Annotation of imach/src/imach.c, revision 1.340
1.340 ! brouard 1: /* $Id: imach.c,v 1.339 2022/09/09 17:55:22 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.340 ! brouard 4: Revision 1.339 2022/09/09 17:55:22 brouard
! 5: Summary: version 0.99r37
! 6:
! 7: * imach.c (Module): Many improvements for fixing products of fixed
! 8: timevarying as well as fixed * fixed, and test with quantitative
! 9: covariate.
! 10:
1.339 brouard 11: Revision 1.338 2022/09/04 17:40:33 brouard
12: Summary: 0.99r36
13:
14: * imach.c (Module): Now the easy runs i.e. without result or
15: model=1+age only did not work. The defautl combination should be 1
16: and not 0 because everything hasn't been tranformed yet.
17:
1.338 brouard 18: Revision 1.337 2022/09/02 14:26:02 brouard
19: Summary: version 0.99r35
20:
21: * src/imach.c: Version 0.99r35 because it outputs same results with
22: 1+age+V1+V1*age for females and 1+age for females only
23: (education=1 noweight)
24:
1.337 brouard 25: Revision 1.336 2022/08/31 09:52:36 brouard
26: *** empty log message ***
27:
1.336 brouard 28: Revision 1.335 2022/08/31 08:23:16 brouard
29: Summary: improvements...
30:
1.335 brouard 31: Revision 1.334 2022/08/25 09:08:41 brouard
32: Summary: In progress for quantitative
33:
1.334 brouard 34: Revision 1.333 2022/08/21 09:10:30 brouard
35: * src/imach.c (Module): Version 0.99r33 A lot of changes in
36: reassigning covariates: my first idea was that people will always
37: use the first covariate V1 into the model but in fact they are
38: producing data with many covariates and can use an equation model
39: with some of the covariate; it means that in a model V2+V3 instead
40: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
41: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
42: the equation model is restricted to two variables only (V2, V3)
43: and the combination for V2 should be codtabm(k,1) instead of
44: (codtabm(k,2), and the code should be
45: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
46: made. All of these should be simplified once a day like we did in
47: hpxij() for example by using precov[nres] which is computed in
48: decoderesult for each nres of each resultline. Loop should be done
49: on the equation model globally by distinguishing only product with
50: age (which are changing with age) and no more on type of
51: covariates, single dummies, single covariates.
52:
1.333 brouard 53: Revision 1.332 2022/08/21 09:06:25 brouard
54: Summary: Version 0.99r33
55:
56: * src/imach.c (Module): Version 0.99r33 A lot of changes in
57: reassigning covariates: my first idea was that people will always
58: use the first covariate V1 into the model but in fact they are
59: producing data with many covariates and can use an equation model
60: with some of the covariate; it means that in a model V2+V3 instead
61: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
62: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
63: the equation model is restricted to two variables only (V2, V3)
64: and the combination for V2 should be codtabm(k,1) instead of
65: (codtabm(k,2), and the code should be
66: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
67: made. All of these should be simplified once a day like we did in
68: hpxij() for example by using precov[nres] which is computed in
69: decoderesult for each nres of each resultline. Loop should be done
70: on the equation model globally by distinguishing only product with
71: age (which are changing with age) and no more on type of
72: covariates, single dummies, single covariates.
73:
1.332 brouard 74: Revision 1.331 2022/08/07 05:40:09 brouard
75: *** empty log message ***
76:
1.331 brouard 77: Revision 1.330 2022/08/06 07:18:25 brouard
78: Summary: last 0.99r31
79:
80: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
81:
1.330 brouard 82: Revision 1.329 2022/08/03 17:29:54 brouard
83: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
84:
1.329 brouard 85: Revision 1.328 2022/07/27 17:40:48 brouard
86: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
87:
1.328 brouard 88: Revision 1.327 2022/07/27 14:47:35 brouard
89: Summary: Still a problem for one-step probabilities in case of quantitative variables
90:
1.327 brouard 91: Revision 1.326 2022/07/26 17:33:55 brouard
92: Summary: some test with nres=1
93:
1.326 brouard 94: Revision 1.325 2022/07/25 14:27:23 brouard
95: Summary: r30
96:
97: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
98: coredumped, revealed by Feiuno, thank you.
99:
1.325 brouard 100: Revision 1.324 2022/07/23 17:44:26 brouard
101: *** empty log message ***
102:
1.324 brouard 103: Revision 1.323 2022/07/22 12:30:08 brouard
104: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
105:
1.323 brouard 106: Revision 1.322 2022/07/22 12:27:48 brouard
107: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
108:
1.322 brouard 109: Revision 1.321 2022/07/22 12:04:24 brouard
110: Summary: r28
111:
112: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
113:
1.321 brouard 114: Revision 1.320 2022/06/02 05:10:11 brouard
115: *** empty log message ***
116:
1.320 brouard 117: Revision 1.319 2022/06/02 04:45:11 brouard
118: * imach.c (Module): Adding the Wald tests from the log to the main
119: htm for better display of the maximum likelihood estimators.
120:
1.319 brouard 121: Revision 1.318 2022/05/24 08:10:59 brouard
122: * imach.c (Module): Some attempts to find a bug of wrong estimates
123: of confidencce intervals with product in the equation modelC
124:
1.318 brouard 125: Revision 1.317 2022/05/15 15:06:23 brouard
126: * imach.c (Module): Some minor improvements
127:
1.317 brouard 128: Revision 1.316 2022/05/11 15:11:31 brouard
129: Summary: r27
130:
1.316 brouard 131: Revision 1.315 2022/05/11 15:06:32 brouard
132: *** empty log message ***
133:
1.315 brouard 134: Revision 1.314 2022/04/13 17:43:09 brouard
135: * imach.c (Module): Adding link to text data files
136:
1.314 brouard 137: Revision 1.313 2022/04/11 15:57:42 brouard
138: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
139:
1.313 brouard 140: Revision 1.312 2022/04/05 21:24:39 brouard
141: *** empty log message ***
142:
1.312 brouard 143: Revision 1.311 2022/04/05 21:03:51 brouard
144: Summary: Fixed quantitative covariates
145:
146: Fixed covariates (dummy or quantitative)
147: with missing values have never been allowed but are ERRORS and
148: program quits. Standard deviations of fixed covariates were
149: wrongly computed. Mean and standard deviations of time varying
150: covariates are still not computed.
151:
1.311 brouard 152: Revision 1.310 2022/03/17 08:45:53 brouard
153: Summary: 99r25
154:
155: Improving detection of errors: result lines should be compatible with
156: the model.
157:
1.310 brouard 158: Revision 1.309 2021/05/20 12:39:14 brouard
159: Summary: Version 0.99r24
160:
1.309 brouard 161: Revision 1.308 2021/03/31 13:11:57 brouard
162: Summary: Version 0.99r23
163:
164:
165: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
166:
1.308 brouard 167: Revision 1.307 2021/03/08 18:11:32 brouard
168: Summary: 0.99r22 fixed bug on result:
169:
1.307 brouard 170: Revision 1.306 2021/02/20 15:44:02 brouard
171: Summary: Version 0.99r21
172:
173: * imach.c (Module): Fix bug on quitting after result lines!
174: (Module): Version 0.99r21
175:
1.306 brouard 176: Revision 1.305 2021/02/20 15:28:30 brouard
177: * imach.c (Module): Fix bug on quitting after result lines!
178:
1.305 brouard 179: Revision 1.304 2021/02/12 11:34:20 brouard
180: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
181:
1.304 brouard 182: Revision 1.303 2021/02/11 19:50:15 brouard
183: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
184:
1.303 brouard 185: Revision 1.302 2020/02/22 21:00:05 brouard
186: * (Module): imach.c Update mle=-3 (for computing Life expectancy
187: and life table from the data without any state)
188:
1.302 brouard 189: Revision 1.301 2019/06/04 13:51:20 brouard
190: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
191:
1.301 brouard 192: Revision 1.300 2019/05/22 19:09:45 brouard
193: Summary: version 0.99r19 of May 2019
194:
1.300 brouard 195: Revision 1.299 2019/05/22 18:37:08 brouard
196: Summary: Cleaned 0.99r19
197:
1.299 brouard 198: Revision 1.298 2019/05/22 18:19:56 brouard
199: *** empty log message ***
200:
1.298 brouard 201: Revision 1.297 2019/05/22 17:56:10 brouard
202: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
203:
1.297 brouard 204: Revision 1.296 2019/05/20 13:03:18 brouard
205: Summary: Projection syntax simplified
206:
207:
208: We can now start projections, forward or backward, from the mean date
209: of inteviews up to or down to a number of years of projection:
210: prevforecast=1 yearsfproj=15.3 mobil_average=0
211: or
212: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
213: or
214: prevbackcast=1 yearsbproj=12.3 mobil_average=1
215: or
216: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
217:
1.296 brouard 218: Revision 1.295 2019/05/18 09:52:50 brouard
219: Summary: doxygen tex bug
220:
1.295 brouard 221: Revision 1.294 2019/05/16 14:54:33 brouard
222: Summary: There was some wrong lines added
223:
1.294 brouard 224: Revision 1.293 2019/05/09 15:17:34 brouard
225: *** empty log message ***
226:
1.293 brouard 227: Revision 1.292 2019/05/09 14:17:20 brouard
228: Summary: Some updates
229:
1.292 brouard 230: Revision 1.291 2019/05/09 13:44:18 brouard
231: Summary: Before ncovmax
232:
1.291 brouard 233: Revision 1.290 2019/05/09 13:39:37 brouard
234: Summary: 0.99r18 unlimited number of individuals
235:
236: 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.
