Annotation of imach/src/imach.c, revision 1.358
1.358 ! brouard 1: /* $Id: imach.c,v 1.357 2023/06/14 14:55:52 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.358 ! brouard 4: Revision 1.357 2023/06/14 14:55:52 brouard
! 5: * imach.c (Module): Testing if conjugate gradient could be quicker when lot of variables POWELLORIGINCONJUGATE
! 6:
1.357 brouard 7: Revision 1.356 2023/05/23 12:08:43 brouard
8: Summary: 0.99r46
9:
10: * imach.c (Module): Fixed PROB_r
11:
1.356 brouard 12: Revision 1.355 2023/05/22 17:03:18 brouard
13: Summary: 0.99r46
14:
15: * imach.c (Module): In the ILK....txt file, the number of columns
16: before the covariates values is dependent of the number of states (16+nlstate): 0.99r46
17:
1.355 brouard 18: Revision 1.354 2023/05/21 05:05:17 brouard
19: Summary: Temporary change for imachprax
20:
1.354 brouard 21: Revision 1.353 2023/05/08 18:48:22 brouard
22: *** empty log message ***
23:
1.353 brouard 24: Revision 1.352 2023/04/29 10:46:21 brouard
25: *** empty log message ***
26:
1.352 brouard 27: Revision 1.351 2023/04/29 10:43:47 brouard
28: Summary: 099r45
29:
1.351 brouard 30: Revision 1.350 2023/04/24 11:38:06 brouard
31: *** empty log message ***
32:
1.350 brouard 33: Revision 1.349 2023/01/31 09:19:37 brouard
34: Summary: Improvements in models with age*Vn*Vm
35:
1.348 brouard 36: Revision 1.347 2022/09/18 14:36:44 brouard
37: Summary: version 0.99r42
38:
1.347 brouard 39: Revision 1.346 2022/09/16 13:52:36 brouard
40: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
41:
1.346 brouard 42: Revision 1.345 2022/09/16 13:40:11 brouard
43: Summary: Version 0.99r41
44:
45: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
46:
1.345 brouard 47: Revision 1.344 2022/09/14 19:33:30 brouard
48: Summary: version 0.99r40
49:
50: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
51:
1.344 brouard 52: Revision 1.343 2022/09/14 14:22:16 brouard
53: Summary: version 0.99r39
54:
55: * imach.c (Module): Version 0.99r39 with colored dummy covariates
56: (fixed or time varying), using new last columns of
57: ILK_parameter.txt file.
58:
1.343 brouard 59: Revision 1.342 2022/09/11 19:54:09 brouard
60: Summary: 0.99r38
61:
62: * imach.c (Module): Adding timevarying products of any kinds,
63: should work before shifting cotvar from ncovcol+nqv columns in
64: order to have a correspondance between the column of cotvar and
65: the id of column.
66: (Module): Some cleaning and adding covariates in ILK.txt
67:
1.342 brouard 68: Revision 1.341 2022/09/11 07:58:42 brouard
69: Summary: Version 0.99r38
70:
71: After adding change in cotvar.
72:
1.341 brouard 73: Revision 1.340 2022/09/11 07:53:11 brouard
74: Summary: Version imach 0.99r37
75:
76: * imach.c (Module): Adding timevarying products of any kinds,
77: should work before shifting cotvar from ncovcol+nqv columns in
78: order to have a correspondance between the column of cotvar and
79: the id of column.
80:
1.340 brouard 81: Revision 1.339 2022/09/09 17:55:22 brouard
82: Summary: version 0.99r37
83:
84: * imach.c (Module): Many improvements for fixing products of fixed
85: timevarying as well as fixed * fixed, and test with quantitative
86: covariate.
87:
1.339 brouard 88: Revision 1.338 2022/09/04 17:40:33 brouard
89: Summary: 0.99r36
90:
91: * imach.c (Module): Now the easy runs i.e. without result or
92: model=1+age only did not work. The defautl combination should be 1
93: and not 0 because everything hasn't been tranformed yet.
94:
1.338 brouard 95: Revision 1.337 2022/09/02 14:26:02 brouard
96: Summary: version 0.99r35
97:
98: * src/imach.c: Version 0.99r35 because it outputs same results with
99: 1+age+V1+V1*age for females and 1+age for females only
100: (education=1 noweight)
101:
1.337 brouard 102: Revision 1.336 2022/08/31 09:52:36 brouard
103: *** empty log message ***
104:
1.336 brouard 105: Revision 1.335 2022/08/31 08:23:16 brouard
106: Summary: improvements...
107:
1.335 brouard 108: Revision 1.334 2022/08/25 09:08:41 brouard
109: Summary: In progress for quantitative
110:
1.334 brouard 111: Revision 1.333 2022/08/21 09:10:30 brouard
112: * src/imach.c (Module): Version 0.99r33 A lot of changes in
113: reassigning covariates: my first idea was that people will always
114: use the first covariate V1 into the model but in fact they are
115: producing data with many covariates and can use an equation model
116: with some of the covariate; it means that in a model V2+V3 instead
117: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
118: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
119: the equation model is restricted to two variables only (V2, V3)
120: and the combination for V2 should be codtabm(k,1) instead of
121: (codtabm(k,2), and the code should be
122: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
123: made. All of these should be simplified once a day like we did in
124: hpxij() for example by using precov[nres] which is computed in
125: decoderesult for each nres of each resultline. Loop should be done
126: on the equation model globally by distinguishing only product with
127: age (which are changing with age) and no more on type of
128: covariates, single dummies, single covariates.
129:
1.333 brouard 130: Revision 1.332 2022/08/21 09:06:25 brouard
131: Summary: Version 0.99r33
132:
133: * src/imach.c (Module): Version 0.99r33 A lot of changes in
134: reassigning covariates: my first idea was that people will always
135: use the first covariate V1 into the model but in fact they are
136: producing data with many covariates and can use an equation model
137: with some of the covariate; it means that in a model V2+V3 instead
138: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
139: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
140: the equation model is restricted to two variables only (V2, V3)
141: and the combination for V2 should be codtabm(k,1) instead of
142: (codtabm(k,2), and the code should be
143: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
144: made. All of these should be simplified once a day like we did in
145: hpxij() for example by using precov[nres] which is computed in
146: decoderesult for each nres of each resultline. Loop should be done
147: on the equation model globally by distinguishing only product with
148: age (which are changing with age) and no more on type of
149: covariates, single dummies, single covariates.
150:
1.332 brouard 151: Revision 1.331 2022/08/07 05:40:09 brouard
152: *** empty log message ***
153:
1.331 brouard 154: Revision 1.330 2022/08/06 07:18:25 brouard
155: Summary: last 0.99r31
156:
157: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
158:
1.330 brouard 159: Revision 1.329 2022/08/03 17:29:54 brouard
160: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
161:
1.329 brouard 162: Revision 1.328 2022/07/27 17:40:48 brouard
163: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
164:
1.328 brouard 165: Revision 1.327 2022/07/27 14:47:35 brouard
166: Summary: Still a problem for one-step probabilities in case of quantitative variables
167:
1.327 brouard 168: Revision 1.326 2022/07/26 17:33:55 brouard
169: Summary: some test with nres=1
170:
1.326 brouard 171: Revision 1.325 2022/07/25 14:27:23 brouard
172: Summary: r30
173:
174: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
175: coredumped, revealed by Feiuno, thank you.
176:
1.325 brouard 177: Revision 1.324 2022/07/23 17:44:26 brouard
178: *** empty log message ***
179:
1.324 brouard 180: Revision 1.323 2022/07/22 12:30:08 brouard
181: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
182:
1.323 brouard 183: Revision 1.322 2022/07/22 12:27:48 brouard
184: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
185:
1.322 brouard 186: Revision 1.321 2022/07/22 12:04:24 brouard
187: Summary: r28
188:
189: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
190:
1.321 brouard 191: Revision 1.320 2022/06/02 05:10:11 brouard
192: *** empty log message ***
193:
1.320 brouard 194: Revision 1.319 2022/06/02 04:45:11 brouard
195: * imach.c (Module): Adding the Wald tests from the log to the main
196: htm for better display of the maximum likelihood estimators.
197:
1.319 brouard 198: Revision 1.318 2022/05/24 08:10:59 brouard
199: * imach.c (Module): Some attempts to find a bug of wrong estimates
200: of confidencce intervals with product in the equation modelC
201:
1.318 brouard 202: Revision 1.317 2022/05/15 15:06:23 brouard
203: * imach.c (Module): Some minor improvements
204:
1.317 brouard 205: Revision 1.316 2022/05/11 15:11:31 brouard
206: Summary: r27
207:
1.316 brouard 208: Revision 1.315 2022/05/11 15:06:32 brouard
209: *** empty log message ***
210:
1.315 brouard 211: Revision 1.314 2022/04/13 17:43:09 brouard
212: * imach.c (Module): Adding link to text data files
213:
1.314 brouard 214: Revision 1.313 2022/04/11 15:57:42 brouard
215: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
216:
1.313 brouard 217: Revision 1.312 2022/04/05 21:24:39 brouard
218: *** empty log message ***
219:
1.312 brouard 220: Revision 1.311 2022/04/05 21:03:51 brouard
221: Summary: Fixed quantitative covariates
222:
223: Fixed covariates (dummy or quantitative)
224: with missing values have never been allowed but are ERRORS and
225: program quits. Standard deviations of fixed covariates were
226: wrongly computed. Mean and standard deviations of time varying
227: covariates are still not computed.
228:
1.311 brouard 229: Revision 1.310 2022/03/17 08:45:53 brouard
230: Summary: 99r25
231:
232: Improving detection of errors: result lines should be compatible with
233: the model.
234:
1.310 brouard 235: Revision 1.309 2021/05/20 12:39:14 brouard
236: Summary: Version 0.99r24
237:
1.309 brouard 238: Revision 1.308 2021/03/31 13:11:57 brouard
239: Summary: Version 0.99r23
240:
241:
242: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
243:
1.308 brouard 244: Revision 1.307 2021/03/08 18:11:32 brouard
245: Summary: 0.99r22 fixed bug on result:
246:
1.307 brouard 247: Revision 1.306 2021/02/20 15:44:02 brouard
248: Summary: Version 0.99r21
249:
250: * imach.c (Module): Fix bug on quitting after result lines!
251: (Module): Version 0.99r21
252:
1.306 brouard 253: Revision 1.305 2021/02/20 15:28:30 brouard
254: * imach.c (Module): Fix bug on quitting after result lines!
255:
1.305 brouard 256: Revision 1.304 2021/02/12 11:34:20 brouard
257: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
258:
1.304 brouard 259: Revision 1.303 2021/02/11 19:50:15 brouard
260: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
261:
1.303 brouard 262: Revision 1.302 2020/02/22 21:00:05 brouard
263: * (Module): imach.c Update mle=-3 (for computing Life expectancy
264: and life table from the data without any state)
265:
1.302 brouard 266: Revision 1.301 2019/06/04 13:51:20 brouard
267: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
268:
1.301 brouard 269: Revision 1.300 2019/05/22 19:09:45 brouard
270: Summary: version 0.99r19 of May 2019
271:
1.300 brouard 272: Revision 1.299 2019/05/22 18:37:08 brouard
273: Summary: Cleaned 0.99r19
274:
1.299 brouard 275: Revision 1.298 2019/05/22 18:19:56 brouard
276: *** empty log message ***
277:
1.298 brouard 278: Revision 1.297 2019/05/22 17:56:10 brouard
279: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
280:
1.297 brouard 281: Revision 1.296 2019/05/20 13:03:18 brouard
282: Summary: Projection syntax simplified
283:
284:
285: We can now start projections, forward or backward, from the mean date
286: of inteviews up to or down to a number of years of projection:
287: prevforecast=1 yearsfproj=15.3 mobil_average=0
288: or
289: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
290: or
291: prevbackcast=1 yearsbproj=12.3 mobil_average=1
292: or
293: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
294:
1.296 brouard 295: Revision 1.295 2019/05/18 09:52:50 brouard
296: Summary: doxygen tex bug
297:
1.295 brouard 298: Revision 1.294 2019/05/16 14:54:33 brouard
299: Summary: There was some wrong lines added
300:
1.294 brouard 301: Revision 1.293 2019/05/09 15:17:34 brouard
302: *** empty log message ***
303:
1.293 brouard 304: Revision 1.292 2019/05/09 14:17:20 brouard
305: Summary: Some updates
306:
1.292 brouard 307: Revision 1.291 2019/05/09 13:44:18 brouard
308: Summary: Before ncovmax
309:
1.291 brouard 310: Revision 1.290 2019/05/09 13:39:37 brouard
311: Summary: 0.99r18 unlimited number of individuals
312:
313: 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.
314:
1.290 brouard 315: Revision 1.289 2018/12/13 09:16:26 brouard
316: Summary: Bug for young ages (<-30) will be in r17
317:
1.289 brouard 318: Revision 1.288 2018/05/02 20:58:27 brouard
319: Summary: Some bugs fixed
320:
1.288 brouard 321: Revision 1.287 2018/05/01 17:57:25 brouard
322: Summary: Bug fixed by providing frequencies only for non missing covariates
323:
1.287 brouard 324: Revision 1.286 2018/04/27 14:27:04 brouard
325: Summary: some minor bugs
326:
1.286 brouard 327: Revision 1.285 2018/04/21 21:02:16 brouard
328: Summary: Some bugs fixed, valgrind tested
329:
1.285 brouard 330: Revision 1.284 2018/04/20 05:22:13 brouard
331: Summary: Computing mean and stdeviation of fixed quantitative variables
332:
1.284 brouard 333: Revision 1.283 2018/04/19 14:49:16 brouard
334: Summary: Some minor bugs fixed
335:
1.283 brouard 336: Revision 1.282 2018/02/27 22:50:02 brouard
337: *** empty log message ***
338:
1.282 brouard 339: Revision 1.281 2018/02/27 19:25:23 brouard
340: Summary: Adding second argument for quitting
341:
1.281 brouard 342: Revision 1.280 2018/02/21 07:58:13 brouard
343: Summary: 0.99r15
344:
345: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
346:
1.280 brouard 347: Revision 1.279 2017/07/20 13:35:01 brouard
348: Summary: temporary working
349:
1.279 brouard 350: Revision 1.278 2017/07/19 14:09:02 brouard
351: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
352:
1.278 brouard 353: Revision 1.277 2017/07/17 08:53:49 brouard
354: Summary: BOM files can be read now
355:
1.277 brouard 356: Revision 1.276 2017/06/30 15:48:31 brouard
357: Summary: Graphs improvements
358:
1.276 brouard 359: Revision 1.275 2017/06/30 13:39:33 brouard
360: Summary: Saito's color
361:
1.275 brouard 362: Revision 1.274 2017/06/29 09:47:08 brouard
363: Summary: Version 0.99r14
364:
1.274 brouard 365: Revision 1.273 2017/06/27 11:06:02 brouard
366: Summary: More documentation on projections
367:
1.273 brouard 368: Revision 1.272 2017/06/27 10:22:40 brouard
369: Summary: Color of backprojection changed from 6 to 5(yellow)
370:
1.272 brouard 371: Revision 1.271 2017/06/27 10:17:50 brouard
372: Summary: Some bug with rint
373:
1.271 brouard 374: Revision 1.270 2017/05/24 05:45:29 brouard
375: *** empty log message ***
376:
1.270 brouard 377: Revision 1.269 2017/05/23 08:39:25 brouard
378: Summary: Code into subroutine, cleanings
379:
1.269 brouard 380: Revision 1.268 2017/05/18 20:09:32 brouard
381: Summary: backprojection and confidence intervals of backprevalence
382:
1.268 brouard 383: Revision 1.267 2017/05/13 10:25:05 brouard
384: Summary: temporary save for backprojection
385:
1.267 brouard 386: Revision 1.266 2017/05/13 07:26:12 brouard
387: Summary: Version 0.99r13 (improvements and bugs fixed)
388:
1.266 brouard 389: Revision 1.265 2017/04/26 16:22:11 brouard
390: Summary: imach 0.99r13 Some bugs fixed
391:
1.265 brouard 392: Revision 1.264 2017/04/26 06:01:29 brouard
393: Summary: Labels in graphs
394:
1.264 brouard 395: Revision 1.263 2017/04/24 15:23:15 brouard
396: Summary: to save
397:
1.263 brouard 398: Revision 1.262 2017/04/18 16:48:12 brouard
399: *** empty log message ***
400:
1.262 brouard 401: Revision 1.261 2017/04/05 10:14:09 brouard
402: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
403:
1.261 brouard 404: Revision 1.260 2017/04/04 17:46:59 brouard
405: Summary: Gnuplot indexations fixed (humm)
406:
1.260 brouard 407: Revision 1.259 2017/04/04 13:01:16 brouard
408: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
409:
1.259 brouard 410: Revision 1.258 2017/04/03 10:17:47 brouard
411: Summary: Version 0.99r12
412:
413: Some cleanings, conformed with updated documentation.
414:
1.258 brouard 415: Revision 1.257 2017/03/29 16:53:30 brouard
416: Summary: Temp
417:
1.257 brouard 418: Revision 1.256 2017/03/27 05:50:23 brouard
419: Summary: Temporary
420:
1.256 brouard 421: Revision 1.255 2017/03/08 16:02:28 brouard
422: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
423:
1.255 brouard 424: Revision 1.254 2017/03/08 07:13:00 brouard
425: Summary: Fixing data parameter line
426:
1.254 brouard 427: Revision 1.253 2016/12/15 11:59:41 brouard
428: Summary: 0.99 in progress
429:
1.253 brouard 430: Revision 1.252 2016/09/15 21:15:37 brouard
431: *** empty log message ***
432:
1.252 brouard 433: Revision 1.251 2016/09/15 15:01:13 brouard
434: Summary: not working
435:
1.251 brouard 436: Revision 1.250 2016/09/08 16:07:27 brouard
437: Summary: continue
438:
1.250 brouard 439: Revision 1.249 2016/09/07 17:14:18 brouard
440: Summary: Starting values from frequencies
441:
1.249 brouard 442: Revision 1.248 2016/09/07 14:10:18 brouard
443: *** empty log message ***
444:
1.248 brouard 445: Revision 1.247 2016/09/02 11:11:21 brouard
446: *** empty log message ***
447:
1.247 brouard 448: Revision 1.246 2016/09/02 08:49:22 brouard
449: *** empty log message ***
450:
1.246 brouard 451: Revision 1.245 2016/09/02 07:25:01 brouard
452: *** empty log message ***
453:
1.245 brouard 454: Revision 1.244 2016/09/02 07:17:34 brouard
455: *** empty log message ***
456:
1.244 brouard 457: Revision 1.243 2016/09/02 06:45:35 brouard
458: *** empty log message ***
459:
1.243 brouard 460: Revision 1.242 2016/08/30 15:01:20 brouard
461: Summary: Fixing a lots
462:
1.242 brouard 463: Revision 1.241 2016/08/29 17:17:25 brouard
464: Summary: gnuplot problem in Back projection to fix
465:
1.241 brouard 466: Revision 1.240 2016/08/29 07:53:18 brouard
467: Summary: Better
468:
1.240 brouard 469: Revision 1.239 2016/08/26 15:51:03 brouard
470: Summary: Improvement in Powell output in order to copy and paste
471:
472: Author:
473:
1.239 brouard 474: Revision 1.238 2016/08/26 14:23:35 brouard
475: Summary: Starting tests of 0.99
476:
1.238 brouard 477: Revision 1.237 2016/08/26 09:20:19 brouard
478: Summary: to valgrind
479:
1.237 brouard 480: Revision 1.236 2016/08/25 10:50:18 brouard
481: *** empty log message ***
482:
1.236 brouard 483: Revision 1.235 2016/08/25 06:59:23 brouard
484: *** empty log message ***
485:
1.235 brouard 486: Revision 1.234 2016/08/23 16:51:20 brouard
487: *** empty log message ***
488:
1.234 brouard 489: Revision 1.233 2016/08/23 07:40:50 brouard
490: Summary: not working
491:
1.233 brouard 492: Revision 1.232 2016/08/22 14:20:21 brouard
493: Summary: not working
494:
1.232 brouard 495: Revision 1.231 2016/08/22 07:17:15 brouard
496: Summary: not working
497:
1.231 brouard 498: Revision 1.230 2016/08/22 06:55:53 brouard
499: Summary: Not working
500:
1.230 brouard 501: Revision 1.229 2016/07/23 09:45:53 brouard
502: Summary: Completing for func too
503:
1.229 brouard 504: Revision 1.228 2016/07/22 17:45:30 brouard
505: Summary: Fixing some arrays, still debugging
506:
1.227 brouard 507: Revision 1.226 2016/07/12 18:42:34 brouard
508: Summary: temp
509:
1.226 brouard 510: Revision 1.225 2016/07/12 08:40:03 brouard
511: Summary: saving but not running
512:
1.225 brouard 513: Revision 1.224 2016/07/01 13:16:01 brouard
514: Summary: Fixes
515:
1.224 brouard 516: Revision 1.223 2016/02/19 09:23:35 brouard
517: Summary: temporary
518:
1.223 brouard 519: Revision 1.222 2016/02/17 08:14:50 brouard
520: Summary: Probably last 0.98 stable version 0.98r6
521:
1.222 brouard 522: Revision 1.221 2016/02/15 23:35:36 brouard
523: Summary: minor bug
524:
1.220 brouard 525: Revision 1.219 2016/02/15 00:48:12 brouard
526: *** empty log message ***
527:
1.219 brouard 528: Revision 1.218 2016/02/12 11:29:23 brouard
529: Summary: 0.99 Back projections
530:
1.218 brouard 531: Revision 1.217 2015/12/23 17:18:31 brouard
532: Summary: Experimental backcast
533:
1.217 brouard 534: Revision 1.216 2015/12/18 17:32:11 brouard
535: Summary: 0.98r4 Warning and status=-2
536:
537: Version 0.98r4 is now:
538: - displaying an error when status is -1, date of interview unknown and date of death known;
539: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
540: Older changes concerning s=-2, dating from 2005 have been supersed.
541:
1.216 brouard 542: Revision 1.215 2015/12/16 08:52:24 brouard
543: Summary: 0.98r4 working
544:
1.215 brouard 545: Revision 1.214 2015/12/16 06:57:54 brouard
546: Summary: temporary not working
547:
1.214 brouard 548: Revision 1.213 2015/12/11 18:22:17 brouard
549: Summary: 0.98r4
550:
1.213 brouard 551: Revision 1.212 2015/11/21 12:47:24 brouard
552: Summary: minor typo
553:
1.212 brouard 554: Revision 1.211 2015/11/21 12:41:11 brouard
555: Summary: 0.98r3 with some graph of projected cross-sectional
556:
557: Author: Nicolas Brouard
558:
1.211 brouard 559: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 560: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 561: Summary: Adding ftolpl parameter
562: Author: N Brouard
563:
564: We had difficulties to get smoothed confidence intervals. It was due
565: to the period prevalence which wasn't computed accurately. The inner
566: parameter ftolpl is now an outer parameter of the .imach parameter
567: file after estepm. If ftolpl is small 1.e-4 and estepm too,
568: computation are long.
569:
1.209 brouard 570: Revision 1.208 2015/11/17 14:31:57 brouard
571: Summary: temporary
572:
1.208 brouard 573: Revision 1.207 2015/10/27 17:36:57 brouard
574: *** empty log message ***
575:
1.207 brouard 576: Revision 1.206 2015/10/24 07:14:11 brouard
577: *** empty log message ***
578:
1.206 brouard 579: Revision 1.205 2015/10/23 15:50:53 brouard
580: Summary: 0.98r3 some clarification for graphs on likelihood contributions
581:
1.205 brouard 582: Revision 1.204 2015/10/01 16:20:26 brouard
583: Summary: Some new graphs of contribution to likelihood
584:
1.204 brouard 585: Revision 1.203 2015/09/30 17:45:14 brouard
586: Summary: looking at better estimation of the hessian
587:
588: Also a better criteria for convergence to the period prevalence And
589: therefore adding the number of years needed to converge. (The
590: prevalence in any alive state shold sum to one
591:
1.203 brouard 592: Revision 1.202 2015/09/22 19:45:16 brouard
593: Summary: Adding some overall graph on contribution to likelihood. Might change
594:
1.202 brouard 595: Revision 1.201 2015/09/15 17:34:58 brouard
596: Summary: 0.98r0
597:
598: - Some new graphs like suvival functions
599: - Some bugs fixed like model=1+age+V2.
600:
1.201 brouard 601: Revision 1.200 2015/09/09 16:53:55 brouard
602: Summary: Big bug thanks to Flavia
603:
604: Even model=1+age+V2. did not work anymore
605:
1.200 brouard 606: Revision 1.199 2015/09/07 14:09:23 brouard
607: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
608:
1.199 brouard 609: Revision 1.198 2015/09/03 07:14:39 brouard
610: Summary: 0.98q5 Flavia
611:
1.198 brouard 612: Revision 1.197 2015/09/01 18:24:39 brouard
613: *** empty log message ***
614:
1.197 brouard 615: Revision 1.196 2015/08/18 23:17:52 brouard
616: Summary: 0.98q5
617:
1.196 brouard 618: Revision 1.195 2015/08/18 16:28:39 brouard
619: Summary: Adding a hack for testing purpose
620:
621: After reading the title, ftol and model lines, if the comment line has
622: a q, starting with #q, the answer at the end of the run is quit. It
623: permits to run test files in batch with ctest. The former workaround was
624: $ echo q | imach foo.imach
625:
1.195 brouard 626: Revision 1.194 2015/08/18 13:32:00 brouard
627: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
628:
1.194 brouard 629: Revision 1.193 2015/08/04 07:17:42 brouard
630: Summary: 0.98q4
631:
1.193 brouard 632: Revision 1.192 2015/07/16 16:49:02 brouard
633: Summary: Fixing some outputs
634:
1.192 brouard 635: Revision 1.191 2015/07/14 10:00:33 brouard
636: Summary: Some fixes
637:
1.191 brouard 638: Revision 1.190 2015/05/05 08:51:13 brouard
639: Summary: Adding digits in output parameters (7 digits instead of 6)
640:
641: Fix 1+age+.
642:
1.190 brouard 643: Revision 1.189 2015/04/30 14:45:16 brouard
644: Summary: 0.98q2
645:
1.189 brouard 646: Revision 1.188 2015/04/30 08:27:53 brouard
647: *** empty log message ***
648:
1.188 brouard 649: Revision 1.187 2015/04/29 09:11:15 brouard
650: *** empty log message ***
651:
1.187 brouard 652: Revision 1.186 2015/04/23 12:01:52 brouard
653: Summary: V1*age is working now, version 0.98q1
654:
655: Some codes had been disabled in order to simplify and Vn*age was
656: working in the optimization phase, ie, giving correct MLE parameters,
657: but, as usual, outputs were not correct and program core dumped.
658:
1.186 brouard 659: Revision 1.185 2015/03/11 13:26:42 brouard
660: Summary: Inclusion of compile and links command line for Intel Compiler
661:
1.185 brouard 662: Revision 1.184 2015/03/11 11:52:39 brouard
663: Summary: Back from Windows 8. Intel Compiler
664:
1.184 brouard 665: Revision 1.183 2015/03/10 20:34:32 brouard
666: Summary: 0.98q0, trying with directest, mnbrak fixed
667:
668: We use directest instead of original Powell test; probably no
669: incidence on the results, but better justifications;
670: We fixed Numerical Recipes mnbrak routine which was wrong and gave
671: wrong results.
672:
1.183 brouard 673: Revision 1.182 2015/02/12 08:19:57 brouard
674: Summary: Trying to keep directest which seems simpler and more general
675: Author: Nicolas Brouard
676:
1.182 brouard 677: Revision 1.181 2015/02/11 23:22:24 brouard
678: Summary: Comments on Powell added
679:
680: Author:
681:
1.181 brouard 682: Revision 1.180 2015/02/11 17:33:45 brouard
683: Summary: Finishing move from main to function (hpijx and prevalence_limit)
684:
1.180 brouard 685: Revision 1.179 2015/01/04 09:57:06 brouard
686: Summary: back to OS/X
687:
1.179 brouard 688: Revision 1.178 2015/01/04 09:35:48 brouard
689: *** empty log message ***
690:
1.178 brouard 691: Revision 1.177 2015/01/03 18:40:56 brouard
692: Summary: Still testing ilc32 on OSX
693:
1.177 brouard 694: Revision 1.176 2015/01/03 16:45:04 brouard
695: *** empty log message ***
696:
1.176 brouard 697: Revision 1.175 2015/01/03 16:33:42 brouard
698: *** empty log message ***
699:
1.175 brouard 700: Revision 1.174 2015/01/03 16:15:49 brouard
701: Summary: Still in cross-compilation
702:
1.174 brouard 703: Revision 1.173 2015/01/03 12:06:26 brouard
704: Summary: trying to detect cross-compilation
705:
1.173 brouard 706: Revision 1.172 2014/12/27 12:07:47 brouard
707: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
708:
1.172 brouard 709: Revision 1.171 2014/12/23 13:26:59 brouard
710: Summary: Back from Visual C
711:
712: Still problem with utsname.h on Windows
713:
1.171 brouard 714: Revision 1.170 2014/12/23 11:17:12 brouard
715: Summary: Cleaning some \%% back to %%
716:
717: The escape was mandatory for a specific compiler (which one?), but too many warnings.
718:
1.170 brouard 719: Revision 1.169 2014/12/22 23:08:31 brouard
720: Summary: 0.98p
721:
722: Outputs some informations on compiler used, OS etc. Testing on different platforms.
723:
1.169 brouard 724: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 725: Summary: update
1.169 brouard 726:
1.168 brouard 727: Revision 1.167 2014/12/22 13:50:56 brouard
728: Summary: Testing uname and compiler version and if compiled 32 or 64
729:
730: Testing on Linux 64
731:
1.167 brouard 732: Revision 1.166 2014/12/22 11:40:47 brouard
733: *** empty log message ***
734:
1.166 brouard 735: Revision 1.165 2014/12/16 11:20:36 brouard
736: Summary: After compiling on Visual C
737:
738: * imach.c (Module): Merging 1.61 to 1.162
739:
1.165 brouard 740: Revision 1.164 2014/12/16 10:52:11 brouard
741: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
742:
743: * imach.c (Module): Merging 1.61 to 1.162
744:
1.164 brouard 745: Revision 1.163 2014/12/16 10:30:11 brouard
746: * imach.c (Module): Merging 1.61 to 1.162
747:
1.163 brouard 748: Revision 1.162 2014/09/25 11:43:39 brouard
749: Summary: temporary backup 0.99!
750:
1.162 brouard 751: Revision 1.1 2014/09/16 11:06:58 brouard
752: Summary: With some code (wrong) for nlopt
753:
754: Author:
755:
756: Revision 1.161 2014/09/15 20:41:41 brouard
757: Summary: Problem with macro SQR on Intel compiler
758:
1.161 brouard 759: Revision 1.160 2014/09/02 09:24:05 brouard
760: *** empty log message ***
761:
1.160 brouard 762: Revision 1.159 2014/09/01 10:34:10 brouard
763: Summary: WIN32
764: Author: Brouard
765:
1.159 brouard 766: Revision 1.158 2014/08/27 17:11:51 brouard
767: *** empty log message ***
768:
1.158 brouard 769: Revision 1.157 2014/08/27 16:26:55 brouard
770: Summary: Preparing windows Visual studio version
771: Author: Brouard
772:
773: In order to compile on Visual studio, time.h is now correct and time_t
774: and tm struct should be used. difftime should be used but sometimes I
775: just make the differences in raw time format (time(&now).
776: Trying to suppress #ifdef LINUX
777: Add xdg-open for __linux in order to open default browser.
778:
1.157 brouard 779: Revision 1.156 2014/08/25 20:10:10 brouard
780: *** empty log message ***
781:
1.156 brouard 782: Revision 1.155 2014/08/25 18:32:34 brouard
783: Summary: New compile, minor changes
784: Author: Brouard
785:
1.155 brouard 786: Revision 1.154 2014/06/20 17:32:08 brouard
787: Summary: Outputs now all graphs of convergence to period prevalence
788:
1.154 brouard 789: Revision 1.153 2014/06/20 16:45:46 brouard
790: Summary: If 3 live state, convergence to period prevalence on same graph
791: Author: Brouard
792:
1.153 brouard 793: Revision 1.152 2014/06/18 17:54:09 brouard
794: Summary: open browser, use gnuplot on same dir than imach if not found in the path
795:
1.152 brouard 796: Revision 1.151 2014/06/18 16:43:30 brouard
797: *** empty log message ***
798:
1.151 brouard 799: Revision 1.150 2014/06/18 16:42:35 brouard
800: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
801: Author: brouard
802:
1.150 brouard 803: Revision 1.149 2014/06/18 15:51:14 brouard
804: Summary: Some fixes in parameter files errors
805: Author: Nicolas Brouard
806:
1.149 brouard 807: Revision 1.148 2014/06/17 17:38:48 brouard
808: Summary: Nothing new
809: Author: Brouard
810:
811: Just a new packaging for OS/X version 0.98nS
812:
1.148 brouard 813: Revision 1.147 2014/06/16 10:33:11 brouard
814: *** empty log message ***
815:
1.147 brouard 816: Revision 1.146 2014/06/16 10:20:28 brouard
817: Summary: Merge
818: Author: Brouard
819:
820: Merge, before building revised version.
821:
1.146 brouard 822: Revision 1.145 2014/06/10 21:23:15 brouard
823: Summary: Debugging with valgrind
824: Author: Nicolas Brouard
825:
826: Lot of changes in order to output the results with some covariates
827: After the Edimburgh REVES conference 2014, it seems mandatory to
828: improve the code.
829: No more memory valgrind error but a lot has to be done in order to
830: continue the work of splitting the code into subroutines.
831: Also, decodemodel has been improved. Tricode is still not
832: optimal. nbcode should be improved. Documentation has been added in
833: the source code.
834:
1.144 brouard 835: Revision 1.143 2014/01/26 09:45:38 brouard
836: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
837:
838: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
839: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
840:
1.143 brouard 841: Revision 1.142 2014/01/26 03:57:36 brouard
842: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
843:
844: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
845:
1.142 brouard 846: Revision 1.141 2014/01/26 02:42:01 brouard
847: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
848:
1.141 brouard 849: Revision 1.140 2011/09/02 10:37:54 brouard
850: Summary: times.h is ok with mingw32 now.
851:
1.140 brouard 852: Revision 1.139 2010/06/14 07:50:17 brouard
853: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
854: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
855:
1.139 brouard 856: Revision 1.138 2010/04/30 18:19:40 brouard
857: *** empty log message ***
858:
1.138 brouard 859: Revision 1.137 2010/04/29 18:11:38 brouard
860: (Module): Checking covariates for more complex models
861: than V1+V2. A lot of change to be done. Unstable.
862:
1.137 brouard 863: Revision 1.136 2010/04/26 20:30:53 brouard
864: (Module): merging some libgsl code. Fixing computation
865: of likelione (using inter/intrapolation if mle = 0) in order to
866: get same likelihood as if mle=1.
867: Some cleaning of code and comments added.
868:
1.136 brouard 869: Revision 1.135 2009/10/29 15:33:14 brouard
870: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
871:
1.135 brouard 872: Revision 1.134 2009/10/29 13:18:53 brouard
873: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
874:
1.134 brouard 875: Revision 1.133 2009/07/06 10:21:25 brouard
876: just nforces
877:
1.133 brouard 878: Revision 1.132 2009/07/06 08:22:05 brouard
879: Many tings
880:
1.132 brouard 881: Revision 1.131 2009/06/20 16:22:47 brouard
882: Some dimensions resccaled
883:
1.131 brouard 884: Revision 1.130 2009/05/26 06:44:34 brouard
885: (Module): Max Covariate is now set to 20 instead of 8. A
886: lot of cleaning with variables initialized to 0. Trying to make
887: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
888:
1.130 brouard 889: Revision 1.129 2007/08/31 13:49:27 lievre
890: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
891:
1.129 lievre 892: Revision 1.128 2006/06/30 13:02:05 brouard
893: (Module): Clarifications on computing e.j
894:
1.128 brouard 895: Revision 1.127 2006/04/28 18:11:50 brouard
896: (Module): Yes the sum of survivors was wrong since
897: imach-114 because nhstepm was no more computed in the age
898: loop. Now we define nhstepma in the age loop.
899: (Module): In order to speed up (in case of numerous covariates) we
900: compute health expectancies (without variances) in a first step
901: and then all the health expectancies with variances or standard
902: deviation (needs data from the Hessian matrices) which slows the
903: computation.
904: In the future we should be able to stop the program is only health
905: expectancies and graph are needed without standard deviations.
906:
1.127 brouard 907: Revision 1.126 2006/04/28 17:23:28 brouard
908: (Module): Yes the sum of survivors was wrong since
909: imach-114 because nhstepm was no more computed in the age
910: loop. Now we define nhstepma in the age loop.
911: Version 0.98h
912:
1.126 brouard 913: Revision 1.125 2006/04/04 15:20:31 lievre
914: Errors in calculation of health expectancies. Age was not initialized.
915: Forecasting file added.
916:
917: Revision 1.124 2006/03/22 17:13:53 lievre
918: Parameters are printed with %lf instead of %f (more numbers after the comma).
919: The log-likelihood is printed in the log file
920:
921: Revision 1.123 2006/03/20 10:52:43 brouard
922: * imach.c (Module): <title> changed, corresponds to .htm file
923: name. <head> headers where missing.
924:
925: * imach.c (Module): Weights can have a decimal point as for
926: English (a comma might work with a correct LC_NUMERIC environment,
927: otherwise the weight is truncated).
928: Modification of warning when the covariates values are not 0 or
929: 1.
930: Version 0.98g
931:
932: Revision 1.122 2006/03/20 09:45:41 brouard
933: (Module): Weights can have a decimal point as for
934: English (a comma might work with a correct LC_NUMERIC environment,
935: otherwise the weight is truncated).
936: Modification of warning when the covariates values are not 0 or
937: 1.
938: Version 0.98g
939:
940: Revision 1.121 2006/03/16 17:45:01 lievre
941: * imach.c (Module): Comments concerning covariates added
942:
943: * imach.c (Module): refinements in the computation of lli if
944: status=-2 in order to have more reliable computation if stepm is
945: not 1 month. Version 0.98f
946:
947: Revision 1.120 2006/03/16 15:10:38 lievre
948: (Module): refinements in the computation of lli if
949: status=-2 in order to have more reliable computation if stepm is
950: not 1 month. Version 0.98f
951:
952: Revision 1.119 2006/03/15 17:42:26 brouard
953: (Module): Bug if status = -2, the loglikelihood was
954: computed as likelihood omitting the logarithm. Version O.98e
955:
956: Revision 1.118 2006/03/14 18:20:07 brouard
957: (Module): varevsij Comments added explaining the second
958: table of variances if popbased=1 .
959: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
960: (Module): Function pstamp added
961: (Module): Version 0.98d
962:
963: Revision 1.117 2006/03/14 17:16:22 brouard
964: (Module): varevsij Comments added explaining the second
965: table of variances if popbased=1 .
966: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
967: (Module): Function pstamp added
968: (Module): Version 0.98d
969:
970: Revision 1.116 2006/03/06 10:29:27 brouard
971: (Module): Variance-covariance wrong links and
972: varian-covariance of ej. is needed (Saito).
973:
974: Revision 1.115 2006/02/27 12:17:45 brouard
975: (Module): One freematrix added in mlikeli! 0.98c
976:
977: Revision 1.114 2006/02/26 12:57:58 brouard
978: (Module): Some improvements in processing parameter
979: filename with strsep.
980:
981: Revision 1.113 2006/02/24 14:20:24 brouard
982: (Module): Memory leaks checks with valgrind and:
983: datafile was not closed, some imatrix were not freed and on matrix
984: allocation too.
985:
986: Revision 1.112 2006/01/30 09:55:26 brouard
987: (Module): Back to gnuplot.exe instead of wgnuplot.exe
988:
989: Revision 1.111 2006/01/25 20:38:18 brouard
990: (Module): Lots of cleaning and bugs added (Gompertz)
991: (Module): Comments can be added in data file. Missing date values
992: can be a simple dot '.'.
993:
994: Revision 1.110 2006/01/25 00:51:50 brouard
995: (Module): Lots of cleaning and bugs added (Gompertz)
996:
997: Revision 1.109 2006/01/24 19:37:15 brouard
998: (Module): Comments (lines starting with a #) are allowed in data.
999:
1000: Revision 1.108 2006/01/19 18:05:42 lievre
1001: Gnuplot problem appeared...
1002: To be fixed
1003:
1004: Revision 1.107 2006/01/19 16:20:37 brouard
1005: Test existence of gnuplot in imach path
1006:
1007: Revision 1.106 2006/01/19 13:24:36 brouard
1008: Some cleaning and links added in html output
1009:
1010: Revision 1.105 2006/01/05 20:23:19 lievre
1011: *** empty log message ***
1012:
1013: Revision 1.104 2005/09/30 16:11:43 lievre
1014: (Module): sump fixed, loop imx fixed, and simplifications.
1015: (Module): If the status is missing at the last wave but we know
1016: that the person is alive, then we can code his/her status as -2
1017: (instead of missing=-1 in earlier versions) and his/her
1018: contributions to the likelihood is 1 - Prob of dying from last
1019: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1020: the healthy state at last known wave). Version is 0.98
1021:
1022: Revision 1.103 2005/09/30 15:54:49 lievre
1023: (Module): sump fixed, loop imx fixed, and simplifications.
1024:
1025: Revision 1.102 2004/09/15 17:31:30 brouard
1026: Add the possibility to read data file including tab characters.
1027:
1028: Revision 1.101 2004/09/15 10:38:38 brouard
1029: Fix on curr_time
1030:
1031: Revision 1.100 2004/07/12 18:29:06 brouard
1032: Add version for Mac OS X. Just define UNIX in Makefile
1033:
1034: Revision 1.99 2004/06/05 08:57:40 brouard
1035: *** empty log message ***
1036:
1037: Revision 1.98 2004/05/16 15:05:56 brouard
1038: New version 0.97 . First attempt to estimate force of mortality
1039: directly from the data i.e. without the need of knowing the health
1040: state at each age, but using a Gompertz model: log u =a + b*age .
1041: This is the basic analysis of mortality and should be done before any
1042: other analysis, in order to test if the mortality estimated from the
1043: cross-longitudinal survey is different from the mortality estimated
1044: from other sources like vital statistic data.
1045:
1046: The same imach parameter file can be used but the option for mle should be -3.
1047:
1.324 brouard 1048: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1049: former routines in order to include the new code within the former code.
1050:
1051: The output is very simple: only an estimate of the intercept and of
1052: the slope with 95% confident intervals.
1053:
1054: Current limitations:
1055: A) Even if you enter covariates, i.e. with the
1056: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1057: B) There is no computation of Life Expectancy nor Life Table.
1058:
1059: Revision 1.97 2004/02/20 13:25:42 lievre
1060: Version 0.96d. Population forecasting command line is (temporarily)
1061: suppressed.
1062:
1063: Revision 1.96 2003/07/15 15:38:55 brouard
1064: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1065: rewritten within the same printf. Workaround: many printfs.
1066:
1067: Revision 1.95 2003/07/08 07:54:34 brouard
1068: * imach.c (Repository):
1069: (Repository): Using imachwizard code to output a more meaningful covariance
1070: matrix (cov(a12,c31) instead of numbers.
1071:
1072: Revision 1.94 2003/06/27 13:00:02 brouard
1073: Just cleaning
1074:
1075: Revision 1.93 2003/06/25 16:33:55 brouard
1076: (Module): On windows (cygwin) function asctime_r doesn't
1077: exist so I changed back to asctime which exists.
1078: (Module): Version 0.96b
1079:
1080: Revision 1.92 2003/06/25 16:30:45 brouard
1081: (Module): On windows (cygwin) function asctime_r doesn't
1082: exist so I changed back to asctime which exists.
1083:
1084: Revision 1.91 2003/06/25 15:30:29 brouard
1085: * imach.c (Repository): Duplicated warning errors corrected.
1086: (Repository): Elapsed time after each iteration is now output. It
1087: helps to forecast when convergence will be reached. Elapsed time
1088: is stamped in powell. We created a new html file for the graphs
1089: concerning matrix of covariance. It has extension -cov.htm.
1090:
1091: Revision 1.90 2003/06/24 12:34:15 brouard
1092: (Module): Some bugs corrected for windows. Also, when
1093: mle=-1 a template is output in file "or"mypar.txt with the design
1094: of the covariance matrix to be input.
1095:
1096: Revision 1.89 2003/06/24 12:30:52 brouard
1097: (Module): Some bugs corrected for windows. Also, when
1098: mle=-1 a template is output in file "or"mypar.txt with the design
1099: of the covariance matrix to be input.
1100:
1101: Revision 1.88 2003/06/23 17:54:56 brouard
1102: * 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.
1103:
1104: Revision 1.87 2003/06/18 12:26:01 brouard
1105: Version 0.96
1106:
1107: Revision 1.86 2003/06/17 20:04:08 brouard
1108: (Module): Change position of html and gnuplot routines and added
1109: routine fileappend.
1110:
1111: Revision 1.85 2003/06/17 13:12:43 brouard
1112: * imach.c (Repository): Check when date of death was earlier that
1113: current date of interview. It may happen when the death was just
1114: prior to the death. In this case, dh was negative and likelihood
1115: was wrong (infinity). We still send an "Error" but patch by
1116: assuming that the date of death was just one stepm after the
1117: interview.
1118: (Repository): Because some people have very long ID (first column)
1119: we changed int to long in num[] and we added a new lvector for
1120: memory allocation. But we also truncated to 8 characters (left
1121: truncation)
1122: (Repository): No more line truncation errors.
1123:
1124: Revision 1.84 2003/06/13 21:44:43 brouard
1125: * imach.c (Repository): Replace "freqsummary" at a correct
1126: place. It differs from routine "prevalence" which may be called
1127: many times. Probs is memory consuming and must be used with
1128: parcimony.
1129: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1130:
1131: Revision 1.83 2003/06/10 13:39:11 lievre
1132: *** empty log message ***
1133:
1134: Revision 1.82 2003/06/05 15:57:20 brouard
1135: Add log in imach.c and fullversion number is now printed.
1136:
1137: */
1138: /*
1139: Interpolated Markov Chain
1140:
1141: Short summary of the programme:
1142:
1.227 brouard 1143: This program computes Healthy Life Expectancies or State-specific
1144: (if states aren't health statuses) Expectancies from
1145: cross-longitudinal data. Cross-longitudinal data consist in:
1146:
1147: -1- a first survey ("cross") where individuals from different ages
1148: are interviewed on their health status or degree of disability (in
1149: the case of a health survey which is our main interest)
1150:
1151: -2- at least a second wave of interviews ("longitudinal") which
1152: measure each change (if any) in individual health status. Health
1153: expectancies are computed from the time spent in each health state
1154: according to a model. More health states you consider, more time is
1155: necessary to reach the Maximum Likelihood of the parameters involved
1156: in the model. The simplest model is the multinomial logistic model
1157: where pij is the probability to be observed in state j at the second
1158: wave conditional to be observed in state i at the first
1159: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1160: etc , where 'age' is age and 'sex' is a covariate. If you want to
1161: have a more complex model than "constant and age", you should modify
1162: the program where the markup *Covariates have to be included here
1163: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1164: convergence.
1165:
1166: The advantage of this computer programme, compared to a simple
1167: multinomial logistic model, is clear when the delay between waves is not
1168: identical for each individual. Also, if a individual missed an
1169: intermediate interview, the information is lost, but taken into
1170: account using an interpolation or extrapolation.
1171:
1172: hPijx is the probability to be observed in state i at age x+h
1173: conditional to the observed state i at age x. The delay 'h' can be
1174: split into an exact number (nh*stepm) of unobserved intermediate
1175: states. This elementary transition (by month, quarter,
1176: semester or year) is modelled as a multinomial logistic. The hPx
1177: matrix is simply the matrix product of nh*stepm elementary matrices
1178: and the contribution of each individual to the likelihood is simply
1179: hPijx.
1180:
1181: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1182: of the life expectancies. It also computes the period (stable) prevalence.
1183:
1184: Back prevalence and projections:
1.227 brouard 1185:
1186: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1187: double agemaxpar, double ftolpl, int *ncvyearp, double
1188: dateprev1,double dateprev2, int firstpass, int lastpass, int
1189: mobilavproj)
1190:
1191: Computes the back prevalence limit for any combination of
1192: covariate values k at any age between ageminpar and agemaxpar and
1193: returns it in **bprlim. In the loops,
1194:
1195: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1196: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1197:
1198: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1199: Computes for any combination of covariates k and any age between bage and fage
1200: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1201: oldm=oldms;savm=savms;
1.227 brouard 1202:
1.267 brouard 1203: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1204: Computes the transition matrix starting at age 'age' over
1205: 'nhstepm*hstepm*stepm' months (i.e. until
1206: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1207: nhstepm*hstepm matrices.
1208:
1209: Returns p3mat[i][j][h] after calling
1210: p3mat[i][j][h]=matprod2(newm,
1211: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1212: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1213: oldm);
1.226 brouard 1214:
1215: Important routines
1216:
1217: - func (or funcone), computes logit (pij) distinguishing
1218: o fixed variables (single or product dummies or quantitative);
1219: o varying variables by:
1220: (1) wave (single, product dummies, quantitative),
1221: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1222: % fixed dummy (treated) or quantitative (not done because time-consuming);
1223: % varying dummy (not done) or quantitative (not done);
1224: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1225: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1226: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1227: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1228: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1229:
1.226 brouard 1230:
1231:
1.324 brouard 1232: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1233: Institut national d'études démographiques, Paris.
1.126 brouard 1234: This software have been partly granted by Euro-REVES, a concerted action
1235: from the European Union.
1236: It is copyrighted identically to a GNU software product, ie programme and
1237: software can be distributed freely for non commercial use. Latest version
1238: can be accessed at http://euroreves.ined.fr/imach .
1239:
1240: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1241: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1242:
1243: **********************************************************************/
1244: /*
1245: main
1246: read parameterfile
1247: read datafile
1248: concatwav
1249: freqsummary
1250: if (mle >= 1)
1251: mlikeli
1252: print results files
1253: if mle==1
1254: computes hessian
1255: read end of parameter file: agemin, agemax, bage, fage, estepm
1256: begin-prev-date,...
1257: open gnuplot file
1258: open html file
1.145 brouard 1259: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1260: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1261: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1262: freexexit2 possible for memory heap.
