPE;
11992: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11993: ncovv++; /* Varying variables without age */
11994: TvarV[ncovv]=Tvar[k];
11995: TvarVind[ncovv]=k;
11996: }
11997: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11998: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11999: Fixed[k]= 0; /* Fixed product */
12000: Dummy[k]= 1;
12001: modell[k].maintype= FTYPE;
12002: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
12003: ncovf++; /* Fixed variables without age */
12004: TvarF[ncovf]=Tvar[k];
12005: TvarFind[ncovf]=k;
12006: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
12007: Fixed[k]= 1;
12008: Dummy[k]= 1;
12009: modell[k].maintype= VTYPE;
12010: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
12011: ncovv++; /* Varying variables without age */
12012: TvarV[ncovv]=Tvar[k];
12013: TvarVind[ncovv]=k;
12014: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
12015: Fixed[k]= 1;
12016: Dummy[k]= 1;
12017: modell[k].maintype= VTYPE;
12018: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
12019: ncovv++; /* Varying variables without age */
12020: TvarV[ncovv]=Tvar[k];
12021: TvarVind[ncovv]=k;
12022: ncovv++; /* Varying variables without age */
12023: TvarV[ncovv]=Tvar[k];
12024: TvarVind[ncovv]=k;
12025: }
12026: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
12027: if(Tvard[k1][2] <=ncovcol){
12028: Fixed[k]= 1;
12029: Dummy[k]= 1;
12030: modell[k].maintype= VTYPE;
12031: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
12032: ncovv++; /* Varying variables without age */
12033: TvarV[ncovv]=Tvar[k];
12034: TvarVind[ncovv]=k;
12035: }else if(Tvard[k1][2] <=ncovcol+nqv){
12036: Fixed[k]= 1;
12037: Dummy[k]= 1;
12038: modell[k].maintype= VTYPE;
12039: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
12040: ncovv++; /* Varying variables without age */
12041: TvarV[ncovv]=Tvar[k];
12042: TvarVind[ncovv]=k;
12043: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12044: Fixed[k]= 1;
12045: Dummy[k]= 0;
12046: modell[k].maintype= VTYPE;
12047: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
12048: ncovv++; /* Varying variables without age */
12049: TvarV[ncovv]=Tvar[k];
12050: TvarVind[ncovv]=k;
12051: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12052: Fixed[k]= 1;
12053: Dummy[k]= 1;
12054: modell[k].maintype= VTYPE;
12055: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
12056: ncovv++; /* Varying variables without age */
12057: TvarV[ncovv]=Tvar[k];
12058: TvarVind[ncovv]=k;
12059: }
12060: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
12061: if(Tvard[k1][2] <=ncovcol){
12062: Fixed[k]= 1;
12063: Dummy[k]= 1;
12064: modell[k].maintype= VTYPE;
12065: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
12066: ncovv++; /* Varying variables without age */
12067: TvarV[ncovv]=Tvar[k];
12068: TvarVind[ncovv]=k;
12069: }else if(Tvard[k1][2] <=ncovcol+nqv){
12070: Fixed[k]= 1;
12071: Dummy[k]= 1;
12072: modell[k].maintype= VTYPE;
12073: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
12074: ncovv++; /* Varying variables without age */
12075: TvarV[ncovv]=Tvar[k];
12076: TvarVind[ncovv]=k;
12077: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12078: Fixed[k]= 1;
12079: Dummy[k]= 1;
12080: modell[k].maintype= VTYPE;
12081: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
12082: ncovv++; /* Varying variables without age */
12083: TvarV[ncovv]=Tvar[k];
12084: TvarVind[ncovv]=k;
12085: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12086: Fixed[k]= 1;
12087: Dummy[k]= 1;
12088: modell[k].maintype= VTYPE;
12089: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
12090: ncovv++; /* Varying variables without age */
12091: TvarV[ncovv]=Tvar[k];
12092: TvarVind[ncovv]=k;
12093: }
12094: }else{
12095: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12096: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12097: } /*end k1*/
12098: }
12099: }else if(Typevar[k] == 3){ /* product Vn * Vm with age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
1.339 brouard 12100: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 12101: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
12102: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
12103: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
12104: ncova++;
12105: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
12106: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
12107: ncova++;
12108: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
12109: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 12110:
1.349 brouard 12111: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
12112: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
12113: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
12114: ncovta++;
12115: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12116: TvarAVVAind[ncovta]=k;
12117: ncovta++;
12118: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12119: TvarAVVAind[ncovta]=k;
12120: }else{
12121: ncovva++; /* HERY reached */
12122: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12123: TvarVVAind[ncovva]=k;
12124: ncovva++;
12125: TvarVVA[ncovva]=Tvard[k1][2]; /* */
12126: TvarVVAind[ncovva]=k;
12127: ncovta++;
12128: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12129: TvarAVVAind[ncovta]=k;
12130: ncovta++;
12131: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12132: TvarAVVAind[ncovta]=k;
12133: }
1.339 brouard 12134: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12135: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 12136: Fixed[k]= 2;
12137: Dummy[k]= 2;
1.240 brouard 12138: modell[k].maintype= FTYPE;
12139: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 12140: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
12141: /* TvarFind[ncova]=k; */
1.339 brouard 12142: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 12143: Fixed[k]= 2; /* Fixed product */
12144: Dummy[k]= 3;
1.240 brouard 12145: modell[k].maintype= FTYPE;
12146: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 12147: /* TvarF[ncova]=Tvar[k]; */
12148: /* TvarFind[ncova]=k; */
1.339 brouard 12149: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 12150: Fixed[k]= 3;
12151: Dummy[k]= 2;
1.240 brouard 12152: modell[k].maintype= VTYPE;
12153: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 12154: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
12155: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12156: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 12157: Fixed[k]= 3;
12158: Dummy[k]= 3;
1.240 brouard 12159: modell[k].maintype= VTYPE;
12160: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 12161: /* ncovv++; /\* Varying variables without age *\/ */
12162: /* TvarV[ncovv]=Tvar[k]; */
12163: /* TvarVind[ncovv]=k; */
1.240 brouard 12164: }
1.339 brouard 12165: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12166: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 12167: Fixed[k]= 2; /* Fixed product */
12168: Dummy[k]= 2;
1.240 brouard 12169: modell[k].maintype= FTYPE;
12170: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 12171: /* ncova++; /\* Fixed variables with age *\/ */
12172: /* TvarF[ncovf]=Tvar[k]; */
12173: /* TvarFind[ncovf]=k; */
1.339 brouard 12174: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 12175: Fixed[k]= 2;
12176: Dummy[k]= 3;
1.240 brouard 12177: modell[k].maintype= VTYPE;
12178: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 12179: /* ncova++; /\* Varying variables with age *\/ */
12180: /* TvarV[ncova]=Tvar[k]; */
12181: /* TvarVind[ncova]=k; */
1.339 brouard 12182: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 12183: Fixed[k]= 3;
12184: Dummy[k]= 2;
1.240 brouard 12185: modell[k].maintype= VTYPE;
12186: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 12187: ncova++; /* Varying variables without age */
12188: TvarV[ncova]=Tvar[k];
12189: TvarVind[ncova]=k;
12190: /* ncova++; /\* Varying variables without age *\/ */
12191: /* TvarV[ncova]=Tvar[k]; */
12192: /* TvarVind[ncova]=k; */
1.240 brouard 12193: }
1.339 brouard 12194: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12195: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12196: Fixed[k]= 2;
12197: Dummy[k]= 2;
1.240 brouard 12198: modell[k].maintype= VTYPE;
12199: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 12200: /* ncova++; /\* Varying variables with age *\/ */
12201: /* TvarV[ncova]=Tvar[k]; */
12202: /* TvarVind[ncova]=k; */
1.240 brouard 12203: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12204: Fixed[k]= 2;
12205: Dummy[k]= 3;
1.240 brouard 12206: modell[k].maintype= VTYPE;
12207: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 12208: /* ncova++; /\* Varying variables with age *\/ */
12209: /* TvarV[ncova]=Tvar[k]; */
12210: /* TvarVind[ncova]=k; */
1.240 brouard 12211: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12212: Fixed[k]= 3;
12213: Dummy[k]= 2;
1.240 brouard 12214: modell[k].maintype= VTYPE;
12215: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 12216: /* ncova++; /\* Varying variables with age *\/ */
12217: /* TvarV[ncova]=Tvar[k]; */
12218: /* TvarVind[ncova]=k; */
1.240 brouard 12219: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12220: Fixed[k]= 3;
12221: Dummy[k]= 3;
1.240 brouard 12222: modell[k].maintype= VTYPE;
12223: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 12224: /* ncova++; /\* Varying variables with age *\/ */
12225: /* TvarV[ncova]=Tvar[k]; */
12226: /* TvarVind[ncova]=k; */
1.240 brouard 12227: }
1.339 brouard 12228: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12229: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12230: Fixed[k]= 2;
12231: Dummy[k]= 2;
1.240 brouard 12232: modell[k].maintype= VTYPE;
12233: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 12234: /* ncova++; /\* Varying variables with age *\/ */
12235: /* TvarV[ncova]=Tvar[k]; */
12236: /* TvarVind[ncova]=k; */
1.240 brouard 12237: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12238: Fixed[k]= 2;
12239: Dummy[k]= 3;
1.240 brouard 12240: modell[k].maintype= VTYPE;
12241: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 12242: /* ncova++; /\* Varying variables with age *\/ */
12243: /* TvarV[ncova]=Tvar[k]; */
12244: /* TvarVind[ncova]=k; */
1.240 brouard 12245: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12246: Fixed[k]= 3;
12247: Dummy[k]= 2;
1.240 brouard 12248: modell[k].maintype= VTYPE;
12249: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 12250: /* ncova++; /\* Varying variables with age *\/ */
12251: /* TvarV[ncova]=Tvar[k]; */
12252: /* TvarVind[ncova]=k; */
1.240 brouard 12253: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12254: Fixed[k]= 3;
12255: Dummy[k]= 3;
1.240 brouard 12256: modell[k].maintype= VTYPE;
12257: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 12258: /* ncova++; /\* Varying variables with age *\/ */
12259: /* TvarV[ncova]=Tvar[k]; */
12260: /* TvarVind[ncova]=k; */
1.240 brouard 12261: }
1.227 brouard 12262: }else{
1.240 brouard 12263: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12264: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12265: } /*end k1*/
1.349 brouard 12266: } else{
1.226 brouard 12267: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12268: 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 12269: }
1.342 brouard 12270: /* 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]); */
12271: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12272: 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]);
12273: }
1.349 brouard 12274: ncovvta=ncovva;
1.227 brouard 12275: /* Searching for doublons in the model */
12276: for(k1=1; k1<= cptcovt;k1++){
12277: for(k2=1; k2 <k1;k2++){
1.285 brouard 12278: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12279: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12280: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12281: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12282: 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]);
12283: 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 12284: return(1);
12285: }
12286: }else if (Typevar[k1] ==2){
12287: k3=Tposprod[k1];
12288: k4=Tposprod[k2];
12289: 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 12290: 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]]);
12291: 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 12292: return(1);
12293: }
12294: }
1.227 brouard 12295: }
12296: }
1.225 brouard 12297: }
12298: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12299: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12300: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12301: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 12302:
12303: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12304: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12305: /*endread:*/
1.225 brouard 12306: printf("Exiting decodemodel: ");
12307: return (1);
1.136 brouard 12308: }
12309:
1.169 brouard 12310: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12311: {/* Check ages at death */
1.136 brouard 12312: int i, m;
1.218 brouard 12313: int firstone=0;
12314:
1.136 brouard 12315: for (i=1; i<=imx; i++) {
12316: for(m=2; (m<= maxwav); m++) {
12317: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12318: anint[m][i]=9999;
1.216 brouard 12319: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12320: s[m][i]=-1;
1.136 brouard 12321: }
12322: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12323: *nberr = *nberr + 1;
1.218 brouard 12324: if(firstone == 0){
12325: firstone=1;
1.260 brouard 12326: 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 12327: }
1.262 brouard 12328: 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 12329: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12330: }
12331: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12332: (*nberr)++;
1.259 brouard 12333: 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 12334: 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 12335: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12336: }
12337: }
12338: }
12339:
12340: for (i=1; i<=imx; i++) {
12341: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12342: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12343: 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 12344: if (s[m][i] >= nlstate+1) {
1.169 brouard 12345: if(agedc[i]>0){
12346: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12347: agev[m][i]=agedc[i];
1.214 brouard 12348: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12349: }else {
1.136 brouard 12350: if ((int)andc[i]!=9999){
12351: nbwarn++;
12352: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12353: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12354: agev[m][i]=-1;
12355: }
12356: }
1.169 brouard 12357: } /* agedc > 0 */
1.214 brouard 12358: } /* end if */
1.136 brouard 12359: else if(s[m][i] !=9){ /* Standard case, age in fractional
12360: years but with the precision of a month */
12361: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12362: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12363: agev[m][i]=1;
12364: else if(agev[m][i] < *agemin){
12365: *agemin=agev[m][i];
12366: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12367: }
12368: else if(agev[m][i] >*agemax){
12369: *agemax=agev[m][i];
1.156 brouard 12370: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12371: }
12372: /*agev[m][i]=anint[m][i]-annais[i];*/
12373: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12374: } /* en if 9*/
1.136 brouard 12375: else { /* =9 */
1.214 brouard 12376: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12377: agev[m][i]=1;
12378: s[m][i]=-1;
12379: }
12380: }
1.214 brouard 12381: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12382: agev[m][i]=1;
1.214 brouard 12383: else{
12384: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12385: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12386: agev[m][i]=0;
12387: }
12388: } /* End for lastpass */
12389: }
1.136 brouard 12390:
12391: for (i=1; i<=imx; i++) {
12392: for(m=firstpass; (m<=lastpass); m++){
12393: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12394: (*nberr)++;
1.136 brouard 12395: 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);
12396: 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);
12397: return 1;
12398: }
12399: }
12400: }
12401:
12402: /*for (i=1; i<=imx; i++){
12403: for (m=firstpass; (m<lastpass); m++){
12404: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12405: }
12406:
12407: }*/
12408:
12409:
1.139 brouard 12410: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12411: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12412:
12413: return (0);
1.164 brouard 12414: /* endread:*/
1.136 brouard 12415: printf("Exiting calandcheckages: ");
12416: return (1);
12417: }
12418:
1.172 brouard 12419: #if defined(_MSC_VER)
12420: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12421: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12422: //#include "stdafx.h"
12423: //#include <stdio.h>
12424: //#include <tchar.h>
12425: //#include <windows.h>
12426: //#include <iostream>
12427: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12428:
12429: LPFN_ISWOW64PROCESS fnIsWow64Process;
12430:
12431: BOOL IsWow64()
12432: {
12433: BOOL bIsWow64 = FALSE;
12434:
12435: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12436: // (HANDLE, PBOOL);
12437:
12438: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12439:
12440: HMODULE module = GetModuleHandle(_T("kernel32"));
12441: const char funcName[] = "IsWow64Process";