237:
1.290 brouard 238: Revision 1.289 2018/12/13 09:16:26 brouard
239: Summary: Bug for young ages (<-30) will be in r17
240:
1.289 brouard 241: Revision 1.288 2018/05/02 20:58:27 brouard
242: Summary: Some bugs fixed
243:
1.288 brouard 244: Revision 1.287 2018/05/01 17:57:25 brouard
245: Summary: Bug fixed by providing frequencies only for non missing covariates
246:
1.287 brouard 247: Revision 1.286 2018/04/27 14:27:04 brouard
248: Summary: some minor bugs
249:
1.286 brouard 250: Revision 1.285 2018/04/21 21:02:16 brouard
251: Summary: Some bugs fixed, valgrind tested
252:
1.285 brouard 253: Revision 1.284 2018/04/20 05:22:13 brouard
254: Summary: Computing mean and stdeviation of fixed quantitative variables
255:
1.284 brouard 256: Revision 1.283 2018/04/19 14:49:16 brouard
257: Summary: Some minor bugs fixed
258:
1.283 brouard 259: Revision 1.282 2018/02/27 22:50:02 brouard
260: *** empty log message ***
261:
1.282 brouard 262: Revision 1.281 2018/02/27 19:25:23 brouard
263: Summary: Adding second argument for quitting
264:
1.281 brouard 265: Revision 1.280 2018/02/21 07:58:13 brouard
266: Summary: 0.99r15
267:
268: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
269:
1.280 brouard 270: Revision 1.279 2017/07/20 13:35:01 brouard
271: Summary: temporary working
272:
1.279 brouard 273: Revision 1.278 2017/07/19 14:09:02 brouard
274: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
275:
1.278 brouard 276: Revision 1.277 2017/07/17 08:53:49 brouard
277: Summary: BOM files can be read now
278:
1.277 brouard 279: Revision 1.276 2017/06/30 15:48:31 brouard
280: Summary: Graphs improvements
281:
1.276 brouard 282: Revision 1.275 2017/06/30 13:39:33 brouard
283: Summary: Saito's color
284:
1.275 brouard 285: Revision 1.274 2017/06/29 09:47:08 brouard
286: Summary: Version 0.99r14
287:
1.274 brouard 288: Revision 1.273 2017/06/27 11:06:02 brouard
289: Summary: More documentation on projections
290:
1.273 brouard 291: Revision 1.272 2017/06/27 10:22:40 brouard
292: Summary: Color of backprojection changed from 6 to 5(yellow)
293:
1.272 brouard 294: Revision 1.271 2017/06/27 10:17:50 brouard
295: Summary: Some bug with rint
296:
1.271 brouard 297: Revision 1.270 2017/05/24 05:45:29 brouard
298: *** empty log message ***
299:
1.270 brouard 300: Revision 1.269 2017/05/23 08:39:25 brouard
301: Summary: Code into subroutine, cleanings
302:
1.269 brouard 303: Revision 1.268 2017/05/18 20:09:32 brouard
304: Summary: backprojection and confidence intervals of backprevalence
305:
1.268 brouard 306: Revision 1.267 2017/05/13 10:25:05 brouard
307: Summary: temporary save for backprojection
308:
1.267 brouard 309: Revision 1.266 2017/05/13 07:26:12 brouard
310: Summary: Version 0.99r13 (improvements and bugs fixed)
311:
1.266 brouard 312: Revision 1.265 2017/04/26 16:22:11 brouard
313: Summary: imach 0.99r13 Some bugs fixed
314:
1.265 brouard 315: Revision 1.264 2017/04/26 06:01:29 brouard
316: Summary: Labels in graphs
317:
1.264 brouard 318: Revision 1.263 2017/04/24 15:23:15 brouard
319: Summary: to save
320:
1.263 brouard 321: Revision 1.262 2017/04/18 16:48:12 brouard
322: *** empty log message ***
323:
1.262 brouard 324: Revision 1.261 2017/04/05 10:14:09 brouard
325: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
326:
1.261 brouard 327: Revision 1.260 2017/04/04 17:46:59 brouard
328: Summary: Gnuplot indexations fixed (humm)
329:
1.260 brouard 330: Revision 1.259 2017/04/04 13:01:16 brouard
331: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
332:
1.259 brouard 333: Revision 1.258 2017/04/03 10:17:47 brouard
334: Summary: Version 0.99r12
335:
336: Some cleanings, conformed with updated documentation.
337:
1.258 brouard 338: Revision 1.257 2017/03/29 16:53:30 brouard
339: Summary: Temp
340:
1.257 brouard 341: Revision 1.256 2017/03/27 05:50:23 brouard
342: Summary: Temporary
343:
1.256 brouard 344: Revision 1.255 2017/03/08 16:02:28 brouard
345: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
346:
1.255 brouard 347: Revision 1.254 2017/03/08 07:13:00 brouard
348: Summary: Fixing data parameter line
349:
1.254 brouard 350: Revision 1.253 2016/12/15 11:59:41 brouard
351: Summary: 0.99 in progress
352:
1.253 brouard 353: Revision 1.252 2016/09/15 21:15:37 brouard
354: *** empty log message ***
355:
1.252 brouard 356: Revision 1.251 2016/09/15 15:01:13 brouard
357: Summary: not working
358:
1.251 brouard 359: Revision 1.250 2016/09/08 16:07:27 brouard
360: Summary: continue
361:
1.250 brouard 362: Revision 1.249 2016/09/07 17:14:18 brouard
363: Summary: Starting values from frequencies
364:
1.249 brouard 365: Revision 1.248 2016/09/07 14:10:18 brouard
366: *** empty log message ***
367:
1.248 brouard 368: Revision 1.247 2016/09/02 11:11:21 brouard
369: *** empty log message ***
370:
1.247 brouard 371: Revision 1.246 2016/09/02 08:49:22 brouard
372: *** empty log message ***
373:
1.246 brouard 374: Revision 1.245 2016/09/02 07:25:01 brouard
375: *** empty log message ***
376:
1.245 brouard 377: Revision 1.244 2016/09/02 07:17:34 brouard
378: *** empty log message ***
379:
1.244 brouard 380: Revision 1.243 2016/09/02 06:45:35 brouard
381: *** empty log message ***
382:
1.243 brouard 383: Revision 1.242 2016/08/30 15:01:20 brouard
384: Summary: Fixing a lots
385:
1.242 brouard 386: Revision 1.241 2016/08/29 17:17:25 brouard
387: Summary: gnuplot problem in Back projection to fix
388:
1.241 brouard 389: Revision 1.240 2016/08/29 07:53:18 brouard
390: Summary: Better
391:
1.240 brouard 392: Revision 1.239 2016/08/26 15:51:03 brouard
393: Summary: Improvement in Powell output in order to copy and paste
394:
395: Author:
396:
1.239 brouard 397: Revision 1.238 2016/08/26 14:23:35 brouard
398: Summary: Starting tests of 0.99
399:
1.238 brouard 400: Revision 1.237 2016/08/26 09:20:19 brouard
401: Summary: to valgrind
402:
1.237 brouard 403: Revision 1.236 2016/08/25 10:50:18 brouard
404: *** empty log message ***
405:
1.236 brouard 406: Revision 1.235 2016/08/25 06:59:23 brouard
407: *** empty log message ***
408:
1.235 brouard 409: Revision 1.234 2016/08/23 16:51:20 brouard
410: *** empty log message ***
411:
1.234 brouard 412: Revision 1.233 2016/08/23 07:40:50 brouard
413: Summary: not working
414:
1.233 brouard 415: Revision 1.232 2016/08/22 14:20:21 brouard
416: Summary: not working
417:
1.232 brouard 418: Revision 1.231 2016/08/22 07:17:15 brouard
419: Summary: not working
420:
1.231 brouard 421: Revision 1.230 2016/08/22 06:55:53 brouard
422: Summary: Not working
423:
1.230 brouard 424: Revision 1.229 2016/07/23 09:45:53 brouard
425: Summary: Completing for func too
426:
1.229 brouard 427: Revision 1.228 2016/07/22 17:45:30 brouard
428: Summary: Fixing some arrays, still debugging
429:
1.227 brouard 430: Revision 1.226 2016/07/12 18:42:34 brouard
431: Summary: temp
432:
1.226 brouard 433: Revision 1.225 2016/07/12 08:40:03 brouard
434: Summary: saving but not running
435:
1.225 brouard 436: Revision 1.224 2016/07/01 13:16:01 brouard
437: Summary: Fixes
438:
1.224 brouard 439: Revision 1.223 2016/02/19 09:23:35 brouard
440: Summary: temporary
441:
1.223 brouard 442: Revision 1.222 2016/02/17 08:14:50 brouard
443: Summary: Probably last 0.98 stable version 0.98r6
444:
1.222 brouard 445: Revision 1.221 2016/02/15 23:35:36 brouard
446: Summary: minor bug
447:
1.220 brouard 448: Revision 1.219 2016/02/15 00:48:12 brouard
449: *** empty log message ***
450:
1.219 brouard 451: Revision 1.218 2016/02/12 11:29:23 brouard
452: Summary: 0.99 Back projections
453:
1.218 brouard 454: Revision 1.217 2015/12/23 17:18:31 brouard
455: Summary: Experimental backcast
456:
1.217 brouard 457: Revision 1.216 2015/12/18 17:32:11 brouard
458: Summary: 0.98r4 Warning and status=-2
459:
460: Version 0.98r4 is now:
461: - displaying an error when status is -1, date of interview unknown and date of death known;
462: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
463: Older changes concerning s=-2, dating from 2005 have been supersed.