1263:
1264: h Pij x | pij_nom ficrestpij
1265: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1266: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1267: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1268:
1269: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1270: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1271: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1272: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1273: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1274:
1.126 brouard 1275: forecasting if prevfcast==1 prevforecast call prevalence()
1276: health expectancies
1277: Variance-covariance of DFLE
1278: prevalence()
1279: movingaverage()
1280: varevsij()
1281: if popbased==1 varevsij(,popbased)
1282: total life expectancies
1283: Variance of period (stable) prevalence
1284: end
1285: */
1286:
1.187 brouard 1287: /* #define DEBUG */
1288: /* #define DEBUGBRENT */
1.203 brouard 1289: /* #define DEBUGLINMIN */
1290: /* #define DEBUGHESS */
1291: #define DEBUGHESSIJ
1.224 brouard 1292: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1293: #define POWELL /* Instead of NLOPT */
1.224 brouard 1294: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1295: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1296: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1297: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.357 brouard 1298: #define POWELLORIGINCONJUGATE /* Don't use conjugate but biggest decrease if valuable */
1.126 brouard 1299:
1300: #include <math.h>
1301: #include <stdio.h>
1302: #include <stdlib.h>
1303: #include <string.h>
1.226 brouard 1304: #include <ctype.h>
1.159 brouard 1305:
1306: #ifdef _WIN32
1307: #include <io.h>
1.172 brouard 1308: #include <windows.h>
1309: #include <tchar.h>
1.159 brouard 1310: #else
1.126 brouard 1311: #include <unistd.h>
1.159 brouard 1312: #endif
1.126 brouard 1313:
1314: #include <limits.h>
1315: #include <sys/types.h>
1.171 brouard 1316:
1317: #if defined(__GNUC__)
1318: #include <sys/utsname.h> /* Doesn't work on Windows */
1319: #endif
1320:
1.126 brouard 1321: #include <sys/stat.h>
1322: #include <errno.h>
1.159 brouard 1323: /* extern int errno; */
1.126 brouard 1324:
1.157 brouard 1325: /* #ifdef LINUX */
1326: /* #include <time.h> */
1327: /* #include "timeval.h" */
1328: /* #else */
1329: /* #include <sys/time.h> */
1330: /* #endif */
1331:
1.126 brouard 1332: #include <time.h>
1333:
1.136 brouard 1334: #ifdef GSL
1335: #include <gsl/gsl_errno.h>
1336: #include <gsl/gsl_multimin.h>
1337: #endif
1338:
1.167 brouard 1339:
1.162 brouard 1340: #ifdef NLOPT
1341: #include <nlopt.h>
1342: typedef struct {
1343: double (* function)(double [] );
1344: } myfunc_data ;
1345: #endif
1346:
1.126 brouard 1347: /* #include <libintl.h> */
1348: /* #define _(String) gettext (String) */
1349:
1.349 brouard 1350: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1351:
1352: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1353: #define GNUPLOTVERSION 5.1
1354: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1355: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1356: #define FILENAMELENGTH 256
1.126 brouard 1357:
1358: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1359: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1360:
1.349 brouard 1361: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1362: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1363:
1364: #define NINTERVMAX 8
1.144 brouard 1365: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1366: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1367: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1368: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1369: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1370: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1371: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1372: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1373: /* #define AGESUP 130 */
1.288 brouard 1374: /* #define AGESUP 150 */
1375: #define AGESUP 200
1.268 brouard 1376: #define AGEINF 0
1.218 brouard 1377: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1378: #define AGEBASE 40
1.194 brouard 1379: #define AGEOVERFLOW 1.e20
1.164 brouard 1380: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1381: #ifdef _WIN32
1382: #define DIRSEPARATOR '\\'
1383: #define CHARSEPARATOR "\\"
1384: #define ODIRSEPARATOR '/'
1385: #else
1.126 brouard 1386: #define DIRSEPARATOR '/'
1387: #define CHARSEPARATOR "/"
1388: #define ODIRSEPARATOR '\\'
1389: #endif
1390:
1.358 ! brouard 1391: /* $Id: imach.c,v 1.357 2023/06/14 14:55:52 brouard Exp $ */
1.126 brouard 1392: /* $State: Exp $ */
1.196 brouard 1393: #include "version.h"
1394: char version[]=__IMACH_VERSION__;
1.358 ! brouard 1395: char copyright[]="Testing conjugate 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";
! 1396: char fullversion[]="$Revision: 1.357 $ $Date: 2023/06/14 14:55:52 $";
1.126 brouard 1397: char strstart[80];
1398: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1399: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1400: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1401: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1402: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1403: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1404: 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 1405: 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 1406: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1407: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1408: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1409: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1410: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1411: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1412: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1413: 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 1414: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1415: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1416: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1417: 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 */
1418: 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 */
1419: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1420: 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 1421: int nsd=0; /**< Total number of single dummy variables (output) */
1422: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1423: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1424: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1425: int ntveff=0; /**< ntveff number of effective time varying variables */
1426: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1427: int cptcov=0; /* Working variable */
1.334 brouard 1428: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1429: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1430: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1431: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1432: int nlstate=2; /* Number of live states */
1433: int ndeath=1; /* Number of dead states */
1.130 brouard 1434: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1435: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1436: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1437: int popbased=0;
1438:
1439: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1440: int maxwav=0; /* Maxim number of waves */
1441: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1442: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1443: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1444: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1445: int mle=1, weightopt=0;
1.126 brouard 1446: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1447: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1448: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1449: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1450: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1451: int selected(int kvar); /* Is covariate kvar selected for printing results */
1452:
1.130 brouard 1453: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1454: double **matprod2(); /* test */
1.126 brouard 1455: double **oldm, **newm, **savm; /* Working pointers to matrices */
1456: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1457: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1458:
1.136 brouard 1459: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1460: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1461: FILE *ficlog, *ficrespow;
1.130 brouard 1462: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1463: double fretone; /* Only one call to likelihood */
1.130 brouard 1464: long ipmx=0; /* Number of contributions */
1.126 brouard 1465: double sw; /* Sum of weights */
1466: char filerespow[FILENAMELENGTH];
1467: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1468: FILE *ficresilk;
1469: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1470: FILE *ficresprobmorprev;
1471: FILE *fichtm, *fichtmcov; /* Html File */
1472: FILE *ficreseij;
1473: char filerese[FILENAMELENGTH];
1474: FILE *ficresstdeij;
1475: char fileresstde[FILENAMELENGTH];
1476: FILE *ficrescveij;
1477: char filerescve[FILENAMELENGTH];
1478: FILE *ficresvij;
1479: char fileresv[FILENAMELENGTH];
1.269 brouard 1480:
1.126 brouard 1481: char title[MAXLINE];
1.234 brouard 1482: char model[MAXLINE]; /**< The model line */
1.217 brouard 1483: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1484: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1485: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1486: char command[FILENAMELENGTH];
1487: int outcmd=0;
1488:
1.217 brouard 1489: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1490: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1491: char filelog[FILENAMELENGTH]; /* Log file */
1492: char filerest[FILENAMELENGTH];
1493: char fileregp[FILENAMELENGTH];
1494: char popfile[FILENAMELENGTH];
1495:
1496: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1497:
1.157 brouard 1498: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1499: /* struct timezone tzp; */
1500: /* extern int gettimeofday(); */
1501: struct tm tml, *gmtime(), *localtime();
1502:
1503: extern time_t time();
1504:
1505: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1506: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1507: time_t rlast_btime; /* raw time */
1.157 brouard 1508: struct tm tm;
1509:
1.126 brouard 1510: char strcurr[80], strfor[80];
1511:
1512: char *endptr;
1513: long lval;
1514: double dval;
1515:
1516: #define NR_END 1
1517: #define FREE_ARG char*
1518: #define FTOL 1.0e-10
1519:
1520: #define NRANSI
1.240 brouard 1521: #define ITMAX 200
1522: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1523:
1524: #define TOL 2.0e-4
1525:
1526: #define CGOLD 0.3819660
1527: #define ZEPS 1.0e-10
1528: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1529:
1530: #define GOLD 1.618034
1531: #define GLIMIT 100.0
1532: #define TINY 1.0e-20
1533:
1534: static double maxarg1,maxarg2;
1535: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1536: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1537:
1538: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1539: #define rint(a) floor(a+0.5)
1.166 brouard 1540: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1541: #define mytinydouble 1.0e-16
1.166 brouard 1542: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1543: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1544: /* static double dsqrarg; */
1545: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1546: static double sqrarg;
1547: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1548: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1549: int agegomp= AGEGOMP;
1550:
1551: int imx;
1552: int stepm=1;
1553: /* Stepm, step in month: minimum step interpolation*/
1554:
1555: int estepm;
1556: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1557:
1558: int m,nb;
1559: long *num;
1.197 brouard 1560: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1561: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1562: covariate for which somebody answered excluding
1563: undefined. Usually 2: 0 and 1. */
1564: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1565: covariate for which somebody answered including
1566: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1567: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1568: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1569: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1570: 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 1571: double *ageexmed,*agecens;
1572: double dateintmean=0;
1.296 brouard 1573: double anprojd, mprojd, jprojd; /* For eventual projections */
1574: double anprojf, mprojf, jprojf;
1.126 brouard 1575:
1.296 brouard 1576: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1577: double anbackf, mbackf, jbackf;
1578: double jintmean,mintmean,aintmean;
1.126 brouard 1579: double *weight;
1580: int **s; /* Status */
1.141 brouard 1581: double *agedc;
1.145 brouard 1582: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1583: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1584: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1585: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1586: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1587: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1588: double idx;
1589: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1590: /* Some documentation */
1591: /* Design original data
1592: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1593: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1594: * ntv=3 nqtv=1
1.330 brouard 1595: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1596: * For time varying covariate, quanti or dummies
1597: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1598: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1599: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1600: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1601: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1602: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1603: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1604: * k= 1 2 3 4 5 6 7 8 9 10 11
1605: */
1606: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1607: /* 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
1608: # States 1=Coresidence, 2 Living alone, 3 Institution
1609: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1610: */
1.349 brouard 1611: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1612: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1613: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1614: /* fixed or varying), 1 for age product, 2 for*/
1615: /* product without age, 3 for age and double product */
1616: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1617: /*(single or product without age), 2 dummy*/
1618: /* with age product, 3 quant with age product*/
1619: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1620: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1621: /*TnsdVar[Tvar] 1 2 3 */
1622: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1623: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1624: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1625: /* nsq 1 2 */ /* Counting single quantit tv */
1626: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1627: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1628: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1629: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1630: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1631: /* 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"*/
1632: /* 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 1633: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>} */
1.350 brouard 1634: /* 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}*/
1635: /* 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 1636: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1637: /* 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 1638: /* 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 1639: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1640: /* Type */
1641: /* V 1 2 3 4 5 */
1642: /* F F V V V */
1643: /* D Q D D Q */
1644: /* */
1645: int *TvarsD;
1.330 brouard 1646: int *TnsdVar;
1.234 brouard 1647: int *TvarsDind;
1648: int *TvarsQ;
1649: int *TvarsQind;
1650:
1.318 brouard 1651: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1652: int nresult=0;
1.258 brouard 1653: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1654: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1655: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1656: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1657: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1658: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1659: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1660: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1661: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1662: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1663: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1664:
1665: /* 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
1666: # States 1=Coresidence, 2 Living alone, 3 Institution
1667: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1668: */
1.234 brouard 1669: /* 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 1670: 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 */
1671: 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 */
1672: 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 */
1673: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1674: 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 */
1675: 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 1676: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1677: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1678: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1679: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1680: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1681: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1682: 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 */
1683: 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 1684: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1685: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1686: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1687: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1688: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1689: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1690: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1691: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1692: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1693: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1694: /* 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 1695: int *Tvarsel; /**< Selected covariates for output */
1696: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1697: 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 1698: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1699: 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 1700: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1701: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1702: int *Tage;
1.227 brouard 1703: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1704: 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 1705: 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*/
1706: 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 1707: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1708: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1709: int **Tvard;
1.330 brouard 1710: int **Tvardk;
1.227 brouard 1711: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1712: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1713: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1714: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1715: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1716: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1717: double *lsurv, *lpop, *tpop;
1718:
1.231 brouard 1719: #define FD 1; /* Fixed dummy covariate */
1720: #define FQ 2; /* Fixed quantitative covariate */
1721: #define FP 3; /* Fixed product covariate */
1722: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1723: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1724: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1725: #define VD 10; /* Varying dummy covariate */
1726: #define VQ 11; /* Varying quantitative covariate */
1727: #define VP 12; /* Varying product covariate */
1728: #define VPDD 13; /* Varying product dummy*dummy covariate */
1729: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1730: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1731: #define APFD 16; /* Age product * fixed dummy covariate */
1732: #define APFQ 17; /* Age product * fixed quantitative covariate */
1733: #define APVD 18; /* Age product * varying dummy covariate */
1734: #define APVQ 19; /* Age product * varying quantitative covariate */
1735:
1736: #define FTYPE 1; /* Fixed covariate */
1737: #define VTYPE 2; /* Varying covariate (loop in wave) */
1738: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1739:
1740: struct kmodel{
1741: int maintype; /* main type */
1742: int subtype; /* subtype */
1743: };
1744: struct kmodel modell[NCOVMAX];
1745:
1.143 brouard 1746: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1747: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1748:
1749: /**************** split *************************/
1750: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1751: {
1752: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1753: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1754: */
1755: char *ss; /* pointer */
1.186 brouard 1756: int l1=0, l2=0; /* length counters */
1.126 brouard 1757:
1758: l1 = strlen(path ); /* length of path */
1759: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1760: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1761: if ( ss == NULL ) { /* no directory, so determine current directory */
1762: strcpy( name, path ); /* we got the fullname name because no directory */
1763: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1764: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1765: /* get current working directory */
1766: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1767: #ifdef WIN32
1768: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1769: #else
1770: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1771: #endif
1.126 brouard 1772: return( GLOCK_ERROR_GETCWD );
1773: }
1774: /* got dirc from getcwd*/
1775: printf(" DIRC = %s \n",dirc);
1.205 brouard 1776: } else { /* strip directory from path */
1.126 brouard 1777: ss++; /* after this, the filename */
1778: l2 = strlen( ss ); /* length of filename */
1779: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1780: strcpy( name, ss ); /* save file name */
1781: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1782: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1783: printf(" DIRC2 = %s \n",dirc);
1784: }
1785: /* We add a separator at the end of dirc if not exists */
1786: l1 = strlen( dirc ); /* length of directory */
1787: if( dirc[l1-1] != DIRSEPARATOR ){
1788: dirc[l1] = DIRSEPARATOR;
1789: dirc[l1+1] = 0;
1790: printf(" DIRC3 = %s \n",dirc);
1791: }
1792: ss = strrchr( name, '.' ); /* find last / */
1793: if (ss >0){
1794: ss++;
1795: strcpy(ext,ss); /* save extension */
1796: l1= strlen( name);
1797: l2= strlen(ss)+1;
1798: strncpy( finame, name, l1-l2);
1799: finame[l1-l2]= 0;
1800: }
1801:
1802: return( 0 ); /* we're done */
1803: }
1804:
1805:
1806: /******************************************/
1807:
1808: void replace_back_to_slash(char *s, char*t)
1809: {
1810: int i;
1811: int lg=0;
1812: i=0;
1813: lg=strlen(t);
1814: for(i=0; i<= lg; i++) {
1815: (s[i] = t[i]);
1816: if (t[i]== '\\') s[i]='/';
1817: }
1818: }
1819:
1.132 brouard 1820: char *trimbb(char *out, char *in)
1.137 brouard 1821: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1822: char *s;
1823: s=out;
1824: while (*in != '\0'){
1.137 brouard 1825: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1826: in++;
1827: }
1828: *out++ = *in++;
1829: }
1830: *out='\0';
1831: return s;
1832: }
1833:
1.351 brouard 1834: char *trimbtab(char *out, char *in)
1835: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1836: char *s;
1837: s=out;
1838: while (*in != '\0'){
1839: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1840: in++;
1841: }
1842: *out++ = *in++;
1843: }
1844: *out='\0';
1845: return s;
1846: }
1847:
1.187 brouard 1848: /* char *substrchaine(char *out, char *in, char *chain) */
1849: /* { */
1850: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1851: /* char *s, *t; */
1852: /* t=in;s=out; */
1853: /* while ((*in != *chain) && (*in != '\0')){ */
1854: /* *out++ = *in++; */
1855: /* } */
1856:
1857: /* /\* *in matches *chain *\/ */
1858: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1859: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1860: /* } */
1861: /* in--; chain--; */
1862: /* while ( (*in != '\0')){ */
1863: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1864: /* *out++ = *in++; */
1865: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1866: /* } */
1867: /* *out='\0'; */
1868: /* out=s; */
1869: /* return out; */
1870: /* } */
1871: char *substrchaine(char *out, char *in, char *chain)
1872: {
1873: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1874: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1875:
1876: char *strloc;
1877:
1.349 brouard 1878: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1879: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1880: 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 1881: if(strloc != NULL){
1.349 brouard 1882: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1883: 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)*/
1884: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1885: }
1.349 brouard 1886: 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 1887: return out;
1888: }
1889:
1890:
1.145 brouard 1891: char *cutl(char *blocc, char *alocc, char *in, char occ)
1892: {
1.187 brouard 1893: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1894: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1895: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1896: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1897: */
1.160 brouard 1898: char *s, *t;
1.145 brouard 1899: t=in;s=in;
1900: while ((*in != occ) && (*in != '\0')){
1901: *alocc++ = *in++;
1902: }
1903: if( *in == occ){
1904: *(alocc)='\0';
1905: s=++in;
1906: }
1907:
1908: if (s == t) {/* occ not found */
1909: *(alocc-(in-s))='\0';
1910: in=s;
1911: }
1912: while ( *in != '\0'){
1913: *blocc++ = *in++;
1914: }
1915:
1916: *blocc='\0';
1917: return t;
1918: }
1.137 brouard 1919: char *cutv(char *blocc, char *alocc, char *in, char occ)
1920: {
1.187 brouard 1921: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1922: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1923: gives blocc="abcdef2ghi" and alocc="j".
1924: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1925: */
1926: char *s, *t;
1927: t=in;s=in;
1928: while (*in != '\0'){
1929: while( *in == occ){
1930: *blocc++ = *in++;
1931: s=in;
1932: }
1933: *blocc++ = *in++;
1934: }
1935: if (s == t) /* occ not found */
1936: *(blocc-(in-s))='\0';
1937: else
1938: *(blocc-(in-s)-1)='\0';
1939: in=s;
1940: while ( *in != '\0'){
1941: *alocc++ = *in++;
1942: }
1943:
1944: *alocc='\0';
1945: return s;
1946: }
1947:
1.126 brouard 1948: int nbocc(char *s, char occ)
1949: {
1950: int i,j=0;
1951: int lg=20;
1952: i=0;
1953: lg=strlen(s);
1954: for(i=0; i<= lg; i++) {
1.234 brouard 1955: if (s[i] == occ ) j++;
1.126 brouard 1956: }
1957: return j;
1958: }
1959:
1.349 brouard 1960: int nboccstr(char *textin, char *chain)
1961: {
1962: /* Counts the number of occurence of "chain" in string textin */
1963: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1964: char *strloc;
1965:
1966: int i,j=0;
1967:
1968: i=0;
1969:
1970: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1971: for(;;) {
1972: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1973: if(strloc != NULL){
1974: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1975: j++;
1976: }else
1977: break;
1978: }
1979: return j;
1980:
1981: }
1.137 brouard 1982: /* void cutv(char *u,char *v, char*t, char occ) */
1983: /* { */
1984: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1985: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1986: /* gives u="abcdef2ghi" and v="j" *\/ */
1987: /* int i,lg,j,p=0; */
1988: /* i=0; */
1989: /* lg=strlen(t); */
1990: /* for(j=0; j<=lg-1; j++) { */
1991: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1992: /* } */
1.126 brouard 1993:
1.137 brouard 1994: /* for(j=0; j<p; j++) { */
1995: /* (u[j] = t[j]); */
1996: /* } */
1997: /* u[p]='\0'; */
1.126 brouard 1998:
1.137 brouard 1999: /* for(j=0; j<= lg; j++) { */
2000: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
2001: /* } */
2002: /* } */
1.126 brouard 2003:
1.160 brouard 2004: #ifdef _WIN32
2005: char * strsep(char **pp, const char *delim)
2006: {
2007: char *p, *q;
2008:
2009: if ((p = *pp) == NULL)
2010: return 0;
2011: if ((q = strpbrk (p, delim)) != NULL)
2012: {
2013: *pp = q + 1;
2014: *q = '\0';
2015: }
2016: else
2017: *pp = 0;
2018: return p;
2019: }
2020: #endif
2021:
1.126 brouard 2022: /********************** nrerror ********************/
2023:
2024: void nrerror(char error_text[])
2025: {
2026: fprintf(stderr,"ERREUR ...\n");
2027: fprintf(stderr,"%s\n",error_text);
2028: exit(EXIT_FAILURE);
2029: }
2030: /*********************** vector *******************/
2031: double *vector(int nl, int nh)
2032: {
2033: double *v;
2034: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2035: if (!v) nrerror("allocation failure in vector");
2036: return v-nl+NR_END;
2037: }
2038:
2039: /************************ free vector ******************/
2040: void free_vector(double*v, int nl, int nh)
2041: {
2042: free((FREE_ARG)(v+nl-NR_END));
2043: }
2044:
2045: /************************ivector *******************************/
2046: int *ivector(long nl,long nh)
2047: {
2048: int *v;
2049: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2050: if (!v) nrerror("allocation failure in ivector");
2051: return v-nl+NR_END;
2052: }
2053:
2054: /******************free ivector **************************/
2055: void free_ivector(int *v, long nl, long nh)
2056: {
2057: free((FREE_ARG)(v+nl-NR_END));
2058: }
2059:
2060: /************************lvector *******************************/
2061: long *lvector(long nl,long nh)
2062: {
2063: long *v;
2064: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2065: if (!v) nrerror("allocation failure in ivector");
2066: return v-nl+NR_END;
2067: }
2068:
2069: /******************free lvector **************************/
2070: void free_lvector(long *v, long nl, long nh)
2071: {
2072: free((FREE_ARG)(v+nl-NR_END));
2073: }
2074:
2075: /******************* imatrix *******************************/
2076: int **imatrix(long nrl, long nrh, long ncl, long nch)
2077: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2078: {
2079: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2080: int **m;
2081:
2082: /* allocate pointers to rows */
2083: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2084: if (!m) nrerror("allocation failure 1 in matrix()");
2085: m += NR_END;
2086: m -= nrl;
2087:
2088:
2089: /* allocate rows and set pointers to them */
2090: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2091: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2092: m[nrl] += NR_END;
2093: m[nrl] -= ncl;
2094:
2095: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2096:
2097: /* return pointer to array of pointers to rows */
2098: return m;
2099: }
2100:
2101: /****************** free_imatrix *************************/
2102: void free_imatrix(m,nrl,nrh,ncl,nch)
2103: int **m;
2104: long nch,ncl,nrh,nrl;
2105: /* free an int matrix allocated by imatrix() */
2106: {
2107: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2108: free((FREE_ARG) (m+nrl-NR_END));
2109: }
2110:
2111: /******************* matrix *******************************/
2112: double **matrix(long nrl, long nrh, long ncl, long nch)
2113: {
2114: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2115: double **m;
2116:
2117: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2118: if (!m) nrerror("allocation failure 1 in matrix()");
2119: m += NR_END;
2120: m -= nrl;
2121:
2122: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2123: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2124: m[nrl] += NR_END;
2125: m[nrl] -= ncl;
2126:
2127: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2128: return m;
1.145 brouard 2129: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2130: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2131: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2132: */
2133: }
2134:
2135: /*************************free matrix ************************/
2136: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2137: {
2138: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2139: free((FREE_ARG)(m+nrl-NR_END));
2140: }
2141:
2142: /******************* ma3x *******************************/
2143: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2144: {
2145: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2146: double ***m;
2147:
2148: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2149: if (!m) nrerror("allocation failure 1 in matrix()");
2150: m += NR_END;
2151: m -= nrl;
2152:
2153: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2154: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2155: m[nrl] += NR_END;
2156: m[nrl] -= ncl;
2157:
2158: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2159:
2160: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2161: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2162: m[nrl][ncl] += NR_END;
2163: m[nrl][ncl] -= nll;
2164: for (j=ncl+1; j<=nch; j++)
2165: m[nrl][j]=m[nrl][j-1]+nlay;
2166:
2167: for (i=nrl+1; i<=nrh; i++) {
2168: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2169: for (j=ncl+1; j<=nch; j++)
2170: m[i][j]=m[i][j-1]+nlay;
2171: }
2172: return m;
2173: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2174: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2175: */
2176: }
2177:
2178: /*************************free ma3x ************************/
2179: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2180: {
2181: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2182: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2183: free((FREE_ARG)(m+nrl-NR_END));
2184: }
2185:
2186: /*************** function subdirf ***********/
2187: char *subdirf(char fileres[])
2188: {
2189: /* Caution optionfilefiname is hidden */
2190: strcpy(tmpout,optionfilefiname);
2191: strcat(tmpout,"/"); /* Add to the right */
2192: strcat(tmpout,fileres);
2193: return tmpout;
2194: }
2195:
2196: /*************** function subdirf2 ***********/
2197: char *subdirf2(char fileres[], char *preop)
2198: {
1.314 brouard 2199: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2200: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2201: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2202: /* Caution optionfilefiname is hidden */
2203: strcpy(tmpout,optionfilefiname);
2204: strcat(tmpout,"/");
2205: strcat(tmpout,preop);
2206: strcat(tmpout,fileres);
2207: return tmpout;
2208: }
2209:
2210: /*************** function subdirf3 ***********/
2211: char *subdirf3(char fileres[], char *preop, char *preop2)
2212: {
2213:
2214: /* Caution optionfilefiname is hidden */
2215: strcpy(tmpout,optionfilefiname);
2216: strcat(tmpout,"/");
2217: strcat(tmpout,preop);
2218: strcat(tmpout,preop2);
2219: strcat(tmpout,fileres);
2220: return tmpout;
2221: }
1.213 brouard 2222:
2223: /*************** function subdirfext ***********/
2224: char *subdirfext(char fileres[], char *preop, char *postop)
2225: {
2226:
2227: strcpy(tmpout,preop);
2228: strcat(tmpout,fileres);
2229: strcat(tmpout,postop);
2230: return tmpout;
2231: }
1.126 brouard 2232:
1.213 brouard 2233: /*************** function subdirfext3 ***********/
2234: char *subdirfext3(char fileres[], char *preop, char *postop)
2235: {
2236:
2237: /* Caution optionfilefiname is hidden */
2238: strcpy(tmpout,optionfilefiname);
2239: strcat(tmpout,"/");
2240: strcat(tmpout,preop);
2241: strcat(tmpout,fileres);
2242: strcat(tmpout,postop);
2243: return tmpout;
2244: }
2245:
1.162 brouard 2246: char *asc_diff_time(long time_sec, char ascdiff[])
2247: {
2248: long sec_left, days, hours, minutes;
2249: days = (time_sec) / (60*60*24);
2250: sec_left = (time_sec) % (60*60*24);
2251: hours = (sec_left) / (60*60) ;
2252: sec_left = (sec_left) %(60*60);
2253: minutes = (sec_left) /60;
2254: sec_left = (sec_left) % (60);
2255: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2256: return ascdiff;
2257: }
2258:
1.126 brouard 2259: /***************** f1dim *************************/
2260: extern int ncom;
2261: extern double *pcom,*xicom;
2262: extern double (*nrfunc)(double []);
2263:
2264: double f1dim(double x)
2265: {
2266: int j;
2267: double f;
2268: double *xt;
2269:
2270: xt=vector(1,ncom);
2271: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2272: f=(*nrfunc)(xt);
2273: free_vector(xt,1,ncom);
2274: return f;
2275: }
2276:
2277: /*****************brent *************************/
2278: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2279: {
2280: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2281: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2282: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2283: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2284: * returned function value.
2285: */
1.126 brouard 2286: int iter;
2287: double a,b,d,etemp;
1.159 brouard 2288: double fu=0,fv,fw,fx;
1.164 brouard 2289: double ftemp=0.;
1.126 brouard 2290: double p,q,r,tol1,tol2,u,v,w,x,xm;
2291: double e=0.0;
2292:
2293: a=(ax < cx ? ax : cx);
2294: b=(ax > cx ? ax : cx);
2295: x=w=v=bx;
2296: fw=fv=fx=(*f)(x);
2297: for (iter=1;iter<=ITMAX;iter++) {
2298: xm=0.5*(a+b);
2299: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2300: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2301: printf(".");fflush(stdout);
2302: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2303: #ifdef DEBUGBRENT
1.126 brouard 2304: 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);
2305: 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);
2306: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2307: #endif
2308: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2309: *xmin=x;
2310: return fx;
2311: }
2312: ftemp=fu;
2313: if (fabs(e) > tol1) {
2314: r=(x-w)*(fx-fv);
2315: q=(x-v)*(fx-fw);
2316: p=(x-v)*q-(x-w)*r;
2317: q=2.0*(q-r);
2318: if (q > 0.0) p = -p;
2319: q=fabs(q);
2320: etemp=e;
2321: e=d;
2322: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2323: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2324: else {
1.224 brouard 2325: d=p/q;
2326: u=x+d;
2327: if (u-a < tol2 || b-u < tol2)
2328: d=SIGN(tol1,xm-x);
1.126 brouard 2329: }
2330: } else {
2331: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2332: }
2333: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2334: fu=(*f)(u);
2335: if (fu <= fx) {
2336: if (u >= x) a=x; else b=x;
2337: SHFT(v,w,x,u)
1.183 brouard 2338: SHFT(fv,fw,fx,fu)
2339: } else {
2340: if (u < x) a=u; else b=u;
2341: if (fu <= fw || w == x) {
1.224 brouard 2342: v=w;
2343: w=u;
2344: fv=fw;
2345: fw=fu;
1.183 brouard 2346: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2347: v=u;
2348: fv=fu;
1.183 brouard 2349: }
2350: }
1.126 brouard 2351: }
2352: nrerror("Too many iterations in brent");
2353: *xmin=x;
2354: return fx;
2355: }
2356:
2357: /****************** mnbrak ***********************/
2358:
2359: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2360: double (*func)(double))
1.183 brouard 2361: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2362: the downhill direction (defined by the function as evaluated at the initial points) and returns
2363: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2364: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2365: */
1.126 brouard 2366: double ulim,u,r,q, dum;
2367: double fu;
1.187 brouard 2368:
2369: double scale=10.;
2370: int iterscale=0;
2371:
2372: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2373: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2374:
2375:
2376: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2377: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2378: /* *bx = *ax - (*ax - *bx)/scale; */
2379: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2380: /* } */
2381:
1.126 brouard 2382: if (*fb > *fa) {
2383: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2384: SHFT(dum,*fb,*fa,dum)
2385: }
1.126 brouard 2386: *cx=(*bx)+GOLD*(*bx-*ax);
2387: *fc=(*func)(*cx);
1.183 brouard 2388: #ifdef DEBUG
1.224 brouard 2389: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2390: 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 2391: #endif
1.224 brouard 2392: 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 2393: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2394: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2395: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2396: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2397: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2398: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2399: fu=(*func)(u);
1.163 brouard 2400: #ifdef DEBUG
2401: /* f(x)=A(x-u)**2+f(u) */
2402: double A, fparabu;
2403: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2404: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2405: 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);
2406: 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 2407: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2408: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2409: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2410: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2411: #endif
1.184 brouard 2412: #ifdef MNBRAKORIGINAL
1.183 brouard 2413: #else
1.191 brouard 2414: /* if (fu > *fc) { */
2415: /* #ifdef DEBUG */
2416: /* printf("mnbrak4 fu > fc \n"); */
2417: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2418: /* #endif */
2419: /* /\* 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 *\\/ *\/ */
2420: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2421: /* dum=u; /\* Shifting c and u *\/ */
2422: /* u = *cx; */
2423: /* *cx = dum; */
2424: /* dum = fu; */
2425: /* fu = *fc; */
2426: /* *fc =dum; */
2427: /* } else { /\* end *\/ */
2428: /* #ifdef DEBUG */
2429: /* printf("mnbrak3 fu < fc \n"); */
2430: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2431: /* #endif */
2432: /* dum=u; /\* Shifting c and u *\/ */
2433: /* u = *cx; */
2434: /* *cx = dum; */
2435: /* dum = fu; */
2436: /* fu = *fc; */
2437: /* *fc =dum; */
2438: /* } */
1.224 brouard 2439: #ifdef DEBUGMNBRAK
2440: double A, fparabu;
2441: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2442: fparabu= *fa - A*(*ax-u)*(*ax-u);
2443: 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);
2444: 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 2445: #endif
1.191 brouard 2446: dum=u; /* Shifting c and u */
2447: u = *cx;
2448: *cx = dum;
2449: dum = fu;
2450: fu = *fc;
2451: *fc =dum;
1.183 brouard 2452: #endif
1.162 brouard 2453: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2454: #ifdef DEBUG
1.224 brouard 2455: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2456: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2457: #endif
1.126 brouard 2458: fu=(*func)(u);
2459: if (fu < *fc) {
1.183 brouard 2460: #ifdef DEBUG
1.224 brouard 2461: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2462: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2463: #endif
2464: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2465: SHFT(*fb,*fc,fu,(*func)(u))
2466: #ifdef DEBUG
2467: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2468: #endif
2469: }
1.162 brouard 2470: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2471: #ifdef DEBUG
1.224 brouard 2472: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2473: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2474: #endif
1.126 brouard 2475: u=ulim;
2476: fu=(*func)(u);
1.183 brouard 2477: } else { /* u could be left to b (if r > q parabola has a maximum) */
2478: #ifdef DEBUG
1.224 brouard 2479: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2480: 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 2481: #endif
1.126 brouard 2482: u=(*cx)+GOLD*(*cx-*bx);
2483: fu=(*func)(u);
1.224 brouard 2484: #ifdef DEBUG
2485: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2486: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2487: #endif
1.183 brouard 2488: } /* end tests */
1.126 brouard 2489: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2490: SHFT(*fa,*fb,*fc,fu)
2491: #ifdef DEBUG
1.224 brouard 2492: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2493: 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 2494: #endif
2495: } /* 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 2496: }
2497:
2498: /*************** linmin ************************/
1.162 brouard 2499: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2500: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2501: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2502: the value of func at the returned location p . This is actually all accomplished by calling the
2503: routines mnbrak and brent .*/
1.126 brouard 2504: int ncom;
2505: double *pcom,*xicom;
2506: double (*nrfunc)(double []);
2507:
1.224 brouard 2508: #ifdef LINMINORIGINAL
1.126 brouard 2509: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2510: #else
2511: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2512: #endif
1.126 brouard 2513: {
2514: double brent(double ax, double bx, double cx,
2515: double (*f)(double), double tol, double *xmin);
2516: double f1dim(double x);
2517: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2518: double *fc, double (*func)(double));
2519: int j;
2520: double xx,xmin,bx,ax;
2521: double fx,fb,fa;
1.187 brouard 2522:
1.203 brouard 2523: #ifdef LINMINORIGINAL
2524: #else
2525: double scale=10., axs, xxs; /* Scale added for infinity */
2526: #endif
2527:
1.126 brouard 2528: ncom=n;
2529: pcom=vector(1,n);
2530: xicom=vector(1,n);
2531: nrfunc=func;
2532: for (j=1;j<=n;j++) {
2533: pcom[j]=p[j];
1.202 brouard 2534: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2535: }
1.187 brouard 2536:
1.203 brouard 2537: #ifdef LINMINORIGINAL
2538: xx=1.;
2539: #else
2540: axs=0.0;
2541: xxs=1.;
2542: do{
2543: xx= xxs;
2544: #endif
1.187 brouard 2545: ax=0.;
2546: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2547: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2548: /* 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)) */
2549: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2550: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2551: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2552: /* 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 2553: #ifdef LINMINORIGINAL
2554: #else
2555: if (fx != fx){
1.224 brouard 2556: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2557: printf("|");
2558: fprintf(ficlog,"|");
1.203 brouard 2559: #ifdef DEBUGLINMIN
1.224 brouard 2560: 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 2561: #endif
2562: }
1.224 brouard 2563: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2564: #endif
2565:
1.191 brouard 2566: #ifdef DEBUGLINMIN
2567: 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 2568: 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 2569: #endif
1.224 brouard 2570: #ifdef LINMINORIGINAL
2571: #else
1.317 brouard 2572: if(fb == fx){ /* Flat function in the direction */
2573: xmin=xx;
1.224 brouard 2574: *flat=1;
1.317 brouard 2575: }else{
1.224 brouard 2576: *flat=0;
2577: #endif
2578: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2579: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2580: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2581: /* fmin = f(p[j] + xmin * xi[j]) */
2582: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2583: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2584: #ifdef DEBUG
1.224 brouard 2585: 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);
2586: 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);
2587: #endif
2588: #ifdef LINMINORIGINAL
2589: #else
2590: }
1.126 brouard 2591: #endif
1.191 brouard 2592: #ifdef DEBUGLINMIN
2593: printf("linmin end ");
1.202 brouard 2594: fprintf(ficlog,"linmin end ");
1.191 brouard 2595: #endif
1.126 brouard 2596: for (j=1;j<=n;j++) {
1.203 brouard 2597: #ifdef LINMINORIGINAL
2598: xi[j] *= xmin;
2599: #else
2600: #ifdef DEBUGLINMIN
2601: if(xxs <1.0)
2602: printf(" before xi[%d]=%12.8f", j,xi[j]);
2603: #endif
2604: 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) */
2605: #ifdef DEBUGLINMIN
2606: if(xxs <1.0)
2607: 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 );
2608: #endif
2609: #endif
1.187 brouard 2610: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2611: }
1.191 brouard 2612: #ifdef DEBUGLINMIN
1.203 brouard 2613: printf("\n");
1.191 brouard 2614: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2615: 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 2616: for (j=1;j<=n;j++) {
1.202 brouard 2617: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2618: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2619: if(j % ncovmodel == 0){
1.191 brouard 2620: printf("\n");
1.202 brouard 2621: fprintf(ficlog,"\n");
2622: }
1.191 brouard 2623: }
1.203 brouard 2624: #else
1.191 brouard 2625: #endif
1.126 brouard 2626: free_vector(xicom,1,n);
2627: free_vector(pcom,1,n);
2628: }
2629:
2630:
2631: /*************** powell ************************/
1.162 brouard 2632: /*
1.317 brouard 2633: Minimization of a function func of n variables. Input consists in an initial starting point
2634: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2635: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2636: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2637: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2638: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2639: */
1.224 brouard 2640: #ifdef LINMINORIGINAL
2641: #else
2642: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2643: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2644: #endif
1.126 brouard 2645: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2646: double (*func)(double []))
2647: {
1.224 brouard 2648: #ifdef LINMINORIGINAL
2649: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2650: double (*func)(double []));
1.224 brouard 2651: #else
1.241 brouard 2652: void linmin(double p[], double xi[], int n, double *fret,
2653: double (*func)(double []),int *flat);
1.224 brouard 2654: #endif
1.239 brouard 2655: int i,ibig,j,jk,k;
1.126 brouard 2656: double del,t,*pt,*ptt,*xit;
1.181 brouard 2657: double directest;
1.126 brouard 2658: double fp,fptt;
2659: double *xits;
2660: int niterf, itmp;
1.349 brouard 2661: int Bigter=0, nBigterf=1;
2662:
1.126 brouard 2663: pt=vector(1,n);
2664: ptt=vector(1,n);
2665: xit=vector(1,n);
2666: xits=vector(1,n);
2667: *fret=(*func)(p);
2668: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2669: rcurr_time = time(NULL);
2670: fp=(*fret); /* Initialisation */
1.126 brouard 2671: for (*iter=1;;++(*iter)) {
2672: ibig=0;
2673: del=0.0;
1.157 brouard 2674: rlast_time=rcurr_time;
1.349 brouard 2675: rlast_btime=rcurr_time;
1.157 brouard 2676: /* (void) gettimeofday(&curr_time,&tzp); */
2677: rcurr_time = time(NULL);
2678: curr_time = *localtime(&rcurr_time);
1.337 brouard 2679: /* 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); */
2680: /* 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 2681: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
2682: 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);
2683: 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);
2684: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2685: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2686: for (i=1;i<=n;i++) {
1.126 brouard 2687: fprintf(ficrespow," %.12lf", p[i]);
2688: }
1.239 brouard 2689: fprintf(ficrespow,"\n");fflush(ficrespow);
2690: printf("\n#model= 1 + age ");
2691: fprintf(ficlog,"\n#model= 1 + age ");
2692: if(nagesqr==1){
1.241 brouard 2693: printf(" + age*age ");
2694: fprintf(ficlog," + age*age ");
1.239 brouard 2695: }
2696: for(j=1;j <=ncovmodel-2;j++){
2697: if(Typevar[j]==0) {
2698: printf(" + V%d ",Tvar[j]);
2699: fprintf(ficlog," + V%d ",Tvar[j]);
2700: }else if(Typevar[j]==1) {
2701: printf(" + V%d*age ",Tvar[j]);
2702: fprintf(ficlog," + V%d*age ",Tvar[j]);
2703: }else if(Typevar[j]==2) {
2704: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2705: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 2706: }else if(Typevar[j]==3) {
2707: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2708: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2709: }
2710: }
1.126 brouard 2711: printf("\n");
1.239 brouard 2712: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2713: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2714: fprintf(ficlog,"\n");
1.239 brouard 2715: for(i=1,jk=1; i <=nlstate; i++){
2716: for(k=1; k <=(nlstate+ndeath); k++){
2717: if (k != i) {
2718: printf("%d%d ",i,k);
2719: fprintf(ficlog,"%d%d ",i,k);
2720: for(j=1; j <=ncovmodel; j++){
2721: printf("%12.7f ",p[jk]);
2722: fprintf(ficlog,"%12.7f ",p[jk]);
2723: jk++;
2724: }
2725: printf("\n");
2726: fprintf(ficlog,"\n");
2727: }
2728: }
2729: }
1.241 brouard 2730: if(*iter <=3 && *iter >1){
1.157 brouard 2731: tml = *localtime(&rcurr_time);
2732: strcpy(strcurr,asctime(&tml));
2733: rforecast_time=rcurr_time;
1.126 brouard 2734: itmp = strlen(strcurr);
2735: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2736: strcurr[itmp-1]='\0';
1.162 brouard 2737: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2738: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 2739: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
2740: niterf=nBigterf*ncovmodel;
2741: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2742: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2743: forecast_time = *localtime(&rforecast_time);
2744: strcpy(strfor,asctime(&forecast_time));
2745: itmp = strlen(strfor);
2746: if(strfor[itmp-1]=='\n')
2747: strfor[itmp-1]='\0';
1.349 brouard 2748: 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);
2749: 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 2750: }
2751: }
1.187 brouard 2752: for (i=1;i<=n;i++) { /* For each direction i */
2753: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2754: fptt=(*fret);
2755: #ifdef DEBUG
1.203 brouard 2756: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2757: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2758: #endif
1.203 brouard 2759: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2760: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2761: #ifdef LINMINORIGINAL
1.357 brouard 2762: linmin(p,xit,n,fret,func); /* New point i minimizing in direction i has coordinates p[j].*/
2763: /* xit[j] gives the n coordinates of direction i as input.*/
2764: /* *fret gives the maximum value on direction xit */
1.224 brouard 2765: #else
2766: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2767: flatdir[i]=flat; /* Function is vanishing in that direction i */
2768: #endif
2769: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2770: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2771: /* because that direction will be replaced unless the gain del is small */
2772: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2773: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2774: /* with the new direction. */
2775: del=fabs(fptt-(*fret));
2776: ibig=i;
1.126 brouard 2777: }
2778: #ifdef DEBUG
2779: printf("%d %.12e",i,(*fret));
2780: fprintf(ficlog,"%d %.12e",i,(*fret));
2781: for (j=1;j<=n;j++) {
1.224 brouard 2782: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2783: printf(" x(%d)=%.12e",j,xit[j]);
2784: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2785: }
2786: for(j=1;j<=n;j++) {
1.225 brouard 2787: printf(" p(%d)=%.12e",j,p[j]);
2788: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2789: }
2790: printf("\n");
2791: fprintf(ficlog,"\n");
2792: #endif
1.187 brouard 2793: } /* end loop on each direction i */
1.357 brouard 2794: /* Convergence test will use last linmin estimation (fret) and compare to former iteration (fp) */
1.188 brouard 2795: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.319 brouard 2796: for(j=1;j<=n;j++) {
2797: if(flatdir[j] >0){
2798: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2799: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2800: }
1.319 brouard 2801: /* printf("\n"); */
2802: /* fprintf(ficlog,"\n"); */
2803: }
1.243 brouard 2804: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2805: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2806: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2807: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2808: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2809: /* decreased of more than 3.84 */
2810: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2811: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2812: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2813:
1.188 brouard 2814: /* Starting the program with initial values given by a former maximization will simply change */
2815: /* the scales of the directions and the directions, because the are reset to canonical directions */
2816: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2817: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2818: #ifdef DEBUG
2819: int k[2],l;
2820: k[0]=1;
2821: k[1]=-1;
2822: printf("Max: %.12e",(*func)(p));
2823: fprintf(ficlog,"Max: %.12e",(*func)(p));
2824: for (j=1;j<=n;j++) {
2825: printf(" %.12e",p[j]);
2826: fprintf(ficlog," %.12e",p[j]);
2827: }
2828: printf("\n");
2829: fprintf(ficlog,"\n");
2830: for(l=0;l<=1;l++) {
2831: for (j=1;j<=n;j++) {
2832: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2833: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2834: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2835: }
2836: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2837: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2838: }
2839: #endif
2840:
2841: free_vector(xit,1,n);
2842: free_vector(xits,1,n);
2843: free_vector(ptt,1,n);
2844: free_vector(pt,1,n);
2845: return;
1.192 brouard 2846: } /* enough precision */
1.240 brouard 2847: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2848: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2849: ptt[j]=2.0*p[j]-pt[j];
2850: xit[j]=p[j]-pt[j];
2851: pt[j]=p[j];
2852: }
1.181 brouard 2853: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2854: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2855: if (*iter <=4) {
1.225 brouard 2856: #else
2857: #endif
1.224 brouard 2858: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2859: #else
1.161 brouard 2860: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2861: #endif
1.162 brouard 2862: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2863: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2864: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2865: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2866: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2867: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2868: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2869: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2870: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2871: /* Even if f3 <f1, directest can be negative and t >0 */
2872: /* mu² and del² are equal when f3=f1 */
2873: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2874: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2875: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2876: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2877: #ifdef NRCORIGINAL
2878: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2879: #else
2880: 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 2881: t= t- del*SQR(fp-fptt);
1.183 brouard 2882: #endif
1.202 brouard 2883: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2884: #ifdef DEBUG
1.181 brouard 2885: 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);
2886: 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 2887: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2888: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2889: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2890: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2891: 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);
2892: 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);
2893: #endif
1.183 brouard 2894: #ifdef POWELLORIGINAL
2895: if (t < 0.0) { /* Then we use it for new direction */
2896: #else
1.182 brouard 2897: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2898: 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 2899: 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 2900: 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 2901: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2902: }
1.181 brouard 2903: if (directest < 0.0) { /* Then we use it for new direction */
2904: #endif
1.191 brouard 2905: #ifdef DEBUGLINMIN
1.234 brouard 2906: printf("Before linmin in direction P%d-P0\n",n);
2907: for (j=1;j<=n;j++) {
2908: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2909: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2910: if(j % ncovmodel == 0){
2911: printf("\n");
2912: fprintf(ficlog,"\n");
2913: }
2914: }
1.224 brouard 2915: #endif
2916: #ifdef LINMINORIGINAL
1.234 brouard 2917: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2918: #else
1.234 brouard 2919: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2920: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2921: #endif
1.234 brouard 2922:
1.191 brouard 2923: #ifdef DEBUGLINMIN
1.234 brouard 2924: for (j=1;j<=n;j++) {
2925: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2926: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2927: if(j % ncovmodel == 0){
2928: printf("\n");
2929: fprintf(ficlog,"\n");
2930: }
2931: }
1.224 brouard 2932: #endif
1.357 brouard 2933: #ifdef POWELLORIGINCONJUGATE
1.234 brouard 2934: for (j=1;j<=n;j++) {
2935: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2936: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2937: }
1.357 brouard 2938: #else
2939: for (j=1;j<=n-1;j++) {
2940: xi[j][1]=xi[j][j+1]; /* Standard method of conjugate directions */
2941: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2942: }
2943: #endif
1.224 brouard 2944: #ifdef LINMINORIGINAL
2945: #else
1.234 brouard 2946: for (j=1, flatd=0;j<=n;j++) {
2947: if(flatdir[j]>0)
2948: flatd++;
2949: }
2950: if(flatd >0){
1.255 brouard 2951: printf("%d flat directions: ",flatd);
2952: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2953: for (j=1;j<=n;j++) {
2954: if(flatdir[j]>0){
2955: printf("%d ",j);
2956: fprintf(ficlog,"%d ",j);
2957: }
2958: }
2959: printf("\n");
2960: fprintf(ficlog,"\n");
1.319 brouard 2961: #ifdef FLATSUP
2962: free_vector(xit,1,n);
2963: free_vector(xits,1,n);
2964: free_vector(ptt,1,n);
2965: free_vector(pt,1,n);
2966: return;
2967: #endif
1.234 brouard 2968: }
1.191 brouard 2969: #endif
1.234 brouard 2970: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2971: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
1.357 brouard 2972: /* The minimization in direction $\xi_1$ gives $P_1$. From $P_1$ minimization in direction $\xi_2$ gives */
2973: /* $P_2$. Minimization of line $P_2-P_1$ gives new starting point $P^{(1)}_0$ and direction $\xi_1$ is dropped and replaced by second */
2974: /* direction $\xi_1^{(1)}=\xi_2$. Also second direction is replaced by new direction $\xi^{(1)}_2=P_2-P_0$. */
2975:
2976: /* At the second iteration, starting from $P_0^{(1)}$, minimization amongst $\xi^{(1)}_1$ gives point $P^{(1)}_1$. */
2977: /* Minimization amongst $\xi^{(1)}_2=(P_2-P_0)$ gives point $P^{(1)}_2$. As $P^{(2)}_1$ and */
2978: /* $P^{(1)}_0$ are minimizing in the same direction $P^{(1)}_2 - P^{(1)}_1= P_2-P_0$, directions $P^{(1)}_2-P^{(1)}_0$ */
2979: /* and $P_2-P_0$ (parallel to $\xi$ and $\xi^c$) are conjugate. } */
2980:
1.234 brouard 2981:
1.126 brouard 2982: #ifdef DEBUG
1.234 brouard 2983: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2984: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2985: for(j=1;j<=n;j++){
2986: printf(" %lf",xit[j]);
2987: fprintf(ficlog," %lf",xit[j]);
2988: }
2989: printf("\n");
2990: fprintf(ficlog,"\n");
1.126 brouard 2991: #endif
1.192 brouard 2992: } /* end of t or directest negative */
1.224 brouard 2993: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2994: #else
1.234 brouard 2995: } /* end if (fptt < fp) */
1.192 brouard 2996: #endif
1.225 brouard 2997: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2998: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2999: #else
1.224 brouard 3000: #endif
1.234 brouard 3001: } /* loop iteration */
1.126 brouard 3002: }
1.234 brouard 3003:
1.126 brouard 3004: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 3005:
1.235 brouard 3006: 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 3007: {
1.338 brouard 3008: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 3009: * (and selected quantitative values in nres)
3010: * by left multiplying the unit
3011: * matrix by transitions matrix until convergence is reached with precision ftolpl
3012: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
3013: * Wx is row vector: population in state 1, population in state 2, population dead
3014: * or prevalence in state 1, prevalence in state 2, 0
3015: * newm is the matrix after multiplications, its rows are identical at a factor.
3016: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
3017: * Output is prlim.
3018: * Initial matrix pimij
3019: */
1.206 brouard 3020: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3021: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3022: /* 0, 0 , 1} */
3023: /*
3024: * and after some iteration: */
3025: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3026: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3027: /* 0, 0 , 1} */
3028: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3029: /* {0.51571254859325999, 0.4842874514067399, */
3030: /* 0.51326036147820708, 0.48673963852179264} */
3031: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 3032:
1.332 brouard 3033: int i, ii,j,k, k1;
1.209 brouard 3034: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 3035: /* double **matprod2(); */ /* test */
1.218 brouard 3036: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 3037: double **newm;
1.209 brouard 3038: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 3039: int ncvloop=0;
1.288 brouard 3040: int first=0;
1.169 brouard 3041:
1.209 brouard 3042: min=vector(1,nlstate);
3043: max=vector(1,nlstate);
3044: meandiff=vector(1,nlstate);
3045:
1.218 brouard 3046: /* Starting with matrix unity */
1.126 brouard 3047: for (ii=1;ii<=nlstate+ndeath;ii++)
3048: for (j=1;j<=nlstate+ndeath;j++){
3049: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3050: }
1.169 brouard 3051:
3052: cov[1]=1.;
3053:
3054: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 3055: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 3056: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 3057: ncvloop++;
1.126 brouard 3058: newm=savm;
3059: /* Covariates have to be included here again */
1.138 brouard 3060: cov[2]=agefin;
1.319 brouard 3061: if(nagesqr==1){
3062: cov[3]= agefin*agefin;
3063: }
1.332 brouard 3064: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3065: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3066: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3067: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3068: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3069: }else{
3070: cov[2+nagesqr+k1]=precov[nres][k1];
3071: }
3072: }/* End of loop on model equation */
3073:
3074: /* Start of old code (replaced by a loop on position in the model equation */
3075: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3076: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3077: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3078: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3079: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3080: /* * k 1 2 3 4 5 6 7 8 */
3081: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3082: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3083: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3084: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3085: /* *nsd=3 (1) (2) (3) */
3086: /* *TvarsD[nsd] [1]=2 1 3 */
3087: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3088: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3089: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3090: /* *Tvard[] [1][1]=1 [2][1]=1 */
3091: /* * [1][2]=3 [2][2]=2 */
3092: /* *Tprod[](=k) [1]=1 [2]=8 */
3093: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3094: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3095: /* *TvarsDpType */
3096: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3097: /* * nsd=1 (1) (2) */
3098: /* *TvarsD[nsd] 3 2 */
3099: /* *TnsdVar (3)=1 (2)=2 */
3100: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3101: /* *Tage[] [1]=2 [2]= 3 */
3102: /* *\/ */
3103: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3104: /* /\* 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)); *\/ */
3105: /* } */
3106: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3107: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3108: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3109: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3110: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3111: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3112: /* /\* 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]); *\/ */
3113: /* } */
3114: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3115: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3116: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3117: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3118: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3119: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3120: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3121: /* } */
3122: /* /\* 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]); *\/ */
3123: /* } */
3124: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3125: /* /\* 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]); *\/ */
3126: /* if(Dummy[Tvard[k][1]]==0){ */
3127: /* if(Dummy[Tvard[k][2]]==0){ */
3128: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3129: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3130: /* }else{ */
3131: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3132: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3133: /* } */
3134: /* }else{ */
3135: /* if(Dummy[Tvard[k][2]]==0){ */
3136: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3137: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3138: /* }else{ */
3139: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3140: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3141: /* } */
3142: /* } */
3143: /* } /\* End product without age *\/ */
3144: /* ENd of old code */
1.138 brouard 3145: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3146: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3147: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3148: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3149: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3150: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3151: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3152:
1.126 brouard 3153: savm=oldm;
3154: oldm=newm;
1.209 brouard 3155:
3156: for(j=1; j<=nlstate; j++){
3157: max[j]=0.;
3158: min[j]=1.;
3159: }
3160: for(i=1;i<=nlstate;i++){
3161: sumnew=0;
3162: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3163: for(j=1; j<=nlstate; j++){
3164: prlim[i][j]= newm[i][j]/(1-sumnew);
3165: max[j]=FMAX(max[j],prlim[i][j]);
3166: min[j]=FMIN(min[j],prlim[i][j]);
3167: }
3168: }
3169:
1.126 brouard 3170: maxmax=0.;
1.209 brouard 3171: for(j=1; j<=nlstate; j++){
3172: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3173: maxmax=FMAX(maxmax,meandiff[j]);
3174: /* 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 3175: } /* j loop */
1.203 brouard 3176: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3177: /* 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 3178: if(maxmax < ftolpl){
1.209 brouard 3179: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3180: free_vector(min,1,nlstate);
3181: free_vector(max,1,nlstate);
3182: free_vector(meandiff,1,nlstate);
1.126 brouard 3183: return prlim;
3184: }
1.288 brouard 3185: } /* agefin loop */
1.208 brouard 3186: /* After some age loop it doesn't converge */
1.288 brouard 3187: if(!first){
3188: first=1;
3189: 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 3190: 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);
3191: }else if (first >=1 && 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: first++;
3194: }else if (first ==10){
3195: 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);
3196: 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");
3197: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3198: first++;
1.288 brouard 3199: }
3200:
1.209 brouard 3201: /* 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); */
3202: free_vector(min,1,nlstate);
3203: free_vector(max,1,nlstate);
3204: free_vector(meandiff,1,nlstate);
1.208 brouard 3205:
1.169 brouard 3206: return prlim; /* should not reach here */
1.126 brouard 3207: }
3208:
1.217 brouard 3209:
3210: /**** Back Prevalence limit (stable or period prevalence) ****************/
3211:
1.218 brouard 3212: /* 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) */
3213: /* 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 3214: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3215: {
1.264 brouard 3216: /* 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 3217: matrix by transitions matrix until convergence is reached with precision ftolpl */
3218: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3219: /* Wx is row vector: population in state 1, population in state 2, population dead */
3220: /* or prevalence in state 1, prevalence in state 2, 0 */
3221: /* newm is the matrix after multiplications, its rows are identical at a factor */
3222: /* Initial matrix pimij */
3223: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3224: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3225: /* 0, 0 , 1} */
3226: /*
3227: * and after some iteration: */
3228: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3229: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3230: /* 0, 0 , 1} */
3231: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3232: /* {0.51571254859325999, 0.4842874514067399, */
3233: /* 0.51326036147820708, 0.48673963852179264} */
3234: /* If we start from prlim again, prlim tends to a constant matrix */
3235:
1.332 brouard 3236: int i, ii,j,k, k1;
1.247 brouard 3237: int first=0;
1.217 brouard 3238: double *min, *max, *meandiff, maxmax,sumnew=0.;
3239: /* double **matprod2(); */ /* test */
3240: double **out, cov[NCOVMAX+1], **bmij();
3241: double **newm;
1.218 brouard 3242: double **dnewm, **doldm, **dsavm; /* for use */
3243: double **oldm, **savm; /* for use */
3244:
1.217 brouard 3245: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3246: int ncvloop=0;
3247:
3248: min=vector(1,nlstate);
3249: max=vector(1,nlstate);
3250: meandiff=vector(1,nlstate);
3251:
1.266 brouard 3252: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3253: oldm=oldms; savm=savms;
3254:
3255: /* Starting with matrix unity */
3256: for (ii=1;ii<=nlstate+ndeath;ii++)
3257: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3258: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3259: }
3260:
3261: cov[1]=1.;
3262:
3263: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3264: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3265: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3266: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3267: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3268: ncvloop++;
1.218 brouard 3269: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3270: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3271: /* Covariates have to be included here again */
3272: cov[2]=agefin;
1.319 brouard 3273: if(nagesqr==1){
1.217 brouard 3274: cov[3]= agefin*agefin;;
1.319 brouard 3275: }
1.332 brouard 3276: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3277: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3278: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3279: }else{
1.332 brouard 3280: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3281: }
1.332 brouard 3282: }/* End of loop on model equation */
3283:
3284: /* Old code */
3285:
3286: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3287: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3288: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3289: /* /\* 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)); *\/ */
3290: /* } */
3291: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3292: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3293: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3294: /* /\* /\\* 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])]); *\\/ *\/ */
3295: /* /\* } *\/ */
3296: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3297: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3298: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3299: /* /\* 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]); *\/ */
3300: /* } */
3301: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3302: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3303: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3304: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3305: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3306: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3307: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3308: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3309: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3310: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3311: /* } */
3312: /* /\* 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]); *\/ */
3313: /* } */
3314: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3315: /* /\* 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]); *\/ */
3316: /* if(Dummy[Tvard[k][1]]==0){ */
3317: /* if(Dummy[Tvard[k][2]]==0){ */
3318: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3319: /* }else{ */
3320: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3321: /* } */
3322: /* }else{ */
3323: /* if(Dummy[Tvard[k][2]]==0){ */
3324: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3325: /* }else{ */
3326: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3327: /* } */
3328: /* } */
3329: /* } */
1.217 brouard 3330:
3331: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3332: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3333: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3334: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3335: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3336: /* ij should be linked to the correct index of cov */
3337: /* age and covariate values ij are in 'cov', but we need to pass
3338: * ij for the observed prevalence at age and status and covariate
3339: * number: prevacurrent[(int)agefin][ii][ij]
3340: */
3341: /* 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 *\/ */
3342: /* 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 *\/ */
3343: 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 3344: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3345: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3346: /* for(i=1; i<=nlstate+ndeath; i++) { */
3347: /* printf("%d newm= ",i); */
3348: /* for(j=1;j<=nlstate+ndeath;j++) { */
3349: /* printf("%f ",newm[i][j]); */
3350: /* } */
3351: /* printf("oldm * "); */
3352: /* for(j=1;j<=nlstate+ndeath;j++) { */
3353: /* printf("%f ",oldm[i][j]); */
3354: /* } */
1.268 brouard 3355: /* printf(" bmmij "); */
1.266 brouard 3356: /* for(j=1;j<=nlstate+ndeath;j++) { */
3357: /* printf("%f ",pmmij[i][j]); */
3358: /* } */
3359: /* printf("\n"); */
3360: /* } */
3361: /* } */
1.217 brouard 3362: savm=oldm;
3363: oldm=newm;
1.266 brouard 3364:
1.217 brouard 3365: for(j=1; j<=nlstate; j++){
3366: max[j]=0.;
3367: min[j]=1.;
3368: }
3369: for(j=1; j<=nlstate; j++){
3370: for(i=1;i<=nlstate;i++){
1.234 brouard 3371: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3372: bprlim[i][j]= newm[i][j];
3373: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3374: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3375: }
3376: }
1.218 brouard 3377:
1.217 brouard 3378: maxmax=0.;
3379: for(i=1; i<=nlstate; i++){
1.318 brouard 3380: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3381: maxmax=FMAX(maxmax,meandiff[i]);
3382: /* 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 3383: } /* i loop */
1.217 brouard 3384: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3385: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3386: if(maxmax < ftolpl){
1.220 brouard 3387: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3388: free_vector(min,1,nlstate);
3389: free_vector(max,1,nlstate);
3390: free_vector(meandiff,1,nlstate);
3391: return bprlim;
3392: }
1.288 brouard 3393: } /* agefin loop */
1.217 brouard 3394: /* After some age loop it doesn't converge */
1.288 brouard 3395: if(!first){
1.247 brouard 3396: first=1;
3397: 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\
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: }
3400: 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 3401: 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);
3402: /* 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); */
3403: free_vector(min,1,nlstate);
3404: free_vector(max,1,nlstate);
3405: free_vector(meandiff,1,nlstate);
3406:
3407: return bprlim; /* should not reach here */
3408: }
3409:
1.126 brouard 3410: /*************** transition probabilities ***************/
3411:
3412: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3413: {
1.138 brouard 3414: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3415: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3416: model to the ncovmodel covariates (including constant and age).