12442: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12443: GetProcAddress(module, funcName);
12444:
12445: if (NULL != fnIsWow64Process)
12446: {
12447: if (!fnIsWow64Process(GetCurrentProcess(),
12448: &bIsWow64))
12449: //throw std::exception("Unknown error");
12450: printf("Unknown error\n");
12451: }
12452: return bIsWow64 != FALSE;
12453: }
12454: #endif
1.177 brouard 12455:
1.191 brouard 12456: void syscompilerinfo(int logged)
1.292 brouard 12457: {
12458: #include <stdint.h>
12459:
12460: /* #include "syscompilerinfo.h"*/
1.185 brouard 12461: /* command line Intel compiler 32bit windows, XP compatible:*/
12462: /* /GS /W3 /Gy
12463: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12464: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12465: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12466: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12467: */
12468: /* 64 bits */
1.185 brouard 12469: /*
12470: /GS /W3 /Gy
12471: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12472: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12473: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12474: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12475: /* Optimization are useless and O3 is slower than O2 */
12476: /*
12477: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12478: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12479: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12480: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12481: */
1.186 brouard 12482: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12483: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12484: /PDB:"visual studio
12485: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12486: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12487: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12488: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12489: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12490: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12491: uiAccess='false'"
12492: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12493: /NOLOGO /TLBID:1
12494: */
1.292 brouard 12495:
12496:
1.177 brouard 12497: #if defined __INTEL_COMPILER
1.178 brouard 12498: #if defined(__GNUC__)
12499: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12500: #endif
1.177 brouard 12501: #elif defined(__GNUC__)
1.179 brouard 12502: #ifndef __APPLE__
1.174 brouard 12503: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12504: #endif
1.177 brouard 12505: struct utsname sysInfo;
1.178 brouard 12506: int cross = CROSS;
12507: if (cross){
12508: printf("Cross-");
1.191 brouard 12509: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12510: }
1.174 brouard 12511: #endif
12512:
1.191 brouard 12513: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12514: #if defined(__clang__)
1.191 brouard 12515: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12516: #endif
12517: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12518: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12519: #endif
12520: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12521: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12522: #endif
12523: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12524: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12525: #endif
12526: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12527: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12528: #endif
12529: #if defined(_MSC_VER)
1.191 brouard 12530: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12531: #endif
12532: #if defined(__PGI)
1.191 brouard 12533: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12534: #endif
12535: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12536: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12537: #endif
1.191 brouard 12538: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12539:
1.167 brouard 12540: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12541: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12542: // Windows (x64 and x86)
1.191 brouard 12543: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12544: #elif __unix__ // all unices, not all compilers
12545: // Unix
1.191 brouard 12546: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12547: #elif __linux__
12548: // linux
1.191 brouard 12549: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12550: #elif __APPLE__
1.174 brouard 12551: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12552: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12553: #endif
12554:
12555: /* __MINGW32__ */
12556: /* __CYGWIN__ */
12557: /* __MINGW64__ */
12558: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12559: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12560: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12561: /* _WIN64 // Defined for applications for Win64. */
12562: /* _M_X64 // Defined for compilations that target x64 processors. */
12563: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12564:
1.167 brouard 12565: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12566: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12567: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12568: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12569: #else
1.191 brouard 12570: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12571: #endif
12572:
1.169 brouard 12573: #if defined(__GNUC__)
12574: # if defined(__GNUC_PATCHLEVEL__)
12575: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12576: + __GNUC_MINOR__ * 100 \
12577: + __GNUC_PATCHLEVEL__)
12578: # else
12579: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12580: + __GNUC_MINOR__ * 100)
12581: # endif
1.174 brouard 12582: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12583: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12584:
12585: if (uname(&sysInfo) != -1) {
12586: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12587: 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 12588: }
12589: else
12590: perror("uname() error");
1.179 brouard 12591: //#ifndef __INTEL_COMPILER
12592: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12593: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12594: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12595: #endif
1.169 brouard 12596: #endif
1.172 brouard 12597:
1.286 brouard 12598: // void main ()
1.172 brouard 12599: // {
1.169 brouard 12600: #if defined(_MSC_VER)
1.174 brouard 12601: if (IsWow64()){
1.191 brouard 12602: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12603: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12604: }
12605: else{
1.191 brouard 12606: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12607: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12608: }
1.172 brouard 12609: // printf("\nPress Enter to continue...");
12610: // getchar();
12611: // }
12612:
1.169 brouard 12613: #endif
12614:
1.167 brouard 12615:
1.219 brouard 12616: }
1.136 brouard 12617:
1.219 brouard 12618: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12619: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12620: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12621: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12622: /* double ftolpl = 1.e-10; */
1.180 brouard 12623: double age, agebase, agelim;
1.203 brouard 12624: double tot;
1.180 brouard 12625:
1.202 brouard 12626: strcpy(filerespl,"PL_");
12627: strcat(filerespl,fileresu);
12628: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12629: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12630: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12631: }
1.288 brouard 12632: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12633: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12634: pstamp(ficrespl);
1.288 brouard 12635: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12636: fprintf(ficrespl,"#Age ");
12637: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12638: fprintf(ficrespl,"\n");
1.180 brouard 12639:
1.219 brouard 12640: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12641:
1.219 brouard 12642: agebase=ageminpar;
12643: agelim=agemaxpar;
1.180 brouard 12644:
1.227 brouard 12645: /* i1=pow(2,ncoveff); */
1.234 brouard 12646: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12647: if (cptcovn < 1){i1=1;}
1.180 brouard 12648:
1.337 brouard 12649: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12650: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12651: k=TKresult[nres];
1.338 brouard 12652: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12653: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12654: /* continue; */
1.235 brouard 12655:
1.238 brouard 12656: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12657: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12658: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12659: /* k=k+1; */
12660: /* to clean */
1.332 brouard 12661: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12662: fprintf(ficrespl,"#******");
12663: printf("#******");
12664: fprintf(ficlog,"#******");
1.337 brouard 12665: 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 12666: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12667: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12668: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12669: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12670: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12671: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12672: }
12673: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12674: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12675: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12676: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12677: /* } */
1.238 brouard 12678: fprintf(ficrespl,"******\n");
12679: printf("******\n");
12680: fprintf(ficlog,"******\n");
12681: if(invalidvarcomb[k]){
12682: printf("\nCombination (%d) ignored because no case \n",k);
12683: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12684: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12685: continue;
12686: }
1.219 brouard 12687:
1.238 brouard 12688: fprintf(ficrespl,"#Age ");
1.337 brouard 12689: /* for(j=1;j<=cptcoveff;j++) { */
12690: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12691: /* } */
12692: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12693: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12694: }
12695: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12696: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12697:
1.238 brouard 12698: for (age=agebase; age<=agelim; age++){
12699: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12700: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12701: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12702: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12703: /* for(j=1;j<=cptcoveff;j++) */
12704: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12705: for(j=1;j<=cptcovs;j++)
12706: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12707: tot=0.;
12708: for(i=1; i<=nlstate;i++){
12709: tot += prlim[i][i];
12710: fprintf(ficrespl," %.5f", prlim[i][i]);
12711: }
12712: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12713: } /* Age */
12714: /* was end of cptcod */
1.337 brouard 12715: } /* nres */
12716: /* } /\* for each combination *\/ */
1.219 brouard 12717: return 0;
1.180 brouard 12718: }
12719:
1.218 brouard 12720: 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 12721: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12722:
12723: /* Computes the back prevalence limit for any combination of covariate values
12724: * at any age between ageminpar and agemaxpar
12725: */
1.235 brouard 12726: int i, j, k, i1, nres=0 ;
1.217 brouard 12727: /* double ftolpl = 1.e-10; */
12728: double age, agebase, agelim;
12729: double tot;
1.218 brouard 12730: /* double ***mobaverage; */
12731: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12732:
12733: strcpy(fileresplb,"PLB_");
12734: strcat(fileresplb,fileresu);
12735: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12736: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12737: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12738: }
1.288 brouard 12739: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12740: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12741: pstamp(ficresplb);
1.288 brouard 12742: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12743: fprintf(ficresplb,"#Age ");
12744: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12745: fprintf(ficresplb,"\n");
12746:
1.218 brouard 12747:
12748: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12749:
12750: agebase=ageminpar;
12751: agelim=agemaxpar;
12752:
12753:
1.227 brouard 12754: i1=pow(2,cptcoveff);
1.218 brouard 12755: if (cptcovn < 1){i1=1;}
1.227 brouard 12756:
1.238 brouard 12757: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12758: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12759: k=TKresult[nres];
12760: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12761: /* if(i1 != 1 && TKresult[nres]!= k) */
12762: /* continue; */
12763: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12764: fprintf(ficresplb,"#******");
12765: printf("#******");
12766: fprintf(ficlog,"#******");
1.338 brouard 12767: 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) */
12768: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12769: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12770: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12771: }
1.338 brouard 12772: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12773: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12774: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12775: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12776: /* } */
12777: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12778: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12779: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12780: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12781: /* } */
1.238 brouard 12782: fprintf(ficresplb,"******\n");
12783: printf("******\n");
12784: fprintf(ficlog,"******\n");
12785: if(invalidvarcomb[k]){
12786: printf("\nCombination (%d) ignored because no cases \n",k);
12787: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12788: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12789: continue;
12790: }
1.218 brouard 12791:
1.238 brouard 12792: fprintf(ficresplb,"#Age ");
1.338 brouard 12793: for(j=1;j<=cptcovs;j++) {
12794: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12795: }
12796: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12797: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12798:
12799:
1.238 brouard 12800: for (age=agebase; age<=agelim; age++){
12801: /* for (age=agebase; age<=agebase; age++){ */
12802: if(mobilavproj > 0){
12803: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12804: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12805: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12806: }else if (mobilavproj == 0){
12807: 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);
12808: 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);
12809: exit(1);
12810: }else{
12811: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12812: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12813: /* printf("TOTOT\n"); */
12814: /* exit(1); */
1.238 brouard 12815: }
12816: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12817: for(j=1;j<=cptcovs;j++)
12818: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12819: tot=0.;
12820: for(i=1; i<=nlstate;i++){
12821: tot += bprlim[i][i];
12822: fprintf(ficresplb," %.5f", bprlim[i][i]);
12823: }
12824: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12825: } /* Age */
12826: /* was end of cptcod */
1.255 brouard 12827: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12828: /* } /\* end of any combination *\/ */
1.238 brouard 12829: } /* end of nres */
1.218 brouard 12830: /* hBijx(p, bage, fage); */
12831: /* fclose(ficrespijb); */
12832:
12833: return 0;
1.217 brouard 12834: }
1.218 brouard 12835:
1.180 brouard 12836: int hPijx(double *p, int bage, int fage){
12837: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12838: /* to be optimized with precov */
1.180 brouard 12839: int stepsize;
12840: int agelim;
12841: int hstepm;
12842: int nhstepm;
1.235 brouard 12843: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12844:
12845: double agedeb;
12846: double ***p3mat;
12847:
1.337 brouard 12848: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12849: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12850: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12851: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12852: }
12853: printf("Computing pij: result on file '%s' \n", filerespij);
12854: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12855:
12856: stepsize=(int) (stepm+YEARM-1)/YEARM;
12857: /*if (stepm<=24) stepsize=2;*/
12858:
12859: agelim=AGESUP;
12860: hstepm=stepsize*YEARM; /* Every year of age */
12861: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12862:
12863: /* hstepm=1; aff par mois*/
12864: pstamp(ficrespij);
12865: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12866: i1= pow(2,cptcoveff);
12867: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12868: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12869: /* k=k+1; */
12870: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12871: k=TKresult[nres];
1.338 brouard 12872: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12873: /* for(k=1; k<=i1;k++){ */