464:
1.216 brouard 465: Revision 1.215 2015/12/16 08:52:24 brouard
466: Summary: 0.98r4 working
467:
1.215 brouard 468: Revision 1.214 2015/12/16 06:57:54 brouard
469: Summary: temporary not working
470:
1.214 brouard 471: Revision 1.213 2015/12/11 18:22:17 brouard
472: Summary: 0.98r4
473:
1.213 brouard 474: Revision 1.212 2015/11/21 12:47:24 brouard
475: Summary: minor typo
476:
1.212 brouard 477: Revision 1.211 2015/11/21 12:41:11 brouard
478: Summary: 0.98r3 with some graph of projected cross-sectional
479:
480: Author: Nicolas Brouard
481:
1.211 brouard 482: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 483: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 484: Summary: Adding ftolpl parameter
485: Author: N Brouard
486:
487: We had difficulties to get smoothed confidence intervals. It was due
488: to the period prevalence which wasn't computed accurately. The inner
489: parameter ftolpl is now an outer parameter of the .imach parameter
490: file after estepm. If ftolpl is small 1.e-4 and estepm too,
491: computation are long.
492:
1.209 brouard 493: Revision 1.208 2015/11/17 14:31:57 brouard
494: Summary: temporary
495:
1.208 brouard 496: Revision 1.207 2015/10/27 17:36:57 brouard
497: *** empty log message ***
498:
1.207 brouard 499: Revision 1.206 2015/10/24 07:14:11 brouard
500: *** empty log message ***
501:
1.206 brouard 502: Revision 1.205 2015/10/23 15:50:53 brouard
503: Summary: 0.98r3 some clarification for graphs on likelihood contributions
504:
1.205 brouard 505: Revision 1.204 2015/10/01 16:20:26 brouard
506: Summary: Some new graphs of contribution to likelihood
507:
1.204 brouard 508: Revision 1.203 2015/09/30 17:45:14 brouard
509: Summary: looking at better estimation of the hessian
510:
511: Also a better criteria for convergence to the period prevalence And
512: therefore adding the number of years needed to converge. (The
513: prevalence in any alive state shold sum to one
514:
1.203 brouard 515: Revision 1.202 2015/09/22 19:45:16 brouard
516: Summary: Adding some overall graph on contribution to likelihood. Might change
517:
1.202 brouard 518: Revision 1.201 2015/09/15 17:34:58 brouard
519: Summary: 0.98r0
520:
521: - Some new graphs like suvival functions
522: - Some bugs fixed like model=1+age+V2.
523:
1.201 brouard 524: Revision 1.200 2015/09/09 16:53:55 brouard
525: Summary: Big bug thanks to Flavia
526:
527: Even model=1+age+V2. did not work anymore
528:
1.200 brouard 529: Revision 1.199 2015/09/07 14:09:23 brouard
530: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
531:
1.199 brouard 532: Revision 1.198 2015/09/03 07:14:39 brouard
533: Summary: 0.98q5 Flavia
534:
1.198 brouard 535: Revision 1.197 2015/09/01 18:24:39 brouard
536: *** empty log message ***
537:
1.197 brouard 538: Revision 1.196 2015/08/18 23:17:52 brouard
539: Summary: 0.98q5
540:
1.196 brouard 541: Revision 1.195 2015/08/18 16:28:39 brouard
542: Summary: Adding a hack for testing purpose
543:
544: After reading the title, ftol and model lines, if the comment line has
545: a q, starting with #q, the answer at the end of the run is quit. It
546: permits to run test files in batch with ctest. The former workaround was
547: $ echo q | imach foo.imach
548:
1.195 brouard 549: Revision 1.194 2015/08/18 13:32:00 brouard
550: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
551:
1.194 brouard 552: Revision 1.193 2015/08/04 07:17:42 brouard
553: Summary: 0.98q4
554:
1.193 brouard 555: Revision 1.192 2015/07/16 16:49:02 brouard
556: Summary: Fixing some outputs
557:
1.192 brouard 558: Revision 1.191 2015/07/14 10:00:33 brouard
559: Summary: Some fixes
560:
1.191 brouard 561: Revision 1.190 2015/05/05 08:51:13 brouard
562: Summary: Adding digits in output parameters (7 digits instead of 6)
563:
564: Fix 1+age+.
565:
1.190 brouard 566: Revision 1.189 2015/04/30 14:45:16 brouard
567: Summary: 0.98q2
568:
1.189 brouard 569: Revision 1.188 2015/04/30 08:27:53 brouard
570: *** empty log message ***
571:
1.188 brouard 572: Revision 1.187 2015/04/29 09:11:15 brouard
573: *** empty log message ***
574:
1.187 brouard 575: Revision 1.186 2015/04/23 12:01:52 brouard
576: Summary: V1*age is working now, version 0.98q1
577:
578: Some codes had been disabled in order to simplify and Vn*age was
579: working in the optimization phase, ie, giving correct MLE parameters,
580: but, as usual, outputs were not correct and program core dumped.
581:
1.186 brouard 582: Revision 1.185 2015/03/11 13:26:42 brouard
583: Summary: Inclusion of compile and links command line for Intel Compiler
584:
1.185 brouard 585: Revision 1.184 2015/03/11 11:52:39 brouard
586: Summary: Back from Windows 8. Intel Compiler
587:
1.184 brouard 588: Revision 1.183 2015/03/10 20:34:32 brouard
589: Summary: 0.98q0, trying with directest, mnbrak fixed
590:
591: We use directest instead of original Powell test; probably no
592: incidence on the results, but better justifications;
593: We fixed Numerical Recipes mnbrak routine which was wrong and gave
594: wrong results.
595:
1.183 brouard 596: Revision 1.182 2015/02/12 08:19:57 brouard
597: Summary: Trying to keep directest which seems simpler and more general
598: Author: Nicolas Brouard
599:
1.182 brouard 600: Revision 1.181 2015/02/11 23:22:24 brouard
601: Summary: Comments on Powell added
602:
603: Author:
604:
1.181 brouard 605: Revision 1.180 2015/02/11 17:33:45 brouard
606: Summary: Finishing move from main to function (hpijx and prevalence_limit)
607:
1.180 brouard 608: Revision 1.179 2015/01/04 09:57:06 brouard
609: Summary: back to OS/X
610:
1.179 brouard 611: Revision 1.178 2015/01/04 09:35:48 brouard
612: *** empty log message ***
613:
1.178 brouard 614: Revision 1.177 2015/01/03 18:40:56 brouard
615: Summary: Still testing ilc32 on OSX
616:
1.177 brouard 617: Revision 1.176 2015/01/03 16:45:04 brouard
618: *** empty log message ***
619:
1.176 brouard 620: Revision 1.175 2015/01/03 16:33:42 brouard
621: *** empty log message ***
622:
1.175 brouard 623: Revision 1.174 2015/01/03 16:15:49 brouard
624: Summary: Still in cross-compilation
625:
1.174 brouard 626: Revision 1.173 2015/01/03 12:06:26 brouard
627: Summary: trying to detect cross-compilation
628:
1.173 brouard 629: Revision 1.172 2014/12/27 12:07:47 brouard
630: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
631:
1.172 brouard 632: Revision 1.171 2014/12/23 13:26:59 brouard
633: Summary: Back from Visual C
634:
635: Still problem with utsname.h on Windows
636:
1.171 brouard 637: Revision 1.170 2014/12/23 11:17:12 brouard
638: Summary: Cleaning some \%% back to %%
639:
640: The escape was mandatory for a specific compiler (which one?), but too many warnings.