3417: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3418: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3419: ncth covariate in the global vector x is given by the formula:
3420: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3421: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3422: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3423: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3424: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3425: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3426: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3427: */
3428: double s1, lnpijopii;
1.126 brouard 3429: /*double t34;*/
1.164 brouard 3430: int i,j, nc, ii, jj;
1.126 brouard 3431:
1.223 brouard 3432: for(i=1; i<= nlstate; i++){
3433: for(j=1; j<i;j++){
3434: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3435: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3436: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3437: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3438: }
3439: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3440: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3441: }
3442: for(j=i+1; j<=nlstate+ndeath;j++){
3443: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3444: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3445: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3446: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3447: }
3448: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3449: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3450: }
3451: }
1.218 brouard 3452:
1.223 brouard 3453: for(i=1; i<= nlstate; i++){
3454: s1=0;
3455: for(j=1; j<i; j++){
1.339 brouard 3456: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3457: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3458: }
3459: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3460: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3461: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3462: }
3463: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3464: ps[i][i]=1./(s1+1.);
3465: /* Computing other pijs */
3466: for(j=1; j<i; j++)
1.325 brouard 3467: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3468: for(j=i+1; j<=nlstate+ndeath; j++)
3469: ps[i][j]= exp(ps[i][j])*ps[i][i];
3470: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3471: } /* end i */
1.218 brouard 3472:
1.223 brouard 3473: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3474: for(jj=1; jj<= nlstate+ndeath; jj++){
3475: ps[ii][jj]=0;
3476: ps[ii][ii]=1;
3477: }
3478: }
1.294 brouard 3479:
3480:
1.223 brouard 3481: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3482: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3483: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3484: /* } */
3485: /* printf("\n "); */
3486: /* } */
3487: /* printf("\n ");printf("%lf ",cov[2]);*/
3488: /*
3489: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3490: goto end;*/
1.266 brouard 3491: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3492: }
3493:
1.218 brouard 3494: /*************** backward transition probabilities ***************/
3495:
3496: /* 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 ) */
3497: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3498: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3499: {
1.302 brouard 3500: /* 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 3501: * 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 3502: */
1.218 brouard 3503: int i, ii, j,k;
1.222 brouard 3504:
3505: double **out, **pmij();
3506: double sumnew=0.;
1.218 brouard 3507: double agefin;
1.292 brouard 3508: 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 3509: double **dnewm, **dsavm, **doldm;
3510: double **bbmij;
3511:
1.218 brouard 3512: doldm=ddoldms; /* global pointers */
1.222 brouard 3513: dnewm=ddnewms;
3514: dsavm=ddsavms;
1.318 brouard 3515:
3516: /* Debug */
3517: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3518: agefin=cov[2];
1.268 brouard 3519: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3520: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3521: the observed prevalence (with this covariate ij) at beginning of transition */
3522: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3523:
3524: /* P_x */
1.325 brouard 3525: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3526: /* outputs pmmij which is a stochastic matrix in row */
3527:
3528: /* Diag(w_x) */
1.292 brouard 3529: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3530: sumnew=0.;
1.269 brouard 3531: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3532: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3533: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3534: sumnew+=prevacurrent[(int)agefin][ii][ij];
3535: }
3536: if(sumnew >0.01){ /* At least some value in the prevalence */
3537: for (ii=1;ii<=nlstate+ndeath;ii++){
3538: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3539: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3540: }
3541: }else{
3542: for (ii=1;ii<=nlstate+ndeath;ii++){
3543: for (j=1;j<=nlstate+ndeath;j++)
3544: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3545: }
3546: /* if(sumnew <0.9){ */
3547: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3548: /* } */
3549: }
3550: k3=0.0; /* We put the last diagonal to 0 */
3551: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3552: doldm[ii][ii]= k3;
3553: }
3554: /* End doldm, At the end doldm is diag[(w_i)] */
3555:
1.292 brouard 3556: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3557: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3558:
1.292 brouard 3559: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3560: /* 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 3561: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3562: sumnew=0.;
1.222 brouard 3563: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3564: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3565: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3566: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3567: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3568: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3569: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3570: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3571: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3572: /* }else */
1.268 brouard 3573: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3574: } /*End ii */
3575: } /* 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 */
3576:
1.292 brouard 3577: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3578: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3579: /* end bmij */
1.266 brouard 3580: return ps; /*pointer is unchanged */
1.218 brouard 3581: }
1.217 brouard 3582: /*************** transition probabilities ***************/
3583:
1.218 brouard 3584: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3585: {
3586: /* According to parameters values stored in x and the covariate's values stored in cov,
3587: computes the probability to be observed in state j being in state i by appying the
3588: model to the ncovmodel covariates (including constant and age).
3589: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3590: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3591: ncth covariate in the global vector x is given by the formula:
3592: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3593: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3594: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3595: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3596: Outputs ps[i][j] the probability to be observed in j being in j according to
3597: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3598: */
3599: double s1, lnpijopii;
3600: /*double t34;*/
3601: int i,j, nc, ii, jj;
3602:
1.234 brouard 3603: for(i=1; i<= nlstate; i++){
3604: for(j=1; j<i;j++){
3605: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3606: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3607: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3608: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3609: }
3610: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3611: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3612: }
3613: for(j=i+1; j<=nlstate+ndeath;j++){
3614: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3615: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3616: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3617: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3618: }
3619: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3620: }
3621: }
3622:
3623: for(i=1; i<= nlstate; i++){
3624: s1=0;
3625: for(j=1; j<i; j++){
3626: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3627: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3628: }
3629: for(j=i+1; j<=nlstate+ndeath; j++){
3630: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3631: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3632: }
3633: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3634: ps[i][i]=1./(s1+1.);
3635: /* Computing other pijs */
3636: for(j=1; j<i; j++)
3637: ps[i][j]= exp(ps[i][j])*ps[i][i];
3638: for(j=i+1; j<=nlstate+ndeath; j++)
3639: ps[i][j]= exp(ps[i][j])*ps[i][i];
3640: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3641: } /* end i */
3642:
3643: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3644: for(jj=1; jj<= nlstate+ndeath; jj++){
3645: ps[ii][jj]=0;
3646: ps[ii][ii]=1;
3647: }
3648: }
1.296 brouard 3649: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3650: for(jj=1; jj<= nlstate+ndeath; jj++){
3651: s1=0.;
3652: for(ii=1; ii<= nlstate+ndeath; ii++){
3653: s1+=ps[ii][jj];
3654: }
3655: for(ii=1; ii<= nlstate; ii++){
3656: ps[ii][jj]=ps[ii][jj]/s1;
3657: }
3658: }
3659: /* Transposition */
3660: for(jj=1; jj<= nlstate+ndeath; jj++){
3661: for(ii=jj; ii<= nlstate+ndeath; ii++){
3662: s1=ps[ii][jj];
3663: ps[ii][jj]=ps[jj][ii];
3664: ps[jj][ii]=s1;
3665: }
3666: }
3667: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3668: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3669: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3670: /* } */
3671: /* printf("\n "); */
3672: /* } */
3673: /* printf("\n ");printf("%lf ",cov[2]);*/
3674: /*
3675: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3676: goto end;*/
3677: return ps;
1.217 brouard 3678: }
3679:
3680:
1.126 brouard 3681: /**************** Product of 2 matrices ******************/
3682:
1.145 brouard 3683: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3684: {
3685: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3686: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3687: /* in, b, out are matrice of pointers which should have been initialized
3688: before: only the contents of out is modified. The function returns
3689: a pointer to pointers identical to out */
1.145 brouard 3690: int i, j, k;
1.126 brouard 3691: for(i=nrl; i<= nrh; i++)
1.145 brouard 3692: for(k=ncolol; k<=ncoloh; k++){
3693: out[i][k]=0.;
3694: for(j=ncl; j<=nch; j++)
3695: out[i][k] +=in[i][j]*b[j][k];
3696: }
1.126 brouard 3697: return out;
3698: }
3699:
3700:
3701: /************* Higher Matrix Product ***************/
3702:
1.235 brouard 3703: 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 3704: {
1.336 brouard 3705: /* Already optimized with precov.
3706: 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 3707: 'nhstepm*hstepm*stepm' months (i.e. until
3708: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3709: nhstepm*hstepm matrices.
3710: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3711: (typically every 2 years instead of every month which is too big
3712: for the memory).
3713: Model is determined by parameters x and covariates have to be
3714: included manually here.
3715:
3716: */
3717:
1.330 brouard 3718: int i, j, d, h, k, k1;
1.131 brouard 3719: double **out, cov[NCOVMAX+1];
1.126 brouard 3720: double **newm;
1.187 brouard 3721: double agexact;
1.214 brouard 3722: double agebegin, ageend;
1.126 brouard 3723:
3724: /* Hstepm could be zero and should return the unit matrix */
3725: for (i=1;i<=nlstate+ndeath;i++)
3726: for (j=1;j<=nlstate+ndeath;j++){
3727: oldm[i][j]=(i==j ? 1.0 : 0.0);
3728: po[i][j][0]=(i==j ? 1.0 : 0.0);
3729: }
3730: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3731: for(h=1; h <=nhstepm; h++){
3732: for(d=1; d <=hstepm; d++){
3733: newm=savm;
3734: /* Covariates have to be included here again */
3735: cov[1]=1.;
1.214 brouard 3736: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3737: cov[2]=agexact;
1.319 brouard 3738: if(nagesqr==1){
1.227 brouard 3739: cov[3]= agexact*agexact;
1.319 brouard 3740: }
1.330 brouard 3741: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3742: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3743: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3744: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3745: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3746: }else{
3747: cov[2+nagesqr+k1]=precov[nres][k1];
3748: }
3749: }/* End of loop on model equation */
3750: /* Old code */
3751: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3752: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3753: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3754: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3755: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3756: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3757: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3758: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3759: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3760: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3761: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3762: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3763: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3764: /* /\* 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]])); *\/ */
3765: /* 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); */
3766: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3767: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3768: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3769: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3770: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3771: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3772: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3773: /* 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]]); */
3774: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3775: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3776: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3777: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3778: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3779: /* 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]); */
3780: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3781:
3782: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3783: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3784: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3785: /* /\* *\/ */
1.330 brouard 3786: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3787: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3788: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3789: /* /\*cptcovage=2 1 2 *\/ */
3790: /* /\*Tage[k]= 5 8 *\/ */
3791: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3792: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3793: /* 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]]); */
3794: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3795: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3796: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3797: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3798: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3799: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3800: /* /\* 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); *\/ */
3801: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3802: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3803: /* /\* } *\/ */
3804: /* /\* 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]); *\/ */
3805: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3806: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3807: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3808: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3809: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3810: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3811: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3812: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3813: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3814:
1.332 brouard 3815: /* /\* 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])]); *\/ */
3816: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3817: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3818: /* 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]]); */
3819: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3820:
3821: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3822: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3823: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3824: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3825: /* /\* 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]])]; *\/ */
3826: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3827: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3828: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3829: /* /\* } *\/ */
3830: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3831: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3832: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3833: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3834: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3835: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3836: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3837: /* /\* } *\/ */
3838: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3839: /* }/\*end of products *\/ */
3840: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3841: /* for (k=1; k<=cptcovn;k++) */
3842: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3843: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3844: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3845: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3846: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3847:
3848:
1.126 brouard 3849: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3850: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3851: /* right multiplication of oldm by the current matrix */
1.126 brouard 3852: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3853: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3854: /* if((int)age == 70){ */
3855: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3856: /* for(i=1; i<=nlstate+ndeath; i++) { */
3857: /* printf("%d pmmij ",i); */
3858: /* for(j=1;j<=nlstate+ndeath;j++) { */
3859: /* printf("%f ",pmmij[i][j]); */
3860: /* } */
3861: /* printf(" oldm "); */
3862: /* for(j=1;j<=nlstate+ndeath;j++) { */
3863: /* printf("%f ",oldm[i][j]); */
3864: /* } */
3865: /* printf("\n"); */
3866: /* } */
3867: /* } */
1.126 brouard 3868: savm=oldm;
3869: oldm=newm;
3870: }
3871: for(i=1; i<=nlstate+ndeath; i++)
3872: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3873: po[i][j][h]=newm[i][j];
3874: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3875: }
1.128 brouard 3876: /*printf("h=%d ",h);*/
1.126 brouard 3877: } /* end h */
1.267 brouard 3878: /* printf("\n H=%d \n",h); */
1.126 brouard 3879: return po;
3880: }
3881:
1.217 brouard 3882: /************* Higher Back Matrix Product ***************/
1.218 brouard 3883: /* 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 3884: 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 3885: {
1.332 brouard 3886: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3887: computes the transition matrix starting at age 'age' over
1.217 brouard 3888: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3889: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3890: nhstepm*hstepm matrices.
3891: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3892: (typically every 2 years instead of every month which is too big
1.217 brouard 3893: for the memory).
1.218 brouard 3894: Model is determined by parameters x and covariates have to be
1.266 brouard 3895: included manually here. Then we use a call to bmij(x and cov)
3896: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3897: */
1.217 brouard 3898:
1.332 brouard 3899: int i, j, d, h, k, k1;
1.266 brouard 3900: double **out, cov[NCOVMAX+1], **bmij();
3901: double **newm, ***newmm;
1.217 brouard 3902: double agexact;
3903: double agebegin, ageend;
1.222 brouard 3904: double **oldm, **savm;
1.217 brouard 3905:
1.266 brouard 3906: newmm=po; /* To be saved */
3907: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3908: /* Hstepm could be zero and should return the unit matrix */
3909: for (i=1;i<=nlstate+ndeath;i++)
3910: for (j=1;j<=nlstate+ndeath;j++){
3911: oldm[i][j]=(i==j ? 1.0 : 0.0);
3912: po[i][j][0]=(i==j ? 1.0 : 0.0);
3913: }
3914: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3915: for(h=1; h <=nhstepm; h++){
3916: for(d=1; d <=hstepm; d++){
3917: newm=savm;
3918: /* Covariates have to be included here again */
3919: cov[1]=1.;
1.271 brouard 3920: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3921: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3922: /* Debug */
3923: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3924: cov[2]=agexact;
1.332 brouard 3925: if(nagesqr==1){
1.222 brouard 3926: cov[3]= agexact*agexact;
1.332 brouard 3927: }
3928: /** New code */
3929: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3930: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3931: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3932: }else{
1.332 brouard 3933: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3934: }
1.332 brouard 3935: }/* End of loop on model equation */
3936: /** End of new code */
3937: /** This was old code */
3938: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3939: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3940: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3941: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3942: /* /\* 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)); *\/ */
3943: /* } */
3944: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3945: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3946: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3947: /* /\* 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]); *\/ */
3948: /* } */
3949: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3950: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3951: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3952: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3953: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3954: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3955: /* } */
3956: /* /\* 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]); *\/ */
3957: /* } */
3958: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3959: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3960: /* if(Dummy[Tvard[k][1]]==0){ */
3961: /* if(Dummy[Tvard[k][2]]==0){ */
3962: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3963: /* }else{ */
3964: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3965: /* } */
3966: /* }else{ */
3967: /* if(Dummy[Tvard[k][2]]==0){ */
3968: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3969: /* }else{ */
3970: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3971: /* } */
3972: /* } */
3973: /* } */
3974: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3975: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3976: /** End of old code */
3977:
1.218 brouard 3978: /* Careful transposed matrix */
1.266 brouard 3979: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3980: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3981: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3982: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3983: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3984: /* if((int)age == 70){ */
3985: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3986: /* for(i=1; i<=nlstate+ndeath; i++) { */
3987: /* printf("%d pmmij ",i); */
3988: /* for(j=1;j<=nlstate+ndeath;j++) { */
3989: /* printf("%f ",pmmij[i][j]); */
3990: /* } */
3991: /* printf(" oldm "); */
3992: /* for(j=1;j<=nlstate+ndeath;j++) { */
3993: /* printf("%f ",oldm[i][j]); */
3994: /* } */
3995: /* printf("\n"); */
3996: /* } */
3997: /* } */
3998: savm=oldm;
3999: oldm=newm;
4000: }
4001: for(i=1; i<=nlstate+ndeath; i++)
4002: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 4003: po[i][j][h]=newm[i][j];
1.268 brouard 4004: /* if(h==nhstepm) */
4005: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 4006: }
1.268 brouard 4007: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 4008: } /* end h */
1.268 brouard 4009: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 4010: return po;
4011: }
4012:
4013:
1.162 brouard 4014: #ifdef NLOPT
4015: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
4016: double fret;
4017: double *xt;
4018: int j;
4019: myfunc_data *d2 = (myfunc_data *) pd;
4020: /* xt = (p1-1); */
4021: xt=vector(1,n);
4022: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
4023:
4024: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
4025: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
4026: printf("Function = %.12lf ",fret);
4027: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
4028: printf("\n");
4029: free_vector(xt,1,n);
4030: return fret;
4031: }
4032: #endif
1.126 brouard 4033:
4034: /*************** log-likelihood *************/
4035: double func( double *x)
4036: {
1.336 brouard 4037: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 4038: int ioffset=0;
1.339 brouard 4039: int ipos=0,iposold=0,ncovv=0;
4040:
1.340 brouard 4041: double cotvarv, cotvarvold;
1.226 brouard 4042: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
4043: double **out;
4044: double lli; /* Individual log likelihood */
4045: int s1, s2;
1.228 brouard 4046: 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 4047:
1.226 brouard 4048: double bbh, survp;
4049: double agexact;
1.336 brouard 4050: double agebegin, ageend;
1.226 brouard 4051: /*extern weight */
4052: /* We are differentiating ll according to initial status */
4053: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4054: /*for(i=1;i<imx;i++)
4055: printf(" %d\n",s[4][i]);
4056: */
1.162 brouard 4057:
1.226 brouard 4058: ++countcallfunc;
1.162 brouard 4059:
1.226 brouard 4060: cov[1]=1.;
1.126 brouard 4061:
1.226 brouard 4062: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4063: ioffset=0;
1.226 brouard 4064: if(mle==1){
4065: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4066: /* Computes the values of the ncovmodel covariates of the model
4067: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4068: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4069: to be observed in j being in i according to the model.
4070: */
1.243 brouard 4071: ioffset=2+nagesqr ;
1.233 brouard 4072: /* Fixed */
1.345 brouard 4073: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4074: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4075: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4076: /* 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 4077: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4078: 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 4079: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4080: }
1.226 brouard 4081: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4082: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4083: has been calculated etc */
4084: /* For an individual i, wav[i] gives the number of effective waves */
4085: /* We compute the contribution to Likelihood of each effective transition
4086: mw[mi][i] is real wave of the mi th effectve wave */
4087: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4088: s2=s[mw[mi+1][i]][i];
1.341 brouard 4089: 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 4090: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4091: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4092: */
1.336 brouard 4093: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4094: /* Wave varying (but not age varying) */
1.339 brouard 4095: /* 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*\/ */
4096: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4097: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4098: /* } */
1.340 brouard 4099: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4100: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4101: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4102: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4103: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4104: }else{ /* fixed covariate */
1.345 brouard 4105: 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 4106: }
1.339 brouard 4107: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4108: cotvarvold=cotvarv;
4109: }else{ /* A second product */
4110: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4111: }
4112: iposold=ipos;
1.340 brouard 4113: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4114: }
1.339 brouard 4115: /* for products of time varying to be done */
1.234 brouard 4116: for (ii=1;ii<=nlstate+ndeath;ii++)
4117: for (j=1;j<=nlstate+ndeath;j++){
4118: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4119: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4120: }
1.336 brouard 4121:
4122: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4123: 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 4124: for(d=0; d<dh[mi][i]; d++){
4125: newm=savm;
4126: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4127: cov[2]=agexact;
4128: if(nagesqr==1)
4129: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 4130: /* for (kk=1; kk<=cptcovage;kk++) { */
4131: /* if(!FixedV[Tvar[Tage[kk]]]) */
4132: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
4133: /* else */
4134: /* 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) *\/ */
4135: /* } */
4136: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4137: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4138: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4139: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4140: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4141: }else{ /* fixed covariate */
4142: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4143: }
4144: if(ipos!=iposold){ /* Not a product or first of a product */
4145: cotvarvold=cotvarv;
4146: }else{ /* A second product */
4147: cotvarv=cotvarv*cotvarvold;
4148: }
4149: iposold=ipos;
4150: cov[ioffset+ipos]=cotvarv*agexact;
4151: /* For products */
1.234 brouard 4152: }
1.349 brouard 4153:
1.234 brouard 4154: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4155: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4156: savm=oldm;
4157: oldm=newm;
4158: } /* end mult */
4159:
4160: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4161: /* But now since version 0.9 we anticipate for bias at large stepm.
4162: * If stepm is larger than one month (smallest stepm) and if the exact delay
4163: * (in months) between two waves is not a multiple of stepm, we rounded to
4164: * the nearest (and in case of equal distance, to the lowest) interval but now
4165: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4166: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4167: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4168: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4169: * -stepm/2 to stepm/2 .
4170: * For stepm=1 the results are the same as for previous versions of Imach.
4171: * For stepm > 1 the results are less biased than in previous versions.
4172: */
1.234 brouard 4173: s1=s[mw[mi][i]][i];
4174: s2=s[mw[mi+1][i]][i];
4175: bbh=(double)bh[mi][i]/(double)stepm;
4176: /* bias bh is positive if real duration
4177: * is higher than the multiple of stepm and negative otherwise.
4178: */
4179: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4180: if( s2 > nlstate){
4181: /* i.e. if s2 is a death state and if the date of death is known
4182: then the contribution to the likelihood is the probability to
4183: die between last step unit time and current step unit time,
4184: which is also equal to probability to die before dh
4185: minus probability to die before dh-stepm .
4186: In version up to 0.92 likelihood was computed
4187: as if date of death was unknown. Death was treated as any other
4188: health state: the date of the interview describes the actual state
4189: and not the date of a change in health state. The former idea was
4190: to consider that at each interview the state was recorded
4191: (healthy, disable or death) and IMaCh was corrected; but when we
4192: introduced the exact date of death then we should have modified
4193: the contribution of an exact death to the likelihood. This new
4194: contribution is smaller and very dependent of the step unit
4195: stepm. It is no more the probability to die between last interview
4196: and month of death but the probability to survive from last
4197: interview up to one month before death multiplied by the
4198: probability to die within a month. Thanks to Chris
4199: Jackson for correcting this bug. Former versions increased
4200: mortality artificially. The bad side is that we add another loop
4201: which slows down the processing. The difference can be up to 10%
4202: lower mortality.
4203: */
4204: /* If, at the beginning of the maximization mostly, the
4205: cumulative probability or probability to be dead is
4206: constant (ie = 1) over time d, the difference is equal to
4207: 0. out[s1][3] = savm[s1][3]: probability, being at state
4208: s1 at precedent wave, to be dead a month before current
4209: wave is equal to probability, being at state s1 at
4210: precedent wave, to be dead at mont of the current
4211: wave. Then the observed probability (that this person died)
4212: is null according to current estimated parameter. In fact,
4213: it should be very low but not zero otherwise the log go to
4214: infinity.
4215: */
1.183 brouard 4216: /* #ifdef INFINITYORIGINAL */
4217: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4218: /* #else */
4219: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4220: /* lli=log(mytinydouble); */
4221: /* else */
4222: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4223: /* #endif */
1.226 brouard 4224: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4225:
1.226 brouard 4226: } else if ( s2==-1 ) { /* alive */
4227: for (j=1,survp=0. ; j<=nlstate; j++)
4228: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4229: /*survp += out[s1][j]; */
4230: lli= log(survp);
4231: }
1.336 brouard 4232: /* else if (s2==-4) { */
4233: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4234: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4235: /* lli= log(survp); */
4236: /* } */
4237: /* else if (s2==-5) { */
4238: /* for (j=1,survp=0. ; j<=2; j++) */
4239: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4240: /* lli= log(survp); */
4241: /* } */
1.226 brouard 4242: else{
4243: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4244: /* 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 */
4245: }
4246: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4247: /*if(lli ==000.0)*/
1.340 brouard 4248: /* 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 4249: ipmx +=1;
4250: sw += weight[i];
4251: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4252: /* if (lli < log(mytinydouble)){ */
4253: /* 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); */
4254: /* 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]); */
4255: /* } */
4256: } /* end of wave */
4257: } /* end of individual */
4258: } else if(mle==2){
4259: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4260: ioffset=2+nagesqr ;
4261: for (k=1; k<=ncovf;k++)
4262: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4263: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4264: for(k=1; k <= ncovv ; k++){
1.341 brouard 4265: 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 4266: }
1.226 brouard 4267: for (ii=1;ii<=nlstate+ndeath;ii++)
4268: for (j=1;j<=nlstate+ndeath;j++){
4269: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4270: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4271: }
4272: for(d=0; d<=dh[mi][i]; d++){
4273: newm=savm;
4274: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4275: cov[2]=agexact;
4276: if(nagesqr==1)
4277: cov[3]= agexact*agexact;
4278: for (kk=1; kk<=cptcovage;kk++) {
4279: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4280: }
4281: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4282: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4283: savm=oldm;
4284: oldm=newm;
4285: } /* end mult */
4286:
4287: s1=s[mw[mi][i]][i];
4288: s2=s[mw[mi+1][i]][i];
4289: bbh=(double)bh[mi][i]/(double)stepm;
4290: 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 */
4291: ipmx +=1;
4292: sw += weight[i];
4293: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4294: } /* end of wave */
4295: } /* end of individual */
4296: } else if(mle==3){ /* exponential inter-extrapolation */
4297: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4298: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4299: for(mi=1; mi<= wav[i]-1; mi++){
4300: for (ii=1;ii<=nlstate+ndeath;ii++)
4301: for (j=1;j<=nlstate+ndeath;j++){
4302: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4303: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4304: }
4305: for(d=0; d<dh[mi][i]; d++){
4306: newm=savm;
4307: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4308: cov[2]=agexact;
4309: if(nagesqr==1)
4310: cov[3]= agexact*agexact;
4311: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4312: if(!FixedV[Tvar[Tage[kk]]])
4313: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4314: else
1.341 brouard 4315: 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 4316: }
4317: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4318: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4319: savm=oldm;
4320: oldm=newm;
4321: } /* end mult */
4322:
4323: s1=s[mw[mi][i]][i];
4324: s2=s[mw[mi+1][i]][i];
4325: bbh=(double)bh[mi][i]/(double)stepm;
4326: 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 */
4327: ipmx +=1;
4328: sw += weight[i];
4329: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4330: } /* end of wave */
4331: } /* end of individual */
4332: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4333: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4334: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4335: for(mi=1; mi<= wav[i]-1; mi++){
4336: for (ii=1;ii<=nlstate+ndeath;ii++)
4337: for (j=1;j<=nlstate+ndeath;j++){
4338: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4339: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4340: }
4341: for(d=0; d<dh[mi][i]; d++){
4342: newm=savm;
4343: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4344: cov[2]=agexact;
4345: if(nagesqr==1)
4346: cov[3]= agexact*agexact;
4347: for (kk=1; kk<=cptcovage;kk++) {
4348: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4349: }
1.126 brouard 4350:
1.226 brouard 4351: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4352: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4353: savm=oldm;
4354: oldm=newm;
4355: } /* end mult */
4356:
4357: s1=s[mw[mi][i]][i];
4358: s2=s[mw[mi+1][i]][i];
4359: if( s2 > nlstate){
4360: lli=log(out[s1][s2] - savm[s1][s2]);
4361: } else if ( s2==-1 ) { /* alive */
4362: for (j=1,survp=0. ; j<=nlstate; j++)
4363: survp += out[s1][j];
4364: lli= log(survp);
4365: }else{
4366: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4367: }
4368: ipmx +=1;
4369: sw += weight[i];
4370: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4371: /* 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 4372: } /* end of wave */
4373: } /* end of individual */
4374: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4375: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4376: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4377: for(mi=1; mi<= wav[i]-1; mi++){
4378: for (ii=1;ii<=nlstate+ndeath;ii++)
4379: for (j=1;j<=nlstate+ndeath;j++){
4380: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4381: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4382: }
4383: for(d=0; d<dh[mi][i]; d++){
4384: newm=savm;
4385: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4386: cov[2]=agexact;
4387: if(nagesqr==1)
4388: cov[3]= agexact*agexact;
4389: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4390: if(!FixedV[Tvar[Tage[kk]]])
4391: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4392: else
1.341 brouard 4393: 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 4394: }
1.126 brouard 4395:
1.226 brouard 4396: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4397: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4398: savm=oldm;
4399: oldm=newm;
4400: } /* end mult */
4401:
4402: s1=s[mw[mi][i]][i];
4403: s2=s[mw[mi+1][i]][i];
4404: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4405: ipmx +=1;
4406: sw += weight[i];
4407: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4408: /*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]);*/
4409: } /* end of wave */
4410: } /* end of individual */
4411: } /* End of if */
4412: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4413: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4414: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4415: return -l;
1.126 brouard 4416: }
4417:
4418: /*************** log-likelihood *************/
4419: double funcone( double *x)
4420: {
1.228 brouard 4421: /* Same as func but slower because of a lot of printf and if */
1.349 brouard 4422: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4423: int ioffset=0;
1.339 brouard 4424: int ipos=0,iposold=0,ncovv=0;
4425:
1.340 brouard 4426: double cotvarv, cotvarvold;
1.131 brouard 4427: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4428: double **out;
4429: double lli; /* Individual log likelihood */
4430: double llt;
4431: int s1, s2;
1.228 brouard 4432: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4433:
1.126 brouard 4434: double bbh, survp;
1.187 brouard 4435: double agexact;
1.214 brouard 4436: double agebegin, ageend;
1.126 brouard 4437: /*extern weight */
4438: /* We are differentiating ll according to initial status */
4439: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4440: /*for(i=1;i<imx;i++)
4441: printf(" %d\n",s[4][i]);
4442: */
4443: cov[1]=1.;
4444:
4445: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4446: ioffset=0;
4447: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4448: /* Computes the values of the ncovmodel covariates of the model
4449: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4450: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4451: to be observed in j being in i according to the model.
4452: */
1.243 brouard 4453: /* ioffset=2+nagesqr+cptcovage; */
4454: ioffset=2+nagesqr;
1.232 brouard 4455: /* Fixed */
1.224 brouard 4456: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4457: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 4458: 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 4459: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4460: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4461: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4462: 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 4463: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4464: /* cov[2+6]=covar[Tvar[6]][i]; */
4465: /* cov[2+6]=covar[2][i]; V2 */
4466: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4467: /* cov[2+7]=covar[Tvar[7]][i]; */
4468: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4469: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4470: /* cov[2+9]=covar[Tvar[9]][i]; */
4471: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4472: }
1.336 brouard 4473: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4474: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4475: has been calculated etc */
4476: /* For an individual i, wav[i] gives the number of effective waves */
4477: /* We compute the contribution to Likelihood of each effective transition
4478: mw[mi][i] is real wave of the mi th effectve wave */
4479: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4480: s2=s[mw[mi+1][i]][i];
1.341 brouard 4481: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4482: */
4483: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4484: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4485: /* 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?)*\/ */
4486: /* } */
1.231 brouard 4487: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4488: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4489: /* } */
1.225 brouard 4490:
1.233 brouard 4491:
4492: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4493: /* 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 */
4494: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4495: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4496: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4497: /* } */
4498:
4499: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4500: /* model V1+V3+age*V1+age*V3+V1*V3 */
4501: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4502: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4503: /* We need the position of the time varying or product in the model */
4504: /* 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 */
4505: /* TvarVV gives the variable name */
1.340 brouard 4506: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4507: * k= 1 2 3 4 5 6 7 8 9
4508: * varying 1 2 3 4 5
4509: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4510: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4511: * TvarVVind 2 3 7 7 8 8 9 9
4512: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4513: */
1.345 brouard 4514: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 4515: * 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 4516: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 4517: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4518: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
4519: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
4520: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4521: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4522: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4523: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4524: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4525: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4526: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4527: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4528: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4529: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4530: * 12 13 14 15 16
4531: * 17 18 19 20 21
4532: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
4533: * 2 3 4 6 7
4534: * 9 11 12 13 14
4535: * cptcovage=5+5 total of covariates with age
4536: * Tage[cptcovage] age*V2=12 13 14 15 16
4537: *1 17 18 19 20 21 gives the position in model of covariates associated with age
4538: *3 Tage[cptcovage] age*V3*V2=6
4539: *3 age*V2=12 13 14 15 16
4540: *3 age*V6*V3=18 19 20 21
4541: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4542: * 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
4543: * 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
4544: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4545: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4546: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
4547: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
4548: * 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
4549: * Tvar= {2, 3, 4, 6, 7,
4550: * 9, 10, 11, 12, 13, 14,
4551: * Tvar[12]=2, 3, 4, 6, 7,
4552: * Tvar[17]=9, 11, 12, 13, 14}
4553: * Typevar[1]@21 = {0, 0, 0, 0, 0,
4554: * 2, 2, 2, 2, 2, 2,
4555: * 3 3, 2, 2, 2, 2, 2,
4556: * 1, 1, 1, 1, 1,
4557: * 3, 3, 3, 3, 3}
4558: * 3 2, 3, 3, 3, 3}
4559: * 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
4560: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4561: * 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}
4562: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4563: * cptcovprod=11 (6+5)
4564: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
4565: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
4566: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
4567: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
4568: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4569: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4570: * cptcovdageprod=5 for gnuplot printing
4571: * cptcovprodvage=6
4572: * ncova=15 1 2 3 4 5
4573: * 6 7 8 9 10 11 12 13 14 15
4574: * TvarA 2 3 4 6 7
4575: * 6 2 6 7 7 3 6 4 7 4
4576: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4577: * ncovf 1 2 3
1.349 brouard 4578: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4579: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4580: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4581: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4582: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4583: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4584: * 3 1 2 3 4 5 6 7 8 9 10 11 12
4585: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
4586: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
4587: * 3 cptcovprodvage=6
4588: * 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
4589: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
4590: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.354 brouard 4591: *?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 4592: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
4593: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4594: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
4595: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
4596: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
4597: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
4598: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
4599: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4600: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 4601: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
4602: * 2, 3, 4, 6, 7,
4603: * 6, 8, 9, 10, 11}
1.345 brouard 4604: * TvarFind[itv] 0 0 0
4605: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
1.354 brouard 4606: *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0
1.345 brouard 4607: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4608: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4609: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 4610: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4611: */
4612:
1.349 brouard 4613: 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 */
4614: 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 4615: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4616: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4617: 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 4618: /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.345 brouard 4619: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.354 brouard 4620: /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4621: }else{ /* fixed covariate */
1.345 brouard 4622: /* 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 4623: /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.349 brouard 4624: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.354 brouard 4625: /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4626: }
1.339 brouard 4627: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4628: cotvarvold=cotvarv;
4629: }else{ /* A second product */
4630: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4631: }
4632: iposold=ipos;
1.340 brouard 4633: cov[ioffset+ipos]=cotvarv;
1.354 brouard 4634: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
1.339 brouard 4635: /* For products */
4636: }
4637: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4638: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4639: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4640: /* /\* 1 2 3 4 5 *\/ */
4641: /* /\*itv 1 *\/ */
4642: /* /\* TvarVInd[1]= 2 *\/ */
4643: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4644: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4645: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4646: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4647: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4648: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4649: /* /\* 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]); *\/ */
4650: /* } */
1.232 brouard 4651: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4652: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4653: /* /\* 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]); *\/ */
4654: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4655: /* } */
1.126 brouard 4656: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4657: for (j=1;j<=nlstate+ndeath;j++){
4658: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4659: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4660: }
1.214 brouard 4661:
4662: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4663: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4664: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4665: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4666: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4667: and mw[mi+1][i]. dh depends on stepm.*/
4668: newm=savm;
1.247 brouard 4669: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4670: cov[2]=agexact;
4671: if(nagesqr==1)
4672: cov[3]= agexact*agexact;
1.349 brouard 4673: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4674: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4675: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4676: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4677: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4678: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4679: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4680: }else{ /* fixed covariate */
4681: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4682: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4683: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4684: }
4685: if(ipos!=iposold){ /* Not a product or first of a product */
4686: cotvarvold=cotvarv;
4687: }else{ /* A second product */
4688: /* printf("DEBUG * \n"); */
4689: cotvarv=cotvarv*cotvarvold;
4690: }
4691: iposold=ipos;
4692: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4693: cov[ioffset+ipos]=cotvarv*agexact;
4694: /* For products */
1.242 brouard 4695: }
1.349 brouard 4696:
1.242 brouard 4697: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4698: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4699: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4700: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4701: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4702: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4703: savm=oldm;
4704: oldm=newm;
1.126 brouard 4705: } /* end mult */
1.336 brouard 4706: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4707: /* But now since version 0.9 we anticipate for bias at large stepm.
4708: * If stepm is larger than one month (smallest stepm) and if the exact delay
4709: * (in months) between two waves is not a multiple of stepm, we rounded to
4710: * the nearest (and in case of equal distance, to the lowest) interval but now
4711: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4712: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4713: * probability in order to take into account the bias as a fraction of the way
4714: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4715: * -stepm/2 to stepm/2 .
4716: * For stepm=1 the results are the same as for previous versions of Imach.
4717: * For stepm > 1 the results are less biased than in previous versions.
4718: */
1.126 brouard 4719: s1=s[mw[mi][i]][i];
4720: s2=s[mw[mi+1][i]][i];
1.217 brouard 4721: /* if(s2==-1){ */
1.268 brouard 4722: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4723: /* /\* exit(1); *\/ */
4724: /* } */
1.126 brouard 4725: bbh=(double)bh[mi][i]/(double)stepm;
4726: /* bias is positive if real duration
4727: * is higher than the multiple of stepm and negative otherwise.
4728: */
4729: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4730: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4731: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4732: for (j=1,survp=0. ; j<=nlstate; j++)
4733: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4734: lli= log(survp);
1.126 brouard 4735: }else if (mle==1){
1.242 brouard 4736: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4737: } else if(mle==2){
1.242 brouard 4738: 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 4739: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4740: 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 4741: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4742: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4743: } else{ /* mle=0 back to 1 */
1.242 brouard 4744: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4745: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4746: } /* End of if */
4747: ipmx +=1;
4748: sw += weight[i];
4749: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4750: /* Printing covariates values for each contribution for checking */
1.343 brouard 4751: /* 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 4752: if(globpr){
1.246 brouard 4753: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4754: %11.6f %11.6f %11.6f ", \
1.242 brouard 4755: 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 4756: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4757: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4758: /* %11.6f %11.6f %11.6f ", \ */
4759: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4760: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4761: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4762: llt +=ll[k]*gipmx/gsw;
4763: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4764: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4765: }
1.343 brouard 4766: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4767: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4768: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4769: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4770: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4771: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4772: }
4773: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4774: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4775: if(ipos!=iposold){ /* Not a product or first of a product */
4776: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4777: /* printf(" %g",cov[ioffset+ipos]); */
4778: }else{
4779: fprintf(ficresilk,"*");
4780: /* printf("*"); */
1.342 brouard 4781: }
1.343 brouard 4782: iposold=ipos;
4783: }
1.349 brouard 4784: /* for (kk=1; kk<=cptcovage;kk++) { */
4785: /* if(!FixedV[Tvar[Tage[kk]]]){ */
4786: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
4787: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
4788: /* }else{ */
4789: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4790: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
4791: /* } */
4792: /* } */
4793: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4794: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4795: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4796: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4797: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4798: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4799: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4800: }else{ /* fixed covariate */
4801: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4802: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4803: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4804: }
4805: if(ipos!=iposold){ /* Not a product or first of a product */
4806: cotvarvold=cotvarv;
4807: }else{ /* A second product */
4808: /* printf("DEBUG * \n"); */
4809: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4810: }
1.349 brouard 4811: cotvarv=cotvarv*agexact;
4812: fprintf(ficresilk," %g*age",cotvarv);
4813: iposold=ipos;
4814: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4815: cov[ioffset+ipos]=cotvarv;
4816: /* For products */
1.343 brouard 4817: }
4818: /* printf("\n"); */
1.342 brouard 4819: /* } /\* End debugILK *\/ */
4820: fprintf(ficresilk,"\n");
4821: } /* End if globpr */
1.335 brouard 4822: } /* end of wave */
4823: } /* end of individual */
4824: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4825: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4826: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4827: if(globpr==0){ /* First time we count the contributions and weights */
4828: gipmx=ipmx;
4829: gsw=sw;
4830: }
1.343 brouard 4831: return -l;
1.126 brouard 4832: }
4833:
4834:
4835: /*************** function likelione ***********/
1.292 brouard 4836: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4837: {
4838: /* This routine should help understanding what is done with
4839: the selection of individuals/waves and
4840: to check the exact contribution to the likelihood.
4841: Plotting could be done.
1.342 brouard 4842: */
4843: void pstamp(FILE *ficres);
1.343 brouard 4844: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4845:
4846: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4847: strcpy(fileresilk,"ILK_");
1.202 brouard 4848: strcat(fileresilk,fileresu);
1.126 brouard 4849: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4850: printf("Problem with resultfile: %s\n", fileresilk);
4851: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4852: }
1.342 brouard 4853: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4854: 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");
4855: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4856: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4857: for(k=1; k<=nlstate; k++)
4858: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4859: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4860:
4861: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4862: for(kf=1;kf <= ncovf; kf++){
4863: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4864: /* printf("V%d",Tvar[TvarFind[kf]]); */
4865: }
4866: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4867: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4868: if(ipos!=iposold){ /* Not a product or first of a product */
4869: /* printf(" %d",ipos); */
4870: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4871: }else{
4872: /* printf("*"); */
4873: fprintf(ficresilk,"*");
1.343 brouard 4874: }
1.342 brouard 4875: iposold=ipos;
4876: }
4877: for (kk=1; kk<=cptcovage;kk++) {
4878: if(!FixedV[Tvar[Tage[kk]]]){
4879: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4880: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4881: }else{
4882: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4883: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4884: }
4885: }
4886: /* } /\* End if debugILK *\/ */
4887: /* printf("\n"); */
4888: fprintf(ficresilk,"\n");
4889: } /* End glogpri */
1.126 brouard 4890:
1.292 brouard 4891: *fretone=(*func)(p);
1.126 brouard 4892: if(*globpri !=0){
4893: fclose(ficresilk);
1.205 brouard 4894: if (mle ==0)
4895: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4896: else if(mle >=1)
4897: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4898: 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 4899: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4900:
1.207 brouard 4901: 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 4902: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4903: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4904: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4905:
4906: for (k=1; k<= nlstate ; k++) {
4907: 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 \
4908: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4909: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 4910: kvar=Tvar[TvarFind[kf]]; /* variable */
4911: 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]]);
4912: 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);
4913: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 4914: }
4915: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4916: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4917: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4918: /* 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]); */
4919: if(ipos!=iposold){ /* Not a product or first of a product */
4920: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4921: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4922: 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) */
4923: 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> \
4924: <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);
4925: } /* End only for dummies time varying (single?) */
4926: }else{ /* Useless product */
4927: /* printf("*"); */
4928: /* fprintf(ficresilk,"*"); */
4929: }
4930: iposold=ipos;
4931: } /* For each time varying covariate */
4932: } /* End loop on states */
4933:
4934: /* if(debugILK){ */
4935: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4936: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4937: /* for (k=1; k<= nlstate ; k++) { */
4938: /* 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> \ */
4939: /* <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]]); */
4940: /* } */
4941: /* } */
4942: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4943: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4944: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4945: /* /\* 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]); *\/ */
4946: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4947: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4948: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4949: /* 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) *\/ */
4950: /* for (k=1; k<= nlstate ; k++) { */
4951: /* 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> \ */
4952: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4953: /* } /\* End state *\/ */
4954: /* } /\* End only for dummies time varying (single?) *\/ */
4955: /* }else{ /\* Useless product *\/ */
4956: /* /\* printf("*"); *\/ */
4957: /* /\* fprintf(ficresilk,"*"); *\/ */
4958: /* } */
4959: /* iposold=ipos; */
4960: /* } /\* For each time varying covariate *\/ */
4961: /* }/\* End debugILK *\/ */
1.207 brouard 4962: fflush(fichtm);
1.343 brouard 4963: }/* End globpri */
1.126 brouard 4964: return;
4965: }
4966:
4967:
4968: /*********** Maximum Likelihood Estimation ***************/
4969:
4970: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4971: {
1.319 brouard 4972: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4973: double **xi;
4974: double fret;
4975: double fretone; /* Only one call to likelihood */
4976: /* char filerespow[FILENAMELENGTH];*/
1.354 brouard 4977:
4978: double * p1; /* Shifted parameters from 0 instead of 1 */
1.162 brouard 4979: #ifdef NLOPT
4980: int creturn;
4981: nlopt_opt opt;
4982: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4983: double *lb;
4984: double minf; /* the minimum objective value, upon return */
1.354 brouard 4985:
1.162 brouard 4986: myfunc_data dinst, *d = &dinst;
4987: #endif
4988:
4989:
1.126 brouard 4990: xi=matrix(1,npar,1,npar);
1.357 brouard 4991: for (i=1;i<=npar;i++) /* Starting with canonical directions j=1,n xi[i=1,n][j] */
1.126 brouard 4992: for (j=1;j<=npar;j++)
4993: xi[i][j]=(i==j ? 1.0 : 0.0);
4994: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4995: strcpy(filerespow,"POW_");
1.126 brouard 4996: strcat(filerespow,fileres);
4997: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4998: printf("Problem with resultfile: %s\n", filerespow);
4999: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
5000: }
5001: fprintf(ficrespow,"# Powell\n# iter -2*LL");
5002: for (i=1;i<=nlstate;i++)
5003: for(j=1;j<=nlstate+ndeath;j++)
5004: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
5005: fprintf(ficrespow,"\n");
1.162 brouard 5006: #ifdef POWELL
1.319 brouard 5007: #ifdef LINMINORIGINAL
5008: #else /* LINMINORIGINAL */
5009:
5010: flatdir=ivector(1,npar);
5011: for (j=1;j<=npar;j++) flatdir[j]=0;
5012: #endif /*LINMINORIGINAL */
5013:
5014: #ifdef FLATSUP
5015: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5016: /* reorganizing p by suppressing flat directions */
5017: for(i=1, jk=1; i <=nlstate; i++){
5018: for(k=1; k <=(nlstate+ndeath); k++){
5019: if (k != i) {
5020: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
5021: if(flatdir[jk]==1){
5022: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
5023: }
5024: for(j=1; j <=ncovmodel; j++){
5025: printf("%12.7f ",p[jk]);
5026: jk++;
5027: }
5028: printf("\n");
5029: }
5030: }
5031: }
5032: /* skipping */
5033: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
5034: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
5035: for(k=1; k <=(nlstate+ndeath); k++){
5036: if (k != i) {
5037: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
5038: if(flatdir[jk]==1){
5039: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
5040: for(j=1; j <=ncovmodel; jk++,j++){
5041: printf(" p[%d]=%12.7f",jk, p[jk]);
5042: /*q[jjk]=p[jk];*/
5043: }
5044: }else{
5045: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
5046: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
5047: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
5048: /*q[jjk]=p[jk];*/
5049: }
5050: }
5051: printf("\n");
5052: }
5053: fflush(stdout);
5054: }
5055: }
5056: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5057: #else /* FLATSUP */
1.126 brouard 5058: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 5059: #endif /* FLATSUP */
5060:
5061: #ifdef LINMINORIGINAL
5062: #else
5063: free_ivector(flatdir,1,npar);
5064: #endif /* LINMINORIGINAL*/
5065: #endif /* POWELL */
1.126 brouard 5066:
1.162 brouard 5067: #ifdef NLOPT
5068: #ifdef NEWUOA
5069: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
5070: #else
5071: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
5072: #endif
5073: lb=vector(0,npar-1);
5074: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
5075: nlopt_set_lower_bounds(opt, lb);
5076: nlopt_set_initial_step1(opt, 0.1);
5077:
5078: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5079: d->function = func;
5080: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5081: nlopt_set_min_objective(opt, myfunc, d);
5082: nlopt_set_xtol_rel(opt, ftol);
5083: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5084: printf("nlopt failed! %d\n",creturn);
5085: }
5086: else {
5087: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5088: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5089: iter=1; /* not equal */
5090: }
5091: nlopt_destroy(opt);
5092: #endif
1.319 brouard 5093: #ifdef FLATSUP
5094: /* npared = npar -flatd/ncovmodel; */
5095: /* xired= matrix(1,npared,1,npared); */
5096: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5097: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5098: /* free_matrix(xire,1,npared,1,npared); */
5099: #else /* FLATSUP */
5100: #endif /* FLATSUP */
1.126 brouard 5101: free_matrix(xi,1,npar,1,npar);
5102: fclose(ficrespow);
1.203 brouard 5103: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5104: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5105: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5106:
5107: }
5108:
5109: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5110: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5111: {
5112: double **a,**y,*x,pd;
1.203 brouard 5113: /* double **hess; */
1.164 brouard 5114: int i, j;
1.126 brouard 5115: int *indx;
5116:
5117: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5118: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5119: void lubksb(double **a, int npar, int *indx, double b[]) ;
5120: void ludcmp(double **a, int npar, int *indx, double *d) ;
5121: double gompertz(double p[]);
1.203 brouard 5122: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5123:
5124: printf("\nCalculation of the hessian matrix. Wait...\n");
5125: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5126: for (i=1;i<=npar;i++){
1.203 brouard 5127: printf("%d-",i);fflush(stdout);
5128: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5129:
5130: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5131:
5132: /* printf(" %f ",p[i]);
5133: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5134: }
5135:
5136: for (i=1;i<=npar;i++) {
5137: for (j=1;j<=npar;j++) {
5138: if (j>i) {
1.203 brouard 5139: printf(".%d-%d",i,j);fflush(stdout);
5140: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5141: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5142:
5143: hess[j][i]=hess[i][j];
5144: /*printf(" %lf ",hess[i][j]);*/
5145: }
5146: }
5147: }
5148: printf("\n");
5149: fprintf(ficlog,"\n");
5150:
5151: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5152: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5153:
5154: a=matrix(1,npar,1,npar);
5155: y=matrix(1,npar,1,npar);
5156: x=vector(1,npar);
5157: indx=ivector(1,npar);
5158: for (i=1;i<=npar;i++)
5159: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5160: ludcmp(a,npar,indx,&pd);
5161:
5162: for (j=1;j<=npar;j++) {
5163: for (i=1;i<=npar;i++) x[i]=0;
5164: x[j]=1;
5165: lubksb(a,npar,indx,x);
5166: for (i=1;i<=npar;i++){
5167: matcov[i][j]=x[i];
5168: }
5169: }
5170:
5171: printf("\n#Hessian matrix#\n");
5172: fprintf(ficlog,"\n#Hessian matrix#\n");
5173: for (i=1;i<=npar;i++) {
5174: for (j=1;j<=npar;j++) {
1.203 brouard 5175: printf("%.6e ",hess[i][j]);
5176: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5177: }
5178: printf("\n");
5179: fprintf(ficlog,"\n");
5180: }
5181:
1.203 brouard 5182: /* printf("\n#Covariance matrix#\n"); */
5183: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5184: /* for (i=1;i<=npar;i++) { */
5185: /* for (j=1;j<=npar;j++) { */
5186: /* printf("%.6e ",matcov[i][j]); */
5187: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5188: /* } */
5189: /* printf("\n"); */
5190: /* fprintf(ficlog,"\n"); */
5191: /* } */
5192:
1.126 brouard 5193: /* Recompute Inverse */
1.203 brouard 5194: /* for (i=1;i<=npar;i++) */
5195: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5196: /* ludcmp(a,npar,indx,&pd); */
5197:
5198: /* printf("\n#Hessian matrix recomputed#\n"); */
5199:
5200: /* for (j=1;j<=npar;j++) { */
5201: /* for (i=1;i<=npar;i++) x[i]=0; */
5202: /* x[j]=1; */
5203: /* lubksb(a,npar,indx,x); */
5204: /* for (i=1;i<=npar;i++){ */
5205: /* y[i][j]=x[i]; */
5206: /* printf("%.3e ",y[i][j]); */
5207: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5208: /* } */
5209: /* printf("\n"); */
5210: /* fprintf(ficlog,"\n"); */
5211: /* } */
5212:
5213: /* Verifying the inverse matrix */
5214: #ifdef DEBUGHESS
5215: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5216:
1.203 brouard 5217: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5218: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5219:
5220: for (j=1;j<=npar;j++) {
5221: for (i=1;i<=npar;i++){
1.203 brouard 5222: printf("%.2f ",y[i][j]);
5223: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5224: }
5225: printf("\n");
5226: fprintf(ficlog,"\n");
5227: }
1.203 brouard 5228: #endif
1.126 brouard 5229:
5230: free_matrix(a,1,npar,1,npar);
5231: free_matrix(y,1,npar,1,npar);
5232: free_vector(x,1,npar);
5233: free_ivector(indx,1,npar);
1.203 brouard 5234: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5235:
5236:
5237: }
5238:
5239: /*************** hessian matrix ****************/
5240: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5241: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5242: int i;
5243: int l=1, lmax=20;
1.203 brouard 5244: double k1,k2, res, fx;
1.132 brouard 5245: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5246: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5247: int k=0,kmax=10;
5248: double l1;
5249:
5250: fx=func(x);
5251: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5252: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5253: l1=pow(10,l);
5254: delts=delt;
5255: for(k=1 ; k <kmax; k=k+1){
5256: delt = delta*(l1*k);
5257: p2[theta]=x[theta] +delt;
1.145 brouard 5258: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5259: p2[theta]=x[theta]-delt;
5260: k2=func(p2)-fx;
5261: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5262: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5263:
1.203 brouard 5264: #ifdef DEBUGHESSII
1.126 brouard 5265: 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);
5266: 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);
5267: #endif
5268: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5269: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5270: k=kmax;
5271: }
5272: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5273: k=kmax; l=lmax*10;
1.126 brouard 5274: }
5275: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5276: delts=delt;
5277: }
1.203 brouard 5278: } /* End loop k */
1.126 brouard 5279: }
5280: delti[theta]=delts;
5281: return res;
5282:
5283: }
5284:
1.203 brouard 5285: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5286: {
5287: int i;
1.164 brouard 5288: int l=1, lmax=20;
1.126 brouard 5289: double k1,k2,k3,k4,res,fx;
1.132 brouard 5290: double p2[MAXPARM+1];
1.203 brouard 5291: int k, kmax=1;
5292: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5293:
5294: int firstime=0;
1.203 brouard 5295:
1.126 brouard 5296: fx=func(x);
1.203 brouard 5297: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5298: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5299: p2[thetai]=x[thetai]+delti[thetai]*k;
5300: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5301: k1=func(p2)-fx;
5302:
1.203 brouard 5303: p2[thetai]=x[thetai]+delti[thetai]*k;
5304: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5305: k2=func(p2)-fx;
5306:
1.203 brouard 5307: p2[thetai]=x[thetai]-delti[thetai]*k;
5308: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5309: k3=func(p2)-fx;
5310:
1.203 brouard 5311: p2[thetai]=x[thetai]-delti[thetai]*k;
5312: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5313: k4=func(p2)-fx;
1.203 brouard 5314: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5315: if(k1*k2*k3*k4 <0.){
1.208 brouard 5316: firstime=1;
1.203 brouard 5317: kmax=kmax+10;
1.208 brouard 5318: }
5319: if(kmax >=10 || firstime ==1){
1.354 brouard 5320: /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */
1.246 brouard 5321: 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);
5322: 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 5323: 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);
5324: 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);
5325: }
5326: #ifdef DEBUGHESSIJ
5327: v1=hess[thetai][thetai];
5328: v2=hess[thetaj][thetaj];
5329: cv12=res;
5330: /* Computing eigen value of Hessian matrix */
5331: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5332: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5333: if ((lc2 <0) || (lc1 <0) ){
5334: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5335: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5336: 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);
5337: 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);
5338: }
1.126 brouard 5339: #endif
5340: }
5341: return res;
5342: }
5343:
1.203 brouard 5344: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5345: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5346: /* { */
5347: /* int i; */
5348: /* int l=1, lmax=20; */
5349: /* double k1,k2,k3,k4,res,fx; */
5350: /* double p2[MAXPARM+1]; */
5351: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5352: /* int k=0,kmax=10; */
5353: /* double l1; */
5354:
5355: /* fx=func(x); */
5356: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5357: /* l1=pow(10,l); */
5358: /* delts=delt; */
5359: /* for(k=1 ; k <kmax; k=k+1){ */
5360: /* delt = delti*(l1*k); */
5361: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5362: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5363: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5364: /* k1=func(p2)-fx; */
5365:
5366: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5367: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5368: /* k2=func(p2)-fx; */
5369:
5370: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5371: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5372: /* k3=func(p2)-fx; */
5373:
5374: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5375: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5376: /* k4=func(p2)-fx; */
5377: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5378: /* #ifdef DEBUGHESSIJ */
5379: /* 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); */
5380: /* 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); */
5381: /* #endif */
5382: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5383: /* k=kmax; */
5384: /* } */
5385: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5386: /* k=kmax; l=lmax*10; */
5387: /* } */
5388: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5389: /* delts=delt; */
5390: /* } */
5391: /* } /\* End loop k *\/ */
5392: /* } */
5393: /* delti[theta]=delts; */
5394: /* return res; */
5395: /* } */
5396:
5397:
1.126 brouard 5398: /************** Inverse of matrix **************/
5399: void ludcmp(double **a, int n, int *indx, double *d)
5400: {
5401: int i,imax,j,k;
5402: double big,dum,sum,temp;
5403: double *vv;
5404:
5405: vv=vector(1,n);
5406: *d=1.0;
5407: for (i=1;i<=n;i++) {
5408: big=0.0;
5409: for (j=1;j<=n;j++)
5410: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5411: if (big == 0.0){
5412: printf(" Singular Hessian matrix at row %d:\n",i);
5413: for (j=1;j<=n;j++) {
5414: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5415: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5416: }
5417: fflush(ficlog);
5418: fclose(ficlog);
5419: nrerror("Singular matrix in routine ludcmp");
5420: }
1.126 brouard 5421: vv[i]=1.0/big;
5422: }
5423: for (j=1;j<=n;j++) {
5424: for (i=1;i<j;i++) {
5425: sum=a[i][j];
5426: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5427: a[i][j]=sum;
5428: }
5429: big=0.0;
5430: for (i=j;i<=n;i++) {
5431: sum=a[i][j];
5432: for (k=1;k<j;k++)
5433: sum -= a[i][k]*a[k][j];
5434: a[i][j]=sum;
5435: if ( (dum=vv[i]*fabs(sum)) >= big) {
5436: big=dum;
5437: imax=i;
5438: }
5439: }
5440: if (j != imax) {
5441: for (k=1;k<=n;k++) {
5442: dum=a[imax][k];
5443: a[imax][k]=a[j][k];
5444: a[j][k]=dum;
5445: }
5446: *d = -(*d);
5447: vv[imax]=vv[j];
5448: }
5449: indx[j]=imax;
5450: if (a[j][j] == 0.0) a[j][j]=TINY;
5451: if (j != n) {
5452: dum=1.0/(a[j][j]);
5453: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5454: }
5455: }
5456: free_vector(vv,1,n); /* Doesn't work */
5457: ;
5458: }
5459:
5460: void lubksb(double **a, int n, int *indx, double b[])
5461: {
5462: int i,ii=0,ip,j;
5463: double sum;
5464:
5465: for (i=1;i<=n;i++) {
5466: ip=indx[i];
5467: sum=b[ip];
5468: b[ip]=b[i];
5469: if (ii)
5470: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5471: else if (sum) ii=i;
5472: b[i]=sum;
5473: }
5474: for (i=n;i>=1;i--) {
5475: sum=b[i];
5476: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5477: b[i]=sum/a[i][i];
5478: }
5479: }
5480:
5481: void pstamp(FILE *fichier)
5482: {
1.196 brouard 5483: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5484: }
5485:
1.297 brouard 5486: void date2dmy(double date,double *day, double *month, double *year){
5487: double yp=0., yp1=0., yp2=0.;
5488:
5489: yp1=modf(date,&yp);/* extracts integral of date in yp and
5490: fractional in yp1 */
5491: *year=yp;
5492: yp2=modf((yp1*12),&yp);
5493: *month=yp;
5494: yp1=modf((yp2*30.5),&yp);
5495: *day=yp;
5496: if(*day==0) *day=1;
5497: if(*month==0) *month=1;
5498: }
5499:
1.253 brouard 5500:
5501:
1.126 brouard 5502: /************ Frequencies ********************/
1.251 brouard 5503: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5504: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5505: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5506: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5507: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5508: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5509: int iind=0, iage=0;
5510: int mi; /* Effective wave */
5511: int first;
5512: double ***freq; /* Frequencies */
1.268 brouard 5513: 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 */
5514: 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 5515: double *meanq, *stdq, *idq;
1.226 brouard 5516: double **meanqt;
5517: double *pp, **prop, *posprop, *pospropt;
5518: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5519: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5520: double agebegin, ageend;
5521:
5522: pp=vector(1,nlstate);
1.251 brouard 5523: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5524: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5525: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5526: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5527: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5528: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5529: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5530: meanqt=matrix(1,lastpass,1,nqtveff);
5531: strcpy(fileresp,"P_");
5532: strcat(fileresp,fileresu);
5533: /*strcat(fileresphtm,fileresu);*/
5534: if((ficresp=fopen(fileresp,"w"))==NULL) {
5535: printf("Problem with prevalence resultfile: %s\n", fileresp);
5536: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5537: exit(0);
5538: }
1.240 brouard 5539:
1.226 brouard 5540: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5541: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5542: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5543: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5544: fflush(ficlog);
5545: exit(70);
5546: }
5547: else{
5548: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5549: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5550: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5551: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5552: }
1.319 brouard 5553: 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 5554:
1.226 brouard 5555: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5556: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5557: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5558: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5559: fflush(ficlog);
5560: exit(70);
1.240 brouard 5561: } else{
1.226 brouard 5562: 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 5563: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5564: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5565: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5566: }
1.319 brouard 5567: 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 5568:
1.253 brouard 5569: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5570: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5571: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5572: j1=0;
1.126 brouard 5573:
1.227 brouard 5574: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5575: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5576: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5577: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5578:
5579:
1.226 brouard 5580: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5581: reference=low_education V1=0,V2=0
5582: med_educ V1=1 V2=0,
5583: high_educ V1=0 V2=1
1.330 brouard 5584: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5585: */
1.249 brouard 5586: dateintsum=0;
5587: k2cpt=0;
5588:
1.253 brouard 5589: if(cptcoveff == 0 )
1.265 brouard 5590: nl=1; /* Constant and age model only */
1.253 brouard 5591: else
5592: nl=2;
1.265 brouard 5593:
5594: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5595: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5596: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5597: * freq[s1][s2][iage] =0.