12874: /* if(i1 != 1 && TKresult[nres]!= k) */
12875: /* continue; */
12876: fprintf(ficrespij,"\n#****** ");
12877: for(j=1;j<=cptcovs;j++){
12878: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12879: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12880: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12881: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12882: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12883: }
12884: fprintf(ficrespij,"******\n");
12885:
12886: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12887: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12888: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12889:
12890: /* nhstepm=nhstepm*YEARM; aff par mois*/
12891:
12892: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12893: oldm=oldms;savm=savms;
12894: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12895: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12896: for(i=1; i<=nlstate;i++)
12897: for(j=1; j<=nlstate+ndeath;j++)
12898: fprintf(ficrespij," %1d-%1d",i,j);
12899: fprintf(ficrespij,"\n");
12900: for (h=0; h<=nhstepm; h++){
12901: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12902: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12903: for(i=1; i<=nlstate;i++)
12904: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12905: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12906: fprintf(ficrespij,"\n");
12907: }
1.337 brouard 12908: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12909: fprintf(ficrespij,"\n");
1.180 brouard 12910: }
1.337 brouard 12911: }
12912: /*}*/
12913: return 0;
1.180 brouard 12914: }
1.218 brouard 12915:
12916: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12917: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12918: /* To be optimized with precov */
1.217 brouard 12919: int stepsize;
1.218 brouard 12920: /* int agelim; */
12921: int ageminl;
1.217 brouard 12922: int hstepm;
12923: int nhstepm;
1.238 brouard 12924: int h, i, i1, j, k, nres;
1.218 brouard 12925:
1.217 brouard 12926: double agedeb;
12927: double ***p3mat;
1.218 brouard 12928:
12929: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12930: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12931: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12932: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12933: }
12934: printf("Computing pij back: result on file '%s' \n", filerespijb);
12935: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12936:
12937: stepsize=(int) (stepm+YEARM-1)/YEARM;
12938: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12939:
1.218 brouard 12940: /* agelim=AGESUP; */
1.289 brouard 12941: ageminl=AGEINF; /* was 30 */
1.218 brouard 12942: hstepm=stepsize*YEARM; /* Every year of age */
12943: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12944:
12945: /* hstepm=1; aff par mois*/
12946: pstamp(ficrespijb);
1.255 brouard 12947: 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 12948: i1= pow(2,cptcoveff);
1.218 brouard 12949: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12950: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12951: /* k=k+1; */
1.238 brouard 12952: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12953: k=TKresult[nres];
1.338 brouard 12954: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12955: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12956: /* if(i1 != 1 && TKresult[nres]!= k) */
12957: /* continue; */
12958: fprintf(ficrespijb,"\n#****** ");
12959: for(j=1;j<=cptcovs;j++){
1.338 brouard 12960: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12961: /* for(j=1;j<=cptcoveff;j++) */
12962: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12963: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12964: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12965: }
12966: fprintf(ficrespijb,"******\n");
12967: if(invalidvarcomb[k]){ /* Is it necessary here? */
12968: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12969: continue;
12970: }
12971:
12972: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12973: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12974: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12975: 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 */
12976: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12977:
12978: /* nhstepm=nhstepm*YEARM; aff par mois*/
12979:
12980: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12981: /* and memory limitations if stepm is small */
12982:
12983: /* oldm=oldms;savm=savms; */
12984: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12985: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12986: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12987: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12988: for(i=1; i<=nlstate;i++)
12989: for(j=1; j<=nlstate+ndeath;j++)
12990: fprintf(ficrespijb," %1d-%1d",i,j);
12991: fprintf(ficrespijb,"\n");
12992: for (h=0; h<=nhstepm; h++){
12993: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12994: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12995: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12996: for(i=1; i<=nlstate;i++)
12997: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12998: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12999: fprintf(ficrespijb,"\n");
1.337 brouard 13000: }
13001: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
13002: fprintf(ficrespijb,"\n");
13003: } /* end age deb */
13004: /* } /\* end combination *\/ */
1.238 brouard 13005: } /* end nres */
1.218 brouard 13006: return 0;
13007: } /* hBijx */
1.217 brouard 13008:
1.180 brouard 13009:
1.136 brouard 13010: /***********************************************/
13011: /**************** Main Program *****************/
13012: /***********************************************/
13013:
13014: int main(int argc, char *argv[])
13015: {
13016: #ifdef GSL
13017: const gsl_multimin_fminimizer_type *T;
13018: size_t iteri = 0, it;
13019: int rval = GSL_CONTINUE;
13020: int status = GSL_SUCCESS;
13021: double ssval;
13022: #endif
13023: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 13024: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
13025: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 13026: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 13027: int jj, ll, li, lj, lk;
1.136 brouard 13028: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 13029: int num_filled;
1.136 brouard 13030: int itimes;
13031: int NDIM=2;
13032: int vpopbased=0;
1.235 brouard 13033: int nres=0;
1.258 brouard 13034: int endishere=0;
1.277 brouard 13035: int noffset=0;
1.274 brouard 13036: int ncurrv=0; /* Temporary variable */
13037:
1.164 brouard 13038: char ca[32], cb[32];
1.136 brouard 13039: /* FILE *fichtm; *//* Html File */
13040: /* FILE *ficgp;*/ /*Gnuplot File */
13041: struct stat info;
1.191 brouard 13042: double agedeb=0.;
1.194 brouard 13043:
13044: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 13045: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 13046:
1.165 brouard 13047: double fret;
1.191 brouard 13048: double dum=0.; /* Dummy variable */
1.136 brouard 13049: double ***p3mat;
1.218 brouard 13050: /* double ***mobaverage; */
1.319 brouard 13051: double wald;
1.164 brouard 13052:
1.351 brouard 13053: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 13054: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
13055:
1.234 brouard 13056: char modeltemp[MAXLINE];
1.332 brouard 13057: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 13058:
1.136 brouard 13059: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 13060: char *tok, *val; /* pathtot */
1.334 brouard 13061: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 13062: int c, h , cpt, c2;
1.191 brouard 13063: int jl=0;
13064: int i1, j1, jk, stepsize=0;
1.194 brouard 13065: int count=0;
13066:
1.164 brouard 13067: int *tab;
1.136 brouard 13068: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 13069: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
13070: /* double anprojf, mprojf, jprojf; */
13071: /* double jintmean,mintmean,aintmean; */
13072: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13073: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13074: double yrfproj= 10.0; /* Number of years of forward projections */
13075: double yrbproj= 10.0; /* Number of years of backward projections */
13076: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 13077: int mobilav=0,popforecast=0;
1.191 brouard 13078: int hstepm=0, nhstepm=0;
1.136 brouard 13079: int agemortsup;
13080: float sumlpop=0.;
13081: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
13082: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
13083:
1.191 brouard 13084: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 13085: double ftolpl=FTOL;
13086: double **prlim;
1.217 brouard 13087: double **bprlim;
1.317 brouard 13088: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
13089: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 13090: double ***paramstart; /* Matrix of starting parameter values */
13091: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 13092: double **matcov; /* Matrix of covariance */
1.203 brouard 13093: double **hess; /* Hessian matrix */
1.136 brouard 13094: double ***delti3; /* Scale */
13095: double *delti; /* Scale */
13096: double ***eij, ***vareij;
13097: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 13098:
1.136 brouard 13099: double *epj, vepp;
1.164 brouard 13100:
1.273 brouard 13101: double dateprev1, dateprev2;
1.296 brouard 13102: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
13103: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
13104:
1.217 brouard 13105:
1.136 brouard 13106: double **ximort;
1.145 brouard 13107: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 13108: int *dcwave;
13109:
1.164 brouard 13110: char z[1]="c";
1.136 brouard 13111:
13112: /*char *strt;*/
13113: char strtend[80];
1.126 brouard 13114:
1.164 brouard 13115:
1.126 brouard 13116: /* setlocale (LC_ALL, ""); */
13117: /* bindtextdomain (PACKAGE, LOCALEDIR); */
13118: /* textdomain (PACKAGE); */
13119: /* setlocale (LC_CTYPE, ""); */
13120: /* setlocale (LC_MESSAGES, ""); */
13121:
13122: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 13123: rstart_time = time(NULL);
13124: /* (void) gettimeofday(&start_time,&tzp);*/
13125: start_time = *localtime(&rstart_time);
1.126 brouard 13126: curr_time=start_time;
1.157 brouard 13127: /*tml = *localtime(&start_time.tm_sec);*/
13128: /* strcpy(strstart,asctime(&tml)); */
13129: strcpy(strstart,asctime(&start_time));
1.126 brouard 13130:
13131: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13132: /* tp.tm_sec = tp.tm_sec +86400; */
13133: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13134: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13135: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13136: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13137: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13138: /* strt=asctime(&tmg); */
13139: /* printf("Time(after) =%s",strstart); */
13140: /* (void) time (&time_value);
13141: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13142: * tm = *localtime(&time_value);
13143: * strstart=asctime(&tm);
13144: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13145: */
13146:
13147: nberr=0; /* Number of errors and warnings */
13148: nbwarn=0;
1.184 brouard 13149: #ifdef WIN32
13150: _getcwd(pathcd, size);
13151: #else
1.126 brouard 13152: getcwd(pathcd, size);
1.184 brouard 13153: #endif
1.191 brouard 13154: syscompilerinfo(0);
1.196 brouard 13155: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13156: if(argc <=1){
13157: printf("\nEnter the parameter file name: ");
1.205 brouard 13158: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13159: printf("ERROR Empty parameter file name\n");
13160: goto end;
13161: }
1.126 brouard 13162: i=strlen(pathr);
13163: if(pathr[i-1]=='\n')
13164: pathr[i-1]='\0';
1.156 brouard 13165: i=strlen(pathr);
1.205 brouard 13166: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13167: pathr[i-1]='\0';
1.205 brouard 13168: }
13169: i=strlen(pathr);
13170: if( i==0 ){
13171: printf("ERROR Empty parameter file name\n");
13172: goto end;
13173: }
13174: for (tok = pathr; tok != NULL; ){
1.126 brouard 13175: printf("Pathr |%s|\n",pathr);
13176: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13177: printf("val= |%s| pathr=%s\n",val,pathr);
13178: strcpy (pathtot, val);
13179: if(pathr[0] == '\0') break; /* Dirty */
13180: }
13181: }
1.281 brouard 13182: else if (argc<=2){
13183: strcpy(pathtot,argv[1]);
13184: }
1.126 brouard 13185: else{
13186: strcpy(pathtot,argv[1]);
1.281 brouard 13187: strcpy(z,argv[2]);
13188: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13189: }
13190: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13191: /*cygwin_split_path(pathtot,path,optionfile);
13192: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13193: /* cutv(path,optionfile,pathtot,'\\');*/
13194:
13195: /* Split argv[0], imach program to get pathimach */
13196: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13197: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13198: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13199: /* strcpy(pathimach,argv[0]); */
13200: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13201: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13202: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13203: #ifdef WIN32
13204: _chdir(path); /* Can be a relative path */
13205: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13206: #else
1.126 brouard 13207: chdir(path); /* Can be a relative path */
1.184 brouard 13208: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13209: #endif
13210: printf("Current directory %s!\n",pathcd);
1.126 brouard 13211: strcpy(command,"mkdir ");
13212: strcat(command,optionfilefiname);
13213: if((outcmd=system(command)) != 0){
1.169 brouard 13214: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13215: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13216: /* fclose(ficlog); */
13217: /* exit(1); */
13218: }
13219: /* if((imk=mkdir(optionfilefiname))<0){ */
13220: /* perror("mkdir"); */
13221: /* } */
13222:
13223: /*-------- arguments in the command line --------*/
13224:
1.186 brouard 13225: /* Main Log file */
1.126 brouard 13226: strcat(filelog, optionfilefiname);
13227: strcat(filelog,".log"); /* */
13228: if((ficlog=fopen(filelog,"w"))==NULL) {
13229: printf("Problem with logfile %s\n",filelog);
13230: goto end;
13231: }
13232: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13233: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13234: fprintf(ficlog,"\nEnter the parameter file name: \n");
13235: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13236: path=%s \n\
13237: optionfile=%s\n\
13238: optionfilext=%s\n\
1.156 brouard 13239: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13240:
1.197 brouard 13241: syscompilerinfo(1);
1.167 brouard 13242:
1.126 brouard 13243: printf("Local time (at start):%s",strstart);
13244: fprintf(ficlog,"Local time (at start): %s",strstart);
13245: fflush(ficlog);
13246: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13247: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13248:
13249: /* */
13250: strcpy(fileres,"r");
13251: strcat(fileres, optionfilefiname);
1.201 brouard 13252: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13253: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13254: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13255:
1.186 brouard 13256: /* Main ---------arguments file --------*/
1.126 brouard 13257:
13258: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13259: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13260: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13261: fflush(ficlog);
1.149 brouard 13262: /* goto end; */
13263: exit(70);
1.126 brouard 13264: }
13265:
13266: strcpy(filereso,"o");
1.201 brouard 13267: strcat(filereso,fileresu);
1.126 brouard 13268: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13269: printf("Problem with Output resultfile: %s\n", filereso);
13270: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13271: fflush(ficlog);
13272: goto end;
13273: }
1.278 brouard 13274: /*-------- Rewriting parameter file ----------*/
13275: strcpy(rfileres,"r"); /* "Rparameterfile */
13276: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13277: strcat(rfileres,"."); /* */
13278: strcat(rfileres,optionfilext); /* Other files have txt extension */
13279: if((ficres =fopen(rfileres,"w"))==NULL) {
13280: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13281: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13282: fflush(ficlog);
13283: goto end;
13284: }
13285: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13286:
1.278 brouard 13287:
1.126 brouard 13288: /* Reads comments: lines beginning with '#' */
13289: numlinepar=0;
1.277 brouard 13290: /* Is it a BOM UTF-8 Windows file? */
13291: /* First parameter line */
1.197 brouard 13292: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13293: noffset=0;
13294: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13295: {
13296: noffset=noffset+3;
13297: printf("# File is an UTF8 Bom.\n"); // 0xBF
13298: }
1.302 brouard 13299: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13300: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13301: {
13302: noffset=noffset+2;
13303: printf("# File is an UTF16BE BOM file\n");
13304: }
13305: else if( line[0] == 0 && line[1] == 0)