641:
1.170 brouard 642: Revision 1.169 2014/12/22 23:08:31 brouard
643: Summary: 0.98p
644:
645: Outputs some informations on compiler used, OS etc. Testing on different platforms.
646:
1.169 brouard 647: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 648: Summary: update
1.169 brouard 649:
1.168 brouard 650: Revision 1.167 2014/12/22 13:50:56 brouard
651: Summary: Testing uname and compiler version and if compiled 32 or 64
652:
653: Testing on Linux 64
654:
1.167 brouard 655: Revision 1.166 2014/12/22 11:40:47 brouard
656: *** empty log message ***
657:
1.166 brouard 658: Revision 1.165 2014/12/16 11:20:36 brouard
659: Summary: After compiling on Visual C
660:
661: * imach.c (Module): Merging 1.61 to 1.162
662:
1.165 brouard 663: Revision 1.164 2014/12/16 10:52:11 brouard
664: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
665:
666: * imach.c (Module): Merging 1.61 to 1.162
667:
1.164 brouard 668: Revision 1.163 2014/12/16 10:30:11 brouard
669: * imach.c (Module): Merging 1.61 to 1.162
670:
1.163 brouard 671: Revision 1.162 2014/09/25 11:43:39 brouard
672: Summary: temporary backup 0.99!
673:
1.162 brouard 674: Revision 1.1 2014/09/16 11:06:58 brouard
675: Summary: With some code (wrong) for nlopt
676:
677: Author:
678:
679: Revision 1.161 2014/09/15 20:41:41 brouard
680: Summary: Problem with macro SQR on Intel compiler
681:
1.161 brouard 682: Revision 1.160 2014/09/02 09:24:05 brouard
683: *** empty log message ***
684:
1.160 brouard 685: Revision 1.159 2014/09/01 10:34:10 brouard
686: Summary: WIN32
687: Author: Brouard
688:
1.159 brouard 689: Revision 1.158 2014/08/27 17:11:51 brouard
690: *** empty log message ***
691:
1.158 brouard 692: Revision 1.157 2014/08/27 16:26:55 brouard
693: Summary: Preparing windows Visual studio version
694: Author: Brouard
695:
696: In order to compile on Visual studio, time.h is now correct and time_t
697: and tm struct should be used. difftime should be used but sometimes I
698: just make the differences in raw time format (time(&now).
699: Trying to suppress #ifdef LINUX
700: Add xdg-open for __linux in order to open default browser.
701:
1.157 brouard 702: Revision 1.156 2014/08/25 20:10:10 brouard
703: *** empty log message ***
704:
1.156 brouard 705: Revision 1.155 2014/08/25 18:32:34 brouard
706: Summary: New compile, minor changes
707: Author: Brouard
708:
1.155 brouard 709: Revision 1.154 2014/06/20 17:32:08 brouard
710: Summary: Outputs now all graphs of convergence to period prevalence
711:
1.154 brouard 712: Revision 1.153 2014/06/20 16:45:46 brouard
713: Summary: If 3 live state, convergence to period prevalence on same graph
714: Author: Brouard
715:
1.153 brouard 716: Revision 1.152 2014/06/18 17:54:09 brouard
717: Summary: open browser, use gnuplot on same dir than imach if not found in the path
718:
1.152 brouard 719: Revision 1.151 2014/06/18 16:43:30 brouard
720: *** empty log message ***
721:
1.151 brouard 722: Revision 1.150 2014/06/18 16:42:35 brouard
723: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
724: Author: brouard
725:
1.150 brouard 726: Revision 1.149 2014/06/18 15:51:14 brouard
727: Summary: Some fixes in parameter files errors
728: Author: Nicolas Brouard
729:
1.149 brouard 730: Revision 1.148 2014/06/17 17:38:48 brouard
731: Summary: Nothing new
732: Author: Brouard
733:
734: Just a new packaging for OS/X version 0.98nS
735:
1.148 brouard 736: Revision 1.147 2014/06/16 10:33:11 brouard
737: *** empty log message ***
738:
1.147 brouard 739: Revision 1.146 2014/06/16 10:20:28 brouard
740: Summary: Merge
741: Author: Brouard
742:
743: Merge, before building revised version.
744:
1.146 brouard 745: Revision 1.145 2014/06/10 21:23:15 brouard
746: Summary: Debugging with valgrind
747: Author: Nicolas Brouard
748:
749: Lot of changes in order to output the results with some covariates
750: After the Edimburgh REVES conference 2014, it seems mandatory to
751: improve the code.
752: No more memory valgrind error but a lot has to be done in order to
753: continue the work of splitting the code into subroutines.
754: Also, decodemodel has been improved. Tricode is still not
755: optimal. nbcode should be improved. Documentation has been added in
756: the source code.
757:
1.144 brouard 758: Revision 1.143 2014/01/26 09:45:38 brouard
759: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
760:
761: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
762: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
763:
1.143 brouard 764: Revision 1.142 2014/01/26 03:57:36 brouard
765: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
766:
767: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
768:
1.142 brouard 769: Revision 1.141 2014/01/26 02:42:01 brouard
770: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
771:
1.141 brouard 772: Revision 1.140 2011/09/02 10:37:54 brouard
773: Summary: times.h is ok with mingw32 now.
774:
1.140 brouard 775: Revision 1.139 2010/06/14 07:50:17 brouard
776: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
777: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
778:
1.139 brouard 779: Revision 1.138 2010/04/30 18:19:40 brouard
780: *** empty log message ***
781:
1.138 brouard 782: Revision 1.137 2010/04/29 18:11:38 brouard
783: (Module): Checking covariates for more complex models
784: than V1+V2. A lot of change to be done. Unstable.
785:
1.137 brouard 786: Revision 1.136 2010/04/26 20:30:53 brouard
787: (Module): merging some libgsl code. Fixing computation
788: of likelione (using inter/intrapolation if mle = 0) in order to
789: get same likelihood as if mle=1.
790: Some cleaning of code and comments added.
791:
1.136 brouard 792: Revision 1.135 2009/10/29 15:33:14 brouard
793: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
794:
1.135 brouard 795: Revision 1.134 2009/10/29 13:18:53 brouard
796: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
797:
1.134 brouard 798: Revision 1.133 2009/07/06 10:21:25 brouard
799: just nforces
800:
1.133 brouard 801: Revision 1.132 2009/07/06 08:22:05 brouard
802: Many tings
803:
1.132 brouard 804: Revision 1.131 2009/06/20 16:22:47 brouard
805: Some dimensions resccaled
806:
1.131 brouard 807: Revision 1.130 2009/05/26 06:44:34 brouard
808: (Module): Max Covariate is now set to 20 instead of 8. A
809: lot of cleaning with variables initialized to 0. Trying to make
810: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
811:
1.130 brouard 812: Revision 1.129 2007/08/31 13:49:27 lievre
813: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
814:
1.129 lievre 815: Revision 1.128 2006/06/30 13:02:05 brouard
816: (Module): Clarifications on computing e.j
817:
1.128 brouard 818: Revision 1.127 2006/04/28 18:11:50 brouard
819: (Module): Yes the sum of survivors was wrong since
820: imach-114 because nhstepm was no more computed in the age
821: loop. Now we define nhstepma in the age loop.
822: (Module): In order to speed up (in case of numerous covariates) we
823: compute health expectancies (without variances) in a first step
824: and then all the health expectancies with variances or standard
825: deviation (needs data from the Hessian matrices) which slows the
826: computation.
827: In the future we should be able to stop the program is only health
828: expectancies and graph are needed without standard deviations.
829:
1.127 brouard 830: Revision 1.126 2006/04/28 17:23:28 brouard
831: (Module): Yes the sum of survivors was wrong since
832: imach-114 because nhstepm was no more computed in the age
833: loop. Now we define nhstepma in the age loop.
834: Version 0.98h
835:
1.126 brouard 836: Revision 1.125 2006/04/04 15:20:31 lievre
837: Errors in calculation of health expectancies. Age was not initialized.
838: Forecasting file added.
839:
840: Revision 1.124 2006/03/22 17:13:53 lievre
841: Parameters are printed with %lf instead of %f (more numbers after the comma).
842: The log-likelihood is printed in the log file
843:
844: Revision 1.123 2006/03/20 10:52:43 brouard
845: * imach.c (Module): <title> changed, corresponds to .htm file
846: name. <head> headers where missing.
847:
848: * imach.c (Module): Weights can have a decimal point as for
849: English (a comma might work with a correct LC_NUMERIC environment,
850: otherwise the weight is truncated).
851: Modification of warning when the covariates values are not 0 or
852: 1.
853: Version 0.98g
854:
855: Revision 1.122 2006/03/20 09:45:41 brouard
856: (Module): Weights can have a decimal point as for
857: English (a comma might work with a correct LC_NUMERIC environment,
858: otherwise the weight is truncated).