5598: * Loop on iind
5599: * ++freq[s1][s2][iage] weighted
5600: * end iind
5601: * if covariate and j!0
5602: * headers Variable on one line
5603: * endif cov j!=0
5604: * header of frequency table by age
5605: * Loop on age
5606: * pp[s1]+=freq[s1][s2][iage] weighted
5607: * pos+=freq[s1][s2][iage] weighted
5608: * Loop on s1 initial state
5609: * fprintf(ficresp
5610: * end s1
5611: * end age
5612: * if j!=0 computes starting values
5613: * end compute starting values
5614: * end j1
5615: * end nl
5616: */
1.253 brouard 5617: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5618: if(nj==1)
5619: j=0; /* First pass for the constant */
1.265 brouard 5620: else{
1.335 brouard 5621: 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 5622: }
1.251 brouard 5623: first=1;
1.332 brouard 5624: 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 5625: posproptt=0.;
1.330 brouard 5626: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5627: scanf("%d", i);*/
5628: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5629: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5630: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5631: freq[i][s2][m]=0;
1.251 brouard 5632:
5633: for (i=1; i<=nlstate; i++) {
1.240 brouard 5634: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5635: prop[i][m]=0;
5636: posprop[i]=0;
5637: pospropt[i]=0;
5638: }
1.283 brouard 5639: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5640: idq[z1]=0.;
5641: meanq[z1]=0.;
5642: stdq[z1]=0.;
1.283 brouard 5643: }
5644: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5645: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5646: /* meanqt[m][z1]=0.; */
5647: /* } */
5648: /* } */
1.251 brouard 5649: /* dateintsum=0; */
5650: /* k2cpt=0; */
5651:
1.265 brouard 5652: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5653: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5654: bool=1;
5655: if(j !=0){
5656: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5657: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5658: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5659: /* if(Tvaraff[z1] ==-20){ */
5660: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5661: /* }else if(Tvaraff[z1] ==-10){ */
5662: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5663: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5664: /* 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); */
5665: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5666: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5667: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5668: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5669: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5670: /* 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", */
5671: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5672: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5673: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5674: } /* Onlyf fixed */
5675: } /* end z1 */
1.335 brouard 5676: } /* cptcoveff > 0 */
1.251 brouard 5677: } /* end any */
5678: }/* end j==0 */
1.265 brouard 5679: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5680: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5681: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5682: m=mw[mi][iind];
5683: if(j!=0){
5684: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5685: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5686: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5687: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5688: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5689: 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 5690: value is -1, we don't select. It differs from the
5691: constant and age model which counts them. */
5692: bool=0; /* not selected */
5693: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5694: /* i1=Tvaraff[z1]; */
5695: /* i2=TnsdVar[i1]; */
5696: /* i3=nbcode[i1][i2]; */
5697: /* i4=covar[i1][iind]; */
5698: /* if(i4 != i3){ */
5699: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5700: bool=0;
5701: }
5702: }
5703: }
5704: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5705: } /* end j==0 */
5706: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5707: if(bool==1){ /*Selected */
1.251 brouard 5708: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5709: and mw[mi+1][iind]. dh depends on stepm. */
5710: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5711: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5712: if(m >=firstpass && m <=lastpass){
5713: k2=anint[m][iind]+(mint[m][iind]/12.);
5714: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5715: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5716: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5717: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5718: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5719: if (m<lastpass) {
5720: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5721: /* 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]); */
5722: if(s[m][iind]==-1)
5723: 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.));
5724: 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 5725: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5726: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5727: idq[z1]=idq[z1]+weight[iind];
5728: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5729: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5730: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5731: }
1.284 brouard 5732: }
1.251 brouard 5733: /* if((int)agev[m][iind] == 55) */
5734: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5735: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5736: 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 5737: }
1.251 brouard 5738: } /* end if between passes */
5739: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5740: dateintsum=dateintsum+k2; /* on all covariates ?*/
5741: k2cpt++;
5742: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5743: }
1.251 brouard 5744: }else{
5745: bool=1;
5746: }/* end bool 2 */
5747: } /* end m */
1.284 brouard 5748: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5749: /* idq[z1]=idq[z1]+weight[iind]; */
5750: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5751: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5752: /* } */
1.251 brouard 5753: } /* end bool */
5754: } /* end iind = 1 to imx */
1.319 brouard 5755: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5756: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5757:
5758:
5759: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5760: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5761: pstamp(ficresp);
1.335 brouard 5762: if (cptcoveff>0 && j!=0){
1.265 brouard 5763: pstamp(ficresp);
1.251 brouard 5764: printf( "\n#********** Variable ");
5765: fprintf(ficresp, "\n#********** Variable ");
5766: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5767: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5768: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5769: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5770: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5771: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5772: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5773: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5774: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5775: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5776: }else{
1.330 brouard 5777: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5778: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5779: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5780: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5781: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5782: }
5783: }
5784: printf( "**********\n#");
5785: fprintf(ficresp, "**********\n#");
5786: fprintf(ficresphtm, "**********</h3>\n");
5787: fprintf(ficresphtmfr, "**********</h3>\n");
5788: fprintf(ficlog, "**********\n");
5789: }
1.284 brouard 5790: /*
5791: Printing means of quantitative variables if any
5792: */
5793: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5794: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5795: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5796: if(weightopt==1){
5797: printf(" Weighted mean and standard deviation of");
5798: fprintf(ficlog," Weighted mean and standard deviation of");
5799: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5800: }
1.311 brouard 5801: /* mu = \frac{w x}{\sum w}
5802: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5803: */
5804: 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]));
5805: 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]));
5806: 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 5807: }
5808: /* for (z1=1; z1<= nqtveff; z1++) { */
5809: /* for(m=1;m<=lastpass;m++){ */
5810: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5811: /* } */
5812: /* } */
1.283 brouard 5813:
1.251 brouard 5814: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5815: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5816: fprintf(ficresp, " Age");
1.335 brouard 5817: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5818: 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]]);
5819: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5820: }
1.251 brouard 5821: for(i=1; i<=nlstate;i++) {
1.335 brouard 5822: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5823: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5824: }
1.335 brouard 5825: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5826: fprintf(ficresphtm, "\n");
5827:
5828: /* Header of frequency table by age */
5829: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5830: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5831: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5832: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5833: if(s2!=0 && m!=0)
5834: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5835: }
1.226 brouard 5836: }
1.251 brouard 5837: fprintf(ficresphtmfr, "\n");
5838:
5839: /* For each age */
5840: for(iage=iagemin; iage <= iagemax+3; iage++){
5841: fprintf(ficresphtm,"<tr>");
5842: if(iage==iagemax+1){
5843: fprintf(ficlog,"1");
5844: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5845: }else if(iage==iagemax+2){
5846: fprintf(ficlog,"0");
5847: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5848: }else if(iage==iagemax+3){
5849: fprintf(ficlog,"Total");
5850: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5851: }else{
1.240 brouard 5852: if(first==1){
1.251 brouard 5853: first=0;
5854: printf("See log file for details...\n");
5855: }
5856: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5857: fprintf(ficlog,"Age %d", iage);
5858: }
1.265 brouard 5859: for(s1=1; s1 <=nlstate ; s1++){
5860: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5861: pp[s1] += freq[s1][m][iage];
1.251 brouard 5862: }
1.265 brouard 5863: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5864: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5865: pos += freq[s1][m][iage];
5866: if(pp[s1]>=1.e-10){
1.251 brouard 5867: if(first==1){
1.265 brouard 5868: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5869: }
1.265 brouard 5870: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5871: }else{
5872: if(first==1)
1.265 brouard 5873: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5874: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5875: }
5876: }
5877:
1.265 brouard 5878: for(s1=1; s1 <=nlstate ; s1++){
5879: /* posprop[s1]=0; */
5880: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5881: pp[s1] += freq[s1][m][iage];
5882: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5883:
5884: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5885: pos += pp[s1]; /* pos is the total number of transitions until this age */
5886: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5887: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5888: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5889: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5890: }
5891:
5892: /* Writing ficresp */
1.335 brouard 5893: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5894: if( iage <= iagemax){
5895: fprintf(ficresp," %d",iage);
5896: }
5897: }else if( nj==2){
5898: if( iage <= iagemax){
5899: fprintf(ficresp," %d",iage);
1.335 brouard 5900: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5901: }
1.240 brouard 5902: }
1.265 brouard 5903: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5904: if(pos>=1.e-5){
1.251 brouard 5905: if(first==1)
1.265 brouard 5906: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5907: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5908: }else{
5909: if(first==1)
1.265 brouard 5910: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5911: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5912: }
5913: if( iage <= iagemax){
5914: if(pos>=1.e-5){
1.335 brouard 5915: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5916: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5917: }else if( nj==2){
5918: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5919: }
5920: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5921: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5922: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5923: } else{
1.335 brouard 5924: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5925: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5926: }
1.240 brouard 5927: }
1.265 brouard 5928: pospropt[s1] +=posprop[s1];
5929: } /* end loop s1 */
1.251 brouard 5930: /* pospropt=0.; */
1.265 brouard 5931: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5932: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5933: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5934: if(first==1){
1.265 brouard 5935: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5936: }
1.265 brouard 5937: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5938: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5939: }
1.265 brouard 5940: if(s1!=0 && m!=0)
5941: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5942: }
1.265 brouard 5943: } /* end loop s1 */
1.251 brouard 5944: posproptt=0.;
1.265 brouard 5945: for(s1=1; s1 <=nlstate; s1++){
5946: posproptt += pospropt[s1];
1.251 brouard 5947: }
5948: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5949: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5950: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5951: if(iage <= iagemax)
5952: fprintf(ficresp,"\n");
1.240 brouard 5953: }
1.251 brouard 5954: if(first==1)
5955: printf("Others in log...\n");
5956: fprintf(ficlog,"\n");
5957: } /* end loop age iage */
1.265 brouard 5958:
1.251 brouard 5959: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5960: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5961: if(posproptt < 1.e-5){
1.265 brouard 5962: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5963: }else{
1.265 brouard 5964: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5965: }
1.226 brouard 5966: }
1.251 brouard 5967: fprintf(ficresphtm,"</tr>\n");
5968: fprintf(ficresphtm,"</table>\n");
5969: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5970: if(posproptt < 1.e-5){
1.251 brouard 5971: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5972: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5973: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5974: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5975: invalidvarcomb[j1]=1;
1.226 brouard 5976: }else{
1.338 brouard 5977: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5978: invalidvarcomb[j1]=0;
1.226 brouard 5979: }
1.251 brouard 5980: fprintf(ficresphtmfr,"</table>\n");
5981: fprintf(ficlog,"\n");
5982: if(j!=0){
5983: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5984: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5985: for(k=1; k <=(nlstate+ndeath); k++){
5986: if (k != i) {
1.265 brouard 5987: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5988: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5989: if(j1==1){ /* All dummy covariates to zero */
5990: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5991: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5992: printf("%d%d ",i,k);
5993: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5994: 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]));
5995: 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]));
5996: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5997: }
1.253 brouard 5998: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5999: for(iage=iagemin; iage <= iagemax+3; iage++){
6000: x[iage]= (double)iage;
6001: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 6002: /* 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 6003: }
1.268 brouard 6004: /* Some are not finite, but linreg will ignore these ages */
6005: no=0;
1.253 brouard 6006: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 6007: pstart[s1]=b;
6008: pstart[s1-1]=a;
1.252 brouard 6009: }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 */
6010: 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]);
6011: 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 6012: 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 6013: printf("%d%d ",i,k);
6014: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 6015: 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 6016: }else{ /* Other cases, like quantitative fixed or varying covariates */
6017: ;
6018: }
6019: /* printf("%12.7f )", param[i][jj][k]); */
6020: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 6021: s1++;
1.251 brouard 6022: } /* end jj */
6023: } /* end k!= i */
6024: } /* end k */
1.265 brouard 6025: } /* end i, s1 */
1.251 brouard 6026: } /* end j !=0 */
6027: } /* end selected combination of covariate j1 */
6028: if(j==0){ /* We can estimate starting values from the occurences in each case */
6029: printf("#Freqsummary: Starting values for the constants:\n");
6030: fprintf(ficlog,"\n");
1.265 brouard 6031: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 6032: for(k=1; k <=(nlstate+ndeath); k++){
6033: if (k != i) {
6034: printf("%d%d ",i,k);
6035: fprintf(ficlog,"%d%d ",i,k);
6036: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 6037: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 6038: if(jj==1){ /* Age has to be done */
1.265 brouard 6039: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
6040: 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]));
6041: 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 6042: }
6043: /* printf("%12.7f )", param[i][jj][k]); */
6044: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 6045: s1++;
1.250 brouard 6046: }
1.251 brouard 6047: printf("\n");
6048: fprintf(ficlog,"\n");
1.250 brouard 6049: }
6050: }
1.284 brouard 6051: } /* end of state i */
1.251 brouard 6052: printf("#Freqsummary\n");
6053: fprintf(ficlog,"\n");
1.265 brouard 6054: for(s1=-1; s1 <=nlstate+ndeath; s1++){
6055: for(s2=-1; s2 <=nlstate+ndeath; s2++){
6056: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
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]);
6059: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
6060: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
6061: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 6062: /* } */
6063: }
1.265 brouard 6064: } /* end loop s1 */
1.251 brouard 6065:
6066: printf("\n");
6067: fprintf(ficlog,"\n");
6068: } /* end j=0 */
1.249 brouard 6069: } /* end j */
1.252 brouard 6070:
1.253 brouard 6071: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 6072: for(i=1, jk=1; i <=nlstate; i++){
6073: for(j=1; j <=nlstate+ndeath; j++){
6074: if(j!=i){
6075: /*ca[0]= k+'a'-1;ca[1]='\0';*/
6076: printf("%1d%1d",i,j);
6077: fprintf(ficparo,"%1d%1d",i,j);
6078: for(k=1; k<=ncovmodel;k++){
6079: /* printf(" %lf",param[i][j][k]); */
6080: /* fprintf(ficparo," %lf",param[i][j][k]); */
6081: p[jk]=pstart[jk];
6082: printf(" %f ",pstart[jk]);
6083: fprintf(ficparo," %f ",pstart[jk]);
6084: jk++;
6085: }
6086: printf("\n");
6087: fprintf(ficparo,"\n");
6088: }
6089: }
6090: }
6091: } /* end mle=-2 */
1.226 brouard 6092: dateintmean=dateintsum/k2cpt;
1.296 brouard 6093: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6094:
1.226 brouard 6095: fclose(ficresp);
6096: fclose(ficresphtm);
6097: fclose(ficresphtmfr);
1.283 brouard 6098: free_vector(idq,1,nqfveff);
1.226 brouard 6099: free_vector(meanq,1,nqfveff);
1.284 brouard 6100: free_vector(stdq,1,nqfveff);
1.226 brouard 6101: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6102: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6103: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6104: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6105: free_vector(pospropt,1,nlstate);
6106: free_vector(posprop,1,nlstate);
1.251 brouard 6107: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6108: free_vector(pp,1,nlstate);
6109: /* End of freqsummary */
6110: }
1.126 brouard 6111:
1.268 brouard 6112: /* Simple linear regression */
6113: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6114:
6115: /* y=a+bx regression */
6116: double sumx = 0.0; /* sum of x */
6117: double sumx2 = 0.0; /* sum of x**2 */
6118: double sumxy = 0.0; /* sum of x * y */
6119: double sumy = 0.0; /* sum of y */
6120: double sumy2 = 0.0; /* sum of y**2 */
6121: double sume2 = 0.0; /* sum of square or residuals */
6122: double yhat;
6123:
6124: double denom=0;
6125: int i;
6126: int ne=*no;
6127:
6128: for ( i=ifi, ne=0;i<=ila;i++) {
6129: if(!isfinite(x[i]) || !isfinite(y[i])){
6130: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6131: continue;
6132: }
6133: ne=ne+1;
6134: sumx += x[i];
6135: sumx2 += x[i]*x[i];
6136: sumxy += x[i] * y[i];
6137: sumy += y[i];
6138: sumy2 += y[i]*y[i];
6139: denom = (ne * sumx2 - sumx*sumx);
6140: /* 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); */
6141: }
6142:
6143: denom = (ne * sumx2 - sumx*sumx);
6144: if (denom == 0) {
6145: // vertical, slope m is infinity
6146: *b = INFINITY;
6147: *a = 0;
6148: if (r) *r = 0;
6149: return 1;
6150: }
6151:
6152: *b = (ne * sumxy - sumx * sumy) / denom;
6153: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6154: if (r!=NULL) {
6155: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6156: sqrt((sumx2 - sumx*sumx/ne) *
6157: (sumy2 - sumy*sumy/ne));
6158: }
6159: *no=ne;
6160: for ( i=ifi, ne=0;i<=ila;i++) {
6161: if(!isfinite(x[i]) || !isfinite(y[i])){
6162: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6163: continue;
6164: }
6165: ne=ne+1;
6166: yhat = y[i] - *a -*b* x[i];
6167: sume2 += yhat * yhat ;
6168:
6169: denom = (ne * sumx2 - sumx*sumx);
6170: /* 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); */
6171: }
6172: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6173: *sa= *sb * sqrt(sumx2/ne);
6174:
6175: return 0;
6176: }
6177:
1.126 brouard 6178: /************ Prevalence ********************/
1.227 brouard 6179: 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)
6180: {
6181: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6182: in each health status at the date of interview (if between dateprev1 and dateprev2).
6183: We still use firstpass and lastpass as another selection.
6184: */
1.126 brouard 6185:
1.227 brouard 6186: int i, m, jk, j1, bool, z1,j, iv;
6187: int mi; /* Effective wave */
6188: int iage;
6189: double agebegin, ageend;
6190:
6191: double **prop;
6192: double posprop;
6193: double y2; /* in fractional years */
6194: int iagemin, iagemax;
6195: int first; /** to stop verbosity which is redirected to log file */
6196:
6197: iagemin= (int) agemin;
6198: iagemax= (int) agemax;
6199: /*pp=vector(1,nlstate);*/
1.251 brouard 6200: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6201: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6202: j1=0;
1.222 brouard 6203:
1.227 brouard 6204: /*j=cptcoveff;*/
6205: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6206:
1.288 brouard 6207: first=0;
1.335 brouard 6208: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6209: for (i=1; i<=nlstate; i++)
1.251 brouard 6210: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6211: prop[i][iage]=0.0;
6212: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6213: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6214: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6215:
6216: for (i=1; i<=imx; i++) { /* Each individual */
6217: bool=1;
6218: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6219: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6220: m=mw[mi][i];
6221: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6222: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6223: for (z1=1; z1<=cptcoveff; z1++){
6224: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6225: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6226: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6227: bool=0;
6228: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6229: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6230: bool=0;
6231: }
6232: }
6233: if(bool==1){ /* Otherwise we skip that wave/person */
6234: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6235: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6236: if(m >=firstpass && m <=lastpass){
6237: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6238: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6239: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6240: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6241: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6242: 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);
6243: exit(1);
6244: }
6245: if (s[m][i]>0 && s[m][i]<=nlstate) {
6246: /*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]]);*/
6247: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6248: prop[s[m][i]][iagemax+3] += weight[i];
6249: } /* end valid statuses */
6250: } /* end selection of dates */
6251: } /* end selection of waves */
6252: } /* end bool */
6253: } /* end wave */
6254: } /* end individual */
6255: for(i=iagemin; i <= iagemax+3; i++){
6256: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6257: posprop += prop[jk][i];
6258: }
6259:
6260: for(jk=1; jk <=nlstate ; jk++){
6261: if( i <= iagemax){
6262: if(posprop>=1.e-5){
6263: probs[i][jk][j1]= prop[jk][i]/posprop;
6264: } else{
1.288 brouard 6265: if(!first){
6266: first=1;
1.266 brouard 6267: 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]);
6268: }else{
1.288 brouard 6269: 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 6270: }
6271: }
6272: }
6273: }/* end jk */
6274: }/* end i */
1.222 brouard 6275: /*} *//* end i1 */
1.227 brouard 6276: } /* end j1 */
1.222 brouard 6277:
1.227 brouard 6278: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6279: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6280: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6281: } /* End of prevalence */
1.126 brouard 6282:
6283: /************* Waves Concatenation ***************/
6284:
6285: 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)
6286: {
1.298 brouard 6287: /* 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 6288: Death is a valid wave (if date is known).
6289: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6290: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6291: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6292: */
1.126 brouard 6293:
1.224 brouard 6294: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6295: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6296: double sum=0., jmean=0.;*/
1.224 brouard 6297: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6298: int j, k=0,jk, ju, jl;
6299: double sum=0.;
6300: first=0;
1.214 brouard 6301: firstwo=0;
1.217 brouard 6302: firsthree=0;
1.218 brouard 6303: firstfour=0;
1.164 brouard 6304: jmin=100000;
1.126 brouard 6305: jmax=-1;
6306: jmean=0.;
1.224 brouard 6307:
6308: /* Treating live states */
1.214 brouard 6309: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6310: mi=0; /* First valid wave */
1.227 brouard 6311: mli=0; /* Last valid wave */
1.309 brouard 6312: m=firstpass; /* Loop on waves */
6313: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6314: 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 */
6315: mli=m-1;/* mw[++mi][i]=m-1; */
6316: }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 6317: 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 6318: mli=m;
1.224 brouard 6319: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6320: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6321: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6322: }
1.309 brouard 6323: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6324: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6325: break;
1.224 brouard 6326: #else
1.317 brouard 6327: 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 6328: if(firsthree == 0){
1.302 brouard 6329: 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 6330: firsthree=1;
1.317 brouard 6331: }else if(firsthree >=1 && firsthree < 10){
6332: 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);
6333: firsthree++;
6334: }else if(firsthree == 10){
6335: printf("Information, too many Information flags: no more reported to log either\n");
6336: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6337: firsthree++;
6338: }else{
6339: firsthree++;
1.227 brouard 6340: }
1.309 brouard 6341: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6342: mli=m;
6343: }
6344: if(s[m][i]==-2){ /* Vital status is really unknown */
6345: nbwarn++;
1.309 brouard 6346: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6347: 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);
6348: 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);
6349: }
6350: break;
6351: }
6352: break;
1.224 brouard 6353: #endif
1.227 brouard 6354: }/* End m >= lastpass */
1.126 brouard 6355: }/* end while */
1.224 brouard 6356:
1.227 brouard 6357: /* 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 6358: /* After last pass */
1.224 brouard 6359: /* Treating death states */
1.214 brouard 6360: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6361: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6362: /* } */
1.126 brouard 6363: mi++; /* Death is another wave */
6364: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6365: /* Only death is a correct wave */
1.126 brouard 6366: mw[mi][i]=m;
1.257 brouard 6367: } /* else not in a death state */
1.224 brouard 6368: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6369: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6370: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6371: 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 6372: nbwarn++;
6373: if(firstfiv==0){
1.309 brouard 6374: 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 6375: firstfiv=1;
6376: }else{
1.309 brouard 6377: 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 6378: }
1.309 brouard 6379: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6380: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6381: nberr++;
6382: if(firstwo==0){
1.309 brouard 6383: 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 6384: firstwo=1;
6385: }
1.309 brouard 6386: 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 6387: }
1.257 brouard 6388: }else{ /* if date of interview is unknown */
1.227 brouard 6389: /* death is known but not confirmed by death status at any wave */
6390: if(firstfour==0){
1.309 brouard 6391: 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 6392: firstfour=1;
6393: }
1.309 brouard 6394: 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 6395: }
1.224 brouard 6396: } /* end if date of death is known */
6397: #endif
1.309 brouard 6398: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6399: /* wav[i]=mw[mi][i]; */
1.126 brouard 6400: if(mi==0){
6401: nbwarn++;
6402: if(first==0){
1.227 brouard 6403: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6404: first=1;
1.126 brouard 6405: }
6406: if(first==1){
1.227 brouard 6407: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6408: }
6409: } /* end mi==0 */
6410: } /* End individuals */
1.214 brouard 6411: /* wav and mw are no more changed */
1.223 brouard 6412:
1.317 brouard 6413: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6414: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6415:
6416:
1.126 brouard 6417: for(i=1; i<=imx; i++){
6418: for(mi=1; mi<wav[i];mi++){
6419: if (stepm <=0)
1.227 brouard 6420: dh[mi][i]=1;
1.126 brouard 6421: else{
1.260 brouard 6422: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6423: if (agedc[i] < 2*AGESUP) {
6424: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6425: if(j==0) j=1; /* Survives at least one month after exam */
6426: else if(j<0){
6427: nberr++;
6428: 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]);
6429: j=1; /* Temporary Dangerous patch */
6430: 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);
6431: 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]);
6432: 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);
6433: }
6434: k=k+1;
6435: if (j >= jmax){
6436: jmax=j;
6437: ijmax=i;
6438: }
6439: if (j <= jmin){
6440: jmin=j;
6441: ijmin=i;
6442: }
6443: sum=sum+j;
6444: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6445: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6446: }
6447: }
6448: else{
6449: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6450: /* 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 6451:
1.227 brouard 6452: k=k+1;
6453: if (j >= jmax) {
6454: jmax=j;
6455: ijmax=i;
6456: }
6457: else if (j <= jmin){
6458: jmin=j;
6459: ijmin=i;
6460: }
6461: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6462: /*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]);*/
6463: if(j<0){
6464: nberr++;
6465: 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]);
6466: 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]);
6467: }
6468: sum=sum+j;
6469: }
6470: jk= j/stepm;
6471: jl= j -jk*stepm;
6472: ju= j -(jk+1)*stepm;
6473: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6474: if(jl==0){
6475: dh[mi][i]=jk;
6476: bh[mi][i]=0;
6477: }else{ /* We want a negative bias in order to only have interpolation ie
6478: * to avoid the price of an extra matrix product in likelihood */
6479: dh[mi][i]=jk+1;
6480: bh[mi][i]=ju;
6481: }
6482: }else{
6483: if(jl <= -ju){
6484: dh[mi][i]=jk;
6485: bh[mi][i]=jl; /* bias is positive if real duration
6486: * is higher than the multiple of stepm and negative otherwise.
6487: */
6488: }
6489: else{
6490: dh[mi][i]=jk+1;
6491: bh[mi][i]=ju;
6492: }
6493: if(dh[mi][i]==0){
6494: dh[mi][i]=1; /* At least one step */
6495: bh[mi][i]=ju; /* At least one step */
6496: /* 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);*/
6497: }
6498: } /* end if mle */
1.126 brouard 6499: }
6500: } /* end wave */
6501: }
6502: jmean=sum/k;
6503: 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 6504: 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 6505: }
1.126 brouard 6506:
6507: /*********** Tricode ****************************/
1.220 brouard 6508: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6509: {
6510: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6511: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6512: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6513: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6514: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6515: */
1.130 brouard 6516:
1.242 brouard 6517: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6518: int modmaxcovj=0; /* Modality max of covariates j */
6519: int cptcode=0; /* Modality max of covariates j */
6520: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6521:
6522:
1.242 brouard 6523: /* cptcoveff=0; */
6524: /* *cptcov=0; */
1.126 brouard 6525:
1.242 brouard 6526: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6527: for (k=1; k <= maxncov; k++)
6528: for(j=1; j<=2; j++)
6529: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6530:
1.242 brouard 6531: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6532: 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 6533: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6534: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 6535: 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 6536: switch(Fixed[k]) {
6537: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6538: modmaxcovj=0;
6539: modmincovj=0;
1.242 brouard 6540: 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 6541: /* 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 6542: ij=(int)(covar[Tvar[k]][i]);
6543: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6544: * If product of Vn*Vm, still boolean *:
6545: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6546: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6547: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6548: modality of the nth covariate of individual i. */
6549: if (ij > modmaxcovj)
6550: modmaxcovj=ij;
6551: else if (ij < modmincovj)
6552: modmincovj=ij;
1.287 brouard 6553: if (ij <0 || ij >1 ){
1.311 brouard 6554: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6555: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6556: fflush(ficlog);
6557: exit(1);
1.287 brouard 6558: }
6559: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6560: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6561: exit(1);
6562: }else
6563: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6564: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6565: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6566: /* getting the maximum value of the modality of the covariate
6567: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6568: female ies 1, then modmaxcovj=1.
6569: */
6570: } /* end for loop on individuals i */
6571: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6572: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6573: cptcode=modmaxcovj;
6574: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6575: /*for (i=0; i<=cptcode; i++) {*/
6576: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6577: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6578: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6579: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6580: if( j != -1){
6581: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6582: covariate for which somebody answered excluding
6583: undefined. Usually 2: 0 and 1. */
6584: }
6585: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6586: covariate for which somebody answered including
6587: undefined. Usually 3: -1, 0 and 1. */
6588: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6589: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6590: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6591:
1.242 brouard 6592: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6593: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6594: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6595: /* modmincovj=3; modmaxcovj = 7; */
6596: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6597: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6598: /* defining two dummy variables: variables V1_1 and V1_2.*/
6599: /* nbcode[Tvar[j]][ij]=k; */
6600: /* nbcode[Tvar[j]][1]=0; */
6601: /* nbcode[Tvar[j]][2]=1; */
6602: /* nbcode[Tvar[j]][3]=2; */
6603: /* To be continued (not working yet). */
6604: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6605:
6606: /* 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*/
6607: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6608: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6609: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6610: /*, could be restored in the future */
6611: 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 6612: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6613: break;
6614: }
6615: ij++;
1.287 brouard 6616: 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 6617: cptcode = ij; /* New max modality for covar j */
6618: } /* end of loop on modality i=-1 to 1 or more */
6619: break;
6620: case 1: /* Testing on varying covariate, could be simple and
6621: * should look at waves or product of fixed *
6622: * varying. No time to test -1, assuming 0 and 1 only */
6623: ij=0;
6624: for(i=0; i<=1;i++){
6625: nbcode[Tvar[k]][++ij]=i;
6626: }
6627: break;
6628: default:
6629: break;
6630: } /* end switch */
6631: } /* end dummy test */
1.349 brouard 6632: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6633: 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 6634: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6635: printf("Error k=%d \n",k);
6636: exit(1);
6637: }
1.311 brouard 6638: if(isnan(covar[Tvar[k]][i])){
6639: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6640: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6641: fflush(ficlog);
6642: exit(1);
6643: }
6644: }
1.335 brouard 6645: } /* end Quanti */
1.287 brouard 6646: } /* 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 6647:
6648: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6649: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6650: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6651: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6652: 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 */
6653: 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 */
6654: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6655: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6656:
6657: ij=0;
6658: /* 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 6659: 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 */
6660: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6661: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6662: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6663: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6664: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6665: /* 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 6666: /* If product not in single variable we don't print results */
6667: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6668: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6669: /* k= 1 2 3 4 5 6 7 8 9 */
6670: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6671: /* ij 1 2 3 */
6672: /* Tvaraff[ij]= 4 3 1 */
6673: /* Tmodelind[ij]=2 3 9 */
6674: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6675: 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*/
6676: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6677: 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 */
6678: if(Fixed[k]!=0)
6679: anyvaryingduminmodel=1;
6680: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6681: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6682: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6683: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6684: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6685: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6686: }
6687: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6688: /* ij--; */
6689: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6690: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6691: * because they can be excluded from the model and real
6692: * if in the model but excluded because missing values, but how to get k from ij?*/
6693: for(j=ij+1; j<= cptcovt; j++){
6694: Tvaraff[j]=0;
6695: Tmodelind[j]=0;
6696: }
6697: for(j=ntveff+1; j<= cptcovt; j++){
6698: TmodelInvind[j]=0;
6699: }
6700: /* To be sorted */
6701: ;
6702: }
1.126 brouard 6703:
1.145 brouard 6704:
1.126 brouard 6705: /*********** Health Expectancies ****************/
6706:
1.235 brouard 6707: 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 6708:
6709: {
6710: /* Health expectancies, no variances */
1.329 brouard 6711: /* cij is the combination in the list of combination of dummy covariates */
6712: /* strstart is a string of time at start of computing */
1.164 brouard 6713: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6714: int nhstepma, nstepma; /* Decreasing with age */
6715: double age, agelim, hf;
6716: double ***p3mat;
6717: double eip;
6718:
1.238 brouard 6719: /* pstamp(ficreseij); */
1.126 brouard 6720: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6721: fprintf(ficreseij,"# Age");
6722: for(i=1; i<=nlstate;i++){
6723: for(j=1; j<=nlstate;j++){
6724: fprintf(ficreseij," e%1d%1d ",i,j);
6725: }
6726: fprintf(ficreseij," e%1d. ",i);
6727: }
6728: fprintf(ficreseij,"\n");
6729:
6730:
6731: if(estepm < stepm){
6732: printf ("Problem %d lower than %d\n",estepm, stepm);
6733: }
6734: else hstepm=estepm;
6735: /* We compute the life expectancy from trapezoids spaced every estepm months
6736: * This is mainly to measure the difference between two models: for example
6737: * if stepm=24 months pijx are given only every 2 years and by summing them
6738: * we are calculating an estimate of the Life Expectancy assuming a linear
6739: * progression in between and thus overestimating or underestimating according
6740: * to the curvature of the survival function. If, for the same date, we
6741: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6742: * to compare the new estimate of Life expectancy with the same linear
6743: * hypothesis. A more precise result, taking into account a more precise
6744: * curvature will be obtained if estepm is as small as stepm. */
6745:
6746: /* For example we decided to compute the life expectancy with the smallest unit */
6747: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6748: nhstepm is the number of hstepm from age to agelim
6749: nstepm is the number of stepm from age to agelin.
1.270 brouard 6750: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6751: and note for a fixed period like estepm months */
6752: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6753: survival function given by stepm (the optimization length). Unfortunately it
6754: means that if the survival funtion is printed only each two years of age and if
6755: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6756: results. So we changed our mind and took the option of the best precision.
6757: */
6758: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6759:
6760: agelim=AGESUP;
6761: /* If stepm=6 months */
6762: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6763: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6764:
6765: /* nhstepm age range expressed in number of stepm */
6766: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6767: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6768: /* if (stepm >= YEARM) hstepm=1;*/
6769: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6770: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6771:
6772: for (age=bage; age<=fage; age ++){
6773: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6774: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6775: /* if (stepm >= YEARM) hstepm=1;*/
6776: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6777:
6778: /* If stepm=6 months */
6779: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6780: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6781: /* 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 6782: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6783:
6784: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6785:
6786: printf("%d|",(int)age);fflush(stdout);
6787: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6788:
6789: /* Computing expectancies */
6790: for(i=1; i<=nlstate;i++)
6791: for(j=1; j<=nlstate;j++)
6792: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6793: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6794:
6795: /* 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]);*/
6796:
6797: }
6798:
6799: fprintf(ficreseij,"%3.0f",age );
6800: for(i=1; i<=nlstate;i++){
6801: eip=0;
6802: for(j=1; j<=nlstate;j++){
6803: eip +=eij[i][j][(int)age];
6804: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6805: }
6806: fprintf(ficreseij,"%9.4f", eip );
6807: }
6808: fprintf(ficreseij,"\n");
6809:
6810: }
6811: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6812: printf("\n");
6813: fprintf(ficlog,"\n");
6814:
6815: }
6816:
1.235 brouard 6817: 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 6818:
6819: {
6820: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6821: to initial status i, ei. .
1.126 brouard 6822: */
1.336 brouard 6823: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6824: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6825: int nhstepma, nstepma; /* Decreasing with age */
6826: double age, agelim, hf;
6827: double ***p3matp, ***p3matm, ***varhe;
6828: double **dnewm,**doldm;
6829: double *xp, *xm;
6830: double **gp, **gm;
6831: double ***gradg, ***trgradg;
6832: int theta;
6833:
6834: double eip, vip;
6835:
6836: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6837: xp=vector(1,npar);
6838: xm=vector(1,npar);
6839: dnewm=matrix(1,nlstate*nlstate,1,npar);
6840: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6841:
6842: pstamp(ficresstdeij);
6843: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6844: fprintf(ficresstdeij,"# Age");
6845: for(i=1; i<=nlstate;i++){
6846: for(j=1; j<=nlstate;j++)
6847: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6848: fprintf(ficresstdeij," e%1d. ",i);
6849: }
6850: fprintf(ficresstdeij,"\n");
6851:
6852: pstamp(ficrescveij);
6853: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6854: fprintf(ficrescveij,"# Age");
6855: for(i=1; i<=nlstate;i++)
6856: for(j=1; j<=nlstate;j++){
6857: cptj= (j-1)*nlstate+i;
6858: for(i2=1; i2<=nlstate;i2++)
6859: for(j2=1; j2<=nlstate;j2++){
6860: cptj2= (j2-1)*nlstate+i2;
6861: if(cptj2 <= cptj)
6862: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6863: }
6864: }
6865: fprintf(ficrescveij,"\n");
6866:
6867: if(estepm < stepm){
6868: printf ("Problem %d lower than %d\n",estepm, stepm);
6869: }
6870: else hstepm=estepm;
6871: /* We compute the life expectancy from trapezoids spaced every estepm months
6872: * This is mainly to measure the difference between two models: for example
6873: * if stepm=24 months pijx are given only every 2 years and by summing them
6874: * we are calculating an estimate of the Life Expectancy assuming a linear
6875: * progression in between and thus overestimating or underestimating according
6876: * to the curvature of the survival function. If, for the same date, we
6877: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6878: * to compare the new estimate of Life expectancy with the same linear
6879: * hypothesis. A more precise result, taking into account a more precise
6880: * curvature will be obtained if estepm is as small as stepm. */
6881:
6882: /* For example we decided to compute the life expectancy with the smallest unit */
6883: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6884: nhstepm is the number of hstepm from age to agelim
6885: nstepm is the number of stepm from age to agelin.
6886: Look at hpijx to understand the reason of that which relies in memory size
6887: and note for a fixed period like estepm months */
6888: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6889: survival function given by stepm (the optimization length). Unfortunately it
6890: means that if the survival funtion is printed only each two years of age and if
6891: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6892: results. So we changed our mind and took the option of the best precision.
6893: */
6894: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6895:
6896: /* If stepm=6 months */
6897: /* nhstepm age range expressed in number of stepm */
6898: agelim=AGESUP;
6899: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6900: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6901: /* if (stepm >= YEARM) hstepm=1;*/
6902: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6903:
6904: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6905: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6906: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6907: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6908: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6909: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6910:
6911: for (age=bage; age<=fage; age ++){
6912: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6913: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6914: /* if (stepm >= YEARM) hstepm=1;*/
6915: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6916:
1.126 brouard 6917: /* If stepm=6 months */
6918: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6919: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6920:
6921: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6922:
1.126 brouard 6923: /* Computing Variances of health expectancies */
6924: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6925: decrease memory allocation */
6926: for(theta=1; theta <=npar; theta++){
6927: for(i=1; i<=npar; i++){
1.222 brouard 6928: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6929: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6930: }
1.235 brouard 6931: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6932: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6933:
1.126 brouard 6934: for(j=1; j<= nlstate; j++){
1.222 brouard 6935: for(i=1; i<=nlstate; i++){
6936: for(h=0; h<=nhstepm-1; h++){
6937: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6938: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6939: }
6940: }
1.126 brouard 6941: }
1.218 brouard 6942:
1.126 brouard 6943: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6944: for(h=0; h<=nhstepm-1; h++){
6945: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6946: }
1.126 brouard 6947: }/* End theta */
6948:
6949:
6950: for(h=0; h<=nhstepm-1; h++)
6951: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6952: for(theta=1; theta <=npar; theta++)
6953: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6954:
1.218 brouard 6955:
1.222 brouard 6956: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6957: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6958: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6959:
1.222 brouard 6960: printf("%d|",(int)age);fflush(stdout);
6961: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6962: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6963: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6964: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6965: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6966: for(ij=1;ij<=nlstate*nlstate;ij++)
6967: for(ji=1;ji<=nlstate*nlstate;ji++)
6968: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6969: }
6970: }
1.320 brouard 6971: /* if((int)age ==50){ */
6972: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6973: /* } */
1.126 brouard 6974: /* Computing expectancies */
1.235 brouard 6975: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6976: for(i=1; i<=nlstate;i++)
6977: for(j=1; j<=nlstate;j++)
1.222 brouard 6978: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6979: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6980:
1.222 brouard 6981: /* 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 6982:
1.222 brouard 6983: }
1.269 brouard 6984:
6985: /* Standard deviation of expectancies ij */
1.126 brouard 6986: fprintf(ficresstdeij,"%3.0f",age );
6987: for(i=1; i<=nlstate;i++){
6988: eip=0.;
6989: vip=0.;
6990: for(j=1; j<=nlstate;j++){
1.222 brouard 6991: eip += eij[i][j][(int)age];
6992: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6993: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6994: 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 6995: }
6996: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6997: }
6998: fprintf(ficresstdeij,"\n");
1.218 brouard 6999:
1.269 brouard 7000: /* Variance of expectancies ij */
1.126 brouard 7001: fprintf(ficrescveij,"%3.0f",age );
7002: for(i=1; i<=nlstate;i++)
7003: for(j=1; j<=nlstate;j++){
1.222 brouard 7004: cptj= (j-1)*nlstate+i;
7005: for(i2=1; i2<=nlstate;i2++)
7006: for(j2=1; j2<=nlstate;j2++){
7007: cptj2= (j2-1)*nlstate+i2;
7008: if(cptj2 <= cptj)
7009: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
7010: }
1.126 brouard 7011: }
7012: fprintf(ficrescveij,"\n");
1.218 brouard 7013:
1.126 brouard 7014: }
7015: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
7016: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
7017: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
7018: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
7019: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7020: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7021: printf("\n");
7022: fprintf(ficlog,"\n");
1.218 brouard 7023:
1.126 brouard 7024: free_vector(xm,1,npar);
7025: free_vector(xp,1,npar);
7026: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
7027: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
7028: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
7029: }
1.218 brouard 7030:
1.126 brouard 7031: /************ Variance ******************/
1.235 brouard 7032: 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 7033: {
1.279 brouard 7034: /** Variance of health expectancies
7035: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
7036: * double **newm;
7037: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
7038: */
1.218 brouard 7039:
7040: /* int movingaverage(); */
7041: double **dnewm,**doldm;
7042: double **dnewmp,**doldmp;
7043: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 7044: int first=0;
1.218 brouard 7045: int k;
7046: double *xp;
1.279 brouard 7047: double **gp, **gm; /**< for var eij */
7048: double ***gradg, ***trgradg; /**< for var eij */
7049: double **gradgp, **trgradgp; /**< for var p point j */
7050: double *gpp, *gmp; /**< for var p point j */
7051: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 7052: double ***p3mat;
7053: double age,agelim, hf;
7054: /* double ***mobaverage; */
7055: int theta;
7056: char digit[4];
7057: char digitp[25];
7058:
7059: char fileresprobmorprev[FILENAMELENGTH];
7060:
7061: if(popbased==1){
7062: if(mobilav!=0)
7063: strcpy(digitp,"-POPULBASED-MOBILAV_");
7064: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
7065: }
7066: else
7067: strcpy(digitp,"-STABLBASED_");
1.126 brouard 7068:
1.218 brouard 7069: /* if (mobilav!=0) { */
7070: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7071: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
7072: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
7073: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
7074: /* } */
7075: /* } */
7076:
7077: strcpy(fileresprobmorprev,"PRMORPREV-");
7078: sprintf(digit,"%-d",ij);
7079: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7080: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7081: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7082: strcat(fileresprobmorprev,fileresu);
7083: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7084: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7085: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7086: }
7087: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7088: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7089: pstamp(ficresprobmorprev);
7090: 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 7091: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7092:
7093: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7094: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7095: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7096: /* } */
7097: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7098: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7099: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7100: }
1.337 brouard 7101: /* for(j=1;j<=cptcoveff;j++) */
7102: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7103: fprintf(ficresprobmorprev,"\n");
7104:
1.218 brouard 7105: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7106: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7107: fprintf(ficresprobmorprev," p.%-d SE",j);
7108: for(i=1; i<=nlstate;i++)
7109: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7110: }
7111: fprintf(ficresprobmorprev,"\n");
7112:
7113: fprintf(ficgp,"\n# Routine varevsij");
7114: fprintf(ficgp,"\nunset title \n");
7115: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7116: 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");
7117: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7118:
1.218 brouard 7119: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7120: pstamp(ficresvij);
7121: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7122: if(popbased==1)
7123: 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);
7124: else
7125: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7126: fprintf(ficresvij,"# Age");
7127: for(i=1; i<=nlstate;i++)
7128: for(j=1; j<=nlstate;j++)
7129: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7130: fprintf(ficresvij,"\n");
7131:
7132: xp=vector(1,npar);
7133: dnewm=matrix(1,nlstate,1,npar);
7134: doldm=matrix(1,nlstate,1,nlstate);
7135: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7136: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7137:
7138: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7139: gpp=vector(nlstate+1,nlstate+ndeath);
7140: gmp=vector(nlstate+1,nlstate+ndeath);
7141: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7142:
1.218 brouard 7143: if(estepm < stepm){
7144: printf ("Problem %d lower than %d\n",estepm, stepm);
7145: }
7146: else hstepm=estepm;
7147: /* For example we decided to compute the life expectancy with the smallest unit */
7148: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7149: nhstepm is the number of hstepm from age to agelim
7150: nstepm is the number of stepm from age to agelim.
7151: Look at function hpijx to understand why because of memory size limitations,
7152: we decided (b) to get a life expectancy respecting the most precise curvature of the
7153: survival function given by stepm (the optimization length). Unfortunately it
7154: means that if the survival funtion is printed every two years of age and if
7155: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7156: results. So we changed our mind and took the option of the best precision.
7157: */
7158: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7159: agelim = AGESUP;
7160: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7161: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7162: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7163: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7164: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7165: gp=matrix(0,nhstepm,1,nlstate);
7166: gm=matrix(0,nhstepm,1,nlstate);
7167:
7168:
7169: for(theta=1; theta <=npar; theta++){
7170: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7171: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7172: }
1.279 brouard 7173: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7174: * returns into prlim .
1.288 brouard 7175: */
1.242 brouard 7176: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7177:
7178: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7179: if (popbased==1) {
7180: if(mobilav ==0){
7181: for(i=1; i<=nlstate;i++)
7182: prlim[i][i]=probs[(int)age][i][ij];
7183: }else{ /* mobilav */
7184: for(i=1; i<=nlstate;i++)
7185: prlim[i][i]=mobaverage[(int)age][i][ij];
7186: }
7187: }
1.295 brouard 7188: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7189: */
7190: 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 7191: /**< 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 7192: * at horizon h in state j including mortality.
7193: */
1.218 brouard 7194: for(j=1; j<= nlstate; j++){
7195: for(h=0; h<=nhstepm; h++){
7196: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7197: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7198: }
7199: }
1.279 brouard 7200: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7201: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7202: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7203: */
7204: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7205: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7206: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7207: }
7208:
7209: /* Again with minus shift */
1.218 brouard 7210:
7211: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7212: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7213:
1.242 brouard 7214: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7215:
7216: if (popbased==1) {
7217: if(mobilav ==0){
7218: for(i=1; i<=nlstate;i++)
7219: prlim[i][i]=probs[(int)age][i][ij];
7220: }else{ /* mobilav */
7221: for(i=1; i<=nlstate;i++)
7222: prlim[i][i]=mobaverage[(int)age][i][ij];
7223: }
7224: }
7225:
1.235 brouard 7226: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7227:
7228: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7229: for(h=0; h<=nhstepm; h++){
7230: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7231: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7232: }
7233: }
7234: /* This for computing probability of death (h=1 means
7235: computed over hstepm matrices product = hstepm*stepm months)
7236: as a weighted average of prlim.
7237: */
7238: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7239: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7240: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7241: }
1.279 brouard 7242: /* end shifting computations */
7243:
7244: /**< Computing gradient matrix at horizon h
7245: */
1.218 brouard 7246: for(j=1; j<= nlstate; j++) /* vareij */
7247: for(h=0; h<=nhstepm; h++){
7248: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7249: }
1.279 brouard 7250: /**< Gradient of overall mortality p.3 (or p.j)
7251: */
7252: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7253: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7254: }
7255:
7256: } /* End theta */
1.279 brouard 7257:
7258: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7259: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7260:
7261: for(h=0; h<=nhstepm; h++) /* veij */
7262: for(j=1; j<=nlstate;j++)
7263: for(theta=1; theta <=npar; theta++)
7264: trgradg[h][j][theta]=gradg[h][theta][j];
7265:
7266: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7267: for(theta=1; theta <=npar; theta++)
7268: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7269: /**< as well as its transposed matrix
7270: */
1.218 brouard 7271:
7272: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7273: for(i=1;i<=nlstate;i++)
7274: for(j=1;j<=nlstate;j++)
7275: vareij[i][j][(int)age] =0.;
1.279 brouard 7276:
7277: /* Computing trgradg by matcov by gradg at age and summing over h
7278: * and k (nhstepm) formula 15 of article
7279: * Lievre-Brouard-Heathcote
7280: */
7281:
1.218 brouard 7282: for(h=0;h<=nhstepm;h++){
7283: for(k=0;k<=nhstepm;k++){
7284: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7285: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7286: for(i=1;i<=nlstate;i++)
7287: for(j=1;j<=nlstate;j++)
7288: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7289: }
7290: }
7291:
1.279 brouard 7292: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7293: * p.j overall mortality formula 49 but computed directly because
7294: * we compute the grad (wix pijx) instead of grad (pijx),even if
7295: * wix is independent of theta.
7296: */
1.218 brouard 7297: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7298: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7299: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7300: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7301: varppt[j][i]=doldmp[j][i];
7302: /* end ppptj */
7303: /* x centered again */
7304:
1.242 brouard 7305: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7306:
7307: if (popbased==1) {
7308: if(mobilav ==0){
7309: for(i=1; i<=nlstate;i++)
7310: prlim[i][i]=probs[(int)age][i][ij];
7311: }else{ /* mobilav */
7312: for(i=1; i<=nlstate;i++)
7313: prlim[i][i]=mobaverage[(int)age][i][ij];
7314: }
7315: }
7316:
7317: /* This for computing probability of death (h=1 means
7318: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7319: as a weighted average of prlim.