13306: {
13307: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13308: noffset=noffset+4;
13309: printf("# File is an UTF16BE BOM file\n");
13310: }
13311: } else{
13312: ;/*printf(" Not a BOM file\n");*/
13313: }
13314:
1.197 brouard 13315: /* If line starts with a # it is a comment */
1.277 brouard 13316: if (line[noffset] == '#') {
1.197 brouard 13317: numlinepar++;
13318: fputs(line,stdout);
13319: fputs(line,ficparo);
1.278 brouard 13320: fputs(line,ficres);
1.197 brouard 13321: fputs(line,ficlog);
13322: continue;
13323: }else
13324: break;
13325: }
13326: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13327: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13328: if (num_filled != 5) {
13329: printf("Should be 5 parameters\n");
1.283 brouard 13330: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13331: }
1.126 brouard 13332: numlinepar++;
1.197 brouard 13333: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13334: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13335: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13336: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13337: }
13338: /* Second parameter line */
13339: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13340: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13341: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13342: if (line[0] == '#') {
13343: numlinepar++;
1.283 brouard 13344: printf("%s",line);
13345: fprintf(ficres,"%s",line);
13346: fprintf(ficparo,"%s",line);
13347: fprintf(ficlog,"%s",line);
1.197 brouard 13348: continue;
13349: }else
13350: break;
13351: }
1.223 brouard 13352: 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", \
13353: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13354: if (num_filled != 11) {
13355: 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 13356: printf("but line=%s\n",line);
1.283 brouard 13357: 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");
13358: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13359: }
1.286 brouard 13360: if( lastpass > maxwav){
13361: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13362: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13363: fflush(ficlog);
13364: goto end;
13365: }
13366: 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 13367: 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 13368: 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 13369: 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 13370: }
1.203 brouard 13371: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13372: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13373: /* Third parameter line */
13374: while(fgets(line, MAXLINE, ficpar)) {
13375: /* If line starts with a # it is a comment */
13376: if (line[0] == '#') {
13377: numlinepar++;
1.283 brouard 13378: printf("%s",line);
13379: fprintf(ficres,"%s",line);
13380: fprintf(ficparo,"%s",line);
13381: fprintf(ficlog,"%s",line);
1.197 brouard 13382: continue;
13383: }else
13384: break;
13385: }
1.351 brouard 13386: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
13387: if (num_filled != 1){
13388: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13389: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13390: model[0]='\0';
13391: goto end;
13392: }else{
13393: trimbtab(linetmp,line); /* Trims multiple blanks in line */
13394: strcpy(line, linetmp);
13395: }
13396: }
13397: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 13398: if (num_filled != 1){
1.302 brouard 13399: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13400: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13401: model[0]='\0';
13402: goto end;
13403: }
13404: else{
13405: if (model[0]=='+'){
13406: for(i=1; i<=strlen(model);i++)
13407: modeltemp[i-1]=model[i];
1.201 brouard 13408: strcpy(model,modeltemp);
1.197 brouard 13409: }
13410: }
1.338 brouard 13411: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13412: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13413: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13414: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13415: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13416: }
13417: /* 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); */
13418: /* numlinepar=numlinepar+3; /\* In general *\/ */
13419: /* 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 13420: /* 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); */
13421: /* 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 13422: fflush(ficlog);
1.190 brouard 13423: /* if(model[0]=='#'|| model[0]== '\0'){ */
13424: if(model[0]=='#'){
1.279 brouard 13425: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13426: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13427: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13428: if(mle != -1){
1.279 brouard 13429: 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 13430: exit(1);
13431: }
13432: }
1.126 brouard 13433: while((c=getc(ficpar))=='#' && c!= EOF){
13434: ungetc(c,ficpar);
13435: fgets(line, MAXLINE, ficpar);
13436: numlinepar++;
1.195 brouard 13437: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13438: z[0]=line[1];
1.342 brouard 13439: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13440: debugILK=1;printf("DebugILK\n");
1.195 brouard 13441: }
13442: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13443: fputs(line, stdout);
13444: //puts(line);
1.126 brouard 13445: fputs(line,ficparo);
13446: fputs(line,ficlog);
13447: }
13448: ungetc(c,ficpar);
13449:
13450:
1.290 brouard 13451: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13452: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13453: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13454: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13455: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13456: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13457: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13458: v1+v2*age+v2*v3 makes cptcovn = 3
13459: */
13460: if (strlen(model)>1)
1.187 brouard 13461: 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 13462: else
1.187 brouard 13463: ncovmodel=2; /* Constant and age */
1.133 brouard 13464: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13465: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13466: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13467: 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);
13468: 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);
13469: fflush(stdout);
13470: fclose (ficlog);
13471: goto end;
13472: }
1.126 brouard 13473: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13474: delti=delti3[1][1];
13475: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13476: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13477: /* We could also provide initial parameters values giving by simple logistic regression
13478: * only one way, that is without matrix product. We will have nlstate maximizations */
13479: /* for(i=1;i<nlstate;i++){ */
13480: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13481: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13482: /* } */
1.126 brouard 13483: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13484: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13485: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13486: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13487: fclose (ficparo);
13488: fclose (ficlog);
13489: goto end;
13490: exit(0);
1.220 brouard 13491: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13492: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13493: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13494: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13495: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13496: matcov=matrix(1,npar,1,npar);
1.203 brouard 13497: hess=matrix(1,npar,1,npar);
1.220 brouard 13498: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13499: /* Read guessed parameters */
1.126 brouard 13500: /* Reads comments: lines beginning with '#' */
13501: while((c=getc(ficpar))=='#' && c!= EOF){
13502: ungetc(c,ficpar);
13503: fgets(line, MAXLINE, ficpar);
13504: numlinepar++;
1.141 brouard 13505: fputs(line,stdout);
1.126 brouard 13506: fputs(line,ficparo);
13507: fputs(line,ficlog);
13508: }
13509: ungetc(c,ficpar);
13510:
13511: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13512: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13513: for(i=1; i <=nlstate; i++){
1.234 brouard 13514: j=0;
1.126 brouard 13515: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13516: if(jj==i) continue;
13517: j++;
1.292 brouard 13518: while((c=getc(ficpar))=='#' && c!= EOF){
13519: ungetc(c,ficpar);
13520: fgets(line, MAXLINE, ficpar);
13521: numlinepar++;
13522: fputs(line,stdout);
13523: fputs(line,ficparo);
13524: fputs(line,ficlog);
13525: }
13526: ungetc(c,ficpar);
1.234 brouard 13527: fscanf(ficpar,"%1d%1d",&i1,&j1);
13528: if ((i1 != i) || (j1 != jj)){
13529: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13530: It might be a problem of design; if ncovcol and the model are correct\n \
13531: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13532: exit(1);
13533: }
13534: fprintf(ficparo,"%1d%1d",i1,j1);
13535: if(mle==1)
13536: printf("%1d%1d",i,jj);
13537: fprintf(ficlog,"%1d%1d",i,jj);
13538: for(k=1; k<=ncovmodel;k++){
13539: fscanf(ficpar," %lf",¶m[i][j][k]);
13540: if(mle==1){
13541: printf(" %lf",param[i][j][k]);
13542: fprintf(ficlog," %lf",param[i][j][k]);
13543: }
13544: else
13545: fprintf(ficlog," %lf",param[i][j][k]);
13546: fprintf(ficparo," %lf",param[i][j][k]);
13547: }
13548: fscanf(ficpar,"\n");
13549: numlinepar++;
13550: if(mle==1)
13551: printf("\n");
13552: fprintf(ficlog,"\n");
13553: fprintf(ficparo,"\n");
1.126 brouard 13554: }
13555: }
13556: fflush(ficlog);
1.234 brouard 13557:
1.251 brouard 13558: /* Reads parameters values */
1.126 brouard 13559: p=param[1][1];
1.251 brouard 13560: pstart=paramstart[1][1];
1.126 brouard 13561:
13562: /* Reads comments: lines beginning with '#' */
13563: while((c=getc(ficpar))=='#' && c!= EOF){
13564: ungetc(c,ficpar);
13565: fgets(line, MAXLINE, ficpar);
13566: numlinepar++;
1.141 brouard 13567: fputs(line,stdout);
1.126 brouard 13568: fputs(line,ficparo);
13569: fputs(line,ficlog);
13570: }
13571: ungetc(c,ficpar);
13572:
13573: for(i=1; i <=nlstate; i++){
13574: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13575: fscanf(ficpar,"%1d%1d",&i1,&j1);
13576: if ( (i1-i) * (j1-j) != 0){
13577: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13578: exit(1);
13579: }
13580: printf("%1d%1d",i,j);
13581: fprintf(ficparo,"%1d%1d",i1,j1);
13582: fprintf(ficlog,"%1d%1d",i1,j1);
13583: for(k=1; k<=ncovmodel;k++){
13584: fscanf(ficpar,"%le",&delti3[i][j][k]);
13585: printf(" %le",delti3[i][j][k]);
13586: fprintf(ficparo," %le",delti3[i][j][k]);
13587: fprintf(ficlog," %le",delti3[i][j][k]);
13588: }
13589: fscanf(ficpar,"\n");
13590: numlinepar++;
13591: printf("\n");
13592: fprintf(ficparo,"\n");
13593: fprintf(ficlog,"\n");
1.126 brouard 13594: }
13595: }
13596: fflush(ficlog);
1.234 brouard 13597:
1.145 brouard 13598: /* Reads covariance matrix */
1.126 brouard 13599: delti=delti3[1][1];
1.220 brouard 13600:
13601:
1.126 brouard 13602: /* 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 13603:
1.126 brouard 13604: /* Reads comments: lines beginning with '#' */
13605: while((c=getc(ficpar))=='#' && c!= EOF){
13606: ungetc(c,ficpar);
13607: fgets(line, MAXLINE, ficpar);
13608: numlinepar++;
1.141 brouard 13609: fputs(line,stdout);
1.126 brouard 13610: fputs(line,ficparo);
13611: fputs(line,ficlog);
13612: }
13613: ungetc(c,ficpar);
1.220 brouard 13614:
1.126 brouard 13615: matcov=matrix(1,npar,1,npar);
1.203 brouard 13616: hess=matrix(1,npar,1,npar);
1.131 brouard 13617: for(i=1; i <=npar; i++)
13618: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13619:
1.194 brouard 13620: /* Scans npar lines */
1.126 brouard 13621: for(i=1; i <=npar; i++){
1.226 brouard 13622: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13623: if(count != 3){
1.226 brouard 13624: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13625: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13626: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13627: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13628: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13629: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13630: exit(1);
1.220 brouard 13631: }else{
1.226 brouard 13632: if(mle==1)
13633: printf("%1d%1d%d",i1,j1,jk);
13634: }
13635: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13636: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13637: for(j=1; j <=i; j++){
1.226 brouard 13638: fscanf(ficpar," %le",&matcov[i][j]);
13639: if(mle==1){
13640: printf(" %.5le",matcov[i][j]);
13641: }
13642: fprintf(ficlog," %.5le",matcov[i][j]);
13643: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13644: }
13645: fscanf(ficpar,"\n");
13646: numlinepar++;
13647: if(mle==1)
1.220 brouard 13648: printf("\n");
1.126 brouard 13649: fprintf(ficlog,"\n");
13650: fprintf(ficparo,"\n");
13651: }
1.194 brouard 13652: /* End of read covariance matrix npar lines */
1.126 brouard 13653: for(i=1; i <=npar; i++)
13654: for(j=i+1;j<=npar;j++)
1.226 brouard 13655: matcov[i][j]=matcov[j][i];
1.126 brouard 13656:
13657: if(mle==1)
13658: printf("\n");
13659: fprintf(ficlog,"\n");
13660:
13661: fflush(ficlog);
13662:
13663: } /* End of mle != -3 */
1.218 brouard 13664:
1.186 brouard 13665: /* Main data
13666: */
1.290 brouard 13667: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13668: /* num=lvector(1,n); */
13669: /* moisnais=vector(1,n); */
13670: /* annais=vector(1,n); */
13671: /* moisdc=vector(1,n); */
13672: /* andc=vector(1,n); */
13673: /* weight=vector(1,n); */
13674: /* agedc=vector(1,n); */
13675: /* cod=ivector(1,n); */
13676: /* for(i=1;i<=n;i++){ */
13677: num=lvector(firstobs,lastobs);
13678: moisnais=vector(firstobs,lastobs);
13679: annais=vector(firstobs,lastobs);
13680: moisdc=vector(firstobs,lastobs);
13681: andc=vector(firstobs,lastobs);
13682: weight=vector(firstobs,lastobs);
13683: agedc=vector(firstobs,lastobs);
13684: cod=ivector(firstobs,lastobs);
13685: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13686: num[i]=0;
13687: moisnais[i]=0;
13688: annais[i]=0;
13689: moisdc[i]=0;
13690: andc[i]=0;
13691: agedc[i]=0;
13692: cod[i]=0;
13693: weight[i]=1.0; /* Equal weights, 1 by default */
13694: }
1.290 brouard 13695: mint=matrix(1,maxwav,firstobs,lastobs);
13696: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13697: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13698: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13699: tab=ivector(1,NCOVMAX);
1.144 brouard 13700: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13701: 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 13702:
1.136 brouard 13703: /* Reads data from file datafile */
13704: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13705: goto end;
13706:
13707: /* Calculation of the number of parameters from char model */
1.234 brouard 13708: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13709: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13710: k=3 V4 Tvar[k=3]= 4 (from V4)
13711: k=2 V1 Tvar[k=2]= 1 (from V1)
13712: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13713: */
13714:
13715: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13716: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13717: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13718: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13719: TvarsD=ivector(1,NCOVMAX); /* */
13720: TvarsQind=ivector(1,NCOVMAX); /* */
13721: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13722: TvarF=ivector(1,NCOVMAX); /* */
13723: TvarFind=ivector(1,NCOVMAX); /* */
13724: TvarV=ivector(1,NCOVMAX); /* */
13725: TvarVind=ivector(1,NCOVMAX); /* */
13726: TvarA=ivector(1,NCOVMAX); /* */
13727: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13728: TvarFD=ivector(1,NCOVMAX); /* */
13729: TvarFDind=ivector(1,NCOVMAX); /* */
13730: TvarFQ=ivector(1,NCOVMAX); /* */
13731: TvarFQind=ivector(1,NCOVMAX); /* */
13732: TvarVD=ivector(1,NCOVMAX); /* */
13733: TvarVDind=ivector(1,NCOVMAX); /* */
13734: TvarVQ=ivector(1,NCOVMAX); /* */
13735: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13736: TvarVV=ivector(1,NCOVMAX); /* */
13737: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 13738: TvarVVA=ivector(1,NCOVMAX); /* */
13739: TvarVVAind=ivector(1,NCOVMAX); /* */
13740: TvarAVVA=ivector(1,NCOVMAX); /* */
13741: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13742:
1.230 brouard 13743: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13744: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13745: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13746: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13747: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 13748: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
13749: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
13750:
1.137 brouard 13751: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13752: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13753: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13754: */
13755: /* For model-covariate k tells which data-covariate to use but
13756: because this model-covariate is a construction we invent a new column
13757: ncovcol + k1