859: Modification of warning when the covariates values are not 0 or
860: 1.
861: Version 0.98g
862:
863: Revision 1.121 2006/03/16 17:45:01 lievre
864: * imach.c (Module): Comments concerning covariates added
865:
866: * imach.c (Module): refinements in the computation of lli if
867: status=-2 in order to have more reliable computation if stepm is
868: not 1 month. Version 0.98f
869:
870: Revision 1.120 2006/03/16 15:10:38 lievre
871: (Module): refinements in the computation of lli if
872: status=-2 in order to have more reliable computation if stepm is
873: not 1 month. Version 0.98f
874:
875: Revision 1.119 2006/03/15 17:42:26 brouard
876: (Module): Bug if status = -2, the loglikelihood was
877: computed as likelihood omitting the logarithm. Version O.98e
878:
879: Revision 1.118 2006/03/14 18:20:07 brouard
880: (Module): varevsij Comments added explaining the second
881: table of variances if popbased=1 .
882: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
883: (Module): Function pstamp added
884: (Module): Version 0.98d
885:
886: Revision 1.117 2006/03/14 17:16:22 brouard
887: (Module): varevsij Comments added explaining the second
888: table of variances if popbased=1 .
889: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
890: (Module): Function pstamp added
891: (Module): Version 0.98d
892:
893: Revision 1.116 2006/03/06 10:29:27 brouard
894: (Module): Variance-covariance wrong links and
895: varian-covariance of ej. is needed (Saito).
896:
897: Revision 1.115 2006/02/27 12:17:45 brouard
898: (Module): One freematrix added in mlikeli! 0.98c
899:
900: Revision 1.114 2006/02/26 12:57:58 brouard
901: (Module): Some improvements in processing parameter
902: filename with strsep.
903:
904: Revision 1.113 2006/02/24 14:20:24 brouard
905: (Module): Memory leaks checks with valgrind and:
906: datafile was not closed, some imatrix were not freed and on matrix
907: allocation too.
908:
909: Revision 1.112 2006/01/30 09:55:26 brouard
910: (Module): Back to gnuplot.exe instead of wgnuplot.exe
911:
912: Revision 1.111 2006/01/25 20:38:18 brouard
913: (Module): Lots of cleaning and bugs added (Gompertz)
914: (Module): Comments can be added in data file. Missing date values
915: can be a simple dot '.'.
916:
917: Revision 1.110 2006/01/25 00:51:50 brouard
918: (Module): Lots of cleaning and bugs added (Gompertz)
919:
920: Revision 1.109 2006/01/24 19:37:15 brouard
921: (Module): Comments (lines starting with a #) are allowed in data.
922:
923: Revision 1.108 2006/01/19 18:05:42 lievre
924: Gnuplot problem appeared...
925: To be fixed
926:
927: Revision 1.107 2006/01/19 16:20:37 brouard
928: Test existence of gnuplot in imach path
929:
930: Revision 1.106 2006/01/19 13:24:36 brouard
931: Some cleaning and links added in html output
932:
933: Revision 1.105 2006/01/05 20:23:19 lievre
934: *** empty log message ***
935:
936: Revision 1.104 2005/09/30 16:11:43 lievre
937: (Module): sump fixed, loop imx fixed, and simplifications.
938: (Module): If the status is missing at the last wave but we know
939: that the person is alive, then we can code his/her status as -2
940: (instead of missing=-1 in earlier versions) and his/her
941: contributions to the likelihood is 1 - Prob of dying from last
942: health status (= 1-p13= p11+p12 in the easiest case of somebody in
943: the healthy state at last known wave). Version is 0.98
944:
945: Revision 1.103 2005/09/30 15:54:49 lievre
946: (Module): sump fixed, loop imx fixed, and simplifications.
947:
948: Revision 1.102 2004/09/15 17:31:30 brouard
949: Add the possibility to read data file including tab characters.
950:
951: Revision 1.101 2004/09/15 10:38:38 brouard
952: Fix on curr_time
953:
954: Revision 1.100 2004/07/12 18:29:06 brouard
955: Add version for Mac OS X. Just define UNIX in Makefile
956:
957: Revision 1.99 2004/06/05 08:57:40 brouard
958: *** empty log message ***
959:
960: Revision 1.98 2004/05/16 15:05:56 brouard
961: New version 0.97 . First attempt to estimate force of mortality
962: directly from the data i.e. without the need of knowing the health
963: state at each age, but using a Gompertz model: log u =a + b*age .
964: This is the basic analysis of mortality and should be done before any
965: other analysis, in order to test if the mortality estimated from the
966: cross-longitudinal survey is different from the mortality estimated
967: from other sources like vital statistic data.
968:
969: The same imach parameter file can be used but the option for mle should be -3.
970:
1.324 brouard 971: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 972: former routines in order to include the new code within the former code.
973:
974: The output is very simple: only an estimate of the intercept and of
975: the slope with 95% confident intervals.
976:
977: Current limitations:
978: A) Even if you enter covariates, i.e. with the
979: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
980: B) There is no computation of Life Expectancy nor Life Table.
981:
982: Revision 1.97 2004/02/20 13:25:42 lievre
983: Version 0.96d. Population forecasting command line is (temporarily)
984: suppressed.
985:
986: Revision 1.96 2003/07/15 15:38:55 brouard
987: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
988: rewritten within the same printf. Workaround: many printfs.
989:
990: Revision 1.95 2003/07/08 07:54:34 brouard
991: * imach.c (Repository):
992: (Repository): Using imachwizard code to output a more meaningful covariance
993: matrix (cov(a12,c31) instead of numbers.
994:
995: Revision 1.94 2003/06/27 13:00:02 brouard
996: Just cleaning
997:
998: Revision 1.93 2003/06/25 16:33:55 brouard
999: (Module): On windows (cygwin) function asctime_r doesn't
1000: exist so I changed back to asctime which exists.
1001: (Module): Version 0.96b
1002:
1003: Revision 1.92 2003/06/25 16:30:45 brouard
1004: (Module): On windows (cygwin) function asctime_r doesn't
1005: exist so I changed back to asctime which exists.
1006:
1007: Revision 1.91 2003/06/25 15:30:29 brouard
1008: * imach.c (Repository): Duplicated warning errors corrected.
1009: (Repository): Elapsed time after each iteration is now output. It
1010: helps to forecast when convergence will be reached. Elapsed time
1011: is stamped in powell. We created a new html file for the graphs
1012: concerning matrix of covariance. It has extension -cov.htm.
1013:
1014: Revision 1.90 2003/06/24 12:34:15 brouard
1015: (Module): Some bugs corrected for windows. Also, when
1016: mle=-1 a template is output in file "or"mypar.txt with the design
1017: of the covariance matrix to be input.
1018:
1019: Revision 1.89 2003/06/24 12:30:52 brouard
1020: (Module): Some bugs corrected for windows. Also, when
1021: mle=-1 a template is output in file "or"mypar.txt with the design
1022: of the covariance matrix to be input.
1023:
1024: Revision 1.88 2003/06/23 17:54:56 brouard
1025: * 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.
1026:
1027: Revision 1.87 2003/06/18 12:26:01 brouard
1028: Version 0.96
1029:
1030: Revision 1.86 2003/06/17 20:04:08 brouard
1031: (Module): Change position of html and gnuplot routines and added
1032: routine fileappend.
1033:
1034: Revision 1.85 2003/06/17 13:12:43 brouard
1035: * imach.c (Repository): Check when date of death was earlier that
1036: current date of interview. It may happen when the death was just
1037: prior to the death. In this case, dh was negative and likelihood
1038: was wrong (infinity). We still send an "Error" but patch by
1039: assuming that the date of death was just one stepm after the
1040: interview.
1041: (Repository): Because some people have very long ID (first column)
1042: we changed int to long in num[] and we added a new lvector for
1043: memory allocation. But we also truncated to 8 characters (left
1044: truncation)
1045: (Repository): No more line truncation errors.
1046:
1047: Revision 1.84 2003/06/13 21:44:43 brouard
1048: * imach.c (Repository): Replace "freqsummary" at a correct
1049: place. It differs from routine "prevalence" which may be called
1050: many times. Probs is memory consuming and must be used with
1051: parcimony.
1052: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1053:
1054: Revision 1.83 2003/06/10 13:39:11 lievre
1055: *** empty log message ***
1056:
1057: Revision 1.82 2003/06/05 15:57:20 brouard
1058: Add log in imach.c and fullversion number is now printed.