7320: */
1.235 brouard 7321: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7322: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7323: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7324: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7325: }
7326: /* end probability of death */
7327:
7328: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7329: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7330: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7331: for(i=1; i<=nlstate;i++){
7332: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7333: }
7334: }
7335: fprintf(ficresprobmorprev,"\n");
7336:
7337: fprintf(ficresvij,"%.0f ",age );
7338: for(i=1; i<=nlstate;i++)
7339: for(j=1; j<=nlstate;j++){
7340: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7341: }
7342: fprintf(ficresvij,"\n");
7343: free_matrix(gp,0,nhstepm,1,nlstate);
7344: free_matrix(gm,0,nhstepm,1,nlstate);
7345: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7346: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7347: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7348: } /* End age */
7349: free_vector(gpp,nlstate+1,nlstate+ndeath);
7350: free_vector(gmp,nlstate+1,nlstate+ndeath);
7351: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7352: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7353: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7354: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7355: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7356: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7357: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7358: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7359: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7360: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7361: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7362: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7363: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7364: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7365: 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);
7366: /* 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 7367: */
1.218 brouard 7368: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7369: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7370:
1.218 brouard 7371: free_vector(xp,1,npar);
7372: free_matrix(doldm,1,nlstate,1,nlstate);
7373: free_matrix(dnewm,1,nlstate,1,npar);
7374: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7375: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7376: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7377: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7378: fclose(ficresprobmorprev);
7379: fflush(ficgp);
7380: fflush(fichtm);
7381: } /* end varevsij */
1.126 brouard 7382:
7383: /************ Variance of prevlim ******************/
1.269 brouard 7384: 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 7385: {
1.205 brouard 7386: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7387: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7388:
1.268 brouard 7389: double **dnewmpar,**doldm;
1.126 brouard 7390: int i, j, nhstepm, hstepm;
7391: double *xp;
7392: double *gp, *gm;
7393: double **gradg, **trgradg;
1.208 brouard 7394: double **mgm, **mgp;
1.126 brouard 7395: double age,agelim;
7396: int theta;
7397:
7398: pstamp(ficresvpl);
1.288 brouard 7399: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7400: fprintf(ficresvpl,"# Age ");
7401: if(nresult >=1)
7402: fprintf(ficresvpl," Result# ");
1.126 brouard 7403: for(i=1; i<=nlstate;i++)
7404: fprintf(ficresvpl," %1d-%1d",i,i);
7405: fprintf(ficresvpl,"\n");
7406:
7407: xp=vector(1,npar);
1.268 brouard 7408: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7409: doldm=matrix(1,nlstate,1,nlstate);
7410:
7411: hstepm=1*YEARM; /* Every year of age */
7412: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7413: agelim = AGESUP;
7414: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7415: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7416: if (stepm >= YEARM) hstepm=1;
7417: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7418: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7419: mgp=matrix(1,npar,1,nlstate);
7420: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7421: gp=vector(1,nlstate);
7422: gm=vector(1,nlstate);
7423:
7424: for(theta=1; theta <=npar; theta++){
7425: for(i=1; i<=npar; i++){ /* Computes gradient */
7426: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7427: }
1.288 brouard 7428: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7429: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7430: /* else */
7431: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7432: for(i=1;i<=nlstate;i++){
1.126 brouard 7433: gp[i] = prlim[i][i];
1.208 brouard 7434: mgp[theta][i] = prlim[i][i];
7435: }
1.126 brouard 7436: for(i=1; i<=npar; i++) /* Computes gradient */
7437: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7438: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7439: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7440: /* else */
7441: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7442: for(i=1;i<=nlstate;i++){
1.126 brouard 7443: gm[i] = prlim[i][i];
1.208 brouard 7444: mgm[theta][i] = prlim[i][i];
7445: }
1.126 brouard 7446: for(i=1;i<=nlstate;i++)
7447: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7448: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7449: } /* End theta */
7450:
7451: trgradg =matrix(1,nlstate,1,npar);
7452:
7453: for(j=1; j<=nlstate;j++)
7454: for(theta=1; theta <=npar; theta++)
7455: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7456: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7457: /* printf("\nmgm mgp %d ",(int)age); */
7458: /* for(j=1; j<=nlstate;j++){ */
7459: /* printf(" %d ",j); */
7460: /* for(theta=1; theta <=npar; theta++) */
7461: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7462: /* printf("\n "); */
7463: /* } */
7464: /* } */
7465: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7466: /* printf("\n gradg %d ",(int)age); */
7467: /* for(j=1; j<=nlstate;j++){ */
7468: /* printf("%d ",j); */
7469: /* for(theta=1; theta <=npar; theta++) */
7470: /* printf("%d %lf ",theta,gradg[theta][j]); */
7471: /* printf("\n "); */
7472: /* } */
7473: /* } */
1.126 brouard 7474:
7475: for(i=1;i<=nlstate;i++)
7476: varpl[i][(int)age] =0.;
1.209 brouard 7477: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
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: }else{
1.268 brouard 7481: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7482: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7483: }
1.126 brouard 7484: for(i=1;i<=nlstate;i++)
7485: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7486:
7487: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7488: if(nresult >=1)
7489: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7490: for(i=1; i<=nlstate;i++){
1.126 brouard 7491: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7492: /* for(j=1;j<=nlstate;j++) */
7493: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7494: }
1.126 brouard 7495: fprintf(ficresvpl,"\n");
7496: free_vector(gp,1,nlstate);
7497: free_vector(gm,1,nlstate);
1.208 brouard 7498: free_matrix(mgm,1,npar,1,nlstate);
7499: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7500: free_matrix(gradg,1,npar,1,nlstate);
7501: free_matrix(trgradg,1,nlstate,1,npar);
7502: } /* End age */
7503:
7504: free_vector(xp,1,npar);
7505: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7506: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7507:
7508: }
7509:
7510:
7511: /************ Variance of backprevalence limit ******************/
1.269 brouard 7512: 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 7513: {
7514: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7515: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7516:
7517: double **dnewmpar,**doldm;
7518: int i, j, nhstepm, hstepm;
7519: double *xp;
7520: double *gp, *gm;
7521: double **gradg, **trgradg;
7522: double **mgm, **mgp;
7523: double age,agelim;
7524: int theta;
7525:
7526: pstamp(ficresvbl);
7527: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7528: fprintf(ficresvbl,"# Age ");
7529: if(nresult >=1)
7530: fprintf(ficresvbl," Result# ");
7531: for(i=1; i<=nlstate;i++)
7532: fprintf(ficresvbl," %1d-%1d",i,i);
7533: fprintf(ficresvbl,"\n");
7534:
7535: xp=vector(1,npar);
7536: dnewmpar=matrix(1,nlstate,1,npar);
7537: doldm=matrix(1,nlstate,1,nlstate);
7538:
7539: hstepm=1*YEARM; /* Every year of age */
7540: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7541: agelim = AGEINF;
7542: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7543: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7544: if (stepm >= YEARM) hstepm=1;
7545: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7546: gradg=matrix(1,npar,1,nlstate);
7547: mgp=matrix(1,npar,1,nlstate);
7548: mgm=matrix(1,npar,1,nlstate);
7549: gp=vector(1,nlstate);
7550: gm=vector(1,nlstate);
7551:
7552: for(theta=1; theta <=npar; theta++){
7553: for(i=1; i<=npar; i++){ /* Computes gradient */
7554: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7555: }
7556: if(mobilavproj > 0 )
7557: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7558: else
7559: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7560: for(i=1;i<=nlstate;i++){
7561: gp[i] = bprlim[i][i];
7562: mgp[theta][i] = bprlim[i][i];
7563: }
7564: for(i=1; i<=npar; i++) /* Computes gradient */
7565: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7566: if(mobilavproj > 0 )
7567: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7568: else
7569: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7570: for(i=1;i<=nlstate;i++){
7571: gm[i] = bprlim[i][i];
7572: mgm[theta][i] = bprlim[i][i];
7573: }
7574: for(i=1;i<=nlstate;i++)
7575: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7576: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7577: } /* End theta */
7578:
7579: trgradg =matrix(1,nlstate,1,npar);
7580:
7581: for(j=1; j<=nlstate;j++)
7582: for(theta=1; theta <=npar; theta++)
7583: trgradg[j][theta]=gradg[theta][j];
7584: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7585: /* printf("\nmgm mgp %d ",(int)age); */
7586: /* for(j=1; j<=nlstate;j++){ */
7587: /* printf(" %d ",j); */
7588: /* for(theta=1; theta <=npar; theta++) */
7589: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7590: /* printf("\n "); */
7591: /* } */
7592: /* } */
7593: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7594: /* printf("\n gradg %d ",(int)age); */
7595: /* for(j=1; j<=nlstate;j++){ */
7596: /* printf("%d ",j); */
7597: /* for(theta=1; theta <=npar; theta++) */
7598: /* printf("%d %lf ",theta,gradg[theta][j]); */
7599: /* printf("\n "); */
7600: /* } */
7601: /* } */
7602:
7603: for(i=1;i<=nlstate;i++)
7604: varbpl[i][(int)age] =0.;
7605: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7606: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7607: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7608: }else{
7609: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7610: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7611: }
7612: for(i=1;i<=nlstate;i++)
7613: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7614:
7615: fprintf(ficresvbl,"%.0f ",age );
7616: if(nresult >=1)
7617: fprintf(ficresvbl,"%d ",nres );
7618: for(i=1; i<=nlstate;i++)
7619: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7620: fprintf(ficresvbl,"\n");
7621: free_vector(gp,1,nlstate);
7622: free_vector(gm,1,nlstate);
7623: free_matrix(mgm,1,npar,1,nlstate);
7624: free_matrix(mgp,1,npar,1,nlstate);
7625: free_matrix(gradg,1,npar,1,nlstate);
7626: free_matrix(trgradg,1,nlstate,1,npar);
7627: } /* End age */
7628:
7629: free_vector(xp,1,npar);
7630: free_matrix(doldm,1,nlstate,1,npar);
7631: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7632:
7633: }
7634:
7635: /************ Variance of one-step probabilities ******************/
7636: 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 7637: {
7638: int i, j=0, k1, l1, tj;
7639: int k2, l2, j1, z1;
7640: int k=0, l;
7641: int first=1, first1, first2;
1.326 brouard 7642: int nres=0; /* New */
1.222 brouard 7643: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7644: double **dnewm,**doldm;
7645: double *xp;
7646: double *gp, *gm;
7647: double **gradg, **trgradg;
7648: double **mu;
7649: double age, cov[NCOVMAX+1];
7650: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7651: int theta;
7652: char fileresprob[FILENAMELENGTH];
7653: char fileresprobcov[FILENAMELENGTH];
7654: char fileresprobcor[FILENAMELENGTH];
7655: double ***varpij;
7656:
7657: strcpy(fileresprob,"PROB_");
1.356 brouard 7658: strcat(fileresprob,fileresu);
1.222 brouard 7659: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7660: printf("Problem with resultfile: %s\n", fileresprob);
7661: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7662: }
7663: strcpy(fileresprobcov,"PROBCOV_");
7664: strcat(fileresprobcov,fileresu);
7665: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7666: printf("Problem with resultfile: %s\n", fileresprobcov);
7667: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7668: }
7669: strcpy(fileresprobcor,"PROBCOR_");
7670: strcat(fileresprobcor,fileresu);
7671: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7672: printf("Problem with resultfile: %s\n", fileresprobcor);
7673: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7674: }
7675: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7676: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7677: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7678: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7679: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7680: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7681: pstamp(ficresprob);
7682: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7683: fprintf(ficresprob,"# Age");
7684: pstamp(ficresprobcov);
7685: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7686: fprintf(ficresprobcov,"# Age");
7687: pstamp(ficresprobcor);
7688: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7689: fprintf(ficresprobcor,"# Age");
1.126 brouard 7690:
7691:
1.222 brouard 7692: for(i=1; i<=nlstate;i++)
7693: for(j=1; j<=(nlstate+ndeath);j++){
7694: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7695: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7696: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7697: }
7698: /* fprintf(ficresprob,"\n");
7699: fprintf(ficresprobcov,"\n");
7700: fprintf(ficresprobcor,"\n");
7701: */
7702: xp=vector(1,npar);
7703: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7704: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7705: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7706: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7707: first=1;
7708: fprintf(ficgp,"\n# Routine varprob");
7709: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7710: fprintf(fichtm,"\n");
7711:
1.288 brouard 7712: 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 7713: 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);
7714: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7715: and drawn. It helps understanding how is the covariance between two incidences.\
7716: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7717: 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 7718: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7719: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7720: standard deviations wide on each axis. <br>\
7721: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7722: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7723: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7724:
1.222 brouard 7725: cov[1]=1;
7726: /* tj=cptcoveff; */
1.225 brouard 7727: tj = (int) pow(2,cptcoveff);
1.222 brouard 7728: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7729: j1=0;
1.332 brouard 7730:
7731: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7732: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7733: /* 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 7734: if(tj != 1 && TKresult[nres]!= j1)
7735: continue;
7736:
7737: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7738: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7739: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7740: if (cptcovn>0) {
1.334 brouard 7741: fprintf(ficresprob, "\n#********** Variable ");
7742: fprintf(ficresprobcov, "\n#********** Variable ");
7743: fprintf(ficgp, "\n#********** Variable ");
7744: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7745: fprintf(ficresprobcor, "\n#********** Variable ");
7746:
7747: /* Including quantitative variables of the resultline to be done */
7748: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7749: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7750: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7751: /* 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 7752: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7753: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7754: 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 */
7755: 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 */
7756: 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 */
7757: 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 */
7758: 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 */
7759: fprintf(ficresprob,"fixed ");
7760: fprintf(ficresprobcov,"fixed ");
7761: fprintf(ficgp,"fixed ");
7762: fprintf(fichtmcov,"fixed ");
7763: fprintf(ficresprobcor,"fixed ");
7764: }else{
7765: fprintf(ficresprob,"varyi ");
7766: fprintf(ficresprobcov,"varyi ");
7767: fprintf(ficgp,"varyi ");
7768: fprintf(fichtmcov,"varyi ");
7769: fprintf(ficresprobcor,"varyi ");
7770: }
7771: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7772: /* For each selected (single) quantitative value */
1.337 brouard 7773: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7774: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7775: fprintf(ficresprob,"fixed ");
7776: fprintf(ficresprobcov,"fixed ");
7777: fprintf(ficgp,"fixed ");
7778: fprintf(fichtmcov,"fixed ");
7779: fprintf(ficresprobcor,"fixed ");
7780: }else{
7781: fprintf(ficresprob,"varyi ");
7782: fprintf(ficresprobcov,"varyi ");
7783: fprintf(ficgp,"varyi ");
7784: fprintf(fichtmcov,"varyi ");
7785: fprintf(ficresprobcor,"varyi ");
7786: }
7787: }else{
7788: 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 */
7789: 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 */
7790: exit(1);
7791: }
7792: } /* End loop on variable of this resultline */
7793: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7794: fprintf(ficresprob, "**********\n#\n");
7795: fprintf(ficresprobcov, "**********\n#\n");
7796: fprintf(ficgp, "**********\n#\n");
7797: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7798: fprintf(ficresprobcor, "**********\n#");
7799: if(invalidvarcomb[j1]){
7800: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7801: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7802: continue;
7803: }
7804: }
7805: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7806: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7807: gp=vector(1,(nlstate)*(nlstate+ndeath));
7808: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7809: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7810: cov[2]=age;
7811: if(nagesqr==1)
7812: cov[3]= age*age;
1.334 brouard 7813: /* New code end of combination but for each resultline */
7814: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 7815: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7816: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7817: }else{
1.334 brouard 7818: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7819: }
1.334 brouard 7820: }/* End of loop on model equation */
7821: /* Old code */
7822: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7823: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7824: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7825: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7826: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7827: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7828: /* * 1 1 1 1 1 */
7829: /* * 2 2 1 1 1 */
7830: /* * 3 1 2 1 1 */
7831: /* *\/ */
7832: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7833: /* } */
7834: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7835: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7836: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7837: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7838: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7839: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7840: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7841: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7842: /* 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]); */
7843: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7844: /* /\* exit(1); *\/ */
7845: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7846: /* } */
7847: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7848: /* } */
7849: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7850: /* if(Dummy[Tvard[k][1]]==0){ */
7851: /* if(Dummy[Tvard[k][2]]==0){ */
7852: /* 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]])]; */
7853: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7854: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7855: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7856: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7857: /* } */
7858: /* }else{ */
7859: /* if(Dummy[Tvard[k][2]]==0){ */
7860: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7861: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7862: /* }else{ */
7863: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7864: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7865: /* } */
7866: /* } */
7867: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7868: /* } */
1.326 brouard 7869: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7870: for(theta=1; theta <=npar; theta++){
7871: for(i=1; i<=npar; i++)
7872: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7873:
1.222 brouard 7874: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7875:
1.222 brouard 7876: k=0;
7877: for(i=1; i<= (nlstate); i++){
7878: for(j=1; j<=(nlstate+ndeath);j++){
7879: k=k+1;
7880: gp[k]=pmmij[i][j];
7881: }
7882: }
1.220 brouard 7883:
1.222 brouard 7884: for(i=1; i<=npar; i++)
7885: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7886:
1.222 brouard 7887: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7888: k=0;
7889: for(i=1; i<=(nlstate); i++){
7890: for(j=1; j<=(nlstate+ndeath);j++){
7891: k=k+1;
7892: gm[k]=pmmij[i][j];
7893: }
7894: }
1.220 brouard 7895:
1.222 brouard 7896: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7897: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7898: }
1.126 brouard 7899:
1.222 brouard 7900: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7901: for(theta=1; theta <=npar; theta++)
7902: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7903:
1.222 brouard 7904: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7905: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7906:
1.222 brouard 7907: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7908:
1.222 brouard 7909: k=0;
7910: for(i=1; i<=(nlstate); i++){
7911: for(j=1; j<=(nlstate+ndeath);j++){
7912: k=k+1;
7913: mu[k][(int) age]=pmmij[i][j];
7914: }
7915: }
7916: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7917: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7918: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7919:
1.222 brouard 7920: /*printf("\n%d ",(int)age);
7921: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7922: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7923: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7924: }*/
1.220 brouard 7925:
1.222 brouard 7926: fprintf(ficresprob,"\n%d ",(int)age);
7927: fprintf(ficresprobcov,"\n%d ",(int)age);
7928: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7929:
1.222 brouard 7930: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7931: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7932: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7933: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7934: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7935: }
7936: i=0;
7937: for (k=1; k<=(nlstate);k++){
7938: for (l=1; l<=(nlstate+ndeath);l++){
7939: i++;
7940: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7941: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7942: for (j=1; j<=i;j++){
7943: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7944: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7945: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7946: }
7947: }
7948: }/* end of loop for state */
7949: } /* end of loop for age */
7950: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7951: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7952: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7953: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7954:
7955: /* Confidence intervalle of pij */
7956: /*
7957: fprintf(ficgp,"\nunset parametric;unset label");
7958: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7959: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7960: 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);
7961: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7962: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7963: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7964: */
7965:
7966: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7967: first1=1;first2=2;
7968: for (k2=1; k2<=(nlstate);k2++){
7969: for (l2=1; l2<=(nlstate+ndeath);l2++){
7970: if(l2==k2) continue;
7971: j=(k2-1)*(nlstate+ndeath)+l2;
7972: for (k1=1; k1<=(nlstate);k1++){
7973: for (l1=1; l1<=(nlstate+ndeath);l1++){
7974: if(l1==k1) continue;
7975: i=(k1-1)*(nlstate+ndeath)+l1;
7976: if(i<=j) continue;
7977: for (age=bage; age<=fage; age ++){
7978: if ((int)age %5==0){
7979: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7980: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7981: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7982: mu1=mu[i][(int) age]/stepm*YEARM ;
7983: mu2=mu[j][(int) age]/stepm*YEARM;
7984: c12=cv12/sqrt(v1*v2);
7985: /* Computing eigen value of matrix of covariance */
7986: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7987: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7988: if ((lc2 <0) || (lc1 <0) ){
7989: if(first2==1){
7990: first1=0;
7991: 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);
7992: }
7993: 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);
7994: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7995: /* lc2=fabs(lc2); */
7996: }
1.220 brouard 7997:
1.222 brouard 7998: /* Eigen vectors */
1.280 brouard 7999: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
8000: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
8001: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
8002: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
8003: }else
8004: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 8005: /*v21=sqrt(1.-v11*v11); *//* error */
8006: v21=(lc1-v1)/cv12*v11;
8007: v12=-v21;
8008: v22=v11;
8009: tnalp=v21/v11;
8010: if(first1==1){
8011: first1=0;
8012: 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);
8013: }
8014: 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);
8015: /*printf(fignu*/
8016: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
8017: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
8018: if(first==1){
8019: first=0;
8020: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
8021: fprintf(ficgp,"\nset parametric;unset label");
8022: 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);
8023: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 8024: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 8025: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 8026: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 8027: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
8028: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8029: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8030: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
8031: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8032: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
8033: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
8034: 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 8035: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
8036: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 8037: }else{
8038: first=0;
8039: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
8040: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
8041: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
8042: 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 8043: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
8044: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 8045: }/* if first */
8046: } /* age mod 5 */
8047: } /* end loop age */
8048: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8049: first=1;
8050: } /*l12 */
8051: } /* k12 */
8052: } /*l1 */
8053: }/* k1 */
1.332 brouard 8054: } /* loop on combination of covariates j1 */
1.326 brouard 8055: } /* loop on nres */
1.222 brouard 8056: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
8057: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
8058: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
8059: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
8060: free_vector(xp,1,npar);
8061: fclose(ficresprob);
8062: fclose(ficresprobcov);
8063: fclose(ficresprobcor);
8064: fflush(ficgp);
8065: fflush(fichtmcov);
8066: }
1.126 brouard 8067:
8068:
8069: /******************* Printing html file ***********/
1.201 brouard 8070: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8071: int lastpass, int stepm, int weightopt, char model[],\
8072: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 8073: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
8074: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
8075: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 8076: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 8077: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8078: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8079: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8080: </ul>");
1.319 brouard 8081: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8082: /* </ul>", model); */
1.214 brouard 8083: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8084: 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",
8085: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8086: 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 8087: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8088: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8089: fprintf(fichtm,"\
8090: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8091: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8092: fprintf(fichtm,"\
1.217 brouard 8093: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8094: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8095: fprintf(fichtm,"\
1.288 brouard 8096: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8097: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8098: fprintf(fichtm,"\
1.288 brouard 8099: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8100: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8101: fprintf(fichtm,"\
1.211 brouard 8102: - (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 8103: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8104: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8105: if(prevfcast==1){
8106: fprintf(fichtm,"\
8107: - Prevalence projections by age and states: \
1.201 brouard 8108: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8109: }
1.126 brouard 8110:
8111:
1.225 brouard 8112: m=pow(2,cptcoveff);
1.222 brouard 8113: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8114:
1.317 brouard 8115: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8116:
8117: jj1=0;
8118:
8119: fprintf(fichtm," \n<ul>");
1.337 brouard 8120: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8121: /* k1=nres; */
1.338 brouard 8122: k1=TKresult[nres];
8123: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8124: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8125: /* if(m != 1 && TKresult[nres]!= k1) */
8126: /* continue; */
1.264 brouard 8127: jj1++;
8128: if (cptcovn > 0) {
8129: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8130: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8131: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8132: }
1.337 brouard 8133: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8134: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8135: /* } */
8136: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8137: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8138: /* } */
1.264 brouard 8139: fprintf(fichtm,"\">");
8140:
8141: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8142: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8143: for (cpt=1; cpt<=cptcovs;cpt++){
8144: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8145: }
1.337 brouard 8146: /* fprintf(fichtm,"************ Results for covariates"); */
8147: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8148: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8149: /* } */
8150: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8151: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8152: /* } */
1.264 brouard 8153: if(invalidvarcomb[k1]){
8154: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8155: continue;
8156: }
8157: fprintf(fichtm,"</a></li>");
8158: } /* cptcovn >0 */
8159: }
1.317 brouard 8160: fprintf(fichtm," \n</ul>");
1.264 brouard 8161:
1.222 brouard 8162: jj1=0;
1.237 brouard 8163:
1.337 brouard 8164: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8165: /* k1=nres; */
1.338 brouard 8166: k1=TKresult[nres];
8167: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8168: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8169: /* if(m != 1 && TKresult[nres]!= k1) */
8170: /* continue; */
1.220 brouard 8171:
1.222 brouard 8172: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8173: jj1++;
8174: if (cptcovn > 0) {
1.264 brouard 8175: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8176: for (cpt=1; cpt<=cptcovs;cpt++){
8177: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8178: }
1.337 brouard 8179: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8180: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8181: /* } */
1.264 brouard 8182: fprintf(fichtm,"\"</a>");
8183:
1.222 brouard 8184: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8185: for (cpt=1; cpt<=cptcovs;cpt++){
8186: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8187: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8188: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8189: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8190: }
1.230 brouard 8191: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8192: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8193: if(invalidvarcomb[k1]){
8194: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8195: printf("\nCombination (%d) ignored because no cases \n",k1);
8196: continue;
8197: }
8198: }
8199: /* aij, bij */
1.259 brouard 8200: 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 8201: <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 8202: /* Pij */
1.241 brouard 8203: 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> \
8204: <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 8205: /* Quasi-incidences */
8206: 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 8207: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8208: 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 8209: 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> \
8210: <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 8211: /* Survival functions (period) in state j */
8212: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8213: 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);
8214: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8215: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8216: }
8217: /* State specific survival functions (period) */
8218: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8219: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8220: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8221: <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);
8222: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8223: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8224: }
1.288 brouard 8225: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8226: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8227: 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 8228: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8229: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8230: }
1.296 brouard 8231: if(prevbcast==1){
1.288 brouard 8232: /* Backward prevalence in each health state */
1.222 brouard 8233: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8234: 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);
8235: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8236: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8237: }
1.217 brouard 8238: }
1.222 brouard 8239: if(prevfcast==1){
1.288 brouard 8240: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8241: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8242: 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);
8243: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8244: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8245: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8246: }
8247: }
1.296 brouard 8248: if(prevbcast==1){
1.268 brouard 8249: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8250: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8251: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8252: 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 \
8253: 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 8254: 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);
8255: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8256: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8257: }
8258: }
1.220 brouard 8259:
1.222 brouard 8260: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8261: 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);
8262: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8263: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8264: }
8265: /* } /\* end i1 *\/ */
1.337 brouard 8266: }/* End k1=nres */
1.222 brouard 8267: fprintf(fichtm,"</ul>");
1.126 brouard 8268:
1.222 brouard 8269: fprintf(fichtm,"\
1.126 brouard 8270: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8271: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8272: - 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 8273: But because parameters are usually highly correlated (a higher incidence of disability \
8274: and a higher incidence of recovery can give very close observed transition) it might \
8275: be very useful to look not only at linear confidence intervals estimated from the \
8276: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8277: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8278: covariance matrix of the one-step probabilities. \
8279: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8280:
1.222 brouard 8281: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8282: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8283: fprintf(fichtm,"\
1.126 brouard 8284: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8285: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8286:
1.222 brouard 8287: fprintf(fichtm,"\
1.126 brouard 8288: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8289: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8290: fprintf(fichtm,"\
1.126 brouard 8291: - 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): \
8292: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8293: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8294: fprintf(fichtm,"\
1.126 brouard 8295: - (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): \
8296: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8297: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8298: fprintf(fichtm,"\
1.288 brouard 8299: - 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 8300: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8301: fprintf(fichtm,"\
1.128 brouard 8302: - 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 8303: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8304: fprintf(fichtm,"\
1.288 brouard 8305: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8306: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8307:
8308: /* if(popforecast==1) fprintf(fichtm,"\n */
8309: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8310: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8311: /* <br>",fileres,fileres,fileres,fileres); */
8312: /* else */
1.338 brouard 8313: /* 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 8314: fflush(fichtm);
1.126 brouard 8315:
1.225 brouard 8316: m=pow(2,cptcoveff);
1.222 brouard 8317: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8318:
1.317 brouard 8319: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8320:
8321: jj1=0;
8322:
8323: fprintf(fichtm," \n<ul>");
1.337 brouard 8324: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8325: /* k1=nres; */
1.338 brouard 8326: k1=TKresult[nres];
1.337 brouard 8327: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8328: /* if(m != 1 && TKresult[nres]!= k1) */
8329: /* continue; */
1.317 brouard 8330: jj1++;
8331: if (cptcovn > 0) {
8332: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8333: for (cpt=1; cpt<=cptcovs;cpt++){
8334: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8335: }
8336: fprintf(fichtm,"\">");
8337:
8338: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8339: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8340: for (cpt=1; cpt<=cptcovs;cpt++){
8341: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8342: }
8343: if(invalidvarcomb[k1]){
8344: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8345: continue;
8346: }
8347: fprintf(fichtm,"</a></li>");
8348: } /* cptcovn >0 */
1.337 brouard 8349: } /* End nres */
1.317 brouard 8350: fprintf(fichtm," \n</ul>");
8351:
1.222 brouard 8352: jj1=0;
1.237 brouard 8353:
1.241 brouard 8354: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8355: /* k1=nres; */
1.338 brouard 8356: k1=TKresult[nres];
8357: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8358: /* for(k1=1; k1<=m;k1++){ */
8359: /* if(m != 1 && TKresult[nres]!= k1) */
8360: /* continue; */
1.222 brouard 8361: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8362: jj1++;
1.126 brouard 8363: if (cptcovn > 0) {
1.317 brouard 8364: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8365: for (cpt=1; cpt<=cptcovs;cpt++){
8366: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8367: }
8368: fprintf(fichtm,"\"</a>");
8369:
1.126 brouard 8370: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8371: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8372: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8373: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8374: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8375: }
1.237 brouard 8376:
1.338 brouard 8377: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8378:
1.222 brouard 8379: if(invalidvarcomb[k1]){
8380: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8381: continue;
8382: }
1.337 brouard 8383: } /* If cptcovn >0 */
1.126 brouard 8384: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8385: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8386: 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);
8387: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8388: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8389: }
8390: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8391: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8392: true period expectancies (those weighted with period prevalences are also\
8393: drawn in addition to the population based expectancies computed using\
1.314 brouard 8394: 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);
8395: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8396: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8397: /* } /\* end i1 *\/ */
1.241 brouard 8398: }/* End nres */
1.222 brouard 8399: fprintf(fichtm,"</ul>");
8400: fflush(fichtm);
1.126 brouard 8401: }
8402:
8403: /******************* Gnuplot file **************/
1.296 brouard 8404: 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 8405:
1.354 brouard 8406: char dirfileres[256],optfileres[256];
8407: char gplotcondition[256], gplotlabel[256];
1.343 brouard 8408: 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 8409: int lv=0, vlv=0, kl=0;
1.130 brouard 8410: int ng=0;
1.201 brouard 8411: int vpopbased;
1.223 brouard 8412: int ioffset; /* variable offset for columns */
1.270 brouard 8413: int iyearc=1; /* variable column for year of projection */
8414: int iagec=1; /* variable column for age of projection */
1.235 brouard 8415: int nres=0; /* Index of resultline */
1.266 brouard 8416: int istart=1; /* For starting graphs in projections */
1.219 brouard 8417:
1.126 brouard 8418: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8419: /* printf("Problem with file %s",optionfilegnuplot); */
8420: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8421: /* } */
8422:
8423: /*#ifdef windows */
8424: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8425: /*#endif */
1.225 brouard 8426: m=pow(2,cptcoveff);
1.126 brouard 8427:
1.274 brouard 8428: /* diagram of the model */
8429: fprintf(ficgp,"\n#Diagram of the model \n");
8430: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8431: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8432: 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);
8433:
1.343 brouard 8434: 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 8435: fprintf(ficgp,"\n#show arrow\nunset label\n");
8436: 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);
8437: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8438: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8439: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8440: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8441:
1.202 brouard 8442: /* Contribution to likelihood */
8443: /* Plot the probability implied in the likelihood */
1.223 brouard 8444: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8445: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8446: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8447: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8448: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8449: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8450: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8451: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8452: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8453: 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));
8454: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8455: 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));
8456: for (i=1; i<= nlstate ; i ++) {
8457: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8458: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8459: 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);
8460: for (j=2; j<= nlstate+ndeath ; j ++) {
8461: 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);
8462: }
8463: fprintf(ficgp,";\nset out; unset ylabel;\n");
8464: }
8465: /* 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 */
8466: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8467: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8468: fprintf(ficgp,"\nset out;unset log\n");
8469: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8470:
1.343 brouard 8471: /* Plot the probability implied in the likelihood by covariate value */
8472: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8473: /* if(debugILK==1){ */
8474: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8475: kvar=Tvar[TvarFind[kf]]; /* variable name */
8476: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 8477: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
1.356 brouard 8478: /* k=19+kf;/\*offset because there are 19 columns in the ILK_ file *\/ */
1.355 brouard 8479: 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 8480: for (i=1; i<= nlstate ; i ++) {
8481: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8482: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8483: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8484: 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);
8485: for (j=2; j<= nlstate+ndeath ; j ++) {
8486: 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);
8487: }
8488: }else{
8489: 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);
8490: for (j=2; j<= nlstate+ndeath ; j ++) {
8491: 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);
8492: }
1.343 brouard 8493: }
8494: fprintf(ficgp,";\nset out; unset ylabel;\n");
8495: }
8496: } /* End of each covariate dummy */
8497: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8498: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8499: * kmodel = 1 2 3 4 5 6 7 8 9
8500: * varying 1 2 3 4 5
8501: * ncovv 1 2 3 4 5 6 7 8
8502: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8503: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8504: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8505: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8506: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8507: */
8508: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8509: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8510: /* 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]); */
8511: if(ipos!=iposold){ /* Not a product or first of a product */
8512: /* printf(" %d",ipos); */
8513: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8514: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8515: kk++; /* Position of the ncovv column in ILK_ */
8516: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8517: 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) */
8518: for (i=1; i<= nlstate ; i ++) {
8519: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8520: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8521:
1.348 brouard 8522: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8523: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8524: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8525: 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);
8526: for (j=2; j<= nlstate+ndeath ; j ++) {
8527: 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);
8528: }
8529: }else{
8530: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8531: 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);
8532: for (j=2; j<= nlstate+ndeath ; j ++) {
8533: 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);
8534: }
8535: }
8536: fprintf(ficgp,";\nset out; unset ylabel;\n");
8537: }
8538: }/* End if dummy varying */
8539: }else{ /*Product */
8540: /* printf("*"); */
8541: /* fprintf(ficresilk,"*"); */
8542: }
8543: iposold=ipos;
8544: } /* For each time varying covariate */
8545: /* } /\* debugILK==1 *\/ */
8546: /* 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 */
8547: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8548: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8549: fprintf(ficgp,"\nset out;unset log\n");
8550: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8551:
8552:
8553:
1.126 brouard 8554: strcpy(dirfileres,optionfilefiname);
8555: strcpy(optfileres,"vpl");
1.223 brouard 8556: /* 1eme*/
1.238 brouard 8557: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8558: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8559: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8560: k1=TKresult[nres];
1.338 brouard 8561: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8562: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8563: /* if(m != 1 && TKresult[nres]!= k1) */
8564: /* continue; */
1.238 brouard 8565: /* We are interested in selected combination by the resultline */
1.246 brouard 8566: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8567: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8568: strcpy(gplotlabel,"(");
1.337 brouard 8569: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8570: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8571: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8572:
8573: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8574: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8575: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8576: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8577: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8578: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8579: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8580: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8581: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8582: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8583: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8584: /* } */
8585: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8586: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8587: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8588: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8589: }
8590: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8591: /* printf("\n#\n"); */
1.238 brouard 8592: fprintf(ficgp,"\n#\n");
8593: if(invalidvarcomb[k1]){
1.260 brouard 8594: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8595: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8596: continue;
8597: }
1.235 brouard 8598:
1.241 brouard 8599: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8600: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8601: /* 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 8602: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8603: 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);
8604: /* 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); */
8605: /* k1-1 error should be nres-1*/
1.238 brouard 8606: for (i=1; i<= nlstate ; i ++) {
8607: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8608: else fprintf(ficgp," %%*lf (%%*lf)");
8609: }
1.288 brouard 8610: 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 8611: for (i=1; i<= nlstate ; i ++) {
8612: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8613: else fprintf(ficgp," %%*lf (%%*lf)");
8614: }
1.260 brouard 8615: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8616: for (i=1; i<= nlstate ; i ++) {
8617: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8618: else fprintf(ficgp," %%*lf (%%*lf)");
8619: }
1.265 brouard 8620: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8621:
8622: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8623: if(cptcoveff ==0){
1.271 brouard 8624: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8625: }else{
8626: kl=0;
8627: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8628: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8629: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8630: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8631: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8632: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8633: vlv= nbcode[Tvaraff[k]][lv];
8634: kl++;
8635: /* 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 *\/ */
8636: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8637: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8638: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8639: if(k==cptcoveff){
8640: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8641: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8642: }else{
8643: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8644: kl++;
8645: }
8646: } /* end covariate */
8647: } /* end if no covariate */
8648:
1.296 brouard 8649: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8650: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8651: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8652: if(cptcoveff ==0){
1.245 brouard 8653: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8654: }else{
8655: kl=0;
8656: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8657: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8658: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8659: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8660: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8661: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8662: /* vlv= nbcode[Tvaraff[k]][lv]; */
8663: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8664: kl++;
1.238 brouard 8665: /* 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 *\/ */
8666: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8667: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8668: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8669: if(k==cptcoveff){
1.245 brouard 8670: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8671: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8672: }else{
1.332 brouard 8673: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8674: kl++;
8675: }
8676: } /* end covariate */
8677: } /* end if no covariate */
1.296 brouard 8678: if(prevbcast == 1){
1.268 brouard 8679: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8680: /* k1-1 error should be nres-1*/
8681: for (i=1; i<= nlstate ; i ++) {
8682: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8683: else fprintf(ficgp," %%*lf (%%*lf)");
8684: }
1.271 brouard 8685: 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 8686: for (i=1; i<= nlstate ; i ++) {
8687: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8688: else fprintf(ficgp," %%*lf (%%*lf)");
8689: }
1.276 brouard 8690: 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 8691: for (i=1; i<= nlstate ; i ++) {
8692: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8693: else fprintf(ficgp," %%*lf (%%*lf)");
8694: }
1.274 brouard 8695: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8696: } /* end if backprojcast */
1.296 brouard 8697: } /* end if prevbcast */
1.276 brouard 8698: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8699: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8700: } /* nres */
1.337 brouard 8701: /* } /\* k1 *\/ */
1.201 brouard 8702: } /* cpt */
1.235 brouard 8703:
8704:
1.126 brouard 8705: /*2 eme*/
1.337 brouard 8706: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8707: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8708: k1=TKresult[nres];
1.338 brouard 8709: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8710: /* if(m != 1 && TKresult[nres]!= k1) */
8711: /* continue; */
1.238 brouard 8712: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8713: strcpy(gplotlabel,"(");
1.337 brouard 8714: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8715: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8716: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8717: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8718: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8719: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8720: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8721: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8722: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8723: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8724: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8725: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8726: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8727: /* } */
8728: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8729: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8730: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8731: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8732: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8733: }
1.264 brouard 8734: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8735: fprintf(ficgp,"\n#\n");
1.223 brouard 8736: if(invalidvarcomb[k1]){
8737: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8738: continue;
8739: }
1.219 brouard 8740:
1.241 brouard 8741: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8742: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8743: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8744: if(vpopbased==0){
1.238 brouard 8745: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8746: }else
1.238 brouard 8747: fprintf(ficgp,"\nreplot ");
8748: for (i=1; i<= nlstate+1 ; i ++) {
8749: k=2*i;
1.261 brouard 8750: 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 8751: for (j=1; j<= nlstate+1 ; j ++) {
8752: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8753: else fprintf(ficgp," %%*lf (%%*lf)");
8754: }
8755: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8756: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8757: 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 8758: for (j=1; j<= nlstate+1 ; j ++) {
8759: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8760: else fprintf(ficgp," %%*lf (%%*lf)");
8761: }
8762: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8763: 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 8764: for (j=1; j<= nlstate+1 ; j ++) {
8765: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8766: else fprintf(ficgp," %%*lf (%%*lf)");
8767: }
8768: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8769: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8770: } /* state */
8771: } /* vpopbased */
1.264 brouard 8772: 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 8773: } /* end nres */
1.337 brouard 8774: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8775:
8776:
8777: /*3eme*/
1.337 brouard 8778: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8779: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8780: k1=TKresult[nres];
1.338 brouard 8781: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8782: /* if(m != 1 && TKresult[nres]!= k1) */
8783: /* continue; */
1.238 brouard 8784:
1.332 brouard 8785: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8786: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8787: strcpy(gplotlabel,"(");
1.337 brouard 8788: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8789: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8790: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8791: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8792: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8793: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8794: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8795: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8796: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8797: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8798: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8799: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8800: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8801: /* } */
8802: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8803: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8804: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8805: }
1.264 brouard 8806: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8807: fprintf(ficgp,"\n#\n");
8808: if(invalidvarcomb[k1]){
8809: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8810: continue;
8811: }
8812:
8813: /* k=2+nlstate*(2*cpt-2); */
8814: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8815: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8816: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8817: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8818: 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 8819: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8820: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8821: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8822: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8823: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8824: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8825:
1.238 brouard 8826: */
8827: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8828: 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 8829: /* 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 8830:
1.238 brouard 8831: }
1.261 brouard 8832: 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 8833: }
1.264 brouard 8834: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8835: } /* end nres */
1.337 brouard 8836: /* } /\* end kl 3eme *\/ */
1.126 brouard 8837:
1.223 brouard 8838: /* 4eme */
1.201 brouard 8839: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8840: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8841: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8842: k1=TKresult[nres];
1.338 brouard 8843: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8844: /* if(m != 1 && TKresult[nres]!= k1) */
8845: /* continue; */
1.238 brouard 8846: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8847: strcpy(gplotlabel,"(");
1.337 brouard 8848: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8849: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8850: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8851: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8852: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8853: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8854: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8855: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8856: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8857: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8858: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8859: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8860: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8861: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8862: /* } */
8863: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8864: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8865: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8866: }
1.264 brouard 8867: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8868: fprintf(ficgp,"\n#\n");
8869: if(invalidvarcomb[k1]){
8870: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8871: continue;
1.223 brouard 8872: }
1.238 brouard 8873:
1.241 brouard 8874: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8875: 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 8876: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8877: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8878: k=3;
8879: for (i=1; i<= nlstate ; i ++){
8880: if(i==1){
8881: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8882: }else{
8883: fprintf(ficgp,", '' ");
8884: }
8885: l=(nlstate+ndeath)*(i-1)+1;
8886: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8887: for (j=2; j<= nlstate+ndeath ; j ++)
8888: fprintf(ficgp,"+$%d",k+l+j-1);
8889: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8890: } /* nlstate */
1.264 brouard 8891: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8892: } /* end cpt state*/
8893: } /* end nres */
1.337 brouard 8894: /* } /\* end covariate k1 *\/ */
1.238 brouard 8895:
1.220 brouard 8896: /* 5eme */
1.201 brouard 8897: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8898: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8899: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8900: k1=TKresult[nres];
1.338 brouard 8901: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8902: /* if(m != 1 && TKresult[nres]!= k1) */
8903: /* continue; */
1.238 brouard 8904: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8905: strcpy(gplotlabel,"(");
1.238 brouard 8906: 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 8907: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8908: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8909: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8910: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8911: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8912: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8913: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8914: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8915: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8916: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8917: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8918: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8919: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8920: /* } */
8921: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8922: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8923: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8924: }
1.264 brouard 8925: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8926: fprintf(ficgp,"\n#\n");
8927: if(invalidvarcomb[k1]){
8928: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8929: continue;
8930: }
1.227 brouard 8931:
1.241 brouard 8932: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8933: 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 8934: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8935: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8936: k=3;
8937: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8938: if(j==1)
8939: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8940: else
8941: fprintf(ficgp,", '' ");
8942: l=(nlstate+ndeath)*(cpt-1) +j;
8943: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8944: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8945: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8946: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8947: } /* nlstate */
8948: fprintf(ficgp,", '' ");
8949: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8950: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8951: l=(nlstate+ndeath)*(cpt-1) +j;
8952: if(j < nlstate)
8953: fprintf(ficgp,"$%d +",k+l);
8954: else
8955: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8956: }
1.264 brouard 8957: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8958: } /* end cpt state*/
1.337 brouard 8959: /* } /\* end covariate *\/ */
1.238 brouard 8960: } /* end nres */
1.227 brouard 8961:
1.220 brouard 8962: /* 6eme */
1.202 brouard 8963: /* CV preval stable (period) for each covariate */
1.337 brouard 8964: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8965: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8966: k1=TKresult[nres];
1.338 brouard 8967: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8968: /* if(m != 1 && TKresult[nres]!= k1) */
8969: /* continue; */
1.255 brouard 8970: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8971: strcpy(gplotlabel,"(");
1.288 brouard 8972: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8973: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8974: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8975: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8976: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8977: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8978: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8979: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8980: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8981: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8982: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8983: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8984: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8985: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8986: /* } */
8987: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8988: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8989: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8990: }
1.264 brouard 8991: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8992: fprintf(ficgp,"\n#\n");
1.223 brouard 8993: if(invalidvarcomb[k1]){
1.227 brouard 8994: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8995: continue;
1.223 brouard 8996: }
1.227 brouard 8997:
1.241 brouard 8998: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8999: 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 9000: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 9001: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 9002: k=3; /* Offset */
1.255 brouard 9003: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 9004: if(i==1)
9005: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
9006: else
9007: fprintf(ficgp,", '' ");
1.255 brouard 9008: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 9009: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
9010: for (j=2; j<= nlstate ; j ++)
9011: fprintf(ficgp,"+$%d",k+l+j-1);
9012: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 9013: } /* nlstate */
1.264 brouard 9014: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 9015: } /* end cpt state*/
9016: } /* end covariate */
1.227 brouard 9017:
9018:
1.220 brouard 9019: /* 7eme */
1.296 brouard 9020: if(prevbcast == 1){
1.288 brouard 9021: /* CV backward prevalence for each covariate */
1.337 brouard 9022: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9023: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9024: k1=TKresult[nres];
1.338 brouard 9025: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9026: /* if(m != 1 && TKresult[nres]!= k1) */
9027: /* continue; */
1.268 brouard 9028: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 9029: strcpy(gplotlabel,"(");
1.288 brouard 9030: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9031: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9032: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9033: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9034: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
9035: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
9036: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9037: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9038: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9039: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9040: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9041: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9042: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9043: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9044: /* } */
9045: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9046: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9047: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9048: }
1.264 brouard 9049: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9050: fprintf(ficgp,"\n#\n");
9051: if(invalidvarcomb[k1]){
9052: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9053: continue;
9054: }
9055:
1.241 brouard 9056: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 9057: 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 9058: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 9059: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 9060: k=3; /* Offset */
1.268 brouard 9061: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 9062: if(i==1)
9063: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
9064: else
9065: fprintf(ficgp,", '' ");
9066: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 9067: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 9068: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
9069: /* 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 9070: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 9071: /* for (j=2; j<= nlstate ; j ++) */
9072: /* fprintf(ficgp,"+$%d",k+l+j-1); */
9073: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 9074: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 9075: } /* nlstate */
1.264 brouard 9076: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 9077: } /* end cpt state*/
9078: } /* end covariate */
1.296 brouard 9079: } /* End if prevbcast */
1.218 brouard 9080:
1.223 brouard 9081: /* 8eme */
1.218 brouard 9082: if(prevfcast==1){
1.288 brouard 9083: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9084:
1.337 brouard 9085: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9086: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9087: k1=TKresult[nres];
1.338 brouard 9088: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9089: /* if(m != 1 && TKresult[nres]!= k1) */
9090: /* continue; */
1.211 brouard 9091: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9092: strcpy(gplotlabel,"(");
1.288 brouard 9093: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9094: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9095: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9096: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9097: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9098: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9099: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9100: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9101: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9102: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9103: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9104: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9105: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9106: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9107: /* } */
9108: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9109: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9110: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9111: }
1.264 brouard 9112: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9113: fprintf(ficgp,"\n#\n");
9114: if(invalidvarcomb[k1]){
9115: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9116: continue;
9117: }
9118:
9119: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9120: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9121: 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 9122: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9123: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9124:
9125: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9126: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9127: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9128: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9129: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9130: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9131: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9132: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9133: if(i==istart){
1.227 brouard 9134: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9135: }else{
9136: fprintf(ficgp,",\\\n '' ");
9137: }
9138: if(cptcoveff ==0){ /* No covariate */
9139: ioffset=2; /* Age is in 2 */
9140: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9141: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9142: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9143: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9144: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9145: if(i==nlstate+1){
1.270 brouard 9146: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9147: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9148: fprintf(ficgp,",\\\n '' ");
9149: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9150: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9151: offyear, \
1.268 brouard 9152: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9153: }else
1.227 brouard 9154: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9155: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9156: }else{ /* more than 2 covariates */
1.270 brouard 9157: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9158: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9159: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9160: iyearc=ioffset-1;
9161: iagec=ioffset;
1.227 brouard 9162: fprintf(ficgp," u %d:(",ioffset);
9163: kl=0;
9164: strcpy(gplotcondition,"(");
1.351 brouard 9165: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 9166: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 9167: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9168: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9169: lv=Tvresult[nres][k];
9170: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 9171: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9172: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9173: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9174: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 9175: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 9176: kl++;
1.351 brouard 9177: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9178: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 9179: kl++;
1.351 brouard 9180: if(k <cptcovs && cptcovs>1)
1.227 brouard 9181: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9182: }
9183: strcpy(gplotcondition+strlen(gplotcondition),")");
9184: /* 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 *\/ */
9185: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9186: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9187: /* '' 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*/
9188: if(i==nlstate+1){
1.270 brouard 9189: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9190: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9191: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9192: fprintf(ficgp," u %d:(",iagec);
9193: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9194: iyearc, iagec, offyear, \
9195: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9196: /* '' 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 9197: }else{
9198: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9199: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9200: }
9201: } /* end if covariate */
9202: } /* nlstate */
1.264 brouard 9203: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9204: } /* end cpt state*/
9205: } /* end covariate */
9206: } /* End if prevfcast */
1.227 brouard 9207:
1.296 brouard 9208: if(prevbcast==1){
1.268 brouard 9209: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9210:
1.337 brouard 9211: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9212: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9213: k1=TKresult[nres];
1.338 brouard 9214: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9215: /* if(m != 1 && TKresult[nres]!= k1) */
9216: /* continue; */
1.268 brouard 9217: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9218: strcpy(gplotlabel,"(");
9219: 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 9220: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9221: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9222: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9223: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9224: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9225: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9226: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9227: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9228: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9229: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9230: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9231: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9232: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9233: /* } */
9234: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9235: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9236: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9237: }
9238: strcpy(gplotlabel+strlen(gplotlabel),")");
9239: fprintf(ficgp,"\n#\n");
9240: if(invalidvarcomb[k1]){
9241: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9242: continue;
9243: }
9244:
9245: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9246: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9247: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9248: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9249: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9250:
9251: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9252: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9253: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9254: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9255: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9256: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9257: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9258: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9259: if(i==istart){
9260: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9261: }else{
9262: fprintf(ficgp,",\\\n '' ");
9263: }
1.351 brouard 9264: /* if(cptcoveff ==0){ /\* No covariate *\/ */
9265: if(cptcovs ==0){ /* No covariate */
1.268 brouard 9266: ioffset=2; /* Age is in 2 */
9267: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9268: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9269: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9270: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9271: fprintf(ficgp," u %d:(", ioffset);
9272: if(i==nlstate+1){
1.270 brouard 9273: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9274: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9275: fprintf(ficgp,",\\\n '' ");
9276: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9277: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9278: offbyear, \
9279: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9280: }else
9281: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9282: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9283: }else{ /* more than 2 covariates */
1.270 brouard 9284: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9285: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9286: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9287: iyearc=ioffset-1;
9288: iagec=ioffset;
1.268 brouard 9289: fprintf(ficgp," u %d:(",ioffset);
9290: kl=0;
9291: strcpy(gplotcondition,"(");
1.337 brouard 9292: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9293: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9294: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9295: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9296: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9297: lv=Tvresult[nres][k];
9298: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9299: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9300: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9301: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9302: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9303: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9304: kl++;
9305: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9306: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9307: kl++;
1.338 brouard 9308: if(k <cptcovs && cptcovs>1)
1.337 brouard 9309: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9310: }
1.268 brouard 9311: }
9312: strcpy(gplotcondition+strlen(gplotcondition),")");
9313: /* 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 *\/ */
9314: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9315: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9316: /* '' 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*/
9317: if(i==nlstate+1){
1.270 brouard 9318: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9319: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9320: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9321: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9322: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9323: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9324: iyearc,iagec,offbyear, \
9325: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9326: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9327: }else{
9328: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9329: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9330: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9331: }
9332: } /* end if covariate */
9333: } /* nlstate */
9334: fprintf(ficgp,"\nset out; unset label;\n");
9335: } /* end cpt state*/
9336: } /* end covariate */
1.296 brouard 9337: } /* End if prevbcast */
1.268 brouard 9338:
1.227 brouard 9339:
1.238 brouard 9340: /* 9eme writing MLE parameters */
9341: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9342: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9343: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9344: for(k=1; k <=(nlstate+ndeath); k++){
9345: if (k != i) {
1.227 brouard 9346: fprintf(ficgp,"# current state %d\n",k);
9347: for(j=1; j <=ncovmodel; j++){
9348: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9349: jk++;
9350: }
9351: fprintf(ficgp,"\n");
1.126 brouard 9352: }
9353: }
1.223 brouard 9354: }
1.187 brouard 9355: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9356:
1.145 brouard 9357: /*goto avoid;*/
1.238 brouard 9358: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9359: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9360: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9361: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9362: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9363: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9364: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9365: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9366: fprintf(ficgp,"# p11=1/(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,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9369: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9370: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9371: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9372: fprintf(ficgp,"#\n");
1.223 brouard 9373: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9374: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9375: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9376: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 9377: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
9378: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 9379: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9380: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9381: /* k1=nres; */
1.338 brouard 9382: k1=TKresult[nres];
9383: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9384: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9385: strcpy(gplotlabel,"(");
1.276 brouard 9386: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9387: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9388: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9389: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9390: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9391: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9392: }
9393: /* if(m != 1 && TKresult[nres]!= k1) */
9394: /* continue; */
9395: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9396: /* strcpy(gplotlabel,"("); */
9397: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9398: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9399: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9400: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9401: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9402: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9403: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9404: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9405: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9406: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9407: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9408: /* } */
9409: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9410: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9411: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9412: /* } */
1.264 brouard 9413: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9414: fprintf(ficgp,"\n#\n");
1.264 brouard 9415: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9416: fprintf(ficgp,"\nset key outside ");
9417: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9418: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9419: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9420: if (ng==1){
9421: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9422: fprintf(ficgp,"\nunset log y");
9423: }else if (ng==2){
9424: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9425: fprintf(ficgp,"\nset log y");
9426: }else if (ng==3){
9427: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9428: fprintf(ficgp,"\nset log y");
9429: }else
9430: fprintf(ficgp,"\nunset title ");
9431: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9432: i=1;
9433: for(k2=1; k2<=nlstate; k2++) {
9434: k3=i;
9435: for(k=1; k<=(nlstate+ndeath); k++) {
9436: if (k != k2){
9437: switch( ng) {
9438: case 1:
9439: if(nagesqr==0)
9440: fprintf(ficgp," p%d+p%d*x",i,i+1);
9441: else /* nagesqr =1 */
9442: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9443: break;
9444: case 2: /* ng=2 */
9445: if(nagesqr==0)
9446: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9447: else /* nagesqr =1 */
9448: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9449: break;
9450: case 3:
9451: if(nagesqr==0)
9452: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9453: else /* nagesqr =1 */
9454: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9455: break;
9456: }
9457: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9458: ijp=1; /* product no age */
9459: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9460: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9461: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9462: switch(Typevar[j]){
9463: case 1:
9464: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9465: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9466: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9467: if(DummyV[j]==0){/* Bug valgrind */
9468: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9469: }else{ /* quantitative */
9470: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9471: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9472: }
9473: ij++;
1.268 brouard 9474: }
1.237 brouard 9475: }
1.329 brouard 9476: }
9477: break;
9478: case 2:
9479: if(cptcovprod >0){
9480: if(j==Tprod[ijp]) { /* */
9481: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9482: if(ijp <=cptcovprod) { /* Product */
9483: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9484: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9485: /* 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)]); */
9486: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9487: }else{ /* Vn is dummy and Vm is quanti */
9488: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9489: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9490: }
9491: }else{ /* Vn*Vm Vn is quanti */
9492: if(DummyV[Tvard[ijp][2]]==0){
9493: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9494: }else{ /* Both quanti */
9495: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9496: }
1.268 brouard 9497: }
1.329 brouard 9498: ijp++;
1.237 brouard 9499: }
1.329 brouard 9500: } /* end Tprod */
9501: }
9502: break;
1.349 brouard 9503: case 3:
9504: if(cptcovdageprod >0){
9505: /* if(j==Tprod[ijp]) { */ /* not necessary */
9506: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 9507: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
9508: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9509: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9510: /* 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)]); */
9511: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9512: }else{ /* Vn is dummy and Vm is quanti */
9513: /* 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 9514: 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 9515: }
1.350 brouard 9516: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 9517: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 9518: 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 9519: }else{ /* Both quanti */
1.350 brouard 9520: 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 9521: }
9522: }
9523: ijp++;
9524: }
9525: /* } */ /* end Tprod */
9526: }
9527: break;
1.329 brouard 9528: case 0:
9529: /* simple covariate */
1.264 brouard 9530: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9531: if(Dummy[j]==0){
9532: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9533: }else{ /* quantitative */
9534: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9535: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9536: }
1.329 brouard 9537: /* end simple */
9538: break;
9539: default:
9540: break;
9541: } /* end switch */
1.237 brouard 9542: } /* end j */
1.329 brouard 9543: }else{ /* k=k2 */
9544: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9545: fprintf(ficgp," (1.");i=i-ncovmodel;
9546: }else
9547: i=i-ncovmodel;
1.223 brouard 9548: }
1.227 brouard 9549:
1.223 brouard 9550: if(ng != 1){
9551: fprintf(ficgp,")/(1");
1.227 brouard 9552:
1.264 brouard 9553: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9554: if(nagesqr==0)
1.264 brouard 9555: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9556: else /* nagesqr =1 */
1.264 brouard 9557: 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 9558:
1.223 brouard 9559: ij=1;
1.329 brouard 9560: ijp=1;
9561: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9562: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9563: switch(Typevar[j]){
9564: case 1:
9565: if(cptcovage >0){
9566: if(j==Tage[ij]) { /* Bug valgrind */
9567: if(ij <=cptcovage) { /* Bug valgrind */
9568: if(DummyV[j]==0){/* Bug valgrind */
9569: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9570: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9571: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9572: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9573: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9574: }else{ /* quantitative */
9575: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9576: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9577: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9578: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9579: }
9580: ij++;
9581: }
9582: }
9583: }
9584: break;
9585: case 2:
9586: if(cptcovprod >0){
9587: if(j==Tprod[ijp]) { /* */
9588: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9589: if(ijp <=cptcovprod) { /* Product */
9590: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9591: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9592: /* 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)]); */
9593: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9594: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9595: }else{ /* Vn is dummy and Vm is quanti */
9596: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9597: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9598: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9599: }
9600: }else{ /* Vn*Vm Vn is quanti */
9601: if(DummyV[Tvard[ijp][2]]==0){
9602: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9603: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9604: }else{ /* Both quanti */
9605: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9606: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9607: }
9608: }
9609: ijp++;
9610: }
9611: } /* end Tprod */
9612: } /* end if */
9613: break;
1.349 brouard 9614: case 3:
9615: if(cptcovdageprod >0){
9616: /* if(j==Tprod[ijp]) { /\* *\/ */
9617: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9618: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 9619: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9620: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9621: /* 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 9622: 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 9623: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9624: }else{ /* Vn is dummy and Vm is quanti */
9625: /* 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 9626: 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 9627: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9628: }
9629: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 9630: if(DummyV[Tvardk[ijp][2]]==0){
9631: 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 9632: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9633: }else{ /* Both quanti */
1.350 brouard 9634: 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 9635: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9636: }
9637: }
9638: ijp++;
9639: }
9640: /* } /\* end Tprod *\/ */
9641: } /* end if */
9642: break;
1.329 brouard 9643: case 0:
9644: /* simple covariate */
9645: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9646: if(Dummy[j]==0){
9647: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9648: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9649: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9650: }else{ /* quantitative */
9651: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9652: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9653: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9654: }
9655: /* end simple */
9656: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9657: break;
9658: default:
9659: break;
9660: } /* end switch */
1.223 brouard 9661: }
9662: fprintf(ficgp,")");
9663: }
9664: fprintf(ficgp,")");
9665: if(ng ==2)
1.276 brouard 9666: 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 9667: else /* ng= 3 */
1.276 brouard 9668: 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 9669: }else{ /* end ng <> 1 */
1.223 brouard 9670: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9671: 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 9672: }
9673: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9674: fprintf(ficgp,",");
9675: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9676: fprintf(ficgp,",");
9677: i=i+ncovmodel;
9678: } /* end k */
9679: } /* end k2 */
1.276 brouard 9680: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9681: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9682: } /* end resultline */
1.223 brouard 9683: } /* end ng */
9684: /* avoid: */
9685: fflush(ficgp);
1.126 brouard 9686: } /* end gnuplot */
9687:
9688:
9689: /*************** Moving average **************/
1.219 brouard 9690: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9691: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9692:
1.222 brouard 9693: int i, cpt, cptcod;
9694: int modcovmax =1;
9695: int mobilavrange, mob;
9696: int iage=0;
1.288 brouard 9697: int firstA1=0, firstA2=0;
1.222 brouard 9698:
1.266 brouard 9699: double sum=0., sumr=0.;
1.222 brouard 9700: double age;
1.266 brouard 9701: double *sumnewp, *sumnewm, *sumnewmr;
9702: double *agemingood, *agemaxgood;
9703: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9704:
9705:
1.278 brouard 9706: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9707: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9708:
9709: sumnewp = vector(1,ncovcombmax);
9710: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9711: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9712: agemingood = vector(1,ncovcombmax);
1.266 brouard 9713: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9714: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9715: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9716:
9717: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9718: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9719: sumnewp[cptcod]=0.;
1.266 brouard 9720: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9721: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9722: }
9723: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9724:
1.266 brouard 9725: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9726: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9727: else mobilavrange=mobilav;
9728: for (age=bage; age<=fage; age++)
9729: for (i=1; i<=nlstate;i++)
9730: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9731: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9732: /* We keep the original values on the extreme ages bage, fage and for
9733: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9734: we use a 5 terms etc. until the borders are no more concerned.