13758: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13759: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13760: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13761: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13762: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13763: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13764: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13765: */
1.145 brouard 13766: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13767: 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 13768: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13769: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 13770: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 13771: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13772: 4 covariates (3 plus signs)
13773: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13774: */
13775: for(i=1;i<NCOVMAX;i++)
13776: Tage[i]=0;
1.230 brouard 13777: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13778: * individual dummy, fixed or varying:
13779: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13780: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13781: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13782: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13783: * Tmodelind[1]@9={9,0,3,2,}*/
13784: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13785: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13786: * individual quantitative, fixed or varying:
13787: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13788: * 3, 1, 0, 0, 0, 0, 0, 0},
13789: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 13790:
13791: /* Probably useless zeroes */
13792: for(i=1;i<NCOVMAX;i++){
13793: DummyV[i]=0;
13794: FixedV[i]=0;
13795: }
13796:
13797: for(i=1; i <=ncovcol;i++){
13798: DummyV[i]=0;
13799: FixedV[i]=0;
13800: }
13801: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
13802: DummyV[i]=1;
13803: FixedV[i]=0;
13804: }
13805: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
13806: DummyV[i]=0;
13807: FixedV[i]=1;
13808: }
13809: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
13810: DummyV[i]=1;
13811: FixedV[i]=1;
13812: }
13813: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
13814: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13815: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13816: }
13817:
13818:
13819:
1.186 brouard 13820: /* Main decodemodel */
13821:
1.187 brouard 13822:
1.223 brouard 13823: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13824: goto end;
13825:
1.137 brouard 13826: if((double)(lastobs-imx)/(double)imx > 1.10){
13827: nbwarn++;
13828: 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);
13829: 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);
13830: }
1.136 brouard 13831: /* if(mle==1){*/
1.137 brouard 13832: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13833: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13834: }
13835:
13836: /*-calculation of age at interview from date of interview and age at death -*/
13837: agev=matrix(1,maxwav,1,imx);
13838:
13839: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13840: goto end;
13841:
1.126 brouard 13842:
1.136 brouard 13843: agegomp=(int)agemin;
1.290 brouard 13844: free_vector(moisnais,firstobs,lastobs);
13845: free_vector(annais,firstobs,lastobs);
1.126 brouard 13846: /* free_matrix(mint,1,maxwav,1,n);
13847: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13848: /* free_vector(moisdc,1,n); */
13849: /* free_vector(andc,1,n); */
1.145 brouard 13850: /* */
13851:
1.126 brouard 13852: wav=ivector(1,imx);
1.214 brouard 13853: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13854: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13855: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13856: 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.*/
13857: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13858: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13859:
13860: /* Concatenates waves */
1.214 brouard 13861: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13862: Death is a valid wave (if date is known).
13863: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13864: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13865: and mw[mi+1][i]. dh depends on stepm.
13866: */
13867:
1.126 brouard 13868: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13869: /* Concatenates waves */
1.145 brouard 13870:
1.290 brouard 13871: free_vector(moisdc,firstobs,lastobs);
13872: free_vector(andc,firstobs,lastobs);
1.215 brouard 13873:
1.126 brouard 13874: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13875: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13876: ncodemax[1]=1;
1.145 brouard 13877: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13878: cptcoveff=0;
1.220 brouard 13879: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13880: 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 13881: }
13882:
13883: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13884: invalidvarcomb=ivector(0, ncovcombmax);
13885: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13886: invalidvarcomb[i]=0;
13887:
1.211 brouard 13888: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13889: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13890: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13891:
1.200 brouard 13892: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13893: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13894: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13895: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13896: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13897: * (currently 0 or 1) in the data.
13898: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13899: * corresponding modality (h,j).
13900: */
13901:
1.145 brouard 13902: h=0;
13903: /*if (cptcovn > 0) */
1.126 brouard 13904: m=pow(2,cptcoveff);
13905:
1.144 brouard 13906: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13907: * For k=4 covariates, h goes from 1 to m=2**k
13908: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13909: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13910: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13911: *______________________________ *______________________
13912: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13913: * 2 2 1 1 1 * 1 0 0 0 1
13914: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13915: * 4 2 2 1 1 * 3 0 0 1 1
13916: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13917: * 6 2 1 2 1 * 5 0 1 0 1
13918: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13919: * 8 2 2 2 1 * 7 0 1 1 1
13920: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13921: * 10 2 1 1 2 * 9 1 0 0 1
13922: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13923: * 12 2 2 1 2 * 11 1 0 1 1
13924: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13925: * 14 2 1 2 2 * 13 1 1 0 1
13926: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13927: * 16 2 2 2 2 * 15 1 1 1 1
13928: */
1.212 brouard 13929: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13930: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13931: * and the value of each covariate?
13932: * V1=1, V2=1, V3=2, V4=1 ?
13933: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13934: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13935: * In order to get the real value in the data, we use nbcode
13936: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13937: * We are keeping this crazy system in order to be able (in the future?)
13938: * to have more than 2 values (0 or 1) for a covariate.
13939: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13940: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13941: * bbbbbbbb
13942: * 76543210
13943: * h-1 00000101 (6-1=5)
1.219 brouard 13944: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13945: * &
13946: * 1 00000001 (1)
1.219 brouard 13947: * 00000000 = 1 & ((h-1) >> (k-1))
13948: * +1= 00000001 =1
1.211 brouard 13949: *
13950: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13951: * h' 1101 =2^3+2^2+0x2^1+2^0
13952: * >>k' 11
13953: * & 00000001
13954: * = 00000001
13955: * +1 = 00000010=2 = codtabm(14,3)
13956: * Reverse h=6 and m=16?
13957: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13958: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13959: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13960: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13961: * V3=decodtabm(14,3,2**4)=2
13962: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13963: *(h-1) >> (j-1) 0011 =13 >> 2
13964: * &1 000000001
13965: * = 000000001
13966: * +1= 000000010 =2
13967: * 2211
13968: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13969: * V3=2
1.220 brouard 13970: * codtabm and decodtabm are identical
1.211 brouard 13971: */
13972:
1.145 brouard 13973:
13974: free_ivector(Ndum,-1,NCOVMAX);
13975:
13976:
1.126 brouard 13977:
1.186 brouard 13978: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13979: strcpy(optionfilegnuplot,optionfilefiname);
13980: if(mle==-3)
1.201 brouard 13981: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13982: strcat(optionfilegnuplot,".gp");
13983:
13984: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13985: printf("Problem with file %s",optionfilegnuplot);
13986: }
13987: else{
1.204 brouard 13988: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13989: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13990: //fprintf(ficgp,"set missing 'NaNq'\n");
13991: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13992: }
13993: /* fclose(ficgp);*/
1.186 brouard 13994:
13995:
13996: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13997:
13998: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13999: if(mle==-3)
1.201 brouard 14000: strcat(optionfilehtm,"-MORT_");
1.126 brouard 14001: strcat(optionfilehtm,".htm");
14002: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 14003: printf("Problem with %s \n",optionfilehtm);
14004: exit(0);
1.126 brouard 14005: }
14006:
14007: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
14008: strcat(optionfilehtmcov,"-cov.htm");
14009: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
14010: printf("Problem with %s \n",optionfilehtmcov), exit(0);
14011: }
14012: else{
14013: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
14014: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 14015: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 14016: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
14017: }
14018:
1.335 brouard 14019: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
14020: <title>IMaCh %s</title></head>\n\
14021: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
14022: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
14023: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
14024: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
14025: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
14026:
14027: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 14028: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 14029: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 14030: 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 14031: \n\
14032: <hr size=\"2\" color=\"#EC5E5E\">\
14033: <ul><li><h4>Parameter files</h4>\n\
14034: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
14035: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
14036: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
14037: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
14038: - Date and time at start: %s</ul>\n",\
1.335 brouard 14039: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 14040: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
14041: fileres,fileres,\
14042: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
14043: fflush(fichtm);
14044:
14045: strcpy(pathr,path);
14046: strcat(pathr,optionfilefiname);
1.184 brouard 14047: #ifdef WIN32
14048: _chdir(optionfilefiname); /* Move to directory named optionfile */
14049: #else
1.126 brouard 14050: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 14051: #endif
14052:
1.126 brouard 14053:
1.220 brouard 14054: /* Calculates basic frequencies. Computes observed prevalence at single age
14055: and for any valid combination of covariates
1.126 brouard 14056: and prints on file fileres'p'. */
1.251 brouard 14057: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 14058: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 14059:
14060: fprintf(fichtm,"\n");
1.286 brouard 14061: 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 14062: ftol, stepm);
14063: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
14064: ncurrv=1;
14065: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
14066: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
14067: ncurrv=i;
14068: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14069: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 14070: ncurrv=i;
14071: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14072: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 14073: ncurrv=i;
14074: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
14075: 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", \
14076: nlstate, ndeath, maxwav, mle, weightopt);
14077:
14078: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
14079: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
14080:
14081:
1.317 brouard 14082: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 14083: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
14084: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 14085: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 14086: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 14087: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14088: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14089: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14090: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 14091:
1.126 brouard 14092: /* For Powell, parameters are in a vector p[] starting at p[1]
14093: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
14094: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
14095:
14096: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 14097: /* For mortality only */
1.126 brouard 14098: if (mle==-3){
1.136 brouard 14099: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 14100: for(i=1;i<=NDIM;i++)
14101: for(j=1;j<=NDIM;j++)
14102: ximort[i][j]=0.;
1.186 brouard 14103: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 14104: cens=ivector(firstobs,lastobs);
14105: ageexmed=vector(firstobs,lastobs);
14106: agecens=vector(firstobs,lastobs);
14107: dcwave=ivector(firstobs,lastobs);
1.223 brouard 14108:
1.126 brouard 14109: for (i=1; i<=imx; i++){
14110: dcwave[i]=-1;
14111: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 14112: if (s[m][i]>nlstate) {
14113: dcwave[i]=m;
14114: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
14115: break;
14116: }
1.126 brouard 14117: }
1.226 brouard 14118:
1.126 brouard 14119: for (i=1; i<=imx; i++) {
14120: if (wav[i]>0){
1.226 brouard 14121: ageexmed[i]=agev[mw[1][i]][i];
14122: j=wav[i];
14123: agecens[i]=1.;
14124:
14125: if (ageexmed[i]> 1 && wav[i] > 0){
14126: agecens[i]=agev[mw[j][i]][i];
14127: cens[i]= 1;
14128: }else if (ageexmed[i]< 1)
14129: cens[i]= -1;
14130: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
14131: cens[i]=0 ;
1.126 brouard 14132: }
14133: else cens[i]=-1;
14134: }
14135:
14136: for (i=1;i<=NDIM;i++) {
14137: for (j=1;j<=NDIM;j++)
1.226 brouard 14138: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 14139: }
14140:
1.302 brouard 14141: p[1]=0.0268; p[NDIM]=0.083;
14142: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14143:
14144:
1.136 brouard 14145: #ifdef GSL
14146: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14147: #else
1.126 brouard 14148: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14149: #endif
1.201 brouard 14150: strcpy(filerespow,"POW-MORT_");
14151: strcat(filerespow,fileresu);
1.126 brouard 14152: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14153: printf("Problem with resultfile: %s\n", filerespow);
14154: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14155: }
1.136 brouard 14156: #ifdef GSL
14157: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14158: #else
1.126 brouard 14159: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14160: #endif
1.126 brouard 14161: /* for (i=1;i<=nlstate;i++)
14162: for(j=1;j<=nlstate+ndeath;j++)
14163: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14164: */
14165: fprintf(ficrespow,"\n");
1.136 brouard 14166: #ifdef GSL
14167: /* gsl starts here */
14168: T = gsl_multimin_fminimizer_nmsimplex;
14169: gsl_multimin_fminimizer *sfm = NULL;
14170: gsl_vector *ss, *x;
14171: gsl_multimin_function minex_func;
14172:
14173: /* Initial vertex size vector */
14174: ss = gsl_vector_alloc (NDIM);
14175:
14176: if (ss == NULL){
14177: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14178: }
14179: /* Set all step sizes to 1 */
14180: gsl_vector_set_all (ss, 0.001);
14181:
14182: /* Starting point */
1.126 brouard 14183:
1.136 brouard 14184: x = gsl_vector_alloc (NDIM);
14185:
14186: if (x == NULL){
14187: gsl_vector_free(ss);
14188: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14189: }
14190:
14191: /* Initialize method and iterate */
14192: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14193: /* gsl_vector_set(x, 0, 0.0268); */
14194: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14195: gsl_vector_set(x, 0, p[1]);
14196: gsl_vector_set(x, 1, p[2]);
14197:
14198: minex_func.f = &gompertz_f;
14199: minex_func.n = NDIM;