1059:
1060: */
1061: /*
1062: Interpolated Markov Chain
1063:
1064: Short summary of the programme:
1065:
1.227 brouard 1066: This program computes Healthy Life Expectancies or State-specific
1067: (if states aren't health statuses) Expectancies from
1068: cross-longitudinal data. Cross-longitudinal data consist in:
1069:
1070: -1- a first survey ("cross") where individuals from different ages
1071: are interviewed on their health status or degree of disability (in
1072: the case of a health survey which is our main interest)
1073:
1074: -2- at least a second wave of interviews ("longitudinal") which
1075: measure each change (if any) in individual health status. Health
1076: expectancies are computed from the time spent in each health state
1077: according to a model. More health states you consider, more time is
1078: necessary to reach the Maximum Likelihood of the parameters involved
1079: in the model. The simplest model is the multinomial logistic model
1080: where pij is the probability to be observed in state j at the second
1081: wave conditional to be observed in state i at the first
1082: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1083: etc , where 'age' is age and 'sex' is a covariate. If you want to
1084: have a more complex model than "constant and age", you should modify
1085: the program where the markup *Covariates have to be included here
1086: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1087: convergence.
1088:
1089: The advantage of this computer programme, compared to a simple
1090: multinomial logistic model, is clear when the delay between waves is not
1091: identical for each individual. Also, if a individual missed an
1092: intermediate interview, the information is lost, but taken into
1093: account using an interpolation or extrapolation.
1094:
1095: hPijx is the probability to be observed in state i at age x+h
1096: conditional to the observed state i at age x. The delay 'h' can be
1097: split into an exact number (nh*stepm) of unobserved intermediate
1098: states. This elementary transition (by month, quarter,
1099: semester or year) is modelled as a multinomial logistic. The hPx
1100: matrix is simply the matrix product of nh*stepm elementary matrices
1101: and the contribution of each individual to the likelihood is simply
1102: hPijx.
1103:
1104: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1105: of the life expectancies. It also computes the period (stable) prevalence.
1106:
1107: Back prevalence and projections:
1.227 brouard 1108:
1109: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1110: double agemaxpar, double ftolpl, int *ncvyearp, double
1111: dateprev1,double dateprev2, int firstpass, int lastpass, int
1112: mobilavproj)
1113:
1114: Computes the back prevalence limit for any combination of
1115: covariate values k at any age between ageminpar and agemaxpar and
1116: returns it in **bprlim. In the loops,
1117:
1118: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1119: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1120:
1121: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1122: Computes for any combination of covariates k and any age between bage and fage
1123: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1124: oldm=oldms;savm=savms;
1.227 brouard 1125:
1.267 brouard 1126: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1127: Computes the transition matrix starting at age 'age' over
1128: 'nhstepm*hstepm*stepm' months (i.e. until
1129: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1130: nhstepm*hstepm matrices.
1131:
1132: Returns p3mat[i][j][h] after calling
1133: p3mat[i][j][h]=matprod2(newm,
1134: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1135: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1136: oldm);
1.226 brouard 1137:
1138: Important routines
1139:
1140: - func (or funcone), computes logit (pij) distinguishing
1141: o fixed variables (single or product dummies or quantitative);
1142: o varying variables by:
1143: (1) wave (single, product dummies, quantitative),
1144: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1145: % fixed dummy (treated) or quantitative (not done because time-consuming);
1146: % varying dummy (not done) or quantitative (not done);
1147: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1148: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1149: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1150: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1151: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1152:
1.226 brouard 1153:
1154:
1.324 brouard 1155: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1156: Institut national d'études démographiques, Paris.
1.126 brouard 1157: This software have been partly granted by Euro-REVES, a concerted action
1158: from the European Union.
1159: It is copyrighted identically to a GNU software product, ie programme and
1160: software can be distributed freely for non commercial use. Latest version
1161: can be accessed at http://euroreves.ined.fr/imach .
1162:
1163: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1164: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1165:
1166: **********************************************************************/
1167: /*
1168: main
1169: read parameterfile
1170: read datafile
1171: concatwav
1172: freqsummary
1173: if (mle >= 1)
1174: mlikeli
1175: print results files
1176: if mle==1
1177: computes hessian
1178: read end of parameter file: agemin, agemax, bage, fage, estepm
1179: begin-prev-date,...
1180: open gnuplot file
1181: open html file
1.145 brouard 1182: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1183: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1184: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1185: freexexit2 possible for memory heap.
1186:
1187: h Pij x | pij_nom ficrestpij
1188: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1189: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1190: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1191:
1192: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1193: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1194: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1195: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1196: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1197:
1.126 brouard 1198: forecasting if prevfcast==1 prevforecast call prevalence()
1199: health expectancies
1200: Variance-covariance of DFLE
1201: prevalence()
1202: movingaverage()
1203: varevsij()
1204: if popbased==1 varevsij(,popbased)
1205: total life expectancies
1206: Variance of period (stable) prevalence
1207: end
1208: */
1209:
1.187 brouard 1210: /* #define DEBUG */
1211: /* #define DEBUGBRENT */
1.203 brouard 1212: /* #define DEBUGLINMIN */
1213: /* #define DEBUGHESS */
1214: #define DEBUGHESSIJ
1.224 brouard 1215: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1216: #define POWELL /* Instead of NLOPT */
1.224 brouard 1217: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1218: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1219: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1220: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1221:
1222: #include <math.h>
1223: #include <stdio.h>
1224: #include <stdlib.h>
1225: #include <string.h>
1.226 brouard 1226: #include <ctype.h>
1.159 brouard 1227:
1228: #ifdef _WIN32
1229: #include <io.h>
1.172 brouard 1230: #include <windows.h>
1231: #include <tchar.h>
1.159 brouard 1232: #else
1.126 brouard 1233: #include <unistd.h>
1.159 brouard 1234: #endif
1.126 brouard 1235:
1236: #include <limits.h>
1237: #include <sys/types.h>
1.171 brouard 1238:
1239: #if defined(__GNUC__)
1240: #include <sys/utsname.h> /* Doesn't work on Windows */
1241: #endif
1242:
1.126 brouard 1243: #include <sys/stat.h>
1244: #include <errno.h>
1.159 brouard 1245: /* extern int errno; */
1.126 brouard 1246:
1.157 brouard 1247: /* #ifdef LINUX */
1248: /* #include <time.h> */
1249: /* #include "timeval.h" */
1250: /* #else */
1251: /* #include <sys/time.h> */
1252: /* #endif */
1253:
1.126 brouard 1254: #include <time.h>
1255:
1.136 brouard 1256: #ifdef GSL
1257: #include <gsl/gsl_errno.h>
1258: #include <gsl/gsl_multimin.h>
1259: #endif
1260:
1.167 brouard 1261:
1.162 brouard 1262: #ifdef NLOPT
1263: #include <nlopt.h>
1264: typedef struct {
1265: double (* function)(double [] );
1266: } myfunc_data ;
1267: #endif
1268:
1.126 brouard 1269: /* #include <libintl.h> */
1270: /* #define _(String) gettext (String) */
1271:
1.251 brouard 1272: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1273:
1274: #define GNUPLOTPROGRAM "gnuplot"
1275: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1276: #define FILENAMELENGTH 256
1.126 brouard 1277:
1278: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1279: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1280:
1.144 brouard 1281: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1282: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1283:
1284: #define NINTERVMAX 8
1.144 brouard 1285: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1286: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1287: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1288: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1289: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1290: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1291: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1292: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1293: /* #define AGESUP 130 */
1.288 brouard 1294: /* #define AGESUP 150 */
1295: #define AGESUP 200
1.268 brouard 1296: #define AGEINF 0
1.218 brouard 1297: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1298: #define AGEBASE 40
1.194 brouard 1299: #define AGEOVERFLOW 1.e20
1.164 brouard 1300: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1301: #ifdef _WIN32
1302: #define DIRSEPARATOR '\\'
1303: #define CHARSEPARATOR "\\"
1304: #define ODIRSEPARATOR '/'
1305: #else
1.126 brouard 1306: #define DIRSEPARATOR '/'
1307: #define CHARSEPARATOR "/"
1308: #define ODIRSEPARATOR '\\'
1309: #endif
1310:
1.340 ! brouard 1311: /* $Id: imach.c,v 1.339 2022/09/09 17:55:22 brouard Exp $ */
1.126 brouard 1312: /* $State: Exp $ */
1.196 brouard 1313: #include "version.h"
1314: char version[]=__IMACH_VERSION__;
1.337 brouard 1315: char copyright[]="September 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
1.340 ! brouard 1316: char fullversion[]="$Revision: 1.339 $ $Date: 2022/09/09 17:55:22 $";
1.126 brouard 1317: char strstart[80];
1318: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1319: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1320: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1321: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1322: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1323: 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 1324: 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 1325: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1326: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1327: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1328: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1329: 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 1330: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1331: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1332: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.232 brouard 1333: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1334: int nsd=0; /**< Total number of single dummy variables (output) */
1335: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1336: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1337: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1338: int ntveff=0; /**< ntveff number of effective time varying variables */
1339: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1340: int cptcov=0; /* Working variable */