9735: */
9736: for (mob=3;mob <=mobilavrange;mob=mob+2){
9737: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9738: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9739: sumnewm[cptcod]=0.;
9740: for (i=1; i<=nlstate;i++){
1.222 brouard 9741: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9742: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9743: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9744: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9745: }
9746: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9747: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9748: } /* end i */
9749: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9750: } /* end cptcod */
1.222 brouard 9751: }/* end age */
9752: }/* end mob */
1.266 brouard 9753: }else{
9754: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9755: return -1;
1.266 brouard 9756: }
9757:
9758: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9759: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9760: if(invalidvarcomb[cptcod]){
9761: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9762: continue;
9763: }
1.219 brouard 9764:
1.266 brouard 9765: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9766: sumnewm[cptcod]=0.;
9767: sumnewmr[cptcod]=0.;
9768: for (i=1; i<=nlstate;i++){
9769: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9770: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9771: }
9772: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9773: agemingoodr[cptcod]=age;
9774: }
9775: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9776: agemingood[cptcod]=age;
9777: }
9778: } /* age */
9779: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9780: sumnewm[cptcod]=0.;
1.266 brouard 9781: sumnewmr[cptcod]=0.;
1.222 brouard 9782: for (i=1; i<=nlstate;i++){
9783: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9784: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9785: }
9786: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9787: agemaxgoodr[cptcod]=age;
1.222 brouard 9788: }
9789: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9790: agemaxgood[cptcod]=age;
9791: }
9792: } /* age */
9793: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9794: /* but they will change */
1.288 brouard 9795: firstA1=0;firstA2=0;
1.266 brouard 9796: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9797: sumnewm[cptcod]=0.;
9798: sumnewmr[cptcod]=0.;
9799: for (i=1; i<=nlstate;i++){
9800: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9801: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9802: }
9803: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9804: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9805: agemaxgoodr[cptcod]=age; /* age min */
9806: for (i=1; i<=nlstate;i++)
9807: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9808: }else{ /* bad we change the value with the values of good ages */
9809: for (i=1; i<=nlstate;i++){
9810: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9811: } /* i */
9812: } /* end bad */
9813: }else{
9814: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9815: agemaxgood[cptcod]=age;
9816: }else{ /* bad we change the value with the values of good ages */
9817: for (i=1; i<=nlstate;i++){
9818: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9819: } /* i */
9820: } /* end bad */
9821: }/* end else */
9822: sum=0.;sumr=0.;
9823: for (i=1; i<=nlstate;i++){
9824: sum+=mobaverage[(int)age][i][cptcod];
9825: sumr+=probs[(int)age][i][cptcod];
9826: }
9827: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9828: if(!firstA1){
9829: firstA1=1;
9830: 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);
9831: }
9832: 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 9833: } /* end bad */
9834: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9835: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9836: if(!firstA2){
9837: firstA2=1;
9838: 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);
9839: }
9840: 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 9841: } /* end bad */
9842: }/* age */
1.266 brouard 9843:
9844: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9845: sumnewm[cptcod]=0.;
1.266 brouard 9846: sumnewmr[cptcod]=0.;
1.222 brouard 9847: for (i=1; i<=nlstate;i++){
9848: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9849: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9850: }
9851: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9852: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9853: agemingoodr[cptcod]=age;
9854: for (i=1; i<=nlstate;i++)
9855: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9856: }else{ /* bad we change the value with the values of good ages */
9857: for (i=1; i<=nlstate;i++){
9858: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9859: } /* i */
9860: } /* end bad */
9861: }else{
9862: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9863: agemingood[cptcod]=age;
9864: }else{ /* bad */
9865: for (i=1; i<=nlstate;i++){
9866: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9867: } /* i */
9868: } /* end bad */
9869: }/* end else */
9870: sum=0.;sumr=0.;
9871: for (i=1; i<=nlstate;i++){
9872: sum+=mobaverage[(int)age][i][cptcod];
9873: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9874: }
1.266 brouard 9875: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9876: 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 9877: } /* end bad */
9878: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9879: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9880: 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 9881: } /* end bad */
9882: }/* age */
1.266 brouard 9883:
1.222 brouard 9884:
9885: for (age=bage; age<=fage; age++){
1.235 brouard 9886: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9887: sumnewp[cptcod]=0.;
9888: sumnewm[cptcod]=0.;
9889: for (i=1; i<=nlstate;i++){
9890: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9891: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9892: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9893: }
9894: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9895: }
9896: /* printf("\n"); */
9897: /* } */
1.266 brouard 9898:
1.222 brouard 9899: /* brutal averaging */
1.266 brouard 9900: /* for (i=1; i<=nlstate;i++){ */
9901: /* for (age=1; age<=bage; age++){ */
9902: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9903: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9904: /* } */
9905: /* for (age=fage; age<=AGESUP; age++){ */
9906: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9907: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9908: /* } */
9909: /* } /\* end i status *\/ */
9910: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9911: /* for (age=1; age<=AGESUP; age++){ */
9912: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9913: /* mobaverage[(int)age][i][cptcod]=0.; */
9914: /* } */
9915: /* } */
1.222 brouard 9916: }/* end cptcod */
1.266 brouard 9917: free_vector(agemaxgoodr,1, ncovcombmax);
9918: free_vector(agemaxgood,1, ncovcombmax);
9919: free_vector(agemingood,1, ncovcombmax);
9920: free_vector(agemingoodr,1, ncovcombmax);
9921: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9922: free_vector(sumnewm,1, ncovcombmax);
9923: free_vector(sumnewp,1, ncovcombmax);
9924: return 0;
9925: }/* End movingaverage */
1.218 brouard 9926:
1.126 brouard 9927:
1.296 brouard 9928:
1.126 brouard 9929: /************** Forecasting ******************/
1.296 brouard 9930: /* 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)*/
9931: 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){
9932: /* dateintemean, mean date of interviews
9933: dateprojd, year, month, day of starting projection
9934: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9935: agemin, agemax range of age
9936: dateprev1 dateprev2 range of dates during which prevalence is computed
9937: */
1.296 brouard 9938: /* double anprojd, mprojd, jprojd; */
9939: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9940: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9941: double agec; /* generic age */
1.296 brouard 9942: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9943: double *popeffectif,*popcount;
9944: double ***p3mat;
1.218 brouard 9945: /* double ***mobaverage; */
1.126 brouard 9946: char fileresf[FILENAMELENGTH];
9947:
9948: agelim=AGESUP;
1.211 brouard 9949: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9950: in each health status at the date of interview (if between dateprev1 and dateprev2).
9951: We still use firstpass and lastpass as another selection.
9952: */
1.214 brouard 9953: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9954: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9955:
1.201 brouard 9956: strcpy(fileresf,"F_");
9957: strcat(fileresf,fileresu);
1.126 brouard 9958: if((ficresf=fopen(fileresf,"w"))==NULL) {
9959: printf("Problem with forecast resultfile: %s\n", fileresf);
9960: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9961: }
1.235 brouard 9962: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9963: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9964:
1.225 brouard 9965: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9966:
9967:
9968: stepsize=(int) (stepm+YEARM-1)/YEARM;
9969: if (stepm<=12) stepsize=1;
9970: if(estepm < stepm){
9971: printf ("Problem %d lower than %d\n",estepm, stepm);
9972: }
1.270 brouard 9973: else{
9974: hstepm=estepm;
9975: }
9976: if(estepm > stepm){ /* Yes every two year */
9977: stepsize=2;
9978: }
1.296 brouard 9979: hstepm=hstepm/stepm;
1.126 brouard 9980:
1.296 brouard 9981:
9982: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9983: /* fractional in yp1 *\/ */
9984: /* aintmean=yp; */
9985: /* yp2=modf((yp1*12),&yp); */
9986: /* mintmean=yp; */
9987: /* yp1=modf((yp2*30.5),&yp); */
9988: /* jintmean=yp; */
9989: /* if(jintmean==0) jintmean=1; */
9990: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9991:
1.296 brouard 9992:
9993: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9994: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9995: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 9996: /* i1=pow(2,cptcoveff); */
9997: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 9998:
1.296 brouard 9999: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 10000:
10001: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 10002:
1.126 brouard 10003: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 10004: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10005: k=TKresult[nres];
10006: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
10007: /* 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) *\/ */
10008: /* if(i1 != 1 && TKresult[nres]!= k) */
10009: /* continue; */
10010: /* if(invalidvarcomb[k]){ */
10011: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
10012: /* continue; */
10013: /* } */
1.227 brouard 10014: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 10015: for(j=1;j<=cptcovs;j++){
10016: /* for(j=1;j<=cptcoveff;j++) { */
10017: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
10018: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10019: /* } */
10020: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10021: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10022: /* } */
10023: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 10024: }
1.351 brouard 10025:
1.227 brouard 10026: fprintf(ficresf," yearproj age");
10027: for(j=1; j<=nlstate+ndeath;j++){
10028: for(i=1; i<=nlstate;i++)
10029: fprintf(ficresf," p%d%d",i,j);
10030: fprintf(ficresf," wp.%d",j);
10031: }
1.296 brouard 10032: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 10033: fprintf(ficresf,"\n");
1.296 brouard 10034: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 10035: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
10036: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 10037: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
10038: nhstepm = nhstepm/hstepm;
10039: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10040: oldm=oldms;savm=savms;
1.268 brouard 10041: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 10042: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 10043: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 10044: for (h=0; h<=nhstepm; h++){
10045: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 10046: break;
10047: }
10048: }
10049: fprintf(ficresf,"\n");
1.351 brouard 10050: /* for(j=1;j<=cptcoveff;j++) */
10051: for(j=1;j<=cptcovs;j++)
10052: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 10053: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 10054: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 10055: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 10056:
10057: for(j=1; j<=nlstate+ndeath;j++) {
10058: ppij=0.;
10059: for(i=1; i<=nlstate;i++) {
1.278 brouard 10060: if (mobilav>=1)
10061: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
10062: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
10063: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
10064: }
1.268 brouard 10065: fprintf(ficresf," %.3f", p3mat[i][j][h]);
10066: } /* end i */
10067: fprintf(ficresf," %.3f", ppij);
10068: }/* end j */
1.227 brouard 10069: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10070: } /* end agec */
1.266 brouard 10071: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
10072: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 10073: } /* end yearp */
10074: } /* end k */
1.219 brouard 10075:
1.126 brouard 10076: fclose(ficresf);
1.215 brouard 10077: printf("End of Computing forecasting \n");
10078: fprintf(ficlog,"End of Computing forecasting\n");
10079:
1.126 brouard 10080: }
10081:
1.269 brouard 10082: /************** Back Forecasting ******************/
1.296 brouard 10083: /* 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){ */
10084: 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){
10085: /* back1, year, month, day of starting backprojection
1.267 brouard 10086: agemin, agemax range of age
10087: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 10088: anback2 year of end of backprojection (same day and month as back1).
10089: prevacurrent and prev are prevalences.
1.267 brouard 10090: */
10091: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
10092: double agec; /* generic age */
1.302 brouard 10093: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10094: double *popeffectif,*popcount;
10095: double ***p3mat;
10096: /* double ***mobaverage; */
10097: char fileresfb[FILENAMELENGTH];
10098:
1.268 brouard 10099: agelim=AGEINF;
1.267 brouard 10100: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10101: in each health status at the date of interview (if between dateprev1 and dateprev2).
10102: We still use firstpass and lastpass as another selection.
10103: */
10104: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10105: /* firstpass, lastpass, stepm, weightopt, model); */
10106:
10107: /*Do we need to compute prevalence again?*/
10108:
10109: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10110:
10111: strcpy(fileresfb,"FB_");
10112: strcat(fileresfb,fileresu);
10113: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10114: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10115: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10116: }
10117: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10118: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10119:
10120: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10121:
10122:
10123: stepsize=(int) (stepm+YEARM-1)/YEARM;
10124: if (stepm<=12) stepsize=1;
10125: if(estepm < stepm){
10126: printf ("Problem %d lower than %d\n",estepm, stepm);
10127: }
1.270 brouard 10128: else{
10129: hstepm=estepm;
10130: }
10131: if(estepm >= stepm){ /* Yes every two year */
10132: stepsize=2;
10133: }
1.267 brouard 10134:
10135: hstepm=hstepm/stepm;
1.296 brouard 10136: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10137: /* fractional in yp1 *\/ */
10138: /* aintmean=yp; */
10139: /* yp2=modf((yp1*12),&yp); */
10140: /* mintmean=yp; */
10141: /* yp1=modf((yp2*30.5),&yp); */
10142: /* jintmean=yp; */
10143: /* if(jintmean==0) jintmean=1; */
10144: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10145:
1.351 brouard 10146: /* i1=pow(2,cptcoveff); */
10147: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 10148:
1.296 brouard 10149: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10150: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10151:
10152: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10153:
1.351 brouard 10154: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10155: k=TKresult[nres];
10156: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
10157: /* for(k=1; k<=i1;k++){ */
10158: /* if(i1 != 1 && TKresult[nres]!= k) */
10159: /* continue; */
10160: /* if(invalidvarcomb[k]){ */
10161: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
10162: /* continue; */
10163: /* } */
1.268 brouard 10164: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 10165: for(j=1;j<=cptcovs;j++){
10166: /* for(j=1;j<=cptcoveff;j++) { */
10167: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10168: /* } */
10169: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 10170: }
1.351 brouard 10171: /* fprintf(ficrespij,"******\n"); */
10172: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10173: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10174: /* } */
1.267 brouard 10175: fprintf(ficresfb," yearbproj age");
10176: for(j=1; j<=nlstate+ndeath;j++){
10177: for(i=1; i<=nlstate;i++)
1.268 brouard 10178: fprintf(ficresfb," b%d%d",i,j);
10179: fprintf(ficresfb," b.%d",j);
1.267 brouard 10180: }
1.296 brouard 10181: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10182: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10183: fprintf(ficresfb,"\n");
1.296 brouard 10184: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10185: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10186: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10187: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10188: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10189: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10190: nhstepm = nhstepm/hstepm;
10191: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10192: oldm=oldms;savm=savms;
1.268 brouard 10193: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10194: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10195: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10196: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10197: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10198: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10199: for (h=0; h<=nhstepm; h++){
1.268 brouard 10200: if (h*hstepm/YEARM*stepm ==-yearp) {
10201: break;
10202: }
10203: }
10204: fprintf(ficresfb,"\n");
1.351 brouard 10205: /* for(j=1;j<=cptcoveff;j++) */
10206: for(j=1;j<=cptcovs;j++)
10207: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10208: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 10209: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10210: for(i=1; i<=nlstate+ndeath;i++) {
10211: ppij=0.;ppi=0.;
10212: for(j=1; j<=nlstate;j++) {
10213: /* if (mobilav==1) */
1.269 brouard 10214: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10215: ppi=ppi+prevacurrent[(int)agec][j][k];
10216: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10217: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10218: /* else { */
10219: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10220: /* } */
1.268 brouard 10221: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10222: } /* end j */
10223: if(ppi <0.99){
10224: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10225: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10226: }
10227: fprintf(ficresfb," %.3f", ppij);
10228: }/* end j */
1.267 brouard 10229: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10230: } /* end agec */
10231: } /* end yearp */
10232: } /* end k */
1.217 brouard 10233:
1.267 brouard 10234: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10235:
1.267 brouard 10236: fclose(ficresfb);
10237: printf("End of Computing Back forecasting \n");
10238: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10239:
1.267 brouard 10240: }
1.217 brouard 10241:
1.269 brouard 10242: /* Variance of prevalence limit: varprlim */
10243: 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 10244: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10245:
10246: char fileresvpl[FILENAMELENGTH];
10247: FILE *ficresvpl;
10248: double **oldm, **savm;
10249: double **varpl; /* Variances of prevalence limits by age */
10250: int i1, k, nres, j ;
10251:
10252: strcpy(fileresvpl,"VPL_");
10253: strcat(fileresvpl,fileresu);
10254: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10255: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10256: exit(0);
10257: }
1.288 brouard 10258: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10259: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10260:
10261: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10262: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10263:
10264: i1=pow(2,cptcoveff);
10265: if (cptcovn < 1){i1=1;}
10266:
1.337 brouard 10267: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10268: k=TKresult[nres];
1.338 brouard 10269: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10270: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10271: if(i1 != 1 && TKresult[nres]!= k)
10272: continue;
10273: fprintf(ficresvpl,"\n#****** ");
10274: printf("\n#****** ");
10275: fprintf(ficlog,"\n#****** ");
1.337 brouard 10276: for(j=1;j<=cptcovs;j++) {
10277: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10278: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10279: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10280: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10281: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10282: }
1.337 brouard 10283: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10284: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10285: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10286: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10287: /* } */
1.269 brouard 10288: fprintf(ficresvpl,"******\n");
10289: printf("******\n");
10290: fprintf(ficlog,"******\n");
10291:
10292: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10293: oldm=oldms;savm=savms;
10294: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10295: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10296: /*}*/
10297: }
10298:
10299: fclose(ficresvpl);
1.288 brouard 10300: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10301: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10302:
10303: }
10304: /* Variance of back prevalence: varbprlim */
10305: 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){
10306: /*------- Variance of back (stable) prevalence------*/
10307:
10308: char fileresvbl[FILENAMELENGTH];
10309: FILE *ficresvbl;
10310:
10311: double **oldm, **savm;
10312: double **varbpl; /* Variances of back prevalence limits by age */
10313: int i1, k, nres, j ;
10314:
10315: strcpy(fileresvbl,"VBL_");
10316: strcat(fileresvbl,fileresu);
10317: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10318: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10319: exit(0);
10320: }
10321: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10322: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10323:
10324:
10325: i1=pow(2,cptcoveff);
10326: if (cptcovn < 1){i1=1;}
10327:
1.337 brouard 10328: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10329: k=TKresult[nres];
1.338 brouard 10330: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10331: /* for(k=1; k<=i1;k++){ */
10332: /* if(i1 != 1 && TKresult[nres]!= k) */
10333: /* continue; */
1.269 brouard 10334: fprintf(ficresvbl,"\n#****** ");
10335: printf("\n#****** ");
10336: fprintf(ficlog,"\n#****** ");
1.337 brouard 10337: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10338: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10339: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10340: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10341: /* for(j=1;j<=cptcoveff;j++) { */
10342: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10343: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10344: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10345: /* } */
10346: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10347: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10348: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10349: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10350: }
10351: fprintf(ficresvbl,"******\n");
10352: printf("******\n");
10353: fprintf(ficlog,"******\n");
10354:
10355: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10356: oldm=oldms;savm=savms;
10357:
10358: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10359: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10360: /*}*/
10361: }
10362:
10363: fclose(ficresvbl);
10364: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10365: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10366:
10367: } /* End of varbprlim */
10368:
1.126 brouard 10369: /************** Forecasting *****not tested NB*************/
1.227 brouard 10370: /* 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 10371:
1.227 brouard 10372: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10373: /* int *popage; */
10374: /* double calagedatem, agelim, kk1, kk2; */
10375: /* double *popeffectif,*popcount; */
10376: /* double ***p3mat,***tabpop,***tabpopprev; */
10377: /* /\* double ***mobaverage; *\/ */
10378: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10379:
1.227 brouard 10380: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10381: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10382: /* agelim=AGESUP; */
10383: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10384:
1.227 brouard 10385: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10386:
10387:
1.227 brouard 10388: /* strcpy(filerespop,"POP_"); */
10389: /* strcat(filerespop,fileresu); */
10390: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10391: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10392: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10393: /* } */
10394: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10395: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10396:
1.227 brouard 10397: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10398:
1.227 brouard 10399: /* /\* if (mobilav!=0) { *\/ */
10400: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10401: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10402: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10403: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10404: /* /\* } *\/ */
10405: /* /\* } *\/ */
1.126 brouard 10406:
1.227 brouard 10407: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10408: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10409:
1.227 brouard 10410: /* agelim=AGESUP; */
1.126 brouard 10411:
1.227 brouard 10412: /* hstepm=1; */
10413: /* hstepm=hstepm/stepm; */
1.218 brouard 10414:
1.227 brouard 10415: /* if (popforecast==1) { */
10416: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10417: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10418: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10419: /* } */
10420: /* popage=ivector(0,AGESUP); */
10421: /* popeffectif=vector(0,AGESUP); */
10422: /* popcount=vector(0,AGESUP); */
1.126 brouard 10423:
1.227 brouard 10424: /* i=1; */
10425: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10426:
1.227 brouard 10427: /* imx=i; */
10428: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10429: /* } */
1.218 brouard 10430:
1.227 brouard 10431: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10432: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10433: /* k=k+1; */
10434: /* fprintf(ficrespop,"\n#******"); */
10435: /* for(j=1;j<=cptcoveff;j++) { */
10436: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10437: /* } */
10438: /* fprintf(ficrespop,"******\n"); */
10439: /* fprintf(ficrespop,"# Age"); */
10440: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10441: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10442:
1.227 brouard 10443: /* for (cpt=0; cpt<=0;cpt++) { */
10444: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10445:
1.227 brouard 10446: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10447: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10448: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10449:
1.227 brouard 10450: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10451: /* oldm=oldms;savm=savms; */
10452: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10453:
1.227 brouard 10454: /* for (h=0; h<=nhstepm; h++){ */
10455: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10456: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10457: /* } */
10458: /* for(j=1; j<=nlstate+ndeath;j++) { */
10459: /* kk1=0.;kk2=0; */
10460: /* for(i=1; i<=nlstate;i++) { */
10461: /* if (mobilav==1) */
10462: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10463: /* else { */
10464: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10465: /* } */
10466: /* } */
10467: /* if (h==(int)(calagedatem+12*cpt)){ */
10468: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10469: /* /\*fprintf(ficrespop," %.3f", kk1); */
10470: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10471: /* } */
10472: /* } */
10473: /* for(i=1; i<=nlstate;i++){ */
10474: /* kk1=0.; */
10475: /* for(j=1; j<=nlstate;j++){ */
10476: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10477: /* } */
10478: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10479: /* } */
1.218 brouard 10480:
1.227 brouard 10481: /* if (h==(int)(calagedatem+12*cpt)) */
10482: /* for(j=1; j<=nlstate;j++) */
10483: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10484: /* } */
10485: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10486: /* } */
10487: /* } */
1.218 brouard 10488:
1.227 brouard 10489: /* /\******\/ */
1.218 brouard 10490:
1.227 brouard 10491: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10492: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10493: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10494: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10495: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10496:
1.227 brouard 10497: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10498: /* oldm=oldms;savm=savms; */
10499: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10500: /* for (h=0; h<=nhstepm; h++){ */
10501: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10502: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10503: /* } */
10504: /* for(j=1; j<=nlstate+ndeath;j++) { */
10505: /* kk1=0.;kk2=0; */
10506: /* for(i=1; i<=nlstate;i++) { */
10507: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10508: /* } */
10509: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10510: /* } */
10511: /* } */
10512: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10513: /* } */
10514: /* } */
10515: /* } */
10516: /* } */
1.218 brouard 10517:
1.227 brouard 10518: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10519:
1.227 brouard 10520: /* if (popforecast==1) { */
10521: /* free_ivector(popage,0,AGESUP); */
10522: /* free_vector(popeffectif,0,AGESUP); */
10523: /* free_vector(popcount,0,AGESUP); */
10524: /* } */
10525: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10526: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10527: /* fclose(ficrespop); */
10528: /* } /\* End of popforecast *\/ */
1.218 brouard 10529:
1.126 brouard 10530: int fileappend(FILE *fichier, char *optionfich)
10531: {
10532: if((fichier=fopen(optionfich,"a"))==NULL) {
10533: printf("Problem with file: %s\n", optionfich);
10534: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10535: return (0);
10536: }
10537: fflush(fichier);
10538: return (1);
10539: }
10540:
10541:
10542: /**************** function prwizard **********************/
10543: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10544: {
10545:
10546: /* Wizard to print covariance matrix template */
10547:
1.164 brouard 10548: char ca[32], cb[32];
10549: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10550: int numlinepar;
10551:
10552: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10553: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10554: for(i=1; i <=nlstate; i++){
10555: jj=0;
10556: for(j=1; j <=nlstate+ndeath; j++){
10557: if(j==i) continue;
10558: jj++;
10559: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10560: printf("%1d%1d",i,j);
10561: fprintf(ficparo,"%1d%1d",i,j);
10562: for(k=1; k<=ncovmodel;k++){
10563: /* printf(" %lf",param[i][j][k]); */
10564: /* fprintf(ficparo," %lf",param[i][j][k]); */
10565: printf(" 0.");
10566: fprintf(ficparo," 0.");
10567: }
10568: printf("\n");
10569: fprintf(ficparo,"\n");
10570: }
10571: }
10572: printf("# Scales (for hessian or gradient estimation)\n");
10573: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10574: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10575: for(i=1; i <=nlstate; i++){
10576: jj=0;
10577: for(j=1; j <=nlstate+ndeath; j++){
10578: if(j==i) continue;
10579: jj++;
10580: fprintf(ficparo,"%1d%1d",i,j);
10581: printf("%1d%1d",i,j);
10582: fflush(stdout);
10583: for(k=1; k<=ncovmodel;k++){
10584: /* printf(" %le",delti3[i][j][k]); */
10585: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10586: printf(" 0.");
10587: fprintf(ficparo," 0.");
10588: }
10589: numlinepar++;
10590: printf("\n");
10591: fprintf(ficparo,"\n");
10592: }
10593: }
10594: printf("# Covariance matrix\n");
10595: /* # 121 Var(a12)\n\ */
10596: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10597: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10598: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10599: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10600: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10601: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10602: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10603: fflush(stdout);
10604: fprintf(ficparo,"# Covariance matrix\n");
10605: /* # 121 Var(a12)\n\ */
10606: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10607: /* # ...\n\ */
10608: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10609:
10610: for(itimes=1;itimes<=2;itimes++){
10611: jj=0;
10612: for(i=1; i <=nlstate; i++){
10613: for(j=1; j <=nlstate+ndeath; j++){
10614: if(j==i) continue;
10615: for(k=1; k<=ncovmodel;k++){
10616: jj++;
10617: ca[0]= k+'a'-1;ca[1]='\0';
10618: if(itimes==1){
10619: printf("#%1d%1d%d",i,j,k);
10620: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10621: }else{
10622: printf("%1d%1d%d",i,j,k);
10623: fprintf(ficparo,"%1d%1d%d",i,j,k);
10624: /* printf(" %.5le",matcov[i][j]); */
10625: }
10626: ll=0;
10627: for(li=1;li <=nlstate; li++){
10628: for(lj=1;lj <=nlstate+ndeath; lj++){
10629: if(lj==li) continue;
10630: for(lk=1;lk<=ncovmodel;lk++){
10631: ll++;
10632: if(ll<=jj){
10633: cb[0]= lk +'a'-1;cb[1]='\0';
10634: if(ll<jj){
10635: if(itimes==1){
10636: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10637: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10638: }else{
10639: printf(" 0.");
10640: fprintf(ficparo," 0.");
10641: }
10642: }else{
10643: if(itimes==1){
10644: printf(" Var(%s%1d%1d)",ca,i,j);
10645: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10646: }else{
10647: printf(" 0.");
10648: fprintf(ficparo," 0.");
10649: }
10650: }
10651: }
10652: } /* end lk */
10653: } /* end lj */
10654: } /* end li */
10655: printf("\n");
10656: fprintf(ficparo,"\n");
10657: numlinepar++;
10658: } /* end k*/
10659: } /*end j */
10660: } /* end i */
10661: } /* end itimes */
10662:
10663: } /* end of prwizard */
10664: /******************* Gompertz Likelihood ******************************/
10665: double gompertz(double x[])
10666: {
1.302 brouard 10667: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10668: int i,n=0; /* n is the size of the sample */
10669:
1.220 brouard 10670: for (i=1;i<=imx ; i++) {
1.126 brouard 10671: sump=sump+weight[i];
10672: /* sump=sump+1;*/
10673: num=num+1;
10674: }
1.302 brouard 10675: L=0.0;
10676: /* agegomp=AGEGOMP; */
1.126 brouard 10677: /* for (i=0; i<=imx; i++)
10678: 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]);*/
10679:
1.302 brouard 10680: for (i=1;i<=imx ; i++) {
10681: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10682: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10683: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10684: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10685: * +
10686: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10687: */
10688: if (wav[i] > 1 || agedc[i] < AGESUP) {
10689: if (cens[i] == 1){
10690: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10691: } else if (cens[i] == 0){
1.126 brouard 10692: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10693: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10694: } else
10695: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10696: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10697: L=L+A*weight[i];
1.126 brouard 10698: /* 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 10699: }
10700: }
1.126 brouard 10701:
1.302 brouard 10702: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10703:
10704: return -2*L*num/sump;
10705: }
10706:
1.136 brouard 10707: #ifdef GSL
10708: /******************* Gompertz_f Likelihood ******************************/
10709: double gompertz_f(const gsl_vector *v, void *params)
10710: {
1.302 brouard 10711: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10712: double *x= (double *) v->data;
10713: int i,n=0; /* n is the size of the sample */
10714:
10715: for (i=0;i<=imx-1 ; i++) {
10716: sump=sump+weight[i];
10717: /* sump=sump+1;*/
10718: num=num+1;
10719: }
10720:
10721:
10722: /* for (i=0; i<=imx; i++)
10723: 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]);*/
10724: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10725: for (i=1;i<=imx ; i++)
10726: {
10727: if (cens[i] == 1 && wav[i]>1)
10728: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10729:
10730: if (cens[i] == 0 && wav[i]>1)
10731: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10732: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10733:
10734: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10735: if (wav[i] > 1 ) { /* ??? */
10736: LL=LL+A*weight[i];
10737: /* 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]);*/
10738: }
10739: }
10740:
10741: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10742: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10743:
10744: return -2*LL*num/sump;
10745: }
10746: #endif
10747:
1.126 brouard 10748: /******************* Printing html file ***********/
1.201 brouard 10749: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10750: int lastpass, int stepm, int weightopt, char model[],\
10751: int imx, double p[],double **matcov,double agemortsup){
10752: int i,k;
10753:
10754: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10755: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10756: for (i=1;i<=2;i++)
10757: 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 10758: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10759: fprintf(fichtm,"</ul>");
10760:
10761: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10762:
10763: 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>");
10764:
10765: for (k=agegomp;k<(agemortsup-2);k++)
10766: 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]);
10767:
10768:
10769: fflush(fichtm);
10770: }
10771:
10772: /******************* Gnuplot file **************/
1.201 brouard 10773: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10774:
10775: char dirfileres[132],optfileres[132];
1.164 brouard 10776:
1.126 brouard 10777: int ng;
10778:
10779:
10780: /*#ifdef windows */
10781: fprintf(ficgp,"cd \"%s\" \n",pathc);
10782: /*#endif */
10783:
10784:
10785: strcpy(dirfileres,optionfilefiname);
10786: strcpy(optfileres,"vpl");
1.199 brouard 10787: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10788: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10789: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10790: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10791: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10792:
10793: }
10794:
1.136 brouard 10795: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10796: {
1.126 brouard 10797:
1.136 brouard 10798: /*-------- data file ----------*/
10799: FILE *fic;
10800: char dummy[]=" ";
1.240 brouard 10801: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10802: int lstra;
1.136 brouard 10803: int linei, month, year,iout;
1.302 brouard 10804: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10805: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10806: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10807: char *stratrunc;
1.223 brouard 10808:
1.349 brouard 10809: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
10810: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10811:
10812: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10813:
1.136 brouard 10814: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10815: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10816: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10817: }
1.126 brouard 10818:
1.302 brouard 10819: /* Is it a BOM UTF-8 Windows file? */
10820: /* First data line */
10821: linei=0;
10822: while(fgets(line, MAXLINE, fic)) {
10823: noffset=0;
10824: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10825: {
10826: noffset=noffset+3;
10827: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10828: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10829: fflush(ficlog); return 1;
10830: }
10831: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10832: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10833: {
10834: noffset=noffset+2;
1.304 brouard 10835: 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);
10836: 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 10837: fflush(ficlog); return 1;
10838: }
10839: else if( line[0] == 0 && line[1] == 0)
10840: {
10841: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10842: noffset=noffset+4;
1.304 brouard 10843: 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);
10844: 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 10845: fflush(ficlog); return 1;
10846: }
10847: } else{
10848: ;/*printf(" Not a BOM file\n");*/
10849: }
10850: /* If line starts with a # it is a comment */
10851: if (line[noffset] == '#') {
10852: linei=linei+1;
10853: break;
10854: }else{
10855: break;
10856: }
10857: }
10858: fclose(fic);
10859: if((fic=fopen(datafile,"r"))==NULL) {
10860: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10861: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10862: }
10863: /* Not a Bom file */
10864:
1.136 brouard 10865: i=1;
10866: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10867: linei=linei+1;
10868: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10869: if(line[j] == '\t')
10870: line[j] = ' ';
10871: }
10872: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10873: ;
10874: };
10875: line[j+1]=0; /* Trims blanks at end of line */
10876: if(line[0]=='#'){
10877: fprintf(ficlog,"Comment line\n%s\n",line);
10878: printf("Comment line\n%s\n",line);
10879: continue;
10880: }
10881: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10882: strcpy(line, linetmp);
1.223 brouard 10883:
10884: /* Loops on waves */
10885: for (j=maxwav;j>=1;j--){
10886: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10887: cutv(stra, strb, line, ' ');
10888: if(strb[0]=='.') { /* Missing value */
10889: lval=-1;
10890: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10891: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10892: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10893: 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);
10894: 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);
10895: return 1;
10896: }
10897: }else{
10898: errno=0;
10899: /* what_kind_of_number(strb); */
10900: dval=strtod(strb,&endptr);
10901: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10902: /* if(strb != endptr && *endptr == '\0') */
10903: /* dval=dlval; */
10904: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10905: if( strb[0]=='\0' || (*endptr != '\0')){
10906: 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);
10907: 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);
10908: return 1;
10909: }
10910: cotqvar[j][iv][i]=dval;
1.341 brouard 10911: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10912: }
10913: strcpy(line,stra);
1.223 brouard 10914: }/* end loop ntqv */
1.225 brouard 10915:
1.223 brouard 10916: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10917: cutv(stra, strb, line, ' ');
10918: if(strb[0]=='.') { /* Missing value */
10919: lval=-1;
10920: }else{
10921: errno=0;
10922: lval=strtol(strb,&endptr,10);
10923: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10924: if( strb[0]=='\0' || (*endptr != '\0')){
10925: 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);
10926: 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);
10927: return 1;
10928: }
10929: }
10930: if(lval <-1 || lval >1){
10931: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10932: 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 10933: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10934: For example, for multinomial values like 1, 2 and 3,\n \
10935: build V1=0 V2=0 for the reference value (1),\n \
10936: V1=1 V2=0 for (2) \n \
1.223 brouard 10937: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10938: output of IMaCh is often meaningless.\n \
1.319 brouard 10939: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10940: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10941: 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 10942: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10943: For example, for multinomial values like 1, 2 and 3,\n \
10944: build V1=0 V2=0 for the reference value (1),\n \
10945: V1=1 V2=0 for (2) \n \
1.223 brouard 10946: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10947: output of IMaCh is often meaningless.\n \
1.319 brouard 10948: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10949: return 1;
10950: }
1.341 brouard 10951: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10952: strcpy(line,stra);
1.223 brouard 10953: }/* end loop ntv */
1.225 brouard 10954:
1.223 brouard 10955: /* Statuses at wave */
1.137 brouard 10956: cutv(stra, strb, line, ' ');
1.223 brouard 10957: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10958: lval=-1;
1.136 brouard 10959: }else{
1.238 brouard 10960: errno=0;
10961: lval=strtol(strb,&endptr,10);
10962: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10963: if( strb[0]=='\0' || (*endptr != '\0' )){
10964: 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);
10965: 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);
10966: return 1;
10967: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10968: 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);
10969: 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 10970: return 1;
10971: }
1.136 brouard 10972: }
1.225 brouard 10973:
1.136 brouard 10974: s[j][i]=lval;
1.225 brouard 10975:
1.223 brouard 10976: /* Date of Interview */
1.136 brouard 10977: strcpy(line,stra);
10978: cutv(stra, strb,line,' ');
1.169 brouard 10979: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10980: }
1.169 brouard 10981: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10982: month=99;
10983: year=9999;
1.136 brouard 10984: }else{
1.225 brouard 10985: 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);
10986: 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);
10987: return 1;
1.136 brouard 10988: }
10989: anint[j][i]= (double) year;
1.302 brouard 10990: mint[j][i]= (double)month;
10991: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10992: /* 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]); */
10993: /* 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]); */
10994: /* } */
1.136 brouard 10995: strcpy(line,stra);
1.223 brouard 10996: } /* End loop on waves */
1.225 brouard 10997:
1.223 brouard 10998: /* Date of death */
1.136 brouard 10999: cutv(stra, strb,line,' ');
1.169 brouard 11000: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 11001: }
1.169 brouard 11002: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 11003: month=99;
11004: year=9999;
11005: }else{
1.141 brouard 11006: 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 11007: 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);
11008: return 1;
1.136 brouard 11009: }
11010: andc[i]=(double) year;
11011: moisdc[i]=(double) month;
11012: strcpy(line,stra);
11013:
1.223 brouard 11014: /* Date of birth */
1.136 brouard 11015: cutv(stra, strb,line,' ');
1.169 brouard 11016: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 11017: }
1.169 brouard 11018: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 11019: month=99;
11020: year=9999;
11021: }else{
1.141 brouard 11022: 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);
11023: 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 11024: return 1;
1.136 brouard 11025: }
11026: if (year==9999) {
1.141 brouard 11027: 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);
11028: 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 11029: return 1;
11030:
1.136 brouard 11031: }
11032: annais[i]=(double)(year);
1.302 brouard 11033: moisnais[i]=(double)(month);
11034: for (j=1;j<=maxwav;j++){
11035: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
11036: 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]);
11037: 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]);
11038: }
11039: }
11040:
1.136 brouard 11041: strcpy(line,stra);
1.225 brouard 11042:
1.223 brouard 11043: /* Sample weight */
1.136 brouard 11044: cutv(stra, strb,line,' ');
11045: errno=0;
11046: dval=strtod(strb,&endptr);
11047: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 11048: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
11049: 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 11050: fflush(ficlog);
11051: return 1;
11052: }
11053: weight[i]=dval;
11054: strcpy(line,stra);
1.225 brouard 11055:
1.223 brouard 11056: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
11057: cutv(stra, strb, line, ' ');
11058: if(strb[0]=='.') { /* Missing value */
1.225 brouard 11059: lval=-1;
1.311 brouard 11060: coqvar[iv][i]=NAN;
11061: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 11062: }else{
1.225 brouard 11063: errno=0;
11064: /* what_kind_of_number(strb); */
11065: dval=strtod(strb,&endptr);
11066: /* if(strb != endptr && *endptr == '\0') */
11067: /* dval=dlval; */
11068: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
11069: if( strb[0]=='\0' || (*endptr != '\0')){
11070: 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);
11071: 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);
11072: return 1;
11073: }
11074: coqvar[iv][i]=dval;
1.226 brouard 11075: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 11076: }
11077: strcpy(line,stra);
11078: }/* end loop nqv */
1.136 brouard 11079:
1.223 brouard 11080: /* Covariate values */
1.136 brouard 11081: for (j=ncovcol;j>=1;j--){
11082: cutv(stra, strb,line,' ');
1.223 brouard 11083: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 11084: lval=-1;
1.136 brouard 11085: }else{
1.225 brouard 11086: errno=0;
11087: lval=strtol(strb,&endptr,10);
11088: if( strb[0]=='\0' || (*endptr != '\0')){
11089: 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);
11090: 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);
11091: return 1;
11092: }
1.136 brouard 11093: }
11094: if(lval <-1 || lval >1){
1.225 brouard 11095: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11096: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11097: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11098: For example, for multinomial values like 1, 2 and 3,\n \
11099: build V1=0 V2=0 for the reference value (1),\n \
11100: V1=1 V2=0 for (2) \n \
1.136 brouard 11101: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11102: output of IMaCh is often meaningless.\n \
1.136 brouard 11103: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11104: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11105: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11106: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11107: For example, for multinomial values like 1, 2 and 3,\n \
11108: build V1=0 V2=0 for the reference value (1),\n \
11109: V1=1 V2=0 for (2) \n \
1.136 brouard 11110: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11111: output of IMaCh is often meaningless.\n \
1.136 brouard 11112: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11113: return 1;
1.136 brouard 11114: }
11115: covar[j][i]=(double)(lval);
11116: strcpy(line,stra);
11117: }
11118: lstra=strlen(stra);
1.225 brouard 11119:
1.136 brouard 11120: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11121: stratrunc = &(stra[lstra-9]);
11122: num[i]=atol(stratrunc);
11123: }
11124: else
11125: num[i]=atol(stra);
11126: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11127: 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;}*/
11128:
11129: i=i+1;
11130: } /* End loop reading data */
1.225 brouard 11131:
1.136 brouard 11132: *imax=i-1; /* Number of individuals */
11133: fclose(fic);
1.225 brouard 11134:
1.136 brouard 11135: return (0);
1.164 brouard 11136: /* endread: */
1.225 brouard 11137: printf("Exiting readdata: ");
11138: fclose(fic);
11139: return (1);
1.223 brouard 11140: }
1.126 brouard 11141:
1.234 brouard 11142: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11143: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11144: while (*p2 == ' ')
1.234 brouard 11145: p2++;
11146: /* while ((*p1++ = *p2++) !=0) */
11147: /* ; */
11148: /* do */
11149: /* while (*p2 == ' ') */
11150: /* p2++; */
11151: /* while (*p1++ == *p2++); */
11152: *stri=p2;
1.145 brouard 11153: }
11154:
1.330 brouard 11155: int decoderesult( char resultline[], int nres)
1.230 brouard 11156: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11157: {
1.235 brouard 11158: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11159: char resultsav[MAXLINE];
1.330 brouard 11160: /* int resultmodel[MAXLINE]; */
1.334 brouard 11161: /* int modelresult[MAXLINE]; */
1.230 brouard 11162: char stra[80], strb[80], strc[80], strd[80],stre[80];
11163:
1.234 brouard 11164: removefirstspace(&resultline);
1.332 brouard 11165: printf("decoderesult:%s\n",resultline);
1.230 brouard 11166:
1.332 brouard 11167: strcpy(resultsav,resultline);
1.342 brouard 11168: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11169: if (strlen(resultsav) >1){
1.334 brouard 11170: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11171: }
1.353 brouard 11172: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 11173: TKresult[nres]=0; /* Combination for the nresult and the model */
11174: return (0);
11175: }
1.234 brouard 11176: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 brouard 11177: 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);
11178: 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);
11179: if(j==0)
11180: return 1;
1.234 brouard 11181: }
1.334 brouard 11182: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11183: if(nbocc(resultsav,'=') >1){
1.318 brouard 11184: 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 11185: /* 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 11186: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11187: /* If a blank, then strc="V4=" and strd='\0' */
11188: if(strc[0]=='\0'){
11189: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11190: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11191: return 1;
11192: }
1.234 brouard 11193: }else
11194: cutl(strc,strd,resultsav,'=');
1.318 brouard 11195: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11196:
1.230 brouard 11197: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11198: 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 11199: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11200: /* cptcovsel++; */
11201: if (nbocc(stra,'=') >0)
11202: strcpy(resultsav,stra); /* and analyzes it */
11203: }
1.235 brouard 11204: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11205: /* 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 11206: 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 11207: if(Typevar[k1]==0){ /* Single covariate in model */
11208: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11209: match=0;
1.318 brouard 11210: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11211: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11212: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11213: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11214: break;
11215: }
11216: }
11217: if(match == 0){
1.338 brouard 11218: 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]);
11219: 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 11220: return 1;
1.234 brouard 11221: }
1.332 brouard 11222: }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*/
11223: /* We feed resultmodel[k1]=k2; */
11224: match=0;
11225: 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 */
11226: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11227: 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 11228: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11229: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11230: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11231: break;
11232: }
11233: }
11234: if(match == 0){
1.338 brouard 11235: 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]);
11236: 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 11237: return 1;
11238: }
1.349 brouard 11239: }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 11240: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11241: match=0;
1.342 brouard 11242: /* 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 11243: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11244: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11245: /* modelresult[k2]=k1; */
1.342 brouard 11246: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11247: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11248: }
11249: }
11250: if(match == 0){
1.349 brouard 11251: 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);
11252: 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 11253: return 1;
11254: }
11255: match=0;
11256: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11257: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11258: /* modelresult[k2]=k1;*/
1.342 brouard 11259: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11260: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11261: break;
11262: }
11263: }
11264: if(match == 0){
1.349 brouard 11265: 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);
11266: 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 11267: return 1;
11268: }
11269: }/* End of testing */
1.333 brouard 11270: }/* End loop cptcovt */
1.235 brouard 11271: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11272: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11273: 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)
11274: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11275: match=0;
1.318 brouard 11276: 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 11277: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 11278: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11279: 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 11280: 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 11281: ++match;
11282: }
11283: }
11284: }
11285: if(match == 0){
1.338 brouard 11286: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11287: 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 11288: return 1;
1.234 brouard 11289: }else if(match > 1){
1.338 brouard 11290: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11291: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11292: return 1;
1.234 brouard 11293: }
11294: }
1.334 brouard 11295: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11296: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11297: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11298: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11299: /* 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*/
11300: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11301: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11302: /* 1 0 0 0 */
11303: /* 2 1 0 0 */
11304: /* 3 0 1 0 */
1.330 brouard 11305: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11306: /* 5 0 0 1 */
1.330 brouard 11307: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11308: /* 7 0 1 1 */
11309: /* 8 1 1 1 */
1.237 brouard 11310: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11311: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11312: /* V5*age V5 known which value for nres? */
11313: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11314: 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.
11315: * loop on position k1 in the MODEL LINE */
1.331 brouard 11316: /* k counting number of combination of single dummies in the equation model */
11317: /* k4 counting single dummies in the equation model */
11318: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11319: 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 11320: /* 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 11321: /* 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 11322: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11323: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11324: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11325: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11326: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11327: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11328: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11329: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11330: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11331: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11332: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11333: 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 11334: 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 11335: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11336: /* Tinvresult[nres][4]=1 */
1.334 brouard 11337: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11338: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11339: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11340: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11341: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11342: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11343: /* 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 11344: k4++;;
1.331 brouard 11345: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11346: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11347: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11348: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11349: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11350: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11351: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11352: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11353: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11354: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11355: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11356: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11357: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11358: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11359: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11360: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11361: /* 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 11362: k4q++;;
1.350 brouard 11363: }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"*/
11364: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 11365: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 11366: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11367: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11368: /* 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]]); */
11369: }else{
11370: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11371: 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)*/
11372: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
11373: precov[nres][k1]=Tvalsel[k3];
11374: }
1.342 brouard 11375: /* 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 11376: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 11377: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11378: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11379: /* 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]]); */
11380: }else{
11381: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
11382: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
11383: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
11384: precov[nres][k1]=Tvalsel[k3q];
11385: }
1.342 brouard 11386: /* 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 11387: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11388: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11389: /* 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 11390: }else{
1.332 brouard 11391: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11392: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11393: }
11394: }
1.234 brouard 11395:
1.334 brouard 11396: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11397: return (0);
11398: }
1.235 brouard 11399:
1.230 brouard 11400: int decodemodel( char model[], int lastobs)
11401: /**< This routine decodes the model and returns:
1.224 brouard 11402: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11403: * - nagesqr = 1 if age*age in the model, otherwise 0.
11404: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11405: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11406: * - cptcovage number of covariates with age*products =2
11407: * - cptcovs number of simple covariates
1.339 brouard 11408: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11409: * - 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 11410: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11411: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11412: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11413: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11414: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11415: */
1.319 brouard 11416: /* 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 11417: {
1.238 brouard 11418: int i, j, k, ks, v;
1.349 brouard 11419: int n,m;
11420: int j1, k1, k11, k12, k2, k3, k4;
11421: char modelsav[300];
11422: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11423: char *strpt;
1.349 brouard 11424: int **existcomb;
11425:
11426: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
11427: for(i=1;i<=NCOVMAX;i++)
11428: for(j=1;j<=NCOVMAX;j++)
11429: existcomb[i][j]=0;
11430:
1.145 brouard 11431: /*removespace(model);*/
1.136 brouard 11432: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 11433: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11434: if (strstr(model,"AGE") !=0){
1.192 brouard 11435: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11436: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11437: return 1;
11438: }
1.141 brouard 11439: if (strstr(model,"v") !=0){
1.338 brouard 11440: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11441: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11442: return 1;
11443: }
1.187 brouard 11444: strcpy(modelsav,model);
11445: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11446: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11447: if(strpt != model){
1.338 brouard 11448: printf("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);
1.338 brouard 11451: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11452: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11453: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11454: return 1;
1.225 brouard 11455: }
1.187 brouard 11456: nagesqr=1;
11457: if (strstr(model,"+age*age") !=0)
1.234 brouard 11458: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11459: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11460: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11461: else
1.234 brouard 11462: substrchaine(modelsav, model, "age*age");
1.187 brouard 11463: }else
11464: nagesqr=0;
1.349 brouard 11465: 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 11466: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11467: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 11468: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 11469: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11470: * cst, age and age*age
11471: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11472: /* including age products which are counted in cptcovage.