14200: minex_func.params = (void *)&p; /* ??? */
14201:
14202: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14203: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14204:
14205: printf("Iterations beginning .....\n\n");
14206: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14207:
14208: iteri=0;
14209: while (rval == GSL_CONTINUE){
14210: iteri++;
14211: status = gsl_multimin_fminimizer_iterate(sfm);
14212:
14213: if (status) printf("error: %s\n", gsl_strerror (status));
14214: fflush(0);
14215:
14216: if (status)
14217: break;
14218:
14219: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14220: ssval = gsl_multimin_fminimizer_size (sfm);
14221:
14222: if (rval == GSL_SUCCESS)
14223: printf ("converged to a local maximum at\n");
14224:
14225: printf("%5d ", iteri);
14226: for (it = 0; it < NDIM; it++){
14227: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14228: }
14229: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14230: }
14231:
14232: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14233:
14234: gsl_vector_free(x); /* initial values */
14235: gsl_vector_free(ss); /* inital step size */
14236: for (it=0; it<NDIM; it++){
14237: p[it+1]=gsl_vector_get(sfm->x,it);
14238: fprintf(ficrespow," %.12lf", p[it]);
14239: }
14240: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14241: #endif
14242: #ifdef POWELL
14243: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14244: #endif
1.126 brouard 14245: fclose(ficrespow);
14246:
1.203 brouard 14247: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14248:
14249: for(i=1; i <=NDIM; i++)
14250: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14251: matcov[i][j]=matcov[j][i];
1.126 brouard 14252:
14253: printf("\nCovariance matrix\n ");
1.203 brouard 14254: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14255: for(i=1; i <=NDIM; i++) {
14256: for(j=1;j<=NDIM;j++){
1.220 brouard 14257: printf("%f ",matcov[i][j]);
14258: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14259: }
1.203 brouard 14260: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14261: }
14262:
14263: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14264: for (i=1;i<=NDIM;i++) {
1.126 brouard 14265: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14266: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14267: }
1.302 brouard 14268: lsurv=vector(agegomp,AGESUP);
14269: lpop=vector(agegomp,AGESUP);
14270: tpop=vector(agegomp,AGESUP);
1.126 brouard 14271: lsurv[agegomp]=100000;
14272:
14273: for (k=agegomp;k<=AGESUP;k++) {
14274: agemortsup=k;
14275: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14276: }
14277:
14278: for (k=agegomp;k<agemortsup;k++)
14279: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14280:
14281: for (k=agegomp;k<agemortsup;k++){
14282: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14283: sumlpop=sumlpop+lpop[k];
14284: }
14285:
14286: tpop[agegomp]=sumlpop;
14287: for (k=agegomp;k<(agemortsup-3);k++){
14288: /* tpop[k+1]=2;*/
14289: tpop[k+1]=tpop[k]-lpop[k];
14290: }
14291:
14292:
14293: printf("\nAge lx qx dx Lx Tx e(x)\n");
14294: for (k=agegomp;k<(agemortsup-2);k++)
14295: 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]);
14296:
14297:
14298: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14299: ageminpar=50;
14300: agemaxpar=100;
1.194 brouard 14301: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14302: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14303: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14304: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
14305: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14306: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14307: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14308: }else{
14309: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14310: 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 14311: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14312: }
1.201 brouard 14313: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14314: stepm, weightopt,\
14315: model,imx,p,matcov,agemortsup);
14316:
1.302 brouard 14317: free_vector(lsurv,agegomp,AGESUP);
14318: free_vector(lpop,agegomp,AGESUP);
14319: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14320: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14321: free_ivector(dcwave,firstobs,lastobs);
14322: free_vector(agecens,firstobs,lastobs);
14323: free_vector(ageexmed,firstobs,lastobs);
14324: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14325: #ifdef GSL
1.136 brouard 14326: #endif
1.186 brouard 14327: } /* Endof if mle==-3 mortality only */
1.205 brouard 14328: /* Standard */
14329: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14330: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14331: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14332: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14333: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14334: for (k=1; k<=npar;k++)
14335: printf(" %d %8.5f",k,p[k]);
14336: printf("\n");
1.205 brouard 14337: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14338: /* mlikeli uses func not funcone */
1.247 brouard 14339: /* for(i=1;i<nlstate;i++){ */
14340: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14341: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14342: /* } */
1.205 brouard 14343: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14344: }
14345: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14346: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14347: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14348: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14349: }
14350: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14351: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14352: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14353: /* exit(0); */
1.126 brouard 14354: for (k=1; k<=npar;k++)
14355: printf(" %d %8.5f",k,p[k]);
14356: printf("\n");
14357:
14358: /*--------- results files --------------*/
1.283 brouard 14359: /* 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 14360:
14361:
14362: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14363: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14364: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14365:
14366: printf("#model= 1 + age ");
14367: fprintf(ficres,"#model= 1 + age ");
14368: fprintf(ficlog,"#model= 1 + age ");
14369: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14370: </ul>", model);
14371:
14372: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14373: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14374: if(nagesqr==1){
14375: printf(" + age*age ");
14376: fprintf(ficres," + age*age ");
14377: fprintf(ficlog," + age*age ");
14378: fprintf(fichtm, "<th>+ age*age</th>");
14379: }
14380: for(j=1;j <=ncovmodel-2;j++){
14381: if(Typevar[j]==0) {
14382: printf(" + V%d ",Tvar[j]);
14383: fprintf(ficres," + V%d ",Tvar[j]);
14384: fprintf(ficlog," + V%d ",Tvar[j]);
14385: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14386: }else if(Typevar[j]==1) {
14387: printf(" + V%d*age ",Tvar[j]);
14388: fprintf(ficres," + V%d*age ",Tvar[j]);
14389: fprintf(ficlog," + V%d*age ",Tvar[j]);
14390: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14391: }else if(Typevar[j]==2) {
14392: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14393: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14394: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14395: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14396: }else if(Typevar[j]==3) { /* TO VERIFY */
14397: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14398: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14399: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14400: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14401: }
14402: }
14403: printf("\n");
14404: fprintf(ficres,"\n");
14405: fprintf(ficlog,"\n");
14406: fprintf(fichtm, "</tr>");
14407: fprintf(fichtm, "\n");
14408:
14409:
1.126 brouard 14410: for(i=1,jk=1; i <=nlstate; i++){
14411: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14412: if (k != i) {
1.319 brouard 14413: fprintf(fichtm, "<tr>");
1.225 brouard 14414: printf("%d%d ",i,k);
14415: fprintf(ficlog,"%d%d ",i,k);
14416: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14417: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14418: for(j=1; j <=ncovmodel; j++){
14419: printf("%12.7f ",p[jk]);
14420: fprintf(ficlog,"%12.7f ",p[jk]);
14421: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14422: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14423: jk++;
14424: }
14425: printf("\n");
14426: fprintf(ficlog,"\n");
14427: fprintf(ficres,"\n");
1.319 brouard 14428: fprintf(fichtm, "</tr>\n");
1.225 brouard 14429: }
1.126 brouard 14430: }
14431: }
1.319 brouard 14432: /* fprintf(fichtm,"</tr>\n"); */
14433: fprintf(fichtm,"</table>\n");
14434: fprintf(fichtm, "\n");
14435:
1.203 brouard 14436: if(mle != 0){
14437: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14438: ftolhess=ftol; /* Usually correct */
1.203 brouard 14439: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14440: 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");
14441: 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 14442: 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 14443: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14444: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14445: if(nagesqr==1){
14446: printf(" + age*age ");
14447: fprintf(ficres," + age*age ");
14448: fprintf(ficlog," + age*age ");
14449: fprintf(fichtm, "<th>+ age*age</th>");
14450: }
14451: for(j=1;j <=ncovmodel-2;j++){
14452: if(Typevar[j]==0) {
14453: printf(" + V%d ",Tvar[j]);
14454: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14455: }else if(Typevar[j]==1) {
14456: printf(" + V%d*age ",Tvar[j]);
14457: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14458: }else if(Typevar[j]==2) {
14459: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14460: }else if(Typevar[j]==3) { /* TO VERIFY */
14461: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14462: }
14463: }
14464: fprintf(fichtm, "</tr>\n");
14465:
1.203 brouard 14466: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14467: for(k=1; k <=(nlstate+ndeath); k++){
14468: if (k != i) {
1.319 brouard 14469: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14470: printf("%d%d ",i,k);
14471: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14472: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14473: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14474: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14475: 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]));
14476: 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 14477: if(fabs(wald) > 1.96){
1.321 brouard 14478: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14479: }else{
14480: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14481: }
1.324 brouard 14482: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14483: 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 14484: jk++;
14485: }
14486: printf("\n");
14487: fprintf(ficlog,"\n");
1.319 brouard 14488: fprintf(fichtm, "</tr>\n");
1.225 brouard 14489: }
14490: }
1.193 brouard 14491: }
1.203 brouard 14492: } /* end of hesscov and Wald tests */
1.319 brouard 14493: fprintf(fichtm,"</table>\n");
1.225 brouard 14494:
1.203 brouard 14495: /* */
1.126 brouard 14496: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14497: printf("# Scales (for hessian or gradient estimation)\n");
14498: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14499: for(i=1,jk=1; i <=nlstate; i++){
14500: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14501: if (j!=i) {
14502: fprintf(ficres,"%1d%1d",i,j);
14503: printf("%1d%1d",i,j);
14504: fprintf(ficlog,"%1d%1d",i,j);
14505: for(k=1; k<=ncovmodel;k++){
14506: printf(" %.5e",delti[jk]);
14507: fprintf(ficlog," %.5e",delti[jk]);
14508: fprintf(ficres," %.5e",delti[jk]);
14509: jk++;
14510: }
14511: printf("\n");
14512: fprintf(ficlog,"\n");
14513: fprintf(ficres,"\n");
14514: }
1.126 brouard 14515: }
14516: }
14517:
14518: fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
1.349 brouard 14519: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14520: 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");
14521: 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");
14522: /* # 121 Var(a12)\n\ */
14523: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14524: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14525: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14526: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14527: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14528: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14529: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14530:
14531:
14532: /* Just to have a covariance matrix which will be more understandable
14533: even is we still don't want to manage dictionary of variables
14534: */
14535: for(itimes=1;itimes<=2;itimes++){
14536: jj=0;
14537: for(i=1; i <=nlstate; i++){
1.225 brouard 14538: for(j=1; j <=nlstate+ndeath; j++){
14539: if(j==i) continue;
14540: for(k=1; k<=ncovmodel;k++){
14541: jj++;
14542: ca[0]= k+'a'-1;ca[1]='\0';
14543: if(itimes==1){
14544: if(mle>=1)
14545: printf("#%1d%1d%d",i,j,k);
14546: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14547: fprintf(ficres,"#%1d%1d%d",i,j,k);
14548: }else{
14549: if(mle>=1)
14550: printf("%1d%1d%d",i,j,k);
14551: fprintf(ficlog,"%1d%1d%d",i,j,k);
14552: fprintf(ficres,"%1d%1d%d",i,j,k);
14553: }
14554: ll=0;
14555: for(li=1;li <=nlstate; li++){
14556: for(lj=1;lj <=nlstate+ndeath; lj++){
14557: if(lj==li) continue;
14558: for(lk=1;lk<=ncovmodel;lk++){
14559: ll++;
14560: if(ll<=jj){
14561: cb[0]= lk +'a'-1;cb[1]='\0';
14562: if(ll<jj){
14563: if(itimes==1){
14564: if(mle>=1)
14565: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14566: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14567: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14568: }else{
14569: if(mle>=1)
14570: printf(" %.5e",matcov[jj][ll]);
14571: fprintf(ficlog," %.5e",matcov[jj][ll]);
14572: fprintf(ficres," %.5e",matcov[jj][ll]);
14573: }
14574: }else{
14575: if(itimes==1){
14576: if(mle>=1)
14577: printf(" Var(%s%1d%1d)",ca,i,j);
14578: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14579: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14580: }else{
14581: if(mle>=1)
14582: printf(" %.7e",matcov[jj][ll]);
14583: fprintf(ficlog," %.7e",matcov[jj][ll]);
14584: fprintf(ficres," %.7e",matcov[jj][ll]);
14585: }
14586: }
14587: }
14588: } /* end lk */
14589: } /* end lj */
14590: } /* end li */
14591: if(mle>=1)
14592: printf("\n");
14593: fprintf(ficlog,"\n");
14594: fprintf(ficres,"\n");
14595: numlinepar++;
14596: } /* end k*/
14597: } /*end j */
1.126 brouard 14598: } /* end i */
14599: } /* end itimes */
14600:
14601: fflush(ficlog);
14602: fflush(ficres);
1.225 brouard 14603: while(fgets(line, MAXLINE, ficpar)) {
14604: /* If line starts with a # it is a comment */
14605: if (line[0] == '#') {
14606: numlinepar++;
14607: fputs(line,stdout);
14608: fputs(line,ficparo);
14609: fputs(line,ficlog);
1.299 brouard 14610: fputs(line,ficres);
1.225 brouard 14611: continue;
14612: }else
14613: break;
14614: }
14615:
1.209 brouard 14616: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14617: /* ungetc(c,ficpar); */
14618: /* fgets(line, MAXLINE, ficpar); */
14619: /* fputs(line,stdout); */
14620: /* fputs(line,ficparo); */
14621: /* } */
14622: /* ungetc(c,ficpar); */
1.126 brouard 14623:
14624: estepm=0;
1.209 brouard 14625: 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 14626:
14627: if (num_filled != 6) {
14628: 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);
14629: 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);
14630: goto end;
14631: }
14632: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14633: }
14634: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14635: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14636:
1.209 brouard 14637: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14638: if (estepm==0 || estepm < stepm) estepm=stepm;
14639: if (fage <= 2) {
14640: bage = ageminpar;
14641: fage = agemaxpar;
14642: }
14643:
14644: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14645: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14646: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14647:
1.186 brouard 14648: /* Other stuffs, more or less useful */
1.254 brouard 14649: while(fgets(line, MAXLINE, ficpar)) {
14650: /* If line starts with a # it is a comment */
14651: if (line[0] == '#') {
14652: numlinepar++;
14653: fputs(line,stdout);
14654: fputs(line,ficparo);
14655: fputs(line,ficlog);
1.299 brouard 14656: fputs(line,ficres);
1.254 brouard 14657: continue;
14658: }else
14659: break;
14660: }
14661:
14662: 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){
14663:
14664: if (num_filled != 7) {
14665: 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);
14666: 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);
14667: goto end;
14668: }
14669: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14670: 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);
14671: 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);
14672: 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 14673: }
1.254 brouard 14674:
14675: while(fgets(line, MAXLINE, ficpar)) {
14676: /* If line starts with a # it is a comment */
14677: if (line[0] == '#') {
14678: numlinepar++;