1.334 brouard 1341: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1342: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1343: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1344: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1345: int nlstate=2; /* Number of live states */
1346: int ndeath=1; /* Number of dead states */
1.130 brouard 1347: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1348: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1349: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1350: int popbased=0;
1351:
1352: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1353: int maxwav=0; /* Maxim number of waves */
1354: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1355: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1356: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1357: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1358: int mle=1, weightopt=0;
1.126 brouard 1359: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1360: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1361: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1362: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1363: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1364: int selected(int kvar); /* Is covariate kvar selected for printing results */
1365:
1.130 brouard 1366: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1367: double **matprod2(); /* test */
1.126 brouard 1368: double **oldm, **newm, **savm; /* Working pointers to matrices */
1369: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1370: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1371:
1.136 brouard 1372: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1373: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1374: FILE *ficlog, *ficrespow;
1.130 brouard 1375: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1376: double fretone; /* Only one call to likelihood */
1.130 brouard 1377: long ipmx=0; /* Number of contributions */
1.126 brouard 1378: double sw; /* Sum of weights */
1379: char filerespow[FILENAMELENGTH];
1380: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1381: FILE *ficresilk;
1382: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1383: FILE *ficresprobmorprev;
1384: FILE *fichtm, *fichtmcov; /* Html File */
1385: FILE *ficreseij;
1386: char filerese[FILENAMELENGTH];
1387: FILE *ficresstdeij;
1388: char fileresstde[FILENAMELENGTH];
1389: FILE *ficrescveij;
1390: char filerescve[FILENAMELENGTH];
1391: FILE *ficresvij;
1392: char fileresv[FILENAMELENGTH];
1.269 brouard 1393:
1.126 brouard 1394: char title[MAXLINE];
1.234 brouard 1395: char model[MAXLINE]; /**< The model line */
1.217 brouard 1396: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1397: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1398: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1399: char command[FILENAMELENGTH];
1400: int outcmd=0;
1401:
1.217 brouard 1402: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1403: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1404: char filelog[FILENAMELENGTH]; /* Log file */
1405: char filerest[FILENAMELENGTH];
1406: char fileregp[FILENAMELENGTH];
1407: char popfile[FILENAMELENGTH];
1408:
1409: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1410:
1.157 brouard 1411: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1412: /* struct timezone tzp; */
1413: /* extern int gettimeofday(); */
1414: struct tm tml, *gmtime(), *localtime();
1415:
1416: extern time_t time();
1417:
1418: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1419: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1420: struct tm tm;
1421:
1.126 brouard 1422: char strcurr[80], strfor[80];
1423:
1424: char *endptr;
1425: long lval;
1426: double dval;
1427:
1428: #define NR_END 1
1429: #define FREE_ARG char*
1430: #define FTOL 1.0e-10
1431:
1432: #define NRANSI
1.240 brouard 1433: #define ITMAX 200
1434: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1435:
1436: #define TOL 2.0e-4
1437:
1438: #define CGOLD 0.3819660
1439: #define ZEPS 1.0e-10
1440: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1441:
1442: #define GOLD 1.618034
1443: #define GLIMIT 100.0
1444: #define TINY 1.0e-20
1445:
1446: static double maxarg1,maxarg2;
1447: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1448: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1449:
1450: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1451: #define rint(a) floor(a+0.5)
1.166 brouard 1452: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1453: #define mytinydouble 1.0e-16
1.166 brouard 1454: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1455: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1456: /* static double dsqrarg; */
1457: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1458: static double sqrarg;
1459: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1460: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1461: int agegomp= AGEGOMP;
1462:
1463: int imx;
1464: int stepm=1;
1465: /* Stepm, step in month: minimum step interpolation*/
1466:
1467: int estepm;
1468: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1469:
1470: int m,nb;
1471: long *num;
1.197 brouard 1472: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1473: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1474: covariate for which somebody answered excluding
1475: undefined. Usually 2: 0 and 1. */
1476: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1477: covariate for which somebody answered including
1478: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1479: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1480: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1481: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1482: 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 1483: double *ageexmed,*agecens;
1484: double dateintmean=0;
1.296 brouard 1485: double anprojd, mprojd, jprojd; /* For eventual projections */
1486: double anprojf, mprojf, jprojf;
1.126 brouard 1487:
1.296 brouard 1488: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1489: double anbackf, mbackf, jbackf;
1490: double jintmean,mintmean,aintmean;
1.126 brouard 1491: double *weight;
1492: int **s; /* Status */
1.141 brouard 1493: double *agedc;
1.145 brouard 1494: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1495: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1496: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1497: double **coqvar; /* Fixed quantitative covariate nqv */
1498: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1499: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1500: double idx;
1501: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1502: /* Some documentation */
1503: /* Design original data
1504: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1505: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1506: * ntv=3 nqtv=1
1.330 brouard 1507: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1508: * For time varying covariate, quanti or dummies
1509: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1510: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1511: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1512: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1513: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1514: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1515: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1516: * k= 1 2 3 4 5 6 7 8 9 10 11
1517: */
1518: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1519: /* 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
1520: # States 1=Coresidence, 2 Living alone, 3 Institution
1521: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1522: */
1.319 brouard 1523: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1524: /* k 1 2 3 4 5 6 7 8 9 */
1525: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1526: /* fixed or varying), 1 for age product, 2 for*/
1527: /* product */
1528: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1529: /*(single or product without age), 2 dummy*/
1530: /* with age product, 3 quant with age product*/
1531: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1532: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1.330 brouard 1533: /*TnsdVar[Tvar] 1 2 3 */
1.337 brouard 1534: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.319 brouard 1535: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.338 brouard 1536: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1.319 brouard 1537: /* nsq 1 2 */ /* Counting single quantit tv */
1538: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1539: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1540: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1541: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1542: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1543: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1544: /* 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 1545: /* 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 1546: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1547: /* Type */
1548: /* V 1 2 3 4 5 */
1549: /* F F V V V */
1550: /* D Q D D Q */
1551: /* */
1552: int *TvarsD;
1.330 brouard 1553: int *TnsdVar;
1.234 brouard 1554: int *TvarsDind;
1555: int *TvarsQ;
1556: int *TvarsQind;
1557:
1.318 brouard 1558: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1559: int nresult=0;
1.258 brouard 1560: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1561: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1562: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1563: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1564: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1565: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1566: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1567: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1568: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1569: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1570: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1571:
1572: /* 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
1573: # States 1=Coresidence, 2 Living alone, 3 Institution
1574: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1575: */
1.234 brouard 1576: /* 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 1577: 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 */
1578: 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 */
1579: 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 */
1580: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1581: 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 */
1582: 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 1583: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1584: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1585: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1586: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1587: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1588: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1589: 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 */
1590: 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 1591: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1592: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1593: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1594: /* model V1+V3+age*V1+age*V3+V1*V3 */
1595: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1596: /* TvarVV={3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1597: /* TvarVVind={2,5,5}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1.230 brouard 1598: int *Tvarsel; /**< Selected covariates for output */
1599: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1600: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1601: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1602: 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 1603: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1604: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1605: int *Tage;