11473: * but the covariates which are products must be treated
11474: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 11475: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
11476: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11477: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 11478: cptcovprodage=0;
11479: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11480:
1.187 brouard 11481: /* Design
11482: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11483: * < ncovcol=8 >
11484: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11485: * k= 1 2 3 4 5 6 7 8
11486: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11487: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11488: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11489: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11490: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11491: * Tage[++cptcovage]=k
1.345 brouard 11492: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11493: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11494: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11495: * 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
11496: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11497: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11498: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11499: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11500: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11501: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11502: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11503: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11504: * p Tprod[1]@2={ 6, 5}
11505: *p Tvard[1][1]@4= {7, 8, 5, 6}
11506: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11507: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11508: *How to reorganize? Tvars(orted)
1.187 brouard 11509: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11510: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11511: * {2, 1, 4, 8, 5, 6, 3, 7}
11512: * Struct []
11513: */
1.225 brouard 11514:
1.187 brouard 11515: /* This loop fills the array Tvar from the string 'model'.*/
11516: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11517: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11518: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11519: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11520: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11521: /* k=1 Tvar[1]=2 (from V2) */
11522: /* k=5 Tvar[5] */
11523: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11524: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11525: /* } */
1.198 brouard 11526: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11527: /*
11528: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11529: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11530: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11531: }
1.187 brouard 11532: cptcovage=0;
1.351 brouard 11533:
11534: /* First loop in order to calculate */
11535: /* for age*VN*Vm
11536: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
11537: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
11538: */
11539: /* Needs FixedV[Tvardk[k][1]] */
11540: /* For others:
11541: * Sets Typevar[k];
11542: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11543: * Tposprod[k]=k11;
11544: * Tprod[k11]=k;
11545: * Tvardk[k][1] =m;
11546: * Needs FixedV[Tvardk[k][1]] == 0
11547: */
11548:
1.319 brouard 11549: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11550: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11551: 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" */
11552: if (nbocc(modelsav,'+')==0)
11553: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11554: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11555: /*scanf("%d",i);*/
1.349 brouard 11556: 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 */
11557: 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 */
11558: 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 */
11559: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
11560: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
11561: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
11562: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
11563: /* We want strb=Vn*Vm */
11564: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
11565: strcpy(strb,strd);
11566: strcat(strb,"*");
11567: strcat(strb,stre);
11568: }else{ /* strf=Vm If strf=V6 then stre=V2 */
11569: strcpy(strb,strf);
11570: strcat(strb,"*");
11571: strcat(strb,stre);
11572: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
11573: }
1.351 brouard 11574: /* 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]]]); */
11575: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 11576: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
11577: strcpy(stre,strb); /* save full b in stre */
11578: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
11579: strcpy(strf,strc); /* save short c in new short f */
11580: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
11581: /* strcpy(strc,stre);*/ /* save full e in c for future */
11582: }
11583: cptcovdageprod++; /* double product with age Which product is it? */
11584: /* 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 *\/ */
11585: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11586: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 11587: n=atoi(stre);
1.234 brouard 11588: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 11589: m=atoi(strc);
11590: cptcovage++; /* Counts the number of covariates which include age as a product */
11591: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
11592: if(existcomb[n][m] == 0){
11593: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
11594: 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);
11595: 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);
11596: fflush(ficlog);
11597: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
11598: k12++;
11599: existcomb[n][m]=k1;
11600: existcomb[m][n]=k1;
11601: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
11602: 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*/
11603: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
11604: Tvard[k1][1] =m; /* m 1 for V1*/
11605: Tvardk[k][1] =m; /* m 1 for V1*/
11606: Tvard[k1][2] =n; /* n 4 for V4*/
11607: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 11608: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 11609: 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 */
11610: for (i=1; i<=lastobs;i++){/* For fixed product */
11611: /* Computes the new covariate which is a product of
11612: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11613: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11614: }
11615: cptcovprodage++; /* Counting the number of fixed covariate with age */
11616: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11617: k12++;
11618: FixedV[ncovcolt+k12]=0;
11619: }else{ /*End of FixedV */
11620: cptcovprodvage++; /* Counting the number of varying covariate with age */
11621: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11622: k12++;
11623: FixedV[ncovcolt+k12]=1;
11624: }
11625: }else{ /* k1 Vn*Vm already exists */
11626: k11=existcomb[n][m];
11627: Tposprod[k]=k11; /* OK */
11628: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
11629: Tvardk[k][1]=m;
11630: Tvardk[k][2]=n;
11631: 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 */
11632: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11633: cptcovprodage++; /* Counting the number of fixed covariate with age */
11634: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11635: Tvar[Tage[cptcovage]]=k1;
11636: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11637: k12++;
11638: FixedV[ncovcolt+k12]=0;
11639: }else{ /* Already exists but time varying (and age) */
11640: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11641: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11642: /* Tvar[Tage[cptcovage]]=k1; */
11643: cptcovprodvage++;
11644: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11645: k12++;
11646: FixedV[ncovcolt+k12]=1;
11647: }
11648: }
11649: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
11650: /* Tvar[k]=k11; /\* HERY *\/ */
11651: } 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 */
11652: cptcovprod++;
11653: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
11654: /* covar is not filled and then is empty */
11655: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
11656: 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 */
11657: Typevar[k]=1; /* 1 for age product */
11658: cptcovage++; /* Counts the number of covariates which include age as a product */
11659: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
11660: if( FixedV[Tvar[k]] == 0){
11661: cptcovprodage++; /* Counting the number of fixed covariate with age */
11662: }else{
11663: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
11664: }
11665: /*printf("stre=%s ", stre);*/
11666: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
11667: cutl(stre,strb,strc,'V');
11668: Tvar[k]=atoi(stre);
11669: Typevar[k]=1; /* 1 for age product */
11670: cptcovage++;
11671: Tage[cptcovage]=k;
11672: if( FixedV[Tvar[k]] == 0){
11673: cptcovprodage++; /* Counting the number of fixed covariate with age */
11674: }else{
11675: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11676: }
1.349 brouard 11677: }else{ /* for product Vn*Vm */
11678: Typevar[k]=2; /* 2 for product Vn*Vm */
11679: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
11680: n=atoi(stre);
11681: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11682: m=atoi(strc);
11683: k1++;
11684: cptcovprodnoage++;
11685: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
11686: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11687: 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]);
11688: fflush(ficlog);
11689: k11=existcomb[n][m];
11690: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11691: Tposprod[k]=k11;
11692: Tprod[k11]=k;
11693: Tvardk[k][1] =m; /* m 1 for V1*/
11694: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
11695: Tvardk[k][2] =n; /* n 4 for V4*/
11696: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
11697: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
11698: existcomb[n][m]=k1;
11699: existcomb[m][n]=k1;
11700: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
11701: because this model-covariate is a construction we invent a new column
11702: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
11703: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
11704: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
11705: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
11706: /* Please remark that the new variables are model dependent */
11707: /* If we have 4 variable but the model uses only 3, like in
11708: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11709: * k= 1 2 3 4 5 6 7 8
11710: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11711: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11712: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11713: */
11714: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
11715: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
11716: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
11717: Tvard[k1][1] =m; /* m 1 for V1*/
11718: Tvardk[k][1] =m; /* m 1 for V1*/
11719: Tvard[k1][2] =n; /* n 4 for V4*/
11720: Tvardk[k][2] =n; /* n 4 for V4*/
11721: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11722: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11723: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
11724: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
11725: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
11726: 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 */
11727: for (i=1; i<=lastobs;i++){/* For fixed product */
11728: /* Computes the new covariate which is a product of
11729: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11730: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11731: }
11732: /* TvarVV[k2]=n; */
11733: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11734: /* TvarVV[k2+1]=m; */
11735: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11736: }else{ /* not FixedV */
11737: /* TvarVV[k2]=n; */
11738: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11739: /* TvarVV[k2+1]=m; */
11740: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11741: }
11742: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
11743: } /* End of product Vn*Vm */
11744: } /* End of age*double product or simple product */
11745: }else { /* not a product */
1.234 brouard 11746: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11747: /* scanf("%d",i);*/
11748: cutl(strd,strc,strb,'V');
11749: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11750: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11751: Tvar[k]=atoi(strd);
11752: Typevar[k]=0; /* 0 for simple covariates */
11753: }
11754: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11755: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11756: scanf("%d",i);*/
1.187 brouard 11757: } /* end of loop + on total covariates */
1.351 brouard 11758:
11759:
1.187 brouard 11760: } /* end if strlen(modelsave == 0) age*age might exist */
11761: } /* end if strlen(model == 0) */
1.349 brouard 11762: 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 */
11763:
1.136 brouard 11764: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11765: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11766:
1.136 brouard 11767: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11768: printf("cptcovprod=%d ", cptcovprod);
11769: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11770: scanf("%d ",i);*/
11771:
11772:
1.230 brouard 11773: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11774: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11775: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11776: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11777: k = 1 2 3 4 5 6 7 8 9
11778: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11779: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11780: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11781: Dummy[k] 1 0 0 0 3 1 1 2 3
11782: Tmodelind[combination of covar]=k;
1.225 brouard 11783: */
11784: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11785: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11786: /* 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 11787: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11788: printf("Model=1+age+%s\n\
1.349 brouard 11789: 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 11790: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11791: 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 11792: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 11793: 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 11794: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11795: 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 11796: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11797: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 11798:
11799:
11800: /* Second loop for calculating Fixed[k], Dummy[k]*/
11801:
11802:
1.349 brouard 11803: 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 11804: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11805: Fixed[k]= 0;
11806: Dummy[k]= 0;
1.225 brouard 11807: ncoveff++;
1.232 brouard 11808: ncovf++;
1.234 brouard 11809: nsd++;
11810: modell[k].maintype= FTYPE;
11811: TvarsD[nsd]=Tvar[k];
11812: TvarsDind[nsd]=k;
1.330 brouard 11813: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11814: TvarF[ncovf]=Tvar[k];
11815: TvarFind[ncovf]=k;
11816: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11817: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11818: /* }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 11819: }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 11820: Fixed[k]= 0;
11821: Dummy[k]= 1;
1.230 brouard 11822: nqfveff++;
1.234 brouard 11823: modell[k].maintype= FTYPE;
11824: modell[k].subtype= FQ;
11825: nsq++;
1.334 brouard 11826: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11827: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11828: ncovf++;
1.234 brouard 11829: TvarF[ncovf]=Tvar[k];
11830: TvarFind[ncovf]=k;
1.231 brouard 11831: 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 11832: 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 11833: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11834: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11835: /* model V1+V3+age*V1+age*V3+V1*V3 */
11836: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11837: ncovvt++;
11838: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11839: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11840:
1.227 brouard 11841: Fixed[k]= 1;
11842: Dummy[k]= 0;
1.225 brouard 11843: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11844: modell[k].maintype= VTYPE;
11845: modell[k].subtype= VD;
11846: nsd++;
11847: TvarsD[nsd]=Tvar[k];
11848: TvarsDind[nsd]=k;
1.330 brouard 11849: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11850: ncovv++; /* Only simple time varying variables */
11851: TvarV[ncovv]=Tvar[k];
1.242 brouard 11852: 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 11853: 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 */
11854: 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 11855: 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);
11856: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11857: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11858: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11859: /* model V1+V3+age*V1+age*V3+V1*V3 */
11860: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11861: ncovvt++;
11862: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11863: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11864:
1.234 brouard 11865: Fixed[k]= 1;
11866: Dummy[k]= 1;
11867: nqtveff++;
11868: modell[k].maintype= VTYPE;
11869: modell[k].subtype= VQ;
11870: ncovv++; /* Only simple time varying variables */
11871: nsq++;
1.334 brouard 11872: 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) */
11873: 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 11874: TvarV[ncovv]=Tvar[k];
1.242 brouard 11875: 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 11876: 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 */
11877: 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 11878: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11879: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 11880: /* 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 11881: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11882: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11883: ncova++;
11884: TvarA[ncova]=Tvar[k];
11885: TvarAind[ncova]=k;
1.349 brouard 11886: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11887: /** 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 11888: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11889: Fixed[k]= 2;
11890: Dummy[k]= 2;
11891: modell[k].maintype= ATYPE;
11892: modell[k].subtype= APFD;
1.349 brouard 11893: ncovta++;
11894: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
11895: TvarAVVAind[ncovta]=k;
1.240 brouard 11896: /* ncoveff++; */
1.227 brouard 11897: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11898: Fixed[k]= 2;
11899: Dummy[k]= 3;
11900: modell[k].maintype= ATYPE;
11901: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 11902: ncovta++;
11903: TvarAVVA[ncovta]=Tvar[k]; /* */
11904: TvarAVVAind[ncovta]=k;
1.240 brouard 11905: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11906: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11907: Fixed[k]= 3;
11908: Dummy[k]= 2;
11909: modell[k].maintype= ATYPE;
11910: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 11911: ncovva++;
11912: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11913: TvarVVAind[ncovva]=k;
11914: ncovta++;
11915: TvarAVVA[ncovta]=Tvar[k]; /* */
11916: TvarAVVAind[ncovta]=k;
1.240 brouard 11917: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11918: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11919: Fixed[k]= 3;
11920: Dummy[k]= 3;
11921: modell[k].maintype= ATYPE;
11922: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 11923: ncovva++;
11924: TvarVVA[ncovva]=Tvar[k]; /* */
11925: TvarVVAind[ncovva]=k;
11926: ncovta++;
11927: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11928: TvarAVVAind[ncovta]=k;
1.240 brouard 11929: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11930: }
1.349 brouard 11931: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
11932: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
11933: 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 */
11934: 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]]);
11935: Fixed[k]= 0;
11936: Dummy[k]= 0;
11937: ncoveff++;
11938: ncovf++;
11939: /* ncovv++; */
11940: /* TvarVV[ncovv]=Tvardk[k][1]; */
11941: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11942: /* ncovv++; */
11943: /* TvarVV[ncovv]=Tvardk[k][2]; */
11944: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11945: modell[k].maintype= FTYPE;
11946: TvarF[ncovf]=Tvar[k];
11947: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
11948: TvarFind[ncovf]=k;
11949: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11950: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11951: }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 */
11952: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11953: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11954: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11955: 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 */
11956: ncovvt++;
11957: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11958: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11959: ncovvt++;
11960: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11961: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11962:
11963: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11964: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
11965:
11966: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11967: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
11968: Fixed[k]= 1;
11969: Dummy[k]= 0;
11970: modell[k].maintype= FTYPE;
11971: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11972: ncovf++; /* Fixed variables without age */
11973: TvarF[ncovf]=Tvar[k];
11974: TvarFind[ncovf]=k;
11975: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11976: Fixed[k]= 0; /* Fixed product */
11977: Dummy[k]= 1;
11978: modell[k].maintype= FTYPE;
11979: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11980: ncovf++; /* Varying variables without age */
11981: TvarF[ncovf]=Tvar[k];
11982: TvarFind[ncovf]=k;
11983: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
11984: Fixed[k]= 1;
11985: Dummy[k]= 0;
11986: modell[k].maintype= VTYPE;
11987: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11988: ncovv++; /* Varying variables without age */
11989: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11990: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11991: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
11992: Fixed[k]= 1;
11993: Dummy[k]= 1;
11994: modell[k].maintype= VTYPE;
11995: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11996: ncovv++; /* Varying variables without age */
11997: TvarV[ncovv]=Tvar[k];
11998: TvarVind[ncovv]=k;
11999: }
12000: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12001: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
12002: Fixed[k]= 0; /* Fixed product */
12003: Dummy[k]= 1;
12004: modell[k].maintype= FTYPE;
12005: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
12006: ncovf++; /* Fixed variables without age */
12007: TvarF[ncovf]=Tvar[k];
12008: TvarFind[ncovf]=k;
12009: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
12010: Fixed[k]= 1;
12011: Dummy[k]= 1;
12012: modell[k].maintype= VTYPE;
12013: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
12014: ncovv++; /* Varying variables without age */
12015: TvarV[ncovv]=Tvar[k];
12016: TvarVind[ncovv]=k;
12017: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
12018: Fixed[k]= 1;
12019: Dummy[k]= 1;
12020: modell[k].maintype= VTYPE;
12021: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
12022: ncovv++; /* Varying variables without age */
12023: TvarV[ncovv]=Tvar[k];
12024: TvarVind[ncovv]=k;
12025: ncovv++; /* Varying variables without age */
12026: TvarV[ncovv]=Tvar[k];
12027: TvarVind[ncovv]=k;
12028: }
12029: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
12030: if(Tvard[k1][2] <=ncovcol){
12031: Fixed[k]= 1;
12032: Dummy[k]= 1;
12033: modell[k].maintype= VTYPE;
12034: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
12035: ncovv++; /* Varying variables without age */
12036: TvarV[ncovv]=Tvar[k];
12037: TvarVind[ncovv]=k;
12038: }else if(Tvard[k1][2] <=ncovcol+nqv){
12039: Fixed[k]= 1;
12040: Dummy[k]= 1;
12041: modell[k].maintype= VTYPE;
12042: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
12043: ncovv++; /* Varying variables without age */
12044: TvarV[ncovv]=Tvar[k];
12045: TvarVind[ncovv]=k;
12046: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12047: Fixed[k]= 1;
12048: Dummy[k]= 0;
12049: modell[k].maintype= VTYPE;
12050: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
12051: ncovv++; /* Varying variables without age */
12052: TvarV[ncovv]=Tvar[k];
12053: TvarVind[ncovv]=k;
12054: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12055: Fixed[k]= 1;
12056: Dummy[k]= 1;
12057: modell[k].maintype= VTYPE;
12058: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
12059: ncovv++; /* Varying variables without age */
12060: TvarV[ncovv]=Tvar[k];
12061: TvarVind[ncovv]=k;
12062: }
12063: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
12064: if(Tvard[k1][2] <=ncovcol){
12065: Fixed[k]= 1;
12066: Dummy[k]= 1;
12067: modell[k].maintype= VTYPE;
12068: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
12069: ncovv++; /* Varying variables without age */
12070: TvarV[ncovv]=Tvar[k];
12071: TvarVind[ncovv]=k;
12072: }else if(Tvard[k1][2] <=ncovcol+nqv){
12073: Fixed[k]= 1;
12074: Dummy[k]= 1;
12075: modell[k].maintype= VTYPE;
12076: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
12077: ncovv++; /* Varying variables without age */
12078: TvarV[ncovv]=Tvar[k];
12079: TvarVind[ncovv]=k;
12080: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12081: Fixed[k]= 1;
12082: Dummy[k]= 1;
12083: modell[k].maintype= VTYPE;
12084: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
12085: ncovv++; /* Varying variables without age */
12086: TvarV[ncovv]=Tvar[k];
12087: TvarVind[ncovv]=k;
12088: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12089: Fixed[k]= 1;
12090: Dummy[k]= 1;
12091: modell[k].maintype= VTYPE;
12092: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
12093: ncovv++; /* Varying variables without age */
12094: TvarV[ncovv]=Tvar[k];
12095: TvarVind[ncovv]=k;
12096: }
12097: }else{
12098: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12099: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12100: } /*end k1*/
12101: }
12102: }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 12103: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 12104: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
12105: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
12106: 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 */
12107: ncova++;
12108: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
12109: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
12110: ncova++;
12111: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
12112: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 12113:
1.349 brouard 12114: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
12115: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
12116: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
12117: ncovta++;
12118: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12119: TvarAVVAind[ncovta]=k;
12120: ncovta++;
12121: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12122: TvarAVVAind[ncovta]=k;
12123: }else{
12124: ncovva++; /* HERY reached */
12125: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12126: TvarVVAind[ncovva]=k;
12127: ncovva++;
12128: TvarVVA[ncovva]=Tvard[k1][2]; /* */
12129: TvarVVAind[ncovva]=k;
12130: ncovta++;
12131: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12132: TvarAVVAind[ncovta]=k;
12133: ncovta++;
12134: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12135: TvarAVVAind[ncovta]=k;
12136: }
1.339 brouard 12137: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12138: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 12139: Fixed[k]= 2;
12140: Dummy[k]= 2;
1.240 brouard 12141: modell[k].maintype= FTYPE;
12142: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 12143: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
12144: /* TvarFind[ncova]=k; */
1.339 brouard 12145: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 12146: Fixed[k]= 2; /* Fixed product */
12147: Dummy[k]= 3;
1.240 brouard 12148: modell[k].maintype= FTYPE;
12149: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 12150: /* TvarF[ncova]=Tvar[k]; */
12151: /* TvarFind[ncova]=k; */
1.339 brouard 12152: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 12153: Fixed[k]= 3;
12154: Dummy[k]= 2;
1.240 brouard 12155: modell[k].maintype= VTYPE;
12156: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 12157: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
12158: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12159: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 12160: Fixed[k]= 3;
12161: Dummy[k]= 3;
1.240 brouard 12162: modell[k].maintype= VTYPE;
12163: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 12164: /* ncovv++; /\* Varying variables without age *\/ */
12165: /* TvarV[ncovv]=Tvar[k]; */
12166: /* TvarVind[ncovv]=k; */
1.240 brouard 12167: }
1.339 brouard 12168: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12169: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 12170: Fixed[k]= 2; /* Fixed product */
12171: Dummy[k]= 2;
1.240 brouard 12172: modell[k].maintype= FTYPE;
12173: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 12174: /* ncova++; /\* Fixed variables with age *\/ */
12175: /* TvarF[ncovf]=Tvar[k]; */
12176: /* TvarFind[ncovf]=k; */
1.339 brouard 12177: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 12178: Fixed[k]= 2;
12179: Dummy[k]= 3;
1.240 brouard 12180: modell[k].maintype= VTYPE;
12181: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 12182: /* ncova++; /\* Varying variables with age *\/ */
12183: /* TvarV[ncova]=Tvar[k]; */
12184: /* TvarVind[ncova]=k; */
1.339 brouard 12185: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 12186: Fixed[k]= 3;
12187: Dummy[k]= 2;
1.240 brouard 12188: modell[k].maintype= VTYPE;
12189: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 12190: ncova++; /* Varying variables without age */
12191: TvarV[ncova]=Tvar[k];
12192: TvarVind[ncova]=k;
12193: /* ncova++; /\* Varying variables without age *\/ */
12194: /* TvarV[ncova]=Tvar[k]; */
12195: /* TvarVind[ncova]=k; */
1.240 brouard 12196: }
1.339 brouard 12197: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12198: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12199: Fixed[k]= 2;
12200: Dummy[k]= 2;
1.240 brouard 12201: modell[k].maintype= VTYPE;
12202: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 12203: /* ncova++; /\* Varying variables with age *\/ */
12204: /* TvarV[ncova]=Tvar[k]; */
12205: /* TvarVind[ncova]=k; */
1.240 brouard 12206: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12207: Fixed[k]= 2;
12208: Dummy[k]= 3;
1.240 brouard 12209: modell[k].maintype= VTYPE;
12210: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 12211: /* ncova++; /\* Varying variables with age *\/ */
12212: /* TvarV[ncova]=Tvar[k]; */
12213: /* TvarVind[ncova]=k; */
1.240 brouard 12214: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12215: Fixed[k]= 3;
12216: Dummy[k]= 2;
1.240 brouard 12217: modell[k].maintype= VTYPE;
12218: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 12219: /* ncova++; /\* Varying variables with age *\/ */
12220: /* TvarV[ncova]=Tvar[k]; */
12221: /* TvarVind[ncova]=k; */
1.240 brouard 12222: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12223: Fixed[k]= 3;
12224: Dummy[k]= 3;
1.240 brouard 12225: modell[k].maintype= VTYPE;
12226: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 12227: /* ncova++; /\* Varying variables with age *\/ */
12228: /* TvarV[ncova]=Tvar[k]; */
12229: /* TvarVind[ncova]=k; */
1.240 brouard 12230: }
1.339 brouard 12231: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12232: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12233: Fixed[k]= 2;
12234: Dummy[k]= 2;
1.240 brouard 12235: modell[k].maintype= VTYPE;
12236: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 12237: /* ncova++; /\* Varying variables with age *\/ */
12238: /* TvarV[ncova]=Tvar[k]; */
12239: /* TvarVind[ncova]=k; */
1.240 brouard 12240: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12241: Fixed[k]= 2;
12242: Dummy[k]= 3;
1.240 brouard 12243: modell[k].maintype= VTYPE;
12244: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 12245: /* ncova++; /\* Varying variables with age *\/ */
12246: /* TvarV[ncova]=Tvar[k]; */
12247: /* TvarVind[ncova]=k; */
1.240 brouard 12248: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12249: Fixed[k]= 3;
12250: Dummy[k]= 2;
1.240 brouard 12251: modell[k].maintype= VTYPE;
12252: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 12253: /* ncova++; /\* Varying variables with age *\/ */
12254: /* TvarV[ncova]=Tvar[k]; */
12255: /* TvarVind[ncova]=k; */
1.240 brouard 12256: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12257: Fixed[k]= 3;
12258: Dummy[k]= 3;
1.240 brouard 12259: modell[k].maintype= VTYPE;
12260: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 12261: /* ncova++; /\* Varying variables with age *\/ */
12262: /* TvarV[ncova]=Tvar[k]; */
12263: /* TvarVind[ncova]=k; */
1.240 brouard 12264: }
1.227 brouard 12265: }else{
1.240 brouard 12266: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12267: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12268: } /*end k1*/
1.349 brouard 12269: } else{
1.226 brouard 12270: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12271: 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 12272: }
1.342 brouard 12273: /* 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]); */
12274: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12275: 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]);
12276: }
1.349 brouard 12277: ncovvta=ncovva;
1.227 brouard 12278: /* Searching for doublons in the model */
12279: for(k1=1; k1<= cptcovt;k1++){
12280: for(k2=1; k2 <k1;k2++){
1.285 brouard 12281: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12282: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12283: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12284: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12285: 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]);
12286: 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 12287: return(1);
12288: }
12289: }else if (Typevar[k1] ==2){
12290: k3=Tposprod[k1];
12291: k4=Tposprod[k2];
12292: 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 12293: 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]]);
12294: 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 12295: return(1);
12296: }
12297: }
1.227 brouard 12298: }
12299: }
1.225 brouard 12300: }
12301: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12302: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12303: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12304: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 12305:
12306: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12307: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12308: /*endread:*/
1.225 brouard 12309: printf("Exiting decodemodel: ");
12310: return (1);
1.136 brouard 12311: }
12312:
1.169 brouard 12313: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12314: {/* Check ages at death */
1.136 brouard 12315: int i, m;
1.218 brouard 12316: int firstone=0;
12317:
1.136 brouard 12318: for (i=1; i<=imx; i++) {
12319: for(m=2; (m<= maxwav); m++) {
12320: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12321: anint[m][i]=9999;
1.216 brouard 12322: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12323: s[m][i]=-1;
1.136 brouard 12324: }
12325: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12326: *nberr = *nberr + 1;
1.218 brouard 12327: if(firstone == 0){
12328: firstone=1;
1.260 brouard 12329: 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 12330: }
1.262 brouard 12331: 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 12332: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12333: }
12334: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12335: (*nberr)++;
1.259 brouard 12336: 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 12337: 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 12338: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12339: }
12340: }
12341: }
12342:
12343: for (i=1; i<=imx; i++) {
12344: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12345: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12346: 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 12347: if (s[m][i] >= nlstate+1) {
1.169 brouard 12348: if(agedc[i]>0){
12349: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12350: agev[m][i]=agedc[i];
1.214 brouard 12351: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12352: }else {
1.136 brouard 12353: if ((int)andc[i]!=9999){
12354: nbwarn++;
12355: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12356: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12357: agev[m][i]=-1;
12358: }
12359: }
1.169 brouard 12360: } /* agedc > 0 */
1.214 brouard 12361: } /* end if */
1.136 brouard 12362: else if(s[m][i] !=9){ /* Standard case, age in fractional
12363: years but with the precision of a month */
12364: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12365: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12366: agev[m][i]=1;
12367: else if(agev[m][i] < *agemin){
12368: *agemin=agev[m][i];
12369: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12370: }
12371: else if(agev[m][i] >*agemax){
12372: *agemax=agev[m][i];
1.156 brouard 12373: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12374: }
12375: /*agev[m][i]=anint[m][i]-annais[i];*/
12376: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12377: } /* en if 9*/
1.136 brouard 12378: else { /* =9 */
1.214 brouard 12379: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12380: agev[m][i]=1;
12381: s[m][i]=-1;
12382: }
12383: }
1.214 brouard 12384: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12385: agev[m][i]=1;
1.214 brouard 12386: else{
12387: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12388: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12389: agev[m][i]=0;
12390: }
12391: } /* End for lastpass */
12392: }
1.136 brouard 12393:
12394: for (i=1; i<=imx; i++) {
12395: for(m=firstpass; (m<=lastpass); m++){
12396: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12397: (*nberr)++;
1.136 brouard 12398: 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);
12399: 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);
12400: return 1;
12401: }
12402: }
12403: }
12404:
12405: /*for (i=1; i<=imx; i++){
12406: for (m=firstpass; (m<lastpass); m++){
12407: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12408: }
12409:
12410: }*/
12411:
12412:
1.139 brouard 12413: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12414: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12415:
12416: return (0);
1.164 brouard 12417: /* endread:*/
1.136 brouard 12418: printf("Exiting calandcheckages: ");
12419: return (1);
12420: }
12421:
1.172 brouard 12422: #if defined(_MSC_VER)
12423: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12424: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12425: //#include "stdafx.h"
12426: //#include <stdio.h>
12427: //#include <tchar.h>
12428: //#include <windows.h>
12429: //#include <iostream>
12430: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12431:
12432: LPFN_ISWOW64PROCESS fnIsWow64Process;
12433:
12434: BOOL IsWow64()
12435: {
12436: BOOL bIsWow64 = FALSE;
12437:
12438: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12439: // (HANDLE, PBOOL);
12440:
12441: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12442:
12443: HMODULE module = GetModuleHandle(_T("kernel32"));
12444: const char funcName[] = "IsWow64Process";
12445: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12446: GetProcAddress(module, funcName);
12447:
12448: if (NULL != fnIsWow64Process)
12449: {
12450: if (!fnIsWow64Process(GetCurrentProcess(),
12451: &bIsWow64))
12452: //throw std::exception("Unknown error");
12453: printf("Unknown error\n");
12454: }
12455: return bIsWow64 != FALSE;
12456: }
12457: #endif
1.177 brouard 12458:
1.191 brouard 12459: void syscompilerinfo(int logged)
1.292 brouard 12460: {
12461: #include <stdint.h>
12462:
12463: /* #include "syscompilerinfo.h"*/
1.185 brouard 12464: /* command line Intel compiler 32bit windows, XP compatible:*/
12465: /* /GS /W3 /Gy
12466: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12467: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12468: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12469: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12470: */
12471: /* 64 bits */
1.185 brouard 12472: /*
12473: /GS /W3 /Gy
12474: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12475: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12476: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12477: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12478: /* Optimization are useless and O3 is slower than O2 */
12479: /*
12480: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12481: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12482: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12483: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12484: */
1.186 brouard 12485: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12486: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12487: /PDB:"visual studio
12488: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12489: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12490: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12491: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12492: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12493: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12494: uiAccess='false'"
12495: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12496: /NOLOGO /TLBID:1
12497: */
1.292 brouard 12498:
12499:
1.177 brouard 12500: #if defined __INTEL_COMPILER
1.178 brouard 12501: #if defined(__GNUC__)
12502: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12503: #endif
1.177 brouard 12504: #elif defined(__GNUC__)
1.179 brouard 12505: #ifndef __APPLE__
1.174 brouard 12506: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12507: #endif
1.177 brouard 12508: struct utsname sysInfo;
1.178 brouard 12509: int cross = CROSS;
12510: if (cross){
12511: printf("Cross-");
1.191 brouard 12512: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12513: }
1.174 brouard 12514: #endif
12515:
1.191 brouard 12516: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12517: #if defined(__clang__)
1.191 brouard 12518: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12519: #endif
12520: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12521: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12522: #endif
12523: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12524: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12525: #endif
12526: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12527: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12528: #endif
12529: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12530: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12531: #endif
12532: #if defined(_MSC_VER)
1.191 brouard 12533: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12534: #endif
12535: #if defined(__PGI)
1.191 brouard 12536: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12537: #endif
12538: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12539: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12540: #endif
1.191 brouard 12541: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12542:
1.167 brouard 12543: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12544: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12545: // Windows (x64 and x86)
1.191 brouard 12546: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12547: #elif __unix__ // all unices, not all compilers
12548: // Unix
1.191 brouard 12549: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12550: #elif __linux__
12551: // linux
1.191 brouard 12552: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12553: #elif __APPLE__
1.174 brouard 12554: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12555: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12556: #endif
12557:
12558: /* __MINGW32__ */
12559: /* __CYGWIN__ */
12560: /* __MINGW64__ */
12561: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12562: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12563: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12564: /* _WIN64 // Defined for applications for Win64. */
12565: /* _M_X64 // Defined for compilations that target x64 processors. */
12566: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12567:
1.167 brouard 12568: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12569: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12570: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12571: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12572: #else
1.191 brouard 12573: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12574: #endif
12575:
1.169 brouard 12576: #if defined(__GNUC__)
12577: # if defined(__GNUC_PATCHLEVEL__)
12578: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12579: + __GNUC_MINOR__ * 100 \
12580: + __GNUC_PATCHLEVEL__)
12581: # else
12582: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12583: + __GNUC_MINOR__ * 100)
12584: # endif
1.174 brouard 12585: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12586: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12587:
12588: if (uname(&sysInfo) != -1) {
12589: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12590: 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 12591: }
12592: else
12593: perror("uname() error");
1.179 brouard 12594: //#ifndef __INTEL_COMPILER
12595: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12596: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12597: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12598: #endif
1.169 brouard 12599: #endif
1.172 brouard 12600:
1.286 brouard 12601: // void main ()
1.172 brouard 12602: // {
1.169 brouard 12603: #if defined(_MSC_VER)
1.174 brouard 12604: if (IsWow64()){
1.191 brouard 12605: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12606: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12607: }
12608: else{
1.191 brouard 12609: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12610: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12611: }
1.172 brouard 12612: // printf("\nPress Enter to continue...");
12613: // getchar();
12614: // }
12615:
1.169 brouard 12616: #endif
12617:
1.167 brouard 12618:
1.219 brouard 12619: }
1.136 brouard 12620:
1.219 brouard 12621: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12622: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12623: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12624: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12625: /* double ftolpl = 1.e-10; */
1.180 brouard 12626: double age, agebase, agelim;
1.203 brouard 12627: double tot;
1.180 brouard 12628:
1.202 brouard 12629: strcpy(filerespl,"PL_");
12630: strcat(filerespl,fileresu);
12631: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12632: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12633: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12634: }
1.288 brouard 12635: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12636: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12637: pstamp(ficrespl);
1.288 brouard 12638: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12639: fprintf(ficrespl,"#Age ");
12640: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12641: fprintf(ficrespl,"\n");
1.180 brouard 12642:
1.219 brouard 12643: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12644:
1.219 brouard 12645: agebase=ageminpar;
12646: agelim=agemaxpar;
1.180 brouard 12647:
1.227 brouard 12648: /* i1=pow(2,ncoveff); */
1.234 brouard 12649: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12650: if (cptcovn < 1){i1=1;}
1.180 brouard 12651:
1.337 brouard 12652: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12653: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12654: k=TKresult[nres];
1.338 brouard 12655: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12656: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12657: /* continue; */
1.235 brouard 12658:
1.238 brouard 12659: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12660: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12661: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12662: /* k=k+1; */
12663: /* to clean */
1.332 brouard 12664: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12665: fprintf(ficrespl,"#******");
12666: printf("#******");
12667: fprintf(ficlog,"#******");
1.337 brouard 12668: 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 12669: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12670: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12671: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12672: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12673: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12674: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12675: }
12676: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12677: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12678: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12679: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12680: /* } */
1.238 brouard 12681: fprintf(ficrespl,"******\n");
12682: printf("******\n");
12683: fprintf(ficlog,"******\n");
12684: if(invalidvarcomb[k]){
12685: printf("\nCombination (%d) ignored because no case \n",k);
12686: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12687: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12688: continue;
12689: }
1.219 brouard 12690:
1.238 brouard 12691: fprintf(ficrespl,"#Age ");
1.337 brouard 12692: /* for(j=1;j<=cptcoveff;j++) { */
12693: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12694: /* } */
12695: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12696: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12697: }
12698: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12699: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12700:
1.238 brouard 12701: for (age=agebase; age<=agelim; age++){
12702: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12703: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12704: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12705: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12706: /* for(j=1;j<=cptcoveff;j++) */
12707: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12708: for(j=1;j<=cptcovs;j++)
12709: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12710: tot=0.;
12711: for(i=1; i<=nlstate;i++){
12712: tot += prlim[i][i];
12713: fprintf(ficrespl," %.5f", prlim[i][i]);
12714: }
12715: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12716: } /* Age */
12717: /* was end of cptcod */
1.337 brouard 12718: } /* nres */
12719: /* } /\* for each combination *\/ */
1.219 brouard 12720: return 0;
1.180 brouard 12721: }
12722:
1.218 brouard 12723: 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 12724: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12725:
12726: /* Computes the back prevalence limit for any combination of covariate values
12727: * at any age between ageminpar and agemaxpar
12728: */
1.235 brouard 12729: int i, j, k, i1, nres=0 ;
1.217 brouard 12730: /* double ftolpl = 1.e-10; */
12731: double age, agebase, agelim;
12732: double tot;
1.218 brouard 12733: /* double ***mobaverage; */
12734: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12735:
12736: strcpy(fileresplb,"PLB_");
12737: strcat(fileresplb,fileresu);
12738: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12739: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12740: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12741: }
1.288 brouard 12742: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12743: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12744: pstamp(ficresplb);
1.288 brouard 12745: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12746: fprintf(ficresplb,"#Age ");
12747: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12748: fprintf(ficresplb,"\n");
12749:
1.218 brouard 12750:
12751: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12752:
12753: agebase=ageminpar;
12754: agelim=agemaxpar;
12755:
12756:
1.227 brouard 12757: i1=pow(2,cptcoveff);
1.218 brouard 12758: if (cptcovn < 1){i1=1;}
1.227 brouard 12759:
1.238 brouard 12760: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12761: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12762: k=TKresult[nres];
12763: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12764: /* if(i1 != 1 && TKresult[nres]!= k) */
12765: /* continue; */
12766: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12767: fprintf(ficresplb,"#******");
12768: printf("#******");
12769: fprintf(ficlog,"#******");
1.338 brouard 12770: 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) */
12771: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12772: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12773: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12774: }
1.338 brouard 12775: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12776: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12777: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12778: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12779: /* } */
12780: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12781: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12782: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12783: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12784: /* } */
1.238 brouard 12785: fprintf(ficresplb,"******\n");
12786: printf("******\n");
12787: fprintf(ficlog,"******\n");
12788: if(invalidvarcomb[k]){
12789: printf("\nCombination (%d) ignored because no cases \n",k);
12790: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12791: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12792: continue;
12793: }
1.218 brouard 12794:
1.238 brouard 12795: fprintf(ficresplb,"#Age ");
1.338 brouard 12796: for(j=1;j<=cptcovs;j++) {
12797: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12798: }
12799: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12800: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12801:
12802:
1.238 brouard 12803: for (age=agebase; age<=agelim; age++){
12804: /* for (age=agebase; age<=agebase; age++){ */
12805: if(mobilavproj > 0){
12806: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12807: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12808: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12809: }else if (mobilavproj == 0){
12810: 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);
12811: 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);
12812: exit(1);
12813: }else{
12814: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12815: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12816: /* printf("TOTOT\n"); */
12817: /* exit(1); */
1.238 brouard 12818: }
12819: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12820: for(j=1;j<=cptcovs;j++)
12821: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12822: tot=0.;
12823: for(i=1; i<=nlstate;i++){
12824: tot += bprlim[i][i];
12825: fprintf(ficresplb," %.5f", bprlim[i][i]);
12826: }
12827: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12828: } /* Age */
12829: /* was end of cptcod */
1.255 brouard 12830: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12831: /* } /\* end of any combination *\/ */
1.238 brouard 12832: } /* end of nres */
1.218 brouard 12833: /* hBijx(p, bage, fage); */
12834: /* fclose(ficrespijb); */
12835:
12836: return 0;
1.217 brouard 12837: }
1.218 brouard 12838:
1.180 brouard 12839: int hPijx(double *p, int bage, int fage){
12840: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12841: /* to be optimized with precov */
1.180 brouard 12842: int stepsize;
12843: int agelim;
12844: int hstepm;
12845: int nhstepm;
1.235 brouard 12846: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12847:
12848: double agedeb;
12849: double ***p3mat;
12850:
1.337 brouard 12851: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12852: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12853: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12854: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12855: }
12856: printf("Computing pij: result on file '%s' \n", filerespij);
12857: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12858:
12859: stepsize=(int) (stepm+YEARM-1)/YEARM;
12860: /*if (stepm<=24) stepsize=2;*/
12861:
12862: agelim=AGESUP;
12863: hstepm=stepsize*YEARM; /* Every year of age */
12864: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12865:
12866: /* hstepm=1; aff par mois*/
12867: pstamp(ficrespij);
12868: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12869: i1= pow(2,cptcoveff);
12870: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12871: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12872: /* k=k+1; */
12873: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12874: k=TKresult[nres];
1.338 brouard 12875: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12876: /* for(k=1; k<=i1;k++){ */
12877: /* if(i1 != 1 && TKresult[nres]!= k) */
12878: /* continue; */
12879: fprintf(ficrespij,"\n#****** ");
12880: for(j=1;j<=cptcovs;j++){
12881: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12882: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12883: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12884: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12885: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12886: }
12887: fprintf(ficrespij,"******\n");
12888:
12889: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12890: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12891: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12892:
12893: /* nhstepm=nhstepm*YEARM; aff par mois*/
12894:
12895: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12896: oldm=oldms;savm=savms;
12897: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12898: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12899: for(i=1; i<=nlstate;i++)
12900: for(j=1; j<=nlstate+ndeath;j++)
12901: fprintf(ficrespij," %1d-%1d",i,j);
12902: fprintf(ficrespij,"\n");
12903: for (h=0; h<=nhstepm; h++){
12904: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12905: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12906: for(i=1; i<=nlstate;i++)
12907: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12908: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12909: fprintf(ficrespij,"\n");
12910: }
1.337 brouard 12911: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12912: fprintf(ficrespij,"\n");
1.180 brouard 12913: }
1.337 brouard 12914: }
12915: /*}*/
12916: return 0;
1.180 brouard 12917: }
1.218 brouard 12918:
12919: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12920: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12921: /* To be optimized with precov */
1.217 brouard 12922: int stepsize;
1.218 brouard 12923: /* int agelim; */
12924: int ageminl;
1.217 brouard 12925: int hstepm;
12926: int nhstepm;
1.238 brouard 12927: int h, i, i1, j, k, nres;
1.218 brouard 12928:
1.217 brouard 12929: double agedeb;
12930: double ***p3mat;
1.218 brouard 12931:
12932: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12933: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12934: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12935: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12936: }
12937: printf("Computing pij back: result on file '%s' \n", filerespijb);
12938: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12939:
12940: stepsize=(int) (stepm+YEARM-1)/YEARM;
12941: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12942:
1.218 brouard 12943: /* agelim=AGESUP; */
1.289 brouard 12944: ageminl=AGEINF; /* was 30 */
1.218 brouard 12945: hstepm=stepsize*YEARM; /* Every year of age */
12946: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12947:
12948: /* hstepm=1; aff par mois*/
12949: pstamp(ficrespijb);
1.255 brouard 12950: 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 12951: i1= pow(2,cptcoveff);
1.218 brouard 12952: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12953: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12954: /* k=k+1; */
1.238 brouard 12955: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12956: k=TKresult[nres];
1.338 brouard 12957: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12958: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12959: /* if(i1 != 1 && TKresult[nres]!= k) */
12960: /* continue; */
12961: fprintf(ficrespijb,"\n#****** ");
12962: for(j=1;j<=cptcovs;j++){
1.338 brouard 12963: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12964: /* for(j=1;j<=cptcoveff;j++) */
12965: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12966: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12967: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12968: }
12969: fprintf(ficrespijb,"******\n");
12970: if(invalidvarcomb[k]){ /* Is it necessary here? */
12971: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12972: continue;
12973: }
12974:
12975: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12976: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12977: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12978: 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 */
12979: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12980:
12981: /* nhstepm=nhstepm*YEARM; aff par mois*/
12982:
12983: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12984: /* and memory limitations if stepm is small */
12985:
12986: /* oldm=oldms;savm=savms; */
12987: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12988: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12989: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12990: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12991: for(i=1; i<=nlstate;i++)
12992: for(j=1; j<=nlstate+ndeath;j++)
12993: fprintf(ficrespijb," %1d-%1d",i,j);
12994: fprintf(ficrespijb,"\n");
12995: for (h=0; h<=nhstepm; h++){
12996: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12997: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12998: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12999: for(i=1; i<=nlstate;i++)
13000: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 13001: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 13002: fprintf(ficrespijb,"\n");
1.337 brouard 13003: }
13004: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
13005: fprintf(ficrespijb,"\n");
13006: } /* end age deb */
13007: /* } /\* end combination *\/ */
1.238 brouard 13008: } /* end nres */
1.218 brouard 13009: return 0;
13010: } /* hBijx */
1.217 brouard 13011:
1.180 brouard 13012:
1.136 brouard 13013: /***********************************************/
13014: /**************** Main Program *****************/
13015: /***********************************************/
13016:
13017: int main(int argc, char *argv[])
13018: {
13019: #ifdef GSL
13020: const gsl_multimin_fminimizer_type *T;
13021: size_t iteri = 0, it;
13022: int rval = GSL_CONTINUE;
13023: int status = GSL_SUCCESS;
13024: double ssval;
13025: #endif
13026: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 13027: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
13028: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 13029: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 13030: int jj, ll, li, lj, lk;
1.136 brouard 13031: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 13032: int num_filled;
1.136 brouard 13033: int itimes;
13034: int NDIM=2;
13035: int vpopbased=0;
1.235 brouard 13036: int nres=0;
1.258 brouard 13037: int endishere=0;
1.277 brouard 13038: int noffset=0;
1.274 brouard 13039: int ncurrv=0; /* Temporary variable */
13040:
1.164 brouard 13041: char ca[32], cb[32];
1.136 brouard 13042: /* FILE *fichtm; *//* Html File */
13043: /* FILE *ficgp;*/ /*Gnuplot File */
13044: struct stat info;
1.191 brouard 13045: double agedeb=0.;
1.194 brouard 13046:
13047: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 13048: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 13049:
1.165 brouard 13050: double fret;
1.191 brouard 13051: double dum=0.; /* Dummy variable */
1.136 brouard 13052: double ***p3mat;
1.218 brouard 13053: /* double ***mobaverage; */
1.319 brouard 13054: double wald;
1.164 brouard 13055:
1.351 brouard 13056: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 13057: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
13058:
1.234 brouard 13059: char modeltemp[MAXLINE];
1.332 brouard 13060: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 13061:
1.136 brouard 13062: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 13063: char *tok, *val; /* pathtot */
1.334 brouard 13064: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 13065: int c, h , cpt, c2;
1.191 brouard 13066: int jl=0;
13067: int i1, j1, jk, stepsize=0;
1.194 brouard 13068: int count=0;
13069:
1.164 brouard 13070: int *tab;
1.136 brouard 13071: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 13072: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
13073: /* double anprojf, mprojf, jprojf; */
13074: /* double jintmean,mintmean,aintmean; */
13075: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13076: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13077: double yrfproj= 10.0; /* Number of years of forward projections */
13078: double yrbproj= 10.0; /* Number of years of backward projections */
13079: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 13080: int mobilav=0,popforecast=0;
1.191 brouard 13081: int hstepm=0, nhstepm=0;
1.136 brouard 13082: int agemortsup;
13083: float sumlpop=0.;
13084: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
13085: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
13086:
1.191 brouard 13087: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 13088: double ftolpl=FTOL;
13089: double **prlim;
1.217 brouard 13090: double **bprlim;
1.317 brouard 13091: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
13092: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 13093: double ***paramstart; /* Matrix of starting parameter values */
13094: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 13095: double **matcov; /* Matrix of covariance */
1.203 brouard 13096: double **hess; /* Hessian matrix */
1.136 brouard 13097: double ***delti3; /* Scale */
13098: double *delti; /* Scale */
13099: double ***eij, ***vareij;
13100: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 13101:
1.136 brouard 13102: double *epj, vepp;
1.164 brouard 13103:
1.273 brouard 13104: double dateprev1, dateprev2;
1.296 brouard 13105: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
13106: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
13107:
1.217 brouard 13108:
1.136 brouard 13109: double **ximort;
1.145 brouard 13110: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 13111: int *dcwave;
13112:
1.164 brouard 13113: char z[1]="c";
1.136 brouard 13114:
13115: /*char *strt;*/
13116: char strtend[80];
1.126 brouard 13117:
1.164 brouard 13118:
1.126 brouard 13119: /* setlocale (LC_ALL, ""); */
13120: /* bindtextdomain (PACKAGE, LOCALEDIR); */
13121: /* textdomain (PACKAGE); */
13122: /* setlocale (LC_CTYPE, ""); */
13123: /* setlocale (LC_MESSAGES, ""); */
13124:
13125: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 13126: rstart_time = time(NULL);
13127: /* (void) gettimeofday(&start_time,&tzp);*/
13128: start_time = *localtime(&rstart_time);
1.126 brouard 13129: curr_time=start_time;
1.157 brouard 13130: /*tml = *localtime(&start_time.tm_sec);*/
13131: /* strcpy(strstart,asctime(&tml)); */
13132: strcpy(strstart,asctime(&start_time));
1.126 brouard 13133:
13134: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13135: /* tp.tm_sec = tp.tm_sec +86400; */
13136: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13137: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13138: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13139: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13140: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13141: /* strt=asctime(&tmg); */
13142: /* printf("Time(after) =%s",strstart); */
13143: /* (void) time (&time_value);
13144: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13145: * tm = *localtime(&time_value);
13146: * strstart=asctime(&tm);
13147: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13148: */
13149:
13150: nberr=0; /* Number of errors and warnings */
13151: nbwarn=0;
1.184 brouard 13152: #ifdef WIN32
13153: _getcwd(pathcd, size);
13154: #else
1.126 brouard 13155: getcwd(pathcd, size);
1.184 brouard 13156: #endif
1.191 brouard 13157: syscompilerinfo(0);
1.196 brouard 13158: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13159: if(argc <=1){
13160: printf("\nEnter the parameter file name: ");
1.205 brouard 13161: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13162: printf("ERROR Empty parameter file name\n");
13163: goto end;
13164: }
1.126 brouard 13165: i=strlen(pathr);
13166: if(pathr[i-1]=='\n')
13167: pathr[i-1]='\0';
1.156 brouard 13168: i=strlen(pathr);
1.205 brouard 13169: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13170: pathr[i-1]='\0';
1.205 brouard 13171: }
13172: i=strlen(pathr);
13173: if( i==0 ){
13174: printf("ERROR Empty parameter file name\n");
13175: goto end;
13176: }
13177: for (tok = pathr; tok != NULL; ){
1.126 brouard 13178: printf("Pathr |%s|\n",pathr);
13179: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13180: printf("val= |%s| pathr=%s\n",val,pathr);
13181: strcpy (pathtot, val);
13182: if(pathr[0] == '\0') break; /* Dirty */
13183: }
13184: }
1.281 brouard 13185: else if (argc<=2){
13186: strcpy(pathtot,argv[1]);
13187: }
1.126 brouard 13188: else{
13189: strcpy(pathtot,argv[1]);
1.281 brouard 13190: strcpy(z,argv[2]);
13191: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13192: }
13193: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13194: /*cygwin_split_path(pathtot,path,optionfile);
13195: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13196: /* cutv(path,optionfile,pathtot,'\\');*/
13197:
13198: /* Split argv[0], imach program to get pathimach */
13199: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13200: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13201: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13202: /* strcpy(pathimach,argv[0]); */
13203: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13204: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13205: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13206: #ifdef WIN32
13207: _chdir(path); /* Can be a relative path */
13208: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13209: #else
1.126 brouard 13210: chdir(path); /* Can be a relative path */
1.184 brouard 13211: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13212: #endif
13213: printf("Current directory %s!\n",pathcd);
1.126 brouard 13214: strcpy(command,"mkdir ");
13215: strcat(command,optionfilefiname);
13216: if((outcmd=system(command)) != 0){
1.169 brouard 13217: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13218: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13219: /* fclose(ficlog); */
13220: /* exit(1); */
13221: }
13222: /* if((imk=mkdir(optionfilefiname))<0){ */
13223: /* perror("mkdir"); */
13224: /* } */
13225:
13226: /*-------- arguments in the command line --------*/
13227:
1.186 brouard 13228: /* Main Log file */
1.126 brouard 13229: strcat(filelog, optionfilefiname);
13230: strcat(filelog,".log"); /* */
13231: if((ficlog=fopen(filelog,"w"))==NULL) {
13232: printf("Problem with logfile %s\n",filelog);
13233: goto end;
13234: }
13235: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13236: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13237: fprintf(ficlog,"\nEnter the parameter file name: \n");
13238: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13239: path=%s \n\
13240: optionfile=%s\n\
13241: optionfilext=%s\n\
1.156 brouard 13242: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13243:
1.197 brouard 13244: syscompilerinfo(1);
1.167 brouard 13245:
1.126 brouard 13246: printf("Local time (at start):%s",strstart);
13247: fprintf(ficlog,"Local time (at start): %s",strstart);
13248: fflush(ficlog);
13249: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13250: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13251:
13252: /* */
13253: strcpy(fileres,"r");
13254: strcat(fileres, optionfilefiname);
1.201 brouard 13255: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13256: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13257: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13258:
1.186 brouard 13259: /* Main ---------arguments file --------*/
1.126 brouard 13260:
13261: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13262: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13263: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13264: fflush(ficlog);
1.149 brouard 13265: /* goto end; */
13266: exit(70);
1.126 brouard 13267: }
13268:
13269: strcpy(filereso,"o");
1.201 brouard 13270: strcat(filereso,fileresu);
1.126 brouard 13271: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13272: printf("Problem with Output resultfile: %s\n", filereso);
13273: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13274: fflush(ficlog);
13275: goto end;
13276: }
1.278 brouard 13277: /*-------- Rewriting parameter file ----------*/
13278: strcpy(rfileres,"r"); /* "Rparameterfile */
13279: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13280: strcat(rfileres,"."); /* */
13281: strcat(rfileres,optionfilext); /* Other files have txt extension */
13282: if((ficres =fopen(rfileres,"w"))==NULL) {
13283: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13284: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13285: fflush(ficlog);
13286: goto end;
13287: }
13288: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13289:
1.278 brouard 13290:
1.126 brouard 13291: /* Reads comments: lines beginning with '#' */
13292: numlinepar=0;
1.277 brouard 13293: /* Is it a BOM UTF-8 Windows file? */
13294: /* First parameter line */
1.197 brouard 13295: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13296: noffset=0;
13297: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13298: {
13299: noffset=noffset+3;
13300: printf("# File is an UTF8 Bom.\n"); // 0xBF
13301: }
1.302 brouard 13302: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13303: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13304: {
13305: noffset=noffset+2;
13306: printf("# File is an UTF16BE BOM file\n");
13307: }
13308: else if( line[0] == 0 && line[1] == 0)
13309: {
13310: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13311: noffset=noffset+4;
13312: printf("# File is an UTF16BE BOM file\n");
13313: }
13314: } else{
13315: ;/*printf(" Not a BOM file\n");*/
13316: }
13317:
1.197 brouard 13318: /* If line starts with a # it is a comment */
1.277 brouard 13319: if (line[noffset] == '#') {
1.197 brouard 13320: numlinepar++;
13321: fputs(line,stdout);
13322: fputs(line,ficparo);
1.278 brouard 13323: fputs(line,ficres);
1.197 brouard 13324: fputs(line,ficlog);
13325: continue;
13326: }else
13327: break;
13328: }
13329: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13330: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13331: if (num_filled != 5) {
13332: printf("Should be 5 parameters\n");
1.283 brouard 13333: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13334: }
1.126 brouard 13335: numlinepar++;
1.197 brouard 13336: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13337: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13338: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13339: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13340: }
13341: /* Second parameter line */
13342: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13343: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13344: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13345: if (line[0] == '#') {
13346: numlinepar++;
1.283 brouard 13347: printf("%s",line);
13348: fprintf(ficres,"%s",line);
13349: fprintf(ficparo,"%s",line);
13350: fprintf(ficlog,"%s",line);
1.197 brouard 13351: continue;
13352: }else
13353: break;
13354: }
1.223 brouard 13355: 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", \
13356: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13357: if (num_filled != 11) {
13358: 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 13359: printf("but line=%s\n",line);
1.283 brouard 13360: 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");
13361: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13362: }
1.286 brouard 13363: if( lastpass > maxwav){
13364: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13365: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13366: fflush(ficlog);
13367: goto end;
13368: }
13369: 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 13370: 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 13371: 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 13372: 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 13373: }
1.203 brouard 13374: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13375: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13376: /* Third parameter line */
13377: while(fgets(line, MAXLINE, ficpar)) {
13378: /* If line starts with a # it is a comment */
13379: if (line[0] == '#') {
13380: numlinepar++;
1.283 brouard 13381: printf("%s",line);
13382: fprintf(ficres,"%s",line);
13383: fprintf(ficparo,"%s",line);
13384: fprintf(ficlog,"%s",line);
1.197 brouard 13385: continue;
13386: }else
13387: break;
13388: }
1.351 brouard 13389: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
13390: if (num_filled != 1){
13391: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13392: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13393: model[0]='\0';
13394: goto end;
13395: }else{
13396: trimbtab(linetmp,line); /* Trims multiple blanks in line */
13397: strcpy(line, linetmp);
13398: }
13399: }
13400: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 13401: if (num_filled != 1){
1.302 brouard 13402: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13403: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13404: model[0]='\0';
13405: goto end;
13406: }
13407: else{
13408: if (model[0]=='+'){
13409: for(i=1; i<=strlen(model);i++)
13410: modeltemp[i-1]=model[i];
1.201 brouard 13411: strcpy(model,modeltemp);
1.197 brouard 13412: }
13413: }
1.338 brouard 13414: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13415: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13416: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13417: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13418: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13419: }
13420: /* 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); */
13421: /* numlinepar=numlinepar+3; /\* In general *\/ */
13422: /* 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 13423: /* 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); */
13424: /* 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 13425: fflush(ficlog);
1.190 brouard 13426: /* if(model[0]=='#'|| model[0]== '\0'){ */
13427: if(model[0]=='#'){
1.279 brouard 13428: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13429: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13430: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13431: if(mle != -1){
1.279 brouard 13432: 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 13433: exit(1);
13434: }
13435: }
1.126 brouard 13436: while((c=getc(ficpar))=='#' && c!= EOF){
13437: ungetc(c,ficpar);
13438: fgets(line, MAXLINE, ficpar);
13439: numlinepar++;
1.195 brouard 13440: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13441: z[0]=line[1];
1.342 brouard 13442: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13443: debugILK=1;printf("DebugILK\n");
1.195 brouard 13444: }
13445: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13446: fputs(line, stdout);
13447: //puts(line);
1.126 brouard 13448: fputs(line,ficparo);
13449: fputs(line,ficlog);
13450: }
13451: ungetc(c,ficpar);
13452:
13453:
1.290 brouard 13454: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13455: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13456: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13457: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13458: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13459: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13460: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13461: v1+v2*age+v2*v3 makes cptcovn = 3
13462: */
13463: if (strlen(model)>1)
1.187 brouard 13464: 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 13465: else
1.187 brouard 13466: ncovmodel=2; /* Constant and age */
1.133 brouard 13467: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13468: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13469: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13470: 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);
13471: 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);
13472: fflush(stdout);
13473: fclose (ficlog);
13474: goto end;
13475: }
1.126 brouard 13476: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13477: delti=delti3[1][1];
13478: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13479: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13480: /* We could also provide initial parameters values giving by simple logistic regression
13481: * only one way, that is without matrix product. We will have nlstate maximizations */
13482: /* for(i=1;i<nlstate;i++){ */
13483: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13484: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13485: /* } */
1.126 brouard 13486: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13487: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13488: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13489: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13490: fclose (ficparo);
13491: fclose (ficlog);
13492: goto end;
13493: exit(0);
1.220 brouard 13494: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13495: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13496: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13497: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13498: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13499: matcov=matrix(1,npar,1,npar);
1.203 brouard 13500: hess=matrix(1,npar,1,npar);
1.220 brouard 13501: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13502: /* Read guessed parameters */
1.126 brouard 13503: /* Reads comments: lines beginning with '#' */
13504: while((c=getc(ficpar))=='#' && c!= EOF){
13505: ungetc(c,ficpar);
13506: fgets(line, MAXLINE, ficpar);
13507: numlinepar++;
1.141 brouard 13508: fputs(line,stdout);
1.126 brouard 13509: fputs(line,ficparo);
13510: fputs(line,ficlog);
13511: }
13512: ungetc(c,ficpar);
13513:
13514: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13515: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13516: for(i=1; i <=nlstate; i++){
1.234 brouard 13517: j=0;
1.126 brouard 13518: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13519: if(jj==i) continue;
13520: j++;
1.292 brouard 13521: while((c=getc(ficpar))=='#' && c!= EOF){
13522: ungetc(c,ficpar);
13523: fgets(line, MAXLINE, ficpar);
13524: numlinepar++;
13525: fputs(line,stdout);
13526: fputs(line,ficparo);
13527: fputs(line,ficlog);
13528: }
13529: ungetc(c,ficpar);
1.234 brouard 13530: fscanf(ficpar,"%1d%1d",&i1,&j1);
13531: if ((i1 != i) || (j1 != jj)){
13532: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13533: It might be a problem of design; if ncovcol and the model are correct\n \
13534: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13535: exit(1);
13536: }
13537: fprintf(ficparo,"%1d%1d",i1,j1);
13538: if(mle==1)
13539: printf("%1d%1d",i,jj);
13540: fprintf(ficlog,"%1d%1d",i,jj);
13541: for(k=1; k<=ncovmodel;k++){
13542: fscanf(ficpar," %lf",¶m[i][j][k]);
13543: if(mle==1){
13544: printf(" %lf",param[i][j][k]);
13545: fprintf(ficlog," %lf",param[i][j][k]);
13546: }
13547: else
13548: fprintf(ficlog," %lf",param[i][j][k]);
13549: fprintf(ficparo," %lf",param[i][j][k]);
13550: }
13551: fscanf(ficpar,"\n");
13552: numlinepar++;
13553: if(mle==1)
13554: printf("\n");
13555: fprintf(ficlog,"\n");
13556: fprintf(ficparo,"\n");
1.126 brouard 13557: }
13558: }
13559: fflush(ficlog);
1.234 brouard 13560:
1.251 brouard 13561: /* Reads parameters values */
1.126 brouard 13562: p=param[1][1];
1.251 brouard 13563: pstart=paramstart[1][1];
1.126 brouard 13564:
13565: /* Reads comments: lines beginning with '#' */
13566: while((c=getc(ficpar))=='#' && c!= EOF){
13567: ungetc(c,ficpar);
13568: fgets(line, MAXLINE, ficpar);
13569: numlinepar++;
1.141 brouard 13570: fputs(line,stdout);
1.126 brouard 13571: fputs(line,ficparo);
13572: fputs(line,ficlog);
13573: }
13574: ungetc(c,ficpar);
13575:
13576: for(i=1; i <=nlstate; i++){
13577: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13578: fscanf(ficpar,"%1d%1d",&i1,&j1);
13579: if ( (i1-i) * (j1-j) != 0){
13580: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13581: exit(1);
13582: }
13583: printf("%1d%1d",i,j);
13584: fprintf(ficparo,"%1d%1d",i1,j1);
13585: fprintf(ficlog,"%1d%1d",i1,j1);
13586: for(k=1; k<=ncovmodel;k++){
13587: fscanf(ficpar,"%le",&delti3[i][j][k]);
13588: printf(" %le",delti3[i][j][k]);
13589: fprintf(ficparo," %le",delti3[i][j][k]);
13590: fprintf(ficlog," %le",delti3[i][j][k]);
13591: }
13592: fscanf(ficpar,"\n");
13593: numlinepar++;
13594: printf("\n");
13595: fprintf(ficparo,"\n");
13596: fprintf(ficlog,"\n");
1.126 brouard 13597: }
13598: }
13599: fflush(ficlog);
1.234 brouard 13600:
1.145 brouard 13601: /* Reads covariance matrix */
1.126 brouard 13602: delti=delti3[1][1];
1.220 brouard 13603:
13604:
1.126 brouard 13605: /* 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 13606:
1.126 brouard 13607: /* Reads comments: lines beginning with '#' */
13608: while((c=getc(ficpar))=='#' && c!= EOF){
13609: ungetc(c,ficpar);
13610: fgets(line, MAXLINE, ficpar);
13611: numlinepar++;
1.141 brouard 13612: fputs(line,stdout);
1.126 brouard 13613: fputs(line,ficparo);
13614: fputs(line,ficlog);
13615: }
13616: ungetc(c,ficpar);
1.220 brouard 13617:
1.126 brouard 13618: matcov=matrix(1,npar,1,npar);
1.203 brouard 13619: hess=matrix(1,npar,1,npar);
1.131 brouard 13620: for(i=1; i <=npar; i++)
13621: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13622:
1.194 brouard 13623: /* Scans npar lines */
1.126 brouard 13624: for(i=1; i <=npar; i++){
1.226 brouard 13625: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13626: if(count != 3){
1.226 brouard 13627: printf("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: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13631: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13632: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13633: exit(1);
1.220 brouard 13634: }else{
1.226 brouard 13635: if(mle==1)
13636: printf("%1d%1d%d",i1,j1,jk);
13637: }
13638: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13639: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13640: for(j=1; j <=i; j++){
1.226 brouard 13641: fscanf(ficpar," %le",&matcov[i][j]);
13642: if(mle==1){
13643: printf(" %.5le",matcov[i][j]);
13644: }
13645: fprintf(ficlog," %.5le",matcov[i][j]);
13646: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13647: }
13648: fscanf(ficpar,"\n");
13649: numlinepar++;
13650: if(mle==1)
1.220 brouard 13651: printf("\n");
1.126 brouard 13652: fprintf(ficlog,"\n");
13653: fprintf(ficparo,"\n");
13654: }
1.194 brouard 13655: /* End of read covariance matrix npar lines */
1.126 brouard 13656: for(i=1; i <=npar; i++)
13657: for(j=i+1;j<=npar;j++)
1.226 brouard 13658: matcov[i][j]=matcov[j][i];
1.126 brouard 13659:
13660: if(mle==1)
13661: printf("\n");
13662: fprintf(ficlog,"\n");
13663:
13664: fflush(ficlog);
13665:
13666: } /* End of mle != -3 */
1.218 brouard 13667:
1.186 brouard 13668: /* Main data
13669: */
1.290 brouard 13670: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13671: /* num=lvector(1,n); */
13672: /* moisnais=vector(1,n); */
13673: /* annais=vector(1,n); */
13674: /* moisdc=vector(1,n); */
13675: /* andc=vector(1,n); */
13676: /* weight=vector(1,n); */
13677: /* agedc=vector(1,n); */
13678: /* cod=ivector(1,n); */
13679: /* for(i=1;i<=n;i++){ */
13680: num=lvector(firstobs,lastobs);
13681: moisnais=vector(firstobs,lastobs);
13682: annais=vector(firstobs,lastobs);
13683: moisdc=vector(firstobs,lastobs);
13684: andc=vector(firstobs,lastobs);
13685: weight=vector(firstobs,lastobs);
13686: agedc=vector(firstobs,lastobs);
13687: cod=ivector(firstobs,lastobs);
13688: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13689: num[i]=0;
13690: moisnais[i]=0;
13691: annais[i]=0;
13692: moisdc[i]=0;
13693: andc[i]=0;
13694: agedc[i]=0;
13695: cod[i]=0;
13696: weight[i]=1.0; /* Equal weights, 1 by default */
13697: }
1.290 brouard 13698: mint=matrix(1,maxwav,firstobs,lastobs);
13699: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13700: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13701: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13702: tab=ivector(1,NCOVMAX);
1.144 brouard 13703: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13704: 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 13705:
1.136 brouard 13706: /* Reads data from file datafile */
13707: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13708: goto end;
13709:
13710: /* Calculation of the number of parameters from char model */
1.234 brouard 13711: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13712: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13713: k=3 V4 Tvar[k=3]= 4 (from V4)
13714: k=2 V1 Tvar[k=2]= 1 (from V1)
13715: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13716: */
13717:
13718: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13719: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13720: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13721: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13722: TvarsD=ivector(1,NCOVMAX); /* */
13723: TvarsQind=ivector(1,NCOVMAX); /* */
13724: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13725: TvarF=ivector(1,NCOVMAX); /* */
13726: TvarFind=ivector(1,NCOVMAX); /* */
13727: TvarV=ivector(1,NCOVMAX); /* */
13728: TvarVind=ivector(1,NCOVMAX); /* */
13729: TvarA=ivector(1,NCOVMAX); /* */
13730: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13731: TvarFD=ivector(1,NCOVMAX); /* */
13732: TvarFDind=ivector(1,NCOVMAX); /* */
13733: TvarFQ=ivector(1,NCOVMAX); /* */
13734: TvarFQind=ivector(1,NCOVMAX); /* */
13735: TvarVD=ivector(1,NCOVMAX); /* */
13736: TvarVDind=ivector(1,NCOVMAX); /* */
13737: TvarVQ=ivector(1,NCOVMAX); /* */
13738: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13739: TvarVV=ivector(1,NCOVMAX); /* */
13740: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 13741: TvarVVA=ivector(1,NCOVMAX); /* */
13742: TvarVVAind=ivector(1,NCOVMAX); /* */
13743: TvarAVVA=ivector(1,NCOVMAX); /* */
13744: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13745:
1.230 brouard 13746: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13747: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13748: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13749: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13750: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 13751: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
13752: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
13753:
1.137 brouard 13754: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13755: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13756: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13757: */
13758: /* For model-covariate k tells which data-covariate to use but
13759: because this model-covariate is a construction we invent a new column
13760: ncovcol + k1
13761: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13762: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13763: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13764: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13765: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13766: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13767: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13768: */
1.145 brouard 13769: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13770: 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 13771: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13772: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 13773: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 13774: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13775: 4 covariates (3 plus signs)
13776: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13777: */
13778: for(i=1;i<NCOVMAX;i++)
13779: Tage[i]=0;
1.230 brouard 13780: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13781: * individual dummy, fixed or varying:
13782: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13783: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13784: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13785: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13786: * Tmodelind[1]@9={9,0,3,2,}*/
13787: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13788: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13789: * individual quantitative, fixed or varying:
13790: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13791: * 3, 1, 0, 0, 0, 0, 0, 0},
13792: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 13793:
13794: /* Probably useless zeroes */
13795: for(i=1;i<NCOVMAX;i++){
13796: DummyV[i]=0;
13797: FixedV[i]=0;
13798: }
13799:
13800: for(i=1; i <=ncovcol;i++){
13801: DummyV[i]=0;
13802: FixedV[i]=0;
13803: }
13804: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
13805: DummyV[i]=1;
13806: FixedV[i]=0;
13807: }
13808: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
13809: DummyV[i]=0;
13810: FixedV[i]=1;
13811: }
13812: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
13813: DummyV[i]=1;
13814: FixedV[i]=1;
13815: }
13816: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
13817: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13818: 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]);
13819: }
13820:
13821:
13822:
1.186 brouard 13823: /* Main decodemodel */
13824:
1.187 brouard 13825:
1.223 brouard 13826: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13827: goto end;
13828:
1.137 brouard 13829: if((double)(lastobs-imx)/(double)imx > 1.10){
13830: nbwarn++;
13831: 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);
13832: 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);
13833: }
1.136 brouard 13834: /* if(mle==1){*/
1.137 brouard 13835: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13836: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13837: }
13838:
13839: /*-calculation of age at interview from date of interview and age at death -*/
13840: agev=matrix(1,maxwav,1,imx);
13841:
13842: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13843: goto end;
13844:
1.126 brouard 13845:
1.136 brouard 13846: agegomp=(int)agemin;
1.290 brouard 13847: free_vector(moisnais,firstobs,lastobs);
13848: free_vector(annais,firstobs,lastobs);
1.126 brouard 13849: /* free_matrix(mint,1,maxwav,1,n);
13850: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13851: /* free_vector(moisdc,1,n); */
13852: /* free_vector(andc,1,n); */
1.145 brouard 13853: /* */
13854:
1.126 brouard 13855: wav=ivector(1,imx);
1.214 brouard 13856: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13857: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13858: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13859: 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.*/
13860: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13861: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13862:
13863: /* Concatenates waves */
1.214 brouard 13864: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13865: Death is a valid wave (if date is known).