14679: fputs(line,stdout);
14680: fputs(line,ficparo);
14681: fputs(line,ficlog);
1.299 brouard 14682: fputs(line,ficres);
1.254 brouard 14683: continue;
14684: }else
14685: break;
1.126 brouard 14686: }
14687:
14688:
14689: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14690: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14691:
1.254 brouard 14692: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14693: if (num_filled != 1) {
14694: 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);
14695: 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);
14696: goto end;
14697: }
14698: printf("pop_based=%d\n",popbased);
14699: fprintf(ficlog,"pop_based=%d\n",popbased);
14700: fprintf(ficparo,"pop_based=%d\n",popbased);
14701: fprintf(ficres,"pop_based=%d\n",popbased);
14702: }
14703:
1.258 brouard 14704: /* Results */
1.332 brouard 14705: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14706: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14707: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14708: endishere=0;
1.258 brouard 14709: nresult=0;
1.308 brouard 14710: parameterline=0;
1.258 brouard 14711: do{
14712: if(!fgets(line, MAXLINE, ficpar)){
14713: endishere=1;
1.308 brouard 14714: parameterline=15;
1.258 brouard 14715: }else if (line[0] == '#') {
14716: /* If line starts with a # it is a comment */
1.254 brouard 14717: numlinepar++;
14718: fputs(line,stdout);
14719: fputs(line,ficparo);
14720: fputs(line,ficlog);
1.299 brouard 14721: fputs(line,ficres);
1.254 brouard 14722: continue;
1.258 brouard 14723: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14724: parameterline=11;
1.296 brouard 14725: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14726: parameterline=12;
1.307 brouard 14727: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14728: parameterline=13;
1.307 brouard 14729: }
1.258 brouard 14730: else{
14731: parameterline=14;
1.254 brouard 14732: }
1.308 brouard 14733: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14734: case 11:
1.296 brouard 14735: 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)){
14736: 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 14737: 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);
14738: 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);
14739: 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);
14740: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14741: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14742: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14743: prvforecast = 1;
14744: }
14745: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14746: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14747: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14748: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14749: prvforecast = 2;
14750: }
14751: else {
14752: 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);
14753: 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);
14754: goto end;
1.258 brouard 14755: }
1.254 brouard 14756: break;
1.258 brouard 14757: case 12:
1.296 brouard 14758: 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)){
14759: 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);
14760: 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);
14761: 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);
14762: 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);
14763: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14764: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14765: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14766: prvbackcast = 1;
14767: }
14768: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14769: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14770: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14771: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14772: prvbackcast = 2;
14773: }
14774: else {
14775: 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);
14776: 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);
14777: goto end;
1.258 brouard 14778: }
1.230 brouard 14779: break;
1.258 brouard 14780: case 13:
1.332 brouard 14781: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14782: nresult++; /* Sum of resultlines */
1.342 brouard 14783: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14784: /* removefirstspace(&resultlineori); */
14785:
14786: if(strstr(resultlineori,"v") !=0){
14787: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14788: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14789: return 1;
14790: }
14791: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14792: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14793: if(nresult > MAXRESULTLINESPONE-1){
14794: 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);
14795: 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 14796: goto end;
14797: }
1.332 brouard 14798:
1.310 brouard 14799: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14800: fprintf(ficparo,"result: %s\n",resultline);
14801: fprintf(ficres,"result: %s\n",resultline);
14802: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14803: } else
14804: goto end;
1.307 brouard 14805: break;
14806: case 14:
14807: printf("Error: Unknown command '%s'\n",line);
14808: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14809: if(line[0] == ' ' || line[0] == '\n'){
14810: printf("It should not be an empty line '%s'\n",line);
14811: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14812: }
1.307 brouard 14813: if(ncovmodel >=2 && nresult==0 ){
14814: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14815: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14816: }
1.307 brouard 14817: /* goto end; */
14818: break;
1.308 brouard 14819: case 15:
14820: printf("End of resultlines.\n");
14821: fprintf(ficlog,"End of resultlines.\n");
14822: break;
14823: default: /* parameterline =0 */
1.307 brouard 14824: nresult=1;
14825: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14826: } /* End switch parameterline */
14827: }while(endishere==0); /* End do */
1.126 brouard 14828:
1.230 brouard 14829: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14830: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14831:
14832: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14833: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14834: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14835: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14836: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14837: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14838: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14839: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14840: }else{
1.270 brouard 14841: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14842: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14843: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14844: if(prvforecast==1){
14845: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14846: jprojd=jproj1;
14847: mprojd=mproj1;
14848: anprojd=anproj1;
14849: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14850: jprojf=jproj2;
14851: mprojf=mproj2;
14852: anprojf=anproj2;
14853: } else if(prvforecast == 2){
14854: dateprojd=dateintmean;
14855: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14856: dateprojf=dateintmean+yrfproj;
14857: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14858: }
14859: if(prvbackcast==1){
14860: datebackd=(jback1+12*mback1+365*anback1)/365;
14861: jbackd=jback1;
14862: mbackd=mback1;
14863: anbackd=anback1;
14864: datebackf=(jback2+12*mback2+365*anback2)/365;
14865: jbackf=jback2;
14866: mbackf=mback2;
14867: anbackf=anback2;
14868: } else if(prvbackcast == 2){
14869: datebackd=dateintmean;
14870: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14871: datebackf=dateintmean-yrbproj;
14872: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14873: }
14874:
1.350 brouard 14875: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 14876: }
14877: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14878: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14879: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14880:
1.225 brouard 14881: /*------------ free_vector -------------*/
14882: /* chdir(path); */
1.220 brouard 14883:
1.215 brouard 14884: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14885: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14886: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14887: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14888: free_lvector(num,firstobs,lastobs);
14889: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14890: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14891: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14892: fclose(ficparo);
14893: fclose(ficres);
1.220 brouard 14894:
14895:
1.186 brouard 14896: /* Other results (useful)*/
1.220 brouard 14897:
14898:
1.126 brouard 14899: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14900: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14901: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14902: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14903: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14904: fclose(ficrespl);
14905:
14906: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14907: /*#include "hpijx.h"*/
1.332 brouard 14908: /** 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?*/
14909: /* calls hpxij with combination k */
1.180 brouard 14910: hPijx(p, bage, fage);
1.145 brouard 14911: fclose(ficrespij);
1.227 brouard 14912:
1.220 brouard 14913: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14914: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14915: k=1;
1.126 brouard 14916: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14917:
1.269 brouard 14918: /* Prevalence for each covariate combination in probs[age][status][cov] */
14919: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14920: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14921: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14922: for(k=1;k<=ncovcombmax;k++)
14923: probs[i][j][k]=0.;
1.269 brouard 14924: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14925: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14926: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14927: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14928: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14929: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14930: for(k=1;k<=ncovcombmax;k++)
14931: mobaverages[i][j][k]=0.;
1.219 brouard 14932: mobaverage=mobaverages;
14933: if (mobilav!=0) {
1.235 brouard 14934: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14935: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14936: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14937: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14938: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14939: }
1.269 brouard 14940: } else if (mobilavproj !=0) {
1.235 brouard 14941: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14942: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14943: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14944: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14945: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14946: }
1.269 brouard 14947: }else{
14948: printf("Internal error moving average\n");
14949: fflush(stdout);
14950: exit(1);
1.219 brouard 14951: }
14952: }/* end if moving average */
1.227 brouard 14953:
1.126 brouard 14954: /*---------- Forecasting ------------------*/
1.296 brouard 14955: if(prevfcast==1){
14956: /* /\* if(stepm ==1){*\/ */
14957: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14958: /*This done previously after freqsummary.*/
14959: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14960: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14961:
14962: /* } else if (prvforecast==2){ */
14963: /* /\* if(stepm ==1){*\/ */
14964: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14965: /* } */
14966: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14967: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14968: }
1.269 brouard 14969:
1.296 brouard 14970: /* Prevbcasting */
14971: if(prevbcast==1){
1.219 brouard 14972: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14973: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14974: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14975:
14976: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14977:
14978: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14979:
1.219 brouard 14980: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14981: fclose(ficresplb);
14982:
1.222 brouard 14983: hBijx(p, bage, fage, mobaverage);
14984: fclose(ficrespijb);
1.219 brouard 14985:
1.296 brouard 14986: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14987: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14988: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14989: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14990: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14991: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14992:
14993:
1.269 brouard 14994: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14995:
14996:
1.269 brouard 14997: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14998: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14999: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
15000: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 15001: } /* end Prevbcasting */
1.268 brouard 15002:
1.186 brouard 15003:
15004: /* ------ Other prevalence ratios------------ */
1.126 brouard 15005:
1.215 brouard 15006: free_ivector(wav,1,imx);
15007: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
15008: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
15009: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 15010:
15011:
1.127 brouard 15012: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 15013:
1.201 brouard 15014: strcpy(filerese,"E_");
15015: strcat(filerese,fileresu);
1.126 brouard 15016: if((ficreseij=fopen(filerese,"w"))==NULL) {
15017: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
15018: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
15019: }
1.208 brouard 15020: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
15021: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 15022:
15023: pstamp(ficreseij);
1.219 brouard 15024:
1.351 brouard 15025: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
15026: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 15027:
1.351 brouard 15028: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
15029: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
15030: /* if(i1 != 1 && TKresult[nres]!= k) */
15031: /* continue; */
1.219 brouard 15032: fprintf(ficreseij,"\n#****** ");
1.235 brouard 15033: printf("\n#****** ");
1.351 brouard 15034: for(j=1;j<=cptcovs;j++){
15035: /* for(j=1;j<=cptcoveff;j++) { */
15036: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15037: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15038: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15039: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 15040: }
15041: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 15042: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
15043: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 15044: }
15045: fprintf(ficreseij,"******\n");
1.235 brouard 15046: printf("******\n");
1.219 brouard 15047:
15048: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15049: oldm=oldms;savm=savms;
1.330 brouard 15050: /* 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 15051: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 15052:
1.219 brouard 15053: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 15054: }
15055: fclose(ficreseij);
1.208 brouard 15056: printf("done evsij\n");fflush(stdout);
15057: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 15058:
1.218 brouard 15059:
1.227 brouard 15060: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 15061: /* Should be moved in a function */
1.201 brouard 15062: strcpy(filerest,"T_");
15063: strcat(filerest,fileresu);
1.127 brouard 15064: if((ficrest=fopen(filerest,"w"))==NULL) {
15065: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
15066: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
15067: }
1.208 brouard 15068: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
15069: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 15070: strcpy(fileresstde,"STDE_");
15071: strcat(fileresstde,fileresu);
1.126 brouard 15072: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 15073: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
15074: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 15075: }
1.227 brouard 15076: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
15077: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 15078:
1.201 brouard 15079: strcpy(filerescve,"CVE_");
15080: strcat(filerescve,fileresu);
1.126 brouard 15081: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 15082: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
15083: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 15084: }
1.227 brouard 15085: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
15086: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 15087:
1.201 brouard 15088: strcpy(fileresv,"V_");
15089: strcat(fileresv,fileresu);
1.126 brouard 15090: if((ficresvij=fopen(fileresv,"w"))==NULL) {
15091: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
15092: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
15093: }
1.227 brouard 15094: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
15095: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 15096:
1.235 brouard 15097: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
15098: if (cptcovn < 1){i1=1;}
15099:
1.334 brouard 15100: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
15101: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
15102: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
15103: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
15104: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
15105: /* */
15106: 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 15107: continue;
1.350 brouard 15108: printf("\n# model %s \n#****** Result for:", model); /* HERE model is empty */
1.321 brouard 15109: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
15110: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 15111: /* It might not be a good idea to mix dummies and quantitative */
15112: /* 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 *\/ */
15113: 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 */
15114: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
15115: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
15116: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
15117: * (V5 is quanti) V4 and V3 are dummies
15118: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
15119: * l=1 l=2
15120: * k=1 1 1 0 0
15121: * k=2 2 1 1 0
15122: * k=3 [1] [2] 0 1
15123: * k=4 2 2 1 1
15124: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
15125: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
15126: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
15127: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
15128: */
15129: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
15130: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
15131: /* We give up with the combinations!! */
1.342 brouard 15132: /* if(debugILK) */
15133: /* printf("\n j=%d In computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d Fixed[modelresult[nres][j]]=%d\n", j, nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff,Fixed[modelresult[nres][j]]); /\* end if dummy or quanti *\/ */
1.334 brouard 15134:
15135: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
1.344 brouard 15136: /* printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /\* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline *\/ */ /* TinvDoQresult[nres][Name of the variable] */
15137: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordered by the covariate values in the resultline */
15138: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
15139: fprintf(ficrest,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
1.334 brouard 15140: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15141: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15142: }else{
15143: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15144: }
15145: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15146: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15147: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15148: /* For each selected (single) quantitative value */
1.337 brouard 15149: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15150: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15151: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15152: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15153: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15154: }else{
15155: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15156: }
15157: }else{
15158: 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 */
15159: 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 */
15160: exit(1);
15161: }
1.335 brouard 15162: } /* End loop for each variable in the resultline */
1.334 brouard 15163: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15164: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15165: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15166: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15167: /* } */
1.208 brouard 15168: fprintf(ficrest,"******\n");
1.227 brouard 15169: fprintf(ficlog,"******\n");
15170: printf("******\n");
1.208 brouard 15171:
15172: fprintf(ficresstdeij,"\n#****** ");
15173: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15174: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15175: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15176: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15177: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15178: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15179: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15180: }
15181: 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 15182: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15183: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15184: }
1.208 brouard 15185: fprintf(ficresstdeij,"******\n");
15186: fprintf(ficrescveij,"******\n");
15187:
15188: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15189: /* pstamp(ficresvij); */
1.225 brouard 15190: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15191: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15192: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15193: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15194: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15195: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15196: }
1.208 brouard 15197: fprintf(ficresvij,"******\n");
15198:
15199: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15200: oldm=oldms;savm=savms;
1.235 brouard 15201: printf(" cvevsij ");
15202: fprintf(ficlog, " cvevsij ");
15203: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15204: printf(" end cvevsij \n ");
15205: fprintf(ficlog, " end cvevsij \n ");
15206:
15207: /*
15208: */
15209: /* goto endfree; */
15210:
15211: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15212: pstamp(ficrest);
15213:
1.269 brouard 15214: epj=vector(1,nlstate+1);
1.208 brouard 15215: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15216: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15217: cptcod= 0; /* To be deleted */
15218: printf("varevsij vpopbased=%d \n",vpopbased);
15219: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15220: 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 15221: 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 ");
15222: if(vpopbased==1)
15223: 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);
15224: else
1.288 brouard 15225: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15226: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15227: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15228: fprintf(ficrest,"\n");
15229: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15230: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15231: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15232: for(age=bage; age <=fage ;age++){
1.235 brouard 15233: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15234: if (vpopbased==1) {
15235: if(mobilav ==0){
15236: for(i=1; i<=nlstate;i++)
15237: prlim[i][i]=probs[(int)age][i][k];
15238: }else{ /* mobilav */
15239: for(i=1; i<=nlstate;i++)
15240: prlim[i][i]=mobaverage[(int)age][i][k];
15241: }
15242: }
1.219 brouard 15243:
1.227 brouard 15244: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15245: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15246: /* printf(" age %4.0f ",age); */
15247: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15248: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15249: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15250: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15251: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15252: }
15253: epj[nlstate+1] +=epj[j];
15254: }
15255: /* printf(" age %4.0f \n",age); */
1.219 brouard 15256:
1.227 brouard 15257: for(i=1, vepp=0.;i <=nlstate;i++)
15258: for(j=1;j <=nlstate;j++)
15259: vepp += vareij[i][j][(int)age];
15260: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15261: for(j=1;j <=nlstate;j++){
15262: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15263: }
15264: fprintf(ficrest,"\n");
15265: }
1.208 brouard 15266: } /* End vpopbased */
1.269 brouard 15267: free_vector(epj,1,nlstate+1);
1.208 brouard 15268: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15269: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15270: printf("done selection\n");fflush(stdout);
15271: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15272:
1.335 brouard 15273: } /* End k selection or end covariate selection for nres */
1.227 brouard 15274:
15275: printf("done State-specific expectancies\n");fflush(stdout);
15276: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15277:
1.335 brouard 15278: /* variance-covariance of forward period prevalence */
1.269 brouard 15279: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15280:
1.227 brouard 15281:
1.290 brouard 15282: free_vector(weight,firstobs,lastobs);
1.351 brouard 15283: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 15284: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15285: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15286: free_matrix(anint,1,maxwav,firstobs,lastobs);
15287: free_matrix(mint,1,maxwav,firstobs,lastobs);
15288: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15289: free_ivector(tab,1,NCOVMAX);
15290: fclose(ficresstdeij);
15291: fclose(ficrescveij);
15292: fclose(ficresvij);
15293: fclose(ficrest);
15294: fclose(ficpar);
15295:
15296:
1.126 brouard 15297: /*---------- End : free ----------------*/
1.219 brouard 15298: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15299: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15300: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15301: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15302: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15303: } /* mle==-3 arrives here for freeing */
1.227 brouard 15304: /* endfree:*/
15305: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15306: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15307: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15308: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15309: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15310: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15311: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15312: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15313: free_matrix(matcov,1,npar,1,npar);
15314: free_matrix(hess,1,npar,1,npar);
15315: /*free_vector(delti,1,npar);*/
15316: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15317: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15318: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15319: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15320:
15321: free_ivector(ncodemax,1,NCOVMAX);
15322: free_ivector(ncodemaxwundef,1,NCOVMAX);
15323: free_ivector(Dummy,-1,NCOVMAX);
15324: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 15325: free_ivector(DummyV,-1,NCOVMAX);
15326: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15327: free_ivector(Typevar,-1,NCOVMAX);
15328: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15329: free_ivector(TvarsQ,1,NCOVMAX);
15330: free_ivector(TvarsQind,1,NCOVMAX);
15331: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15332: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15333: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15334: free_ivector(TvarFD,1,NCOVMAX);
15335: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15336: free_ivector(TvarF,1,NCOVMAX);
15337: free_ivector(TvarFind,1,NCOVMAX);
15338: free_ivector(TvarV,1,NCOVMAX);
15339: free_ivector(TvarVind,1,NCOVMAX);
15340: free_ivector(TvarA,1,NCOVMAX);
15341: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15342: free_ivector(TvarFQ,1,NCOVMAX);
15343: free_ivector(TvarFQind,1,NCOVMAX);
15344: free_ivector(TvarVD,1,NCOVMAX);
15345: free_ivector(TvarVDind,1,NCOVMAX);
15346: free_ivector(TvarVQ,1,NCOVMAX);
15347: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 15348: free_ivector(TvarAVVA,1,NCOVMAX);
15349: free_ivector(TvarAVVAind,1,NCOVMAX);
15350: free_ivector(TvarVVA,1,NCOVMAX);
15351: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15352: free_ivector(TvarVV,1,NCOVMAX);
15353: free_ivector(TvarVVind,1,NCOVMAX);
15354:
1.230 brouard 15355: free_ivector(Tvarsel,1,NCOVMAX);
15356: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15357: free_ivector(Tposprod,1,NCOVMAX);
15358: free_ivector(Tprod,1,NCOVMAX);
15359: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15360: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15361: free_ivector(Tage,1,NCOVMAX);
15362: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15363: free_ivector(TmodelInvind,1,NCOVMAX);
15364: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15365:
15366: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15367:
1.227 brouard 15368: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15369: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15370: fflush(fichtm);
15371: fflush(ficgp);
15372:
1.227 brouard 15373:
1.126 brouard 15374: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15375: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15376: 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 15377: }else{
15378: printf("End of Imach\n");
15379: fprintf(ficlog,"End of Imach\n");
15380: }
15381: printf("See log file on %s\n",filelog);
15382: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15383: /*(void) gettimeofday(&end_time,&tzp);*/
15384: rend_time = time(NULL);
15385: end_time = *localtime(&rend_time);
15386: /* tml = *localtime(&end_time.tm_sec); */
15387: strcpy(strtend,asctime(&end_time));
1.126 brouard 15388: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15389: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15390: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15391:
1.157 brouard 15392: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15393: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15394: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15395: /* printf("Total time was %d uSec.\n", total_usecs);*/
15396: /* if(fileappend(fichtm,optionfilehtm)){ */
15397: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15398: fclose(fichtm);
15399: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15400: fclose(fichtmcov);
15401: fclose(ficgp);
15402: fclose(ficlog);
15403: /*------ End -----------*/
1.227 brouard 15404:
1.281 brouard 15405:
15406: /* Executes gnuplot */
1.227 brouard 15407:
15408: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15409: #ifdef WIN32
1.227 brouard 15410: if (_chdir(pathcd) != 0)
15411: printf("Can't move to directory %s!\n",path);
15412: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15413: #else
1.227 brouard 15414: if(chdir(pathcd) != 0)
15415: printf("Can't move to directory %s!\n", path);
15416: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15417: #endif
1.126 brouard 15418: printf("Current directory %s!\n",pathcd);
15419: /*strcat(plotcmd,CHARSEPARATOR);*/
15420: sprintf(plotcmd,"gnuplot");
1.157 brouard 15421: #ifdef _WIN32
1.126 brouard 15422: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15423: #endif
15424: if(!stat(plotcmd,&info)){
1.158 brouard 15425: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15426: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15427: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15428: }else
15429: strcpy(pplotcmd,plotcmd);
1.157 brouard 15430: #ifdef __unix
1.126 brouard 15431: strcpy(plotcmd,GNUPLOTPROGRAM);
15432: if(!stat(plotcmd,&info)){
1.158 brouard 15433: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15434: }else
15435: strcpy(pplotcmd,plotcmd);
15436: #endif
15437: }else
15438: strcpy(pplotcmd,plotcmd);
15439:
15440: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15441: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15442: strcpy(pplotcmd,plotcmd);
1.227 brouard 15443:
1.126 brouard 15444: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15445: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15446: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15447: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15448: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15449: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15450: strcpy(plotcmd,pplotcmd);
15451: }
1.126 brouard 15452: }
1.158 brouard 15453: printf(" Successful, please wait...");
1.126 brouard 15454: while (z[0] != 'q') {
15455: /* chdir(path); */
1.154 brouard 15456: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15457: scanf("%s",z);
15458: /* if (z[0] == 'c') system("./imach"); */
15459: if (z[0] == 'e') {
1.158 brouard 15460: #ifdef __APPLE__
1.152 brouard 15461: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15462: #elif __linux
15463: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15464: #else
1.152 brouard 15465: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15466: #endif
15467: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15468: system(pplotcmd);
1.126 brouard 15469: }
15470: else if (z[0] == 'g') system(plotcmd);
15471: else if (z[0] == 'q') exit(0);
15472: }
1.227 brouard 15473: end:
1.126 brouard 15474: while (z[0] != 'q') {
1.195 brouard 15475: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15476: scanf("%s",z);
15477: }
1.283 brouard 15478: printf("End\n");
1.282 brouard 15479: exit(0);
1.126 brouard 15480: }
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