13866: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13867: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13868: and mw[mi+1][i]. dh depends on stepm.
13869: */
13870:
1.126 brouard 13871: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13872: /* Concatenates waves */
1.145 brouard 13873:
1.290 brouard 13874: free_vector(moisdc,firstobs,lastobs);
13875: free_vector(andc,firstobs,lastobs);
1.215 brouard 13876:
1.126 brouard 13877: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13878: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13879: ncodemax[1]=1;
1.145 brouard 13880: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13881: cptcoveff=0;
1.220 brouard 13882: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13883: 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 13884: }
13885:
13886: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13887: invalidvarcomb=ivector(0, ncovcombmax);
13888: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13889: invalidvarcomb[i]=0;
13890:
1.211 brouard 13891: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13892: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13893: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13894:
1.200 brouard 13895: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13896: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13897: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13898: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13899: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13900: * (currently 0 or 1) in the data.
13901: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13902: * corresponding modality (h,j).
13903: */
13904:
1.145 brouard 13905: h=0;
13906: /*if (cptcovn > 0) */
1.126 brouard 13907: m=pow(2,cptcoveff);
13908:
1.144 brouard 13909: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13910: * For k=4 covariates, h goes from 1 to m=2**k
13911: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13912: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13913: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13914: *______________________________ *______________________
13915: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13916: * 2 2 1 1 1 * 1 0 0 0 1
13917: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13918: * 4 2 2 1 1 * 3 0 0 1 1
13919: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13920: * 6 2 1 2 1 * 5 0 1 0 1
13921: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13922: * 8 2 2 2 1 * 7 0 1 1 1
13923: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13924: * 10 2 1 1 2 * 9 1 0 0 1
13925: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13926: * 12 2 2 1 2 * 11 1 0 1 1
13927: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13928: * 14 2 1 2 2 * 13 1 1 0 1
13929: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13930: * 16 2 2 2 2 * 15 1 1 1 1
13931: */
1.212 brouard 13932: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13933: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13934: * and the value of each covariate?
13935: * V1=1, V2=1, V3=2, V4=1 ?
13936: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13937: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13938: * In order to get the real value in the data, we use nbcode
13939: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13940: * We are keeping this crazy system in order to be able (in the future?)
13941: * to have more than 2 values (0 or 1) for a covariate.
13942: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13943: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13944: * bbbbbbbb
13945: * 76543210
13946: * h-1 00000101 (6-1=5)
1.219 brouard 13947: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13948: * &
13949: * 1 00000001 (1)
1.219 brouard 13950: * 00000000 = 1 & ((h-1) >> (k-1))
13951: * +1= 00000001 =1
1.211 brouard 13952: *
13953: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13954: * h' 1101 =2^3+2^2+0x2^1+2^0
13955: * >>k' 11
13956: * & 00000001
13957: * = 00000001
13958: * +1 = 00000010=2 = codtabm(14,3)
13959: * Reverse h=6 and m=16?
13960: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13961: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13962: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13963: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13964: * V3=decodtabm(14,3,2**4)=2
13965: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13966: *(h-1) >> (j-1) 0011 =13 >> 2
13967: * &1 000000001
13968: * = 000000001
13969: * +1= 000000010 =2
13970: * 2211
13971: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13972: * V3=2
1.220 brouard 13973: * codtabm and decodtabm are identical
1.211 brouard 13974: */
13975:
1.145 brouard 13976:
13977: free_ivector(Ndum,-1,NCOVMAX);
13978:
13979:
1.126 brouard 13980:
1.186 brouard 13981: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13982: strcpy(optionfilegnuplot,optionfilefiname);
13983: if(mle==-3)
1.201 brouard 13984: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13985: strcat(optionfilegnuplot,".gp");
13986:
13987: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13988: printf("Problem with file %s",optionfilegnuplot);
13989: }
13990: else{
1.204 brouard 13991: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13992: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13993: //fprintf(ficgp,"set missing 'NaNq'\n");
13994: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13995: }
13996: /* fclose(ficgp);*/
1.186 brouard 13997:
13998:
13999: /* Initialisation of --------- index.htm --------*/
1.126 brouard 14000:
14001: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
14002: if(mle==-3)
1.201 brouard 14003: strcat(optionfilehtm,"-MORT_");
1.126 brouard 14004: strcat(optionfilehtm,".htm");
14005: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 14006: printf("Problem with %s \n",optionfilehtm);
14007: exit(0);
1.126 brouard 14008: }
14009:
14010: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
14011: strcat(optionfilehtmcov,"-cov.htm");
14012: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
14013: printf("Problem with %s \n",optionfilehtmcov), exit(0);
14014: }
14015: else{
14016: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
14017: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 14018: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 14019: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
14020: }
14021:
1.335 brouard 14022: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
14023: <title>IMaCh %s</title></head>\n\
14024: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
14025: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
14026: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
14027: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
14028: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
14029:
14030: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 14031: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 14032: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 14033: 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 14034: \n\
14035: <hr size=\"2\" color=\"#EC5E5E\">\
14036: <ul><li><h4>Parameter files</h4>\n\
14037: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
14038: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
14039: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
14040: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
14041: - Date and time at start: %s</ul>\n",\
1.335 brouard 14042: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 14043: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
14044: fileres,fileres,\
14045: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
14046: fflush(fichtm);
14047:
14048: strcpy(pathr,path);
14049: strcat(pathr,optionfilefiname);
1.184 brouard 14050: #ifdef WIN32
14051: _chdir(optionfilefiname); /* Move to directory named optionfile */
14052: #else
1.126 brouard 14053: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 14054: #endif
14055:
1.126 brouard 14056:
1.220 brouard 14057: /* Calculates basic frequencies. Computes observed prevalence at single age
14058: and for any valid combination of covariates
1.126 brouard 14059: and prints on file fileres'p'. */
1.251 brouard 14060: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 14061: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 14062:
14063: fprintf(fichtm,"\n");
1.286 brouard 14064: 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 14065: ftol, stepm);
14066: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
14067: ncurrv=1;
14068: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
14069: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
14070: ncurrv=i;
14071: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14072: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 14073: ncurrv=i;
14074: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14075: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 14076: ncurrv=i;
14077: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
14078: 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", \
14079: nlstate, ndeath, maxwav, mle, weightopt);
14080:
14081: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
14082: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
14083:
14084:
1.317 brouard 14085: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 14086: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
14087: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 14088: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 14089: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 14090: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14091: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14092: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14093: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 14094:
1.126 brouard 14095: /* For Powell, parameters are in a vector p[] starting at p[1]
14096: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
14097: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
14098:
14099: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 14100: /* For mortality only */
1.126 brouard 14101: if (mle==-3){
1.136 brouard 14102: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 14103: for(i=1;i<=NDIM;i++)
14104: for(j=1;j<=NDIM;j++)
14105: ximort[i][j]=0.;
1.186 brouard 14106: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 14107: cens=ivector(firstobs,lastobs);
14108: ageexmed=vector(firstobs,lastobs);
14109: agecens=vector(firstobs,lastobs);
14110: dcwave=ivector(firstobs,lastobs);
1.223 brouard 14111:
1.126 brouard 14112: for (i=1; i<=imx; i++){
14113: dcwave[i]=-1;
14114: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 14115: if (s[m][i]>nlstate) {
14116: dcwave[i]=m;
14117: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
14118: break;
14119: }
1.126 brouard 14120: }
1.226 brouard 14121:
1.126 brouard 14122: for (i=1; i<=imx; i++) {
14123: if (wav[i]>0){
1.226 brouard 14124: ageexmed[i]=agev[mw[1][i]][i];
14125: j=wav[i];
14126: agecens[i]=1.;
14127:
14128: if (ageexmed[i]> 1 && wav[i] > 0){
14129: agecens[i]=agev[mw[j][i]][i];
14130: cens[i]= 1;
14131: }else if (ageexmed[i]< 1)
14132: cens[i]= -1;
14133: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
14134: cens[i]=0 ;
1.126 brouard 14135: }
14136: else cens[i]=-1;
14137: }
14138:
14139: for (i=1;i<=NDIM;i++) {
14140: for (j=1;j<=NDIM;j++)
1.226 brouard 14141: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 14142: }
14143:
1.302 brouard 14144: p[1]=0.0268; p[NDIM]=0.083;
14145: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14146:
14147:
1.136 brouard 14148: #ifdef GSL
14149: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14150: #else
1.126 brouard 14151: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14152: #endif
1.201 brouard 14153: strcpy(filerespow,"POW-MORT_");
14154: strcat(filerespow,fileresu);
1.126 brouard 14155: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14156: printf("Problem with resultfile: %s\n", filerespow);
14157: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14158: }
1.136 brouard 14159: #ifdef GSL
14160: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14161: #else
1.126 brouard 14162: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14163: #endif
1.126 brouard 14164: /* for (i=1;i<=nlstate;i++)
14165: for(j=1;j<=nlstate+ndeath;j++)
14166: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14167: */
14168: fprintf(ficrespow,"\n");
1.136 brouard 14169: #ifdef GSL
14170: /* gsl starts here */
14171: T = gsl_multimin_fminimizer_nmsimplex;
14172: gsl_multimin_fminimizer *sfm = NULL;
14173: gsl_vector *ss, *x;
14174: gsl_multimin_function minex_func;
14175:
14176: /* Initial vertex size vector */
14177: ss = gsl_vector_alloc (NDIM);
14178:
14179: if (ss == NULL){
14180: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14181: }
14182: /* Set all step sizes to 1 */
14183: gsl_vector_set_all (ss, 0.001);
14184:
14185: /* Starting point */
1.126 brouard 14186:
1.136 brouard 14187: x = gsl_vector_alloc (NDIM);
14188:
14189: if (x == NULL){
14190: gsl_vector_free(ss);
14191: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14192: }
14193:
14194: /* Initialize method and iterate */
14195: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14196: /* gsl_vector_set(x, 0, 0.0268); */
14197: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14198: gsl_vector_set(x, 0, p[1]);
14199: gsl_vector_set(x, 1, p[2]);
14200:
14201: minex_func.f = &gompertz_f;
14202: minex_func.n = NDIM;
14203: minex_func.params = (void *)&p; /* ??? */
14204:
14205: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14206: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14207:
14208: printf("Iterations beginning .....\n\n");
14209: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14210:
14211: iteri=0;
14212: while (rval == GSL_CONTINUE){
14213: iteri++;
14214: status = gsl_multimin_fminimizer_iterate(sfm);
14215:
14216: if (status) printf("error: %s\n", gsl_strerror (status));
14217: fflush(0);
14218:
14219: if (status)
14220: break;
14221:
14222: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14223: ssval = gsl_multimin_fminimizer_size (sfm);
14224:
14225: if (rval == GSL_SUCCESS)
14226: printf ("converged to a local maximum at\n");
14227:
14228: printf("%5d ", iteri);
14229: for (it = 0; it < NDIM; it++){
14230: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14231: }
14232: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14233: }
14234:
14235: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14236:
14237: gsl_vector_free(x); /* initial values */
14238: gsl_vector_free(ss); /* inital step size */
14239: for (it=0; it<NDIM; it++){
14240: p[it+1]=gsl_vector_get(sfm->x,it);
14241: fprintf(ficrespow," %.12lf", p[it]);
14242: }
14243: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14244: #endif
14245: #ifdef POWELL
14246: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14247: #endif
1.126 brouard 14248: fclose(ficrespow);
14249:
1.203 brouard 14250: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14251:
14252: for(i=1; i <=NDIM; i++)
14253: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14254: matcov[i][j]=matcov[j][i];
1.126 brouard 14255:
14256: printf("\nCovariance matrix\n ");
1.203 brouard 14257: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14258: for(i=1; i <=NDIM; i++) {
14259: for(j=1;j<=NDIM;j++){
1.220 brouard 14260: printf("%f ",matcov[i][j]);
14261: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14262: }
1.203 brouard 14263: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14264: }
14265:
14266: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14267: for (i=1;i<=NDIM;i++) {
1.126 brouard 14268: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14269: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14270: }
1.302 brouard 14271: lsurv=vector(agegomp,AGESUP);
14272: lpop=vector(agegomp,AGESUP);
14273: tpop=vector(agegomp,AGESUP);
1.126 brouard 14274: lsurv[agegomp]=100000;
14275:
14276: for (k=agegomp;k<=AGESUP;k++) {
14277: agemortsup=k;
14278: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14279: }
14280:
14281: for (k=agegomp;k<agemortsup;k++)
14282: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14283:
14284: for (k=agegomp;k<agemortsup;k++){
14285: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14286: sumlpop=sumlpop+lpop[k];
14287: }
14288:
14289: tpop[agegomp]=sumlpop;
14290: for (k=agegomp;k<(agemortsup-3);k++){
14291: /* tpop[k+1]=2;*/
14292: tpop[k+1]=tpop[k]-lpop[k];
14293: }
14294:
14295:
14296: printf("\nAge lx qx dx Lx Tx e(x)\n");
14297: for (k=agegomp;k<(agemortsup-2);k++)
14298: 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]);
14299:
14300:
14301: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14302: ageminpar=50;
14303: agemaxpar=100;
1.194 brouard 14304: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14305: printf("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);
14308: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14309: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14310: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14311: }else{
14312: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14313: 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 14314: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14315: }
1.201 brouard 14316: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14317: stepm, weightopt,\
14318: model,imx,p,matcov,agemortsup);
14319:
1.302 brouard 14320: free_vector(lsurv,agegomp,AGESUP);
14321: free_vector(lpop,agegomp,AGESUP);
14322: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14323: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14324: free_ivector(dcwave,firstobs,lastobs);
14325: free_vector(agecens,firstobs,lastobs);
14326: free_vector(ageexmed,firstobs,lastobs);
14327: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14328: #ifdef GSL
1.136 brouard 14329: #endif
1.186 brouard 14330: } /* Endof if mle==-3 mortality only */
1.205 brouard 14331: /* Standard */
14332: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14333: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14334: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14335: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14336: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14337: for (k=1; k<=npar;k++)
14338: printf(" %d %8.5f",k,p[k]);
14339: printf("\n");
1.205 brouard 14340: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14341: /* mlikeli uses func not funcone */
1.247 brouard 14342: /* for(i=1;i<nlstate;i++){ */
14343: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14344: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14345: /* } */
1.205 brouard 14346: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14347: }
14348: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14349: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14350: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14351: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14352: }
14353: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14354: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14355: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14356: /* exit(0); */
1.126 brouard 14357: for (k=1; k<=npar;k++)
14358: printf(" %d %8.5f",k,p[k]);
14359: printf("\n");
14360:
14361: /*--------- results files --------------*/
1.283 brouard 14362: /* 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 14363:
14364:
14365: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14366: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14367: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14368:
14369: printf("#model= 1 + age ");
14370: fprintf(ficres,"#model= 1 + age ");
14371: fprintf(ficlog,"#model= 1 + age ");
14372: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14373: </ul>", model);
14374:
14375: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14376: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14377: if(nagesqr==1){
14378: printf(" + age*age ");
14379: fprintf(ficres," + age*age ");
14380: fprintf(ficlog," + age*age ");
14381: fprintf(fichtm, "<th>+ age*age</th>");
14382: }
14383: for(j=1;j <=ncovmodel-2;j++){
14384: if(Typevar[j]==0) {
14385: printf(" + V%d ",Tvar[j]);
14386: fprintf(ficres," + V%d ",Tvar[j]);
14387: fprintf(ficlog," + V%d ",Tvar[j]);
14388: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14389: }else if(Typevar[j]==1) {
14390: printf(" + V%d*age ",Tvar[j]);
14391: fprintf(ficres," + V%d*age ",Tvar[j]);
14392: fprintf(ficlog," + V%d*age ",Tvar[j]);
14393: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14394: }else if(Typevar[j]==2) {
14395: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14396: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14397: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14398: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14399: }else if(Typevar[j]==3) { /* TO VERIFY */
14400: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14401: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14402: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14403: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14404: }
14405: }
14406: printf("\n");
14407: fprintf(ficres,"\n");
14408: fprintf(ficlog,"\n");
14409: fprintf(fichtm, "</tr>");
14410: fprintf(fichtm, "\n");
14411:
14412:
1.126 brouard 14413: for(i=1,jk=1; i <=nlstate; i++){
14414: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14415: if (k != i) {
1.319 brouard 14416: fprintf(fichtm, "<tr>");
1.225 brouard 14417: printf("%d%d ",i,k);
14418: fprintf(ficlog,"%d%d ",i,k);
14419: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14420: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14421: for(j=1; j <=ncovmodel; j++){
14422: printf("%12.7f ",p[jk]);
14423: fprintf(ficlog,"%12.7f ",p[jk]);
14424: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14425: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14426: jk++;
14427: }
14428: printf("\n");
14429: fprintf(ficlog,"\n");
14430: fprintf(ficres,"\n");
1.319 brouard 14431: fprintf(fichtm, "</tr>\n");
1.225 brouard 14432: }
1.126 brouard 14433: }
14434: }
1.319 brouard 14435: /* fprintf(fichtm,"</tr>\n"); */
14436: fprintf(fichtm,"</table>\n");
14437: fprintf(fichtm, "\n");
14438:
1.203 brouard 14439: if(mle != 0){
14440: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14441: ftolhess=ftol; /* Usually correct */
1.203 brouard 14442: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14443: 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");
14444: 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 14445: 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 14446: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14447: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14448: if(nagesqr==1){
14449: printf(" + age*age ");
14450: fprintf(ficres," + age*age ");
14451: fprintf(ficlog," + age*age ");
14452: fprintf(fichtm, "<th>+ age*age</th>");
14453: }
14454: for(j=1;j <=ncovmodel-2;j++){
14455: if(Typevar[j]==0) {
14456: printf(" + V%d ",Tvar[j]);
14457: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14458: }else if(Typevar[j]==1) {
14459: printf(" + V%d*age ",Tvar[j]);
14460: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14461: }else if(Typevar[j]==2) {
14462: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14463: }else if(Typevar[j]==3) { /* TO VERIFY */
14464: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14465: }
14466: }
14467: fprintf(fichtm, "</tr>\n");
14468:
1.203 brouard 14469: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14470: for(k=1; k <=(nlstate+ndeath); k++){
14471: if (k != i) {
1.319 brouard 14472: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14473: printf("%d%d ",i,k);
14474: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14475: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14476: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14477: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14478: 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]));
14479: 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 14480: if(fabs(wald) > 1.96){
1.321 brouard 14481: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14482: }else{
14483: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14484: }
1.324 brouard 14485: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14486: 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 14487: jk++;
14488: }
14489: printf("\n");
14490: fprintf(ficlog,"\n");
1.319 brouard 14491: fprintf(fichtm, "</tr>\n");
1.225 brouard 14492: }
14493: }
1.193 brouard 14494: }
1.203 brouard 14495: } /* end of hesscov and Wald tests */
1.319 brouard 14496: fprintf(fichtm,"</table>\n");
1.225 brouard 14497:
1.203 brouard 14498: /* */
1.126 brouard 14499: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14500: printf("# Scales (for hessian or gradient estimation)\n");
14501: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14502: for(i=1,jk=1; i <=nlstate; i++){
14503: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14504: if (j!=i) {
14505: fprintf(ficres,"%1d%1d",i,j);
14506: printf("%1d%1d",i,j);
14507: fprintf(ficlog,"%1d%1d",i,j);
14508: for(k=1; k<=ncovmodel;k++){
14509: printf(" %.5e",delti[jk]);
14510: fprintf(ficlog," %.5e",delti[jk]);
14511: fprintf(ficres," %.5e",delti[jk]);
14512: jk++;
14513: }
14514: printf("\n");
14515: fprintf(ficlog,"\n");
14516: fprintf(ficres,"\n");
14517: }
1.126 brouard 14518: }
14519: }
14520:
14521: 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 14522: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14523: 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");
14524: 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");
14525: /* # 121 Var(a12)\n\ */
14526: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14527: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14528: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14529: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14530: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14531: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14532: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14533:
14534:
14535: /* Just to have a covariance matrix which will be more understandable
14536: even is we still don't want to manage dictionary of variables
14537: */
14538: for(itimes=1;itimes<=2;itimes++){
14539: jj=0;
14540: for(i=1; i <=nlstate; i++){
1.225 brouard 14541: for(j=1; j <=nlstate+ndeath; j++){
14542: if(j==i) continue;
14543: for(k=1; k<=ncovmodel;k++){
14544: jj++;
14545: ca[0]= k+'a'-1;ca[1]='\0';
14546: if(itimes==1){
14547: if(mle>=1)
14548: printf("#%1d%1d%d",i,j,k);
14549: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14550: fprintf(ficres,"#%1d%1d%d",i,j,k);
14551: }else{
14552: if(mle>=1)
14553: printf("%1d%1d%d",i,j,k);
14554: fprintf(ficlog,"%1d%1d%d",i,j,k);
14555: fprintf(ficres,"%1d%1d%d",i,j,k);
14556: }
14557: ll=0;
14558: for(li=1;li <=nlstate; li++){
14559: for(lj=1;lj <=nlstate+ndeath; lj++){
14560: if(lj==li) continue;
14561: for(lk=1;lk<=ncovmodel;lk++){
14562: ll++;
14563: if(ll<=jj){
14564: cb[0]= lk +'a'-1;cb[1]='\0';
14565: if(ll<jj){
14566: if(itimes==1){
14567: if(mle>=1)
14568: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14569: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14570: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14571: }else{
14572: if(mle>=1)
14573: printf(" %.5e",matcov[jj][ll]);
14574: fprintf(ficlog," %.5e",matcov[jj][ll]);
14575: fprintf(ficres," %.5e",matcov[jj][ll]);
14576: }
14577: }else{
14578: if(itimes==1){
14579: if(mle>=1)
14580: printf(" Var(%s%1d%1d)",ca,i,j);
14581: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14582: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14583: }else{
14584: if(mle>=1)
14585: printf(" %.7e",matcov[jj][ll]);
14586: fprintf(ficlog," %.7e",matcov[jj][ll]);
14587: fprintf(ficres," %.7e",matcov[jj][ll]);
14588: }
14589: }
14590: }
14591: } /* end lk */
14592: } /* end lj */
14593: } /* end li */
14594: if(mle>=1)
14595: printf("\n");
14596: fprintf(ficlog,"\n");
14597: fprintf(ficres,"\n");
14598: numlinepar++;
14599: } /* end k*/
14600: } /*end j */
1.126 brouard 14601: } /* end i */
14602: } /* end itimes */
14603:
14604: fflush(ficlog);
14605: fflush(ficres);
1.225 brouard 14606: while(fgets(line, MAXLINE, ficpar)) {
14607: /* If line starts with a # it is a comment */
14608: if (line[0] == '#') {
14609: numlinepar++;
14610: fputs(line,stdout);
14611: fputs(line,ficparo);
14612: fputs(line,ficlog);
1.299 brouard 14613: fputs(line,ficres);
1.225 brouard 14614: continue;
14615: }else
14616: break;
14617: }
14618:
1.209 brouard 14619: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14620: /* ungetc(c,ficpar); */
14621: /* fgets(line, MAXLINE, ficpar); */
14622: /* fputs(line,stdout); */
14623: /* fputs(line,ficparo); */
14624: /* } */
14625: /* ungetc(c,ficpar); */
1.126 brouard 14626:
14627: estepm=0;
1.209 brouard 14628: 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 14629:
14630: if (num_filled != 6) {
14631: 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);
14632: 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);
14633: goto end;
14634: }
14635: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14636: }
14637: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14638: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14639:
1.209 brouard 14640: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14641: if (estepm==0 || estepm < stepm) estepm=stepm;
14642: if (fage <= 2) {
14643: bage = ageminpar;
14644: fage = agemaxpar;
14645: }
14646:
14647: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14648: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14649: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14650:
1.186 brouard 14651: /* Other stuffs, more or less useful */
1.254 brouard 14652: while(fgets(line, MAXLINE, ficpar)) {
14653: /* If line starts with a # it is a comment */
14654: if (line[0] == '#') {
14655: numlinepar++;
14656: fputs(line,stdout);
14657: fputs(line,ficparo);
14658: fputs(line,ficlog);
1.299 brouard 14659: fputs(line,ficres);
1.254 brouard 14660: continue;
14661: }else
14662: break;
14663: }
14664:
14665: 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){
14666:
14667: if (num_filled != 7) {
14668: 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);
14669: 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);
14670: goto end;
14671: }
14672: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14673: 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);
14674: 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);
14675: 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 14676: }
1.254 brouard 14677:
14678: while(fgets(line, MAXLINE, ficpar)) {
14679: /* If line starts with a # it is a comment */
14680: if (line[0] == '#') {
14681: numlinepar++;
14682: fputs(line,stdout);
14683: fputs(line,ficparo);
14684: fputs(line,ficlog);
1.299 brouard 14685: fputs(line,ficres);
1.254 brouard 14686: continue;
14687: }else
14688: break;
1.126 brouard 14689: }
14690:
14691:
14692: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14693: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14694:
1.254 brouard 14695: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14696: if (num_filled != 1) {
14697: 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);
14698: 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);
14699: goto end;
14700: }
14701: printf("pop_based=%d\n",popbased);
14702: fprintf(ficlog,"pop_based=%d\n",popbased);
14703: fprintf(ficparo,"pop_based=%d\n",popbased);
14704: fprintf(ficres,"pop_based=%d\n",popbased);
14705: }
14706:
1.258 brouard 14707: /* Results */
1.332 brouard 14708: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14709: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14710: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14711: endishere=0;
1.258 brouard 14712: nresult=0;
1.308 brouard 14713: parameterline=0;
1.258 brouard 14714: do{
14715: if(!fgets(line, MAXLINE, ficpar)){
14716: endishere=1;
1.308 brouard 14717: parameterline=15;
1.258 brouard 14718: }else if (line[0] == '#') {
14719: /* If line starts with a # it is a comment */
1.254 brouard 14720: numlinepar++;
14721: fputs(line,stdout);
14722: fputs(line,ficparo);
14723: fputs(line,ficlog);
1.299 brouard 14724: fputs(line,ficres);
1.254 brouard 14725: continue;
1.258 brouard 14726: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14727: parameterline=11;
1.296 brouard 14728: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14729: parameterline=12;
1.307 brouard 14730: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14731: parameterline=13;
1.307 brouard 14732: }
1.258 brouard 14733: else{
14734: parameterline=14;
1.254 brouard 14735: }
1.308 brouard 14736: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14737: case 11:
1.296 brouard 14738: 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)){
14739: 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 14740: 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);
14741: 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);
14742: 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);
14743: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14744: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14745: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14746: prvforecast = 1;
14747: }
14748: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14749: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14750: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14751: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14752: prvforecast = 2;
14753: }
14754: else {
14755: 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);
14756: 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);
14757: goto end;
1.258 brouard 14758: }
1.254 brouard 14759: break;
1.258 brouard 14760: case 12:
1.296 brouard 14761: 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)){
14762: 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);
14763: 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);
14764: 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);
14765: 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);
14766: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14767: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14768: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14769: prvbackcast = 1;
14770: }
14771: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14772: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14773: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14774: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14775: prvbackcast = 2;
14776: }
14777: else {
14778: 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);
14779: 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);
14780: goto end;
1.258 brouard 14781: }
1.230 brouard 14782: break;
1.258 brouard 14783: case 13:
1.332 brouard 14784: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14785: nresult++; /* Sum of resultlines */
1.342 brouard 14786: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14787: /* removefirstspace(&resultlineori); */
14788:
14789: if(strstr(resultlineori,"v") !=0){
14790: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14791: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14792: return 1;
14793: }
14794: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14795: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14796: if(nresult > MAXRESULTLINESPONE-1){
14797: 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);
14798: 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 14799: goto end;
14800: }
1.332 brouard 14801:
1.310 brouard 14802: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14803: fprintf(ficparo,"result: %s\n",resultline);
14804: fprintf(ficres,"result: %s\n",resultline);
14805: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14806: } else
14807: goto end;
1.307 brouard 14808: break;
14809: case 14:
14810: printf("Error: Unknown command '%s'\n",line);
14811: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14812: if(line[0] == ' ' || line[0] == '\n'){
14813: printf("It should not be an empty line '%s'\n",line);
14814: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14815: }
1.307 brouard 14816: if(ncovmodel >=2 && nresult==0 ){
14817: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14818: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14819: }
1.307 brouard 14820: /* goto end; */
14821: break;
1.308 brouard 14822: case 15:
14823: printf("End of resultlines.\n");
14824: fprintf(ficlog,"End of resultlines.\n");
14825: break;
14826: default: /* parameterline =0 */
1.307 brouard 14827: nresult=1;
14828: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14829: } /* End switch parameterline */
14830: }while(endishere==0); /* End do */
1.126 brouard 14831:
1.230 brouard 14832: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14833: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14834:
14835: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14836: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14837: printf("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);
1.230 brouard 14840: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14841: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14842: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14843: }else{
1.270 brouard 14844: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14845: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14846: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14847: if(prvforecast==1){
14848: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14849: jprojd=jproj1;
14850: mprojd=mproj1;
14851: anprojd=anproj1;
14852: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14853: jprojf=jproj2;
14854: mprojf=mproj2;
14855: anprojf=anproj2;
14856: } else if(prvforecast == 2){
14857: dateprojd=dateintmean;
14858: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14859: dateprojf=dateintmean+yrfproj;
14860: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14861: }
14862: if(prvbackcast==1){
14863: datebackd=(jback1+12*mback1+365*anback1)/365;
14864: jbackd=jback1;
14865: mbackd=mback1;
14866: anbackd=anback1;
14867: datebackf=(jback2+12*mback2+365*anback2)/365;
14868: jbackf=jback2;
14869: mbackf=mback2;
14870: anbackf=anback2;
14871: } else if(prvbackcast == 2){
14872: datebackd=dateintmean;
14873: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14874: datebackf=dateintmean-yrbproj;
14875: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14876: }
14877:
1.350 brouard 14878: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 14879: }
14880: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14881: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14882: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14883:
1.225 brouard 14884: /*------------ free_vector -------------*/
14885: /* chdir(path); */
1.220 brouard 14886:
1.215 brouard 14887: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14888: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14889: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14890: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14891: free_lvector(num,firstobs,lastobs);
14892: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14893: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14894: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14895: fclose(ficparo);
14896: fclose(ficres);
1.220 brouard 14897:
14898:
1.186 brouard 14899: /* Other results (useful)*/
1.220 brouard 14900:
14901:
1.126 brouard 14902: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14903: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14904: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14905: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14906: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14907: fclose(ficrespl);
14908:
14909: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14910: /*#include "hpijx.h"*/
1.332 brouard 14911: /** 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?*/
14912: /* calls hpxij with combination k */
1.180 brouard 14913: hPijx(p, bage, fage);
1.145 brouard 14914: fclose(ficrespij);
1.227 brouard 14915:
1.220 brouard 14916: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14917: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14918: k=1;
1.126 brouard 14919: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14920:
1.269 brouard 14921: /* Prevalence for each covariate combination in probs[age][status][cov] */
14922: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14923: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14924: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14925: for(k=1;k<=ncovcombmax;k++)
14926: probs[i][j][k]=0.;
1.269 brouard 14927: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14928: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14929: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14930: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14931: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14932: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14933: for(k=1;k<=ncovcombmax;k++)
14934: mobaverages[i][j][k]=0.;
1.219 brouard 14935: mobaverage=mobaverages;
14936: if (mobilav!=0) {
1.235 brouard 14937: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14938: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14939: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14940: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14941: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14942: }
1.269 brouard 14943: } else if (mobilavproj !=0) {
1.235 brouard 14944: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14945: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14946: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14947: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14948: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14949: }
1.269 brouard 14950: }else{
14951: printf("Internal error moving average\n");
14952: fflush(stdout);
14953: exit(1);
1.219 brouard 14954: }
14955: }/* end if moving average */
1.227 brouard 14956:
1.126 brouard 14957: /*---------- Forecasting ------------------*/
1.296 brouard 14958: if(prevfcast==1){
14959: /* /\* if(stepm ==1){*\/ */
14960: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14961: /*This done previously after freqsummary.*/
14962: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14963: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14964:
14965: /* } else if (prvforecast==2){ */
14966: /* /\* if(stepm ==1){*\/ */
14967: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14968: /* } */
14969: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14970: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14971: }
1.269 brouard 14972:
1.296 brouard 14973: /* Prevbcasting */
14974: if(prevbcast==1){
1.219 brouard 14975: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14976: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14977: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14978:
14979: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14980:
14981: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14982:
1.219 brouard 14983: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14984: fclose(ficresplb);
14985:
1.222 brouard 14986: hBijx(p, bage, fage, mobaverage);
14987: fclose(ficrespijb);
1.219 brouard 14988:
1.296 brouard 14989: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14990: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14991: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14992: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14993: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14994: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14995:
14996:
1.269 brouard 14997: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14998:
14999:
1.269 brouard 15000: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 15001: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
15002: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
15003: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 15004: } /* end Prevbcasting */
1.268 brouard 15005:
1.186 brouard 15006:
15007: /* ------ Other prevalence ratios------------ */
1.126 brouard 15008:
1.215 brouard 15009: free_ivector(wav,1,imx);
15010: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
15011: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
15012: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 15013:
15014:
1.127 brouard 15015: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 15016:
1.201 brouard 15017: strcpy(filerese,"E_");
15018: strcat(filerese,fileresu);
1.126 brouard 15019: if((ficreseij=fopen(filerese,"w"))==NULL) {
15020: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
15021: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
15022: }
1.208 brouard 15023: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
15024: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 15025:
15026: pstamp(ficreseij);
1.219 brouard 15027:
1.351 brouard 15028: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
15029: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 15030:
1.351 brouard 15031: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
15032: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
15033: /* if(i1 != 1 && TKresult[nres]!= k) */
15034: /* continue; */
1.219 brouard 15035: fprintf(ficreseij,"\n#****** ");
1.235 brouard 15036: printf("\n#****** ");
1.351 brouard 15037: for(j=1;j<=cptcovs;j++){
15038: /* for(j=1;j<=cptcoveff;j++) { */
15039: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15040: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15041: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15042: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 15043: }
15044: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 15045: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
15046: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 15047: }
15048: fprintf(ficreseij,"******\n");
1.235 brouard 15049: printf("******\n");
1.219 brouard 15050:
15051: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15052: oldm=oldms;savm=savms;
1.330 brouard 15053: /* 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 15054: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 15055:
1.219 brouard 15056: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 15057: }
15058: fclose(ficreseij);
1.208 brouard 15059: printf("done evsij\n");fflush(stdout);
15060: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 15061:
1.218 brouard 15062:
1.227 brouard 15063: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 15064: /* Should be moved in a function */
1.201 brouard 15065: strcpy(filerest,"T_");
15066: strcat(filerest,fileresu);
1.127 brouard 15067: if((ficrest=fopen(filerest,"w"))==NULL) {
15068: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
15069: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
15070: }
1.208 brouard 15071: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
15072: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 15073: strcpy(fileresstde,"STDE_");
15074: strcat(fileresstde,fileresu);
1.126 brouard 15075: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 15076: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
15077: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 15078: }
1.227 brouard 15079: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
15080: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 15081:
1.201 brouard 15082: strcpy(filerescve,"CVE_");
15083: strcat(filerescve,fileresu);
1.126 brouard 15084: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 15085: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
15086: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 15087: }
1.227 brouard 15088: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
15089: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 15090:
1.201 brouard 15091: strcpy(fileresv,"V_");
15092: strcat(fileresv,fileresu);
1.126 brouard 15093: if((ficresvij=fopen(fileresv,"w"))==NULL) {
15094: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
15095: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
15096: }
1.227 brouard 15097: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
15098: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 15099:
1.235 brouard 15100: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
15101: if (cptcovn < 1){i1=1;}
15102:
1.334 brouard 15103: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
15104: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
15105: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
15106: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
15107: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
15108: /* */
15109: 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 15110: continue;
1.350 brouard 15111: printf("\n# model %s \n#****** Result for:", model); /* HERE model is empty */
1.321 brouard 15112: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
15113: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 15114: /* It might not be a good idea to mix dummies and quantitative */
15115: /* 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 *\/ */
15116: 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 */
15117: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
15118: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
15119: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
15120: * (V5 is quanti) V4 and V3 are dummies
15121: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
15122: * l=1 l=2
15123: * k=1 1 1 0 0
15124: * k=2 2 1 1 0
15125: * k=3 [1] [2] 0 1
15126: * k=4 2 2 1 1
15127: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
15128: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
15129: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
15130: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
15131: */
15132: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
15133: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
15134: /* We give up with the combinations!! */
1.342 brouard 15135: /* if(debugILK) */
15136: /* 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 15137:
15138: 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 15139: /* 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] */
15140: 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 */
15141: 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 */
15142: 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 15143: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15144: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15145: }else{
15146: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15147: }
15148: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15149: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15150: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15151: /* For each selected (single) quantitative value */
1.337 brouard 15152: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15153: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15154: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15155: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15156: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15157: }else{
15158: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15159: }
15160: }else{
15161: 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 */
15162: 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 */
15163: exit(1);
15164: }
1.335 brouard 15165: } /* End loop for each variable in the resultline */
1.334 brouard 15166: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15167: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15168: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15169: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15170: /* } */
1.208 brouard 15171: fprintf(ficrest,"******\n");
1.227 brouard 15172: fprintf(ficlog,"******\n");
15173: printf("******\n");
1.208 brouard 15174:
15175: fprintf(ficresstdeij,"\n#****** ");
15176: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15177: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15178: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15179: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15180: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15181: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15182: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15183: }
15184: 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 15185: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15186: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15187: }
1.208 brouard 15188: fprintf(ficresstdeij,"******\n");
15189: fprintf(ficrescveij,"******\n");
15190:
15191: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15192: /* pstamp(ficresvij); */
1.225 brouard 15193: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15194: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15195: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15196: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15197: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15198: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15199: }
1.208 brouard 15200: fprintf(ficresvij,"******\n");
15201:
15202: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15203: oldm=oldms;savm=savms;
1.235 brouard 15204: printf(" cvevsij ");
15205: fprintf(ficlog, " cvevsij ");
15206: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15207: printf(" end cvevsij \n ");
15208: fprintf(ficlog, " end cvevsij \n ");
15209:
15210: /*
15211: */
15212: /* goto endfree; */
15213:
15214: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15215: pstamp(ficrest);
15216:
1.269 brouard 15217: epj=vector(1,nlstate+1);
1.208 brouard 15218: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15219: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15220: cptcod= 0; /* To be deleted */
15221: printf("varevsij vpopbased=%d \n",vpopbased);
15222: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15223: 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 15224: 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 ");
15225: if(vpopbased==1)
15226: 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);
15227: else
1.288 brouard 15228: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15229: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15230: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15231: fprintf(ficrest,"\n");
15232: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15233: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15234: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15235: for(age=bage; age <=fage ;age++){
1.235 brouard 15236: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15237: if (vpopbased==1) {
15238: if(mobilav ==0){
15239: for(i=1; i<=nlstate;i++)
15240: prlim[i][i]=probs[(int)age][i][k];
15241: }else{ /* mobilav */
15242: for(i=1; i<=nlstate;i++)
15243: prlim[i][i]=mobaverage[(int)age][i][k];
15244: }
15245: }
1.219 brouard 15246:
1.227 brouard 15247: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15248: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15249: /* printf(" age %4.0f ",age); */
15250: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15251: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15252: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15253: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15254: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15255: }
15256: epj[nlstate+1] +=epj[j];
15257: }
15258: /* printf(" age %4.0f \n",age); */
1.219 brouard 15259:
1.227 brouard 15260: for(i=1, vepp=0.;i <=nlstate;i++)
15261: for(j=1;j <=nlstate;j++)
15262: vepp += vareij[i][j][(int)age];
15263: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15264: for(j=1;j <=nlstate;j++){
15265: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15266: }
15267: fprintf(ficrest,"\n");
15268: }
1.208 brouard 15269: } /* End vpopbased */
1.269 brouard 15270: free_vector(epj,1,nlstate+1);
1.208 brouard 15271: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15272: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15273: printf("done selection\n");fflush(stdout);
15274: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15275:
1.335 brouard 15276: } /* End k selection or end covariate selection for nres */
1.227 brouard 15277:
15278: printf("done State-specific expectancies\n");fflush(stdout);
15279: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15280:
1.335 brouard 15281: /* variance-covariance of forward period prevalence */
1.269 brouard 15282: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15283:
1.227 brouard 15284:
1.290 brouard 15285: free_vector(weight,firstobs,lastobs);
1.351 brouard 15286: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 15287: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15288: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15289: free_matrix(anint,1,maxwav,firstobs,lastobs);
15290: free_matrix(mint,1,maxwav,firstobs,lastobs);
15291: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15292: free_ivector(tab,1,NCOVMAX);
15293: fclose(ficresstdeij);
15294: fclose(ficrescveij);
15295: fclose(ficresvij);
15296: fclose(ficrest);
15297: fclose(ficpar);
15298:
15299:
1.126 brouard 15300: /*---------- End : free ----------------*/
1.219 brouard 15301: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15302: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15303: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15304: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15305: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15306: } /* mle==-3 arrives here for freeing */
1.227 brouard 15307: /* endfree:*/
15308: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15309: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15310: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15311: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15312: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15313: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15314: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15315: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15316: free_matrix(matcov,1,npar,1,npar);
15317: free_matrix(hess,1,npar,1,npar);
15318: /*free_vector(delti,1,npar);*/
15319: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15320: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15321: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15322: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15323:
15324: free_ivector(ncodemax,1,NCOVMAX);
15325: free_ivector(ncodemaxwundef,1,NCOVMAX);
15326: free_ivector(Dummy,-1,NCOVMAX);
15327: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 15328: free_ivector(DummyV,-1,NCOVMAX);
15329: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15330: free_ivector(Typevar,-1,NCOVMAX);
15331: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15332: free_ivector(TvarsQ,1,NCOVMAX);
15333: free_ivector(TvarsQind,1,NCOVMAX);
15334: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15335: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15336: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15337: free_ivector(TvarFD,1,NCOVMAX);
15338: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15339: free_ivector(TvarF,1,NCOVMAX);
15340: free_ivector(TvarFind,1,NCOVMAX);
15341: free_ivector(TvarV,1,NCOVMAX);
15342: free_ivector(TvarVind,1,NCOVMAX);
15343: free_ivector(TvarA,1,NCOVMAX);
15344: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15345: free_ivector(TvarFQ,1,NCOVMAX);
15346: free_ivector(TvarFQind,1,NCOVMAX);
15347: free_ivector(TvarVD,1,NCOVMAX);
15348: free_ivector(TvarVDind,1,NCOVMAX);
15349: free_ivector(TvarVQ,1,NCOVMAX);
15350: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 15351: free_ivector(TvarAVVA,1,NCOVMAX);
15352: free_ivector(TvarAVVAind,1,NCOVMAX);
15353: free_ivector(TvarVVA,1,NCOVMAX);
15354: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15355: free_ivector(TvarVV,1,NCOVMAX);
15356: free_ivector(TvarVVind,1,NCOVMAX);
15357:
1.230 brouard 15358: free_ivector(Tvarsel,1,NCOVMAX);
15359: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15360: free_ivector(Tposprod,1,NCOVMAX);
15361: free_ivector(Tprod,1,NCOVMAX);
15362: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15363: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15364: free_ivector(Tage,1,NCOVMAX);
15365: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15366: free_ivector(TmodelInvind,1,NCOVMAX);
15367: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15368:
15369: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15370:
1.227 brouard 15371: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15372: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15373: fflush(fichtm);
15374: fflush(ficgp);
15375:
1.227 brouard 15376:
1.126 brouard 15377: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15378: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15379: 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 15380: }else{
15381: printf("End of Imach\n");
15382: fprintf(ficlog,"End of Imach\n");
15383: }
15384: printf("See log file on %s\n",filelog);
15385: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15386: /*(void) gettimeofday(&end_time,&tzp);*/
15387: rend_time = time(NULL);
15388: end_time = *localtime(&rend_time);
15389: /* tml = *localtime(&end_time.tm_sec); */
15390: strcpy(strtend,asctime(&end_time));
1.126 brouard 15391: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15392: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15393: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15394:
1.157 brouard 15395: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15396: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15397: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15398: /* printf("Total time was %d uSec.\n", total_usecs);*/
15399: /* if(fileappend(fichtm,optionfilehtm)){ */
15400: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15401: fclose(fichtm);
15402: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15403: fclose(fichtmcov);
15404: fclose(ficgp);
15405: fclose(ficlog);
15406: /*------ End -----------*/
1.227 brouard 15407:
1.281 brouard 15408:
15409: /* Executes gnuplot */
1.227 brouard 15410:
15411: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15412: #ifdef WIN32
1.227 brouard 15413: if (_chdir(pathcd) != 0)
15414: printf("Can't move to directory %s!\n",path);
15415: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15416: #else
1.227 brouard 15417: if(chdir(pathcd) != 0)
15418: printf("Can't move to directory %s!\n", path);
15419: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15420: #endif
1.126 brouard 15421: printf("Current directory %s!\n",pathcd);
15422: /*strcat(plotcmd,CHARSEPARATOR);*/
15423: sprintf(plotcmd,"gnuplot");
1.157 brouard 15424: #ifdef _WIN32
1.126 brouard 15425: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15426: #endif
15427: if(!stat(plotcmd,&info)){
1.158 brouard 15428: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15429: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15430: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15431: }else
15432: strcpy(pplotcmd,plotcmd);
1.157 brouard 15433: #ifdef __unix
1.126 brouard 15434: strcpy(plotcmd,GNUPLOTPROGRAM);
15435: if(!stat(plotcmd,&info)){
1.158 brouard 15436: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15437: }else
15438: strcpy(pplotcmd,plotcmd);
15439: #endif
15440: }else
15441: strcpy(pplotcmd,plotcmd);
15442:
15443: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15444: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15445: strcpy(pplotcmd,plotcmd);
1.227 brouard 15446:
1.126 brouard 15447: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15448: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15449: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15450: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15451: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15452: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15453: strcpy(plotcmd,pplotcmd);
15454: }
1.126 brouard 15455: }
1.158 brouard 15456: printf(" Successful, please wait...");
1.126 brouard 15457: while (z[0] != 'q') {
15458: /* chdir(path); */
1.154 brouard 15459: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15460: scanf("%s",z);
15461: /* if (z[0] == 'c') system("./imach"); */
15462: if (z[0] == 'e') {
1.158 brouard 15463: #ifdef __APPLE__
1.152 brouard 15464: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15465: #elif __linux
15466: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15467: #else
1.152 brouard 15468: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15469: #endif
15470: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15471: system(pplotcmd);
1.126 brouard 15472: }
15473: else if (z[0] == 'g') system(plotcmd);
15474: else if (z[0] == 'q') exit(0);
15475: }
1.227 brouard 15476: end:
1.126 brouard 15477: while (z[0] != 'q') {
1.195 brouard 15478: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15479: scanf("%s",z);
15480: }
1.283 brouard 15481: printf("End\n");
1.282 brouard 15482: exit(0);
1.126 brouard 15483: }
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