1.227 brouard 1606: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1607: 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 1608: 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*/
1609: 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 1610: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1611: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1612: int **Tvard;
1.330 brouard 1613: int **Tvardk;
1.227 brouard 1614: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1615: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1616: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1617: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1618: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1619: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1620: double *lsurv, *lpop, *tpop;
1621:
1.231 brouard 1622: #define FD 1; /* Fixed dummy covariate */
1623: #define FQ 2; /* Fixed quantitative covariate */
1624: #define FP 3; /* Fixed product covariate */
1625: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1626: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1627: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1628: #define VD 10; /* Varying dummy covariate */
1629: #define VQ 11; /* Varying quantitative covariate */
1630: #define VP 12; /* Varying product covariate */
1631: #define VPDD 13; /* Varying product dummy*dummy covariate */
1632: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1633: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1634: #define APFD 16; /* Age product * fixed dummy covariate */
1635: #define APFQ 17; /* Age product * fixed quantitative covariate */
1636: #define APVD 18; /* Age product * varying dummy covariate */
1637: #define APVQ 19; /* Age product * varying quantitative covariate */
1638:
1639: #define FTYPE 1; /* Fixed covariate */
1640: #define VTYPE 2; /* Varying covariate (loop in wave) */
1641: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1642:
1643: struct kmodel{
1644: int maintype; /* main type */
1645: int subtype; /* subtype */
1646: };
1647: struct kmodel modell[NCOVMAX];
1648:
1.143 brouard 1649: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1650: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1651:
1652: /**************** split *************************/
1653: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1654: {
1655: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1656: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1657: */
1658: char *ss; /* pointer */
1.186 brouard 1659: int l1=0, l2=0; /* length counters */
1.126 brouard 1660:
1661: l1 = strlen(path ); /* length of path */
1662: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1663: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1664: if ( ss == NULL ) { /* no directory, so determine current directory */
1665: strcpy( name, path ); /* we got the fullname name because no directory */
1666: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1667: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1668: /* get current working directory */
1669: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1670: #ifdef WIN32
1671: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1672: #else
1673: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1674: #endif
1.126 brouard 1675: return( GLOCK_ERROR_GETCWD );
1676: }
1677: /* got dirc from getcwd*/
1678: printf(" DIRC = %s \n",dirc);
1.205 brouard 1679: } else { /* strip directory from path */
1.126 brouard 1680: ss++; /* after this, the filename */
1681: l2 = strlen( ss ); /* length of filename */
1682: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1683: strcpy( name, ss ); /* save file name */
1684: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1685: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1686: printf(" DIRC2 = %s \n",dirc);
1687: }
1688: /* We add a separator at the end of dirc if not exists */
1689: l1 = strlen( dirc ); /* length of directory */
1690: if( dirc[l1-1] != DIRSEPARATOR ){
1691: dirc[l1] = DIRSEPARATOR;
1692: dirc[l1+1] = 0;
1693: printf(" DIRC3 = %s \n",dirc);
1694: }
1695: ss = strrchr( name, '.' ); /* find last / */
1696: if (ss >0){
1697: ss++;
1698: strcpy(ext,ss); /* save extension */
1699: l1= strlen( name);
1700: l2= strlen(ss)+1;
1701: strncpy( finame, name, l1-l2);
1702: finame[l1-l2]= 0;
1703: }
1704:
1705: return( 0 ); /* we're done */
1706: }
1707:
1708:
1709: /******************************************/
1710:
1711: void replace_back_to_slash(char *s, char*t)
1712: {
1713: int i;
1714: int lg=0;
1715: i=0;
1716: lg=strlen(t);
1717: for(i=0; i<= lg; i++) {
1718: (s[i] = t[i]);
1719: if (t[i]== '\\') s[i]='/';
1720: }
1721: }
1722:
1.132 brouard 1723: char *trimbb(char *out, char *in)
1.137 brouard 1724: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1725: char *s;
1726: s=out;
1727: while (*in != '\0'){
1.137 brouard 1728: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1729: in++;
1730: }
1731: *out++ = *in++;
1732: }
1733: *out='\0';
1734: return s;
1735: }
1736:
1.187 brouard 1737: /* char *substrchaine(char *out, char *in, char *chain) */
1738: /* { */
1739: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1740: /* char *s, *t; */
1741: /* t=in;s=out; */
1742: /* while ((*in != *chain) && (*in != '\0')){ */
1743: /* *out++ = *in++; */
1744: /* } */
1745:
1746: /* /\* *in matches *chain *\/ */
1747: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1748: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1749: /* } */
1750: /* in--; chain--; */
1751: /* while ( (*in != '\0')){ */
1752: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1753: /* *out++ = *in++; */
1754: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1755: /* } */
1756: /* *out='\0'; */
1757: /* out=s; */
1758: /* return out; */
1759: /* } */
1760: char *substrchaine(char *out, char *in, char *chain)
1761: {
1762: /* Substract chain 'chain' from 'in', return and output 'out' */
1763: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1764:
1765: char *strloc;
1766:
1767: strcpy (out, in);
1768: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1769: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1770: if(strloc != NULL){
1771: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1772: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1773: /* strcpy (strloc, strloc +strlen(chain));*/
1774: }
1775: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1776: return out;
1777: }
1778:
1779:
1.145 brouard 1780: char *cutl(char *blocc, char *alocc, char *in, char occ)
1781: {
1.187 brouard 1782: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1783: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1784: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1785: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1786: */
1.160 brouard 1787: char *s, *t;
1.145 brouard 1788: t=in;s=in;
1789: while ((*in != occ) && (*in != '\0')){
1790: *alocc++ = *in++;
1791: }
1792: if( *in == occ){
1793: *(alocc)='\0';
1794: s=++in;
1795: }
1796:
1797: if (s == t) {/* occ not found */
1798: *(alocc-(in-s))='\0';
1799: in=s;
1800: }
1801: while ( *in != '\0'){
1802: *blocc++ = *in++;
1803: }
1804:
1805: *blocc='\0';
1806: return t;
1807: }
1.137 brouard 1808: char *cutv(char *blocc, char *alocc, char *in, char occ)
1809: {
1.187 brouard 1810: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1811: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1812: gives blocc="abcdef2ghi" and alocc="j".
1813: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1814: */
1815: char *s, *t;
1816: t=in;s=in;
1817: while (*in != '\0'){
1818: while( *in == occ){
1819: *blocc++ = *in++;
1820: s=in;
1821: }
1822: *blocc++ = *in++;
1823: }
1824: if (s == t) /* occ not found */
1825: *(blocc-(in-s))='\0';
1826: else
1827: *(blocc-(in-s)-1)='\0';
1828: in=s;
1829: while ( *in != '\0'){
1830: *alocc++ = *in++;
1831: }
1832:
1833: *alocc='\0';
1834: return s;
1835: }
1836:
1.126 brouard 1837: int nbocc(char *s, char occ)
1838: {
1839: int i,j=0;
1840: int lg=20;
1841: i=0;
1842: lg=strlen(s);
1843: for(i=0; i<= lg; i++) {
1.234 brouard 1844: if (s[i] == occ ) j++;
1.126 brouard 1845: }
1846: return j;
1847: }
1848:
1.137 brouard 1849: /* void cutv(char *u,char *v, char*t, char occ) */
1850: /* { */
1851: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1852: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1853: /* gives u="abcdef2ghi" and v="j" *\/ */
1854: /* int i,lg,j,p=0; */
1855: /* i=0; */
1856: /* lg=strlen(t); */
1857: /* for(j=0; j<=lg-1; j++) { */
1858: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1859: /* } */
1.126 brouard 1860:
1.137 brouard 1861: /* for(j=0; j<p; j++) { */
1862: /* (u[j] = t[j]); */
1863: /* } */
1864: /* u[p]='\0'; */
1.126 brouard 1865:
1.137 brouard 1866: /* for(j=0; j<= lg; j++) { */
1867: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1868: /* } */
1869: /* } */
1.126 brouard 1870:
1.160 brouard 1871: #ifdef _WIN32
1872: char * strsep(char **pp, const char *delim)
1873: {
1874: char *p, *q;
1875:
1876: if ((p = *pp) == NULL)
1877: return 0;
1878: if ((q = strpbrk (p, delim)) != NULL)
1879: {
1880: *pp = q + 1;
1881: *q = '\0';
1882: }
1883: else
1884: *pp = 0;
1885: return p;
1886: }
1887: #endif
1888:
1.126 brouard 1889: /********************** nrerror ********************/
1890:
1891: void nrerror(char error_text[])
1892: {
1893: fprintf(stderr,"ERREUR ...\n");
1894: fprintf(stderr,"%s\n",error_text);
1895: exit(EXIT_FAILURE);
1896: }
1897: /*********************** vector *******************/
1898: double *vector(int nl, int nh)
1899: {
1900: double *v;
1901: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1902: if (!v) nrerror("allocation failure in vector");
1903: return v-nl+NR_END;
1904: }
1905:
1906: /************************ free vector ******************/
1907: void free_vector(double*v, int nl, int nh)
1908: {
1909: free((FREE_ARG)(v+nl-NR_END));
1910: }
1911:
1912: /************************ivector *******************************/
1913: int *ivector(long nl,long nh)
1914: {
1915: int *v;
1916: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1917: if (!v) nrerror("allocation failure in ivector");
1918: return v-nl+NR_END;
1919: }
1920:
1921: /******************free ivector **************************/
1922: void free_ivector(int *v, long nl, long nh)
1923: {
1924: free((FREE_ARG)(v+nl-NR_END));
1925: }
1926:
1927: /************************lvector *******************************/
1928: long *lvector(long nl,long nh)
1929: {
1930: long *v;
1931: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1932: if (!v) nrerror("allocation failure in ivector");
1933: return v-nl+NR_END;
1934: }
1935:
1936: /******************free lvector **************************/
1937: void free_lvector(long *v, long nl, long nh)
1938: {
1939: free((FREE_ARG)(v+nl-NR_END));
1940: }
1941:
1942: /******************* imatrix *******************************/
1943: int **imatrix(long nrl, long nrh, long ncl, long nch)
1944: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1945: {
1946: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1947: int **m;
1948:
1949: /* allocate pointers to rows */
1950: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1951: if (!m) nrerror("allocation failure 1 in matrix()");
1952: m += NR_END;
1953: m -= nrl;
1954:
1955:
1956: /* allocate rows and set pointers to them */
1957: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1958: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1959: m[nrl] += NR_END;
1960: m[nrl] -= ncl;
1961:
1962: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1963:
1964: /* return pointer to array of pointers to rows */
1965: return m;
1966: }
1967:
1968: /****************** free_imatrix *************************/
1969: void free_imatrix(m,nrl,nrh,ncl,nch)
1970: int **m;
1971: long nch,ncl,nrh,nrl;
1972: /* free an int matrix allocated by imatrix() */
1973: {
1974: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1975: free((FREE_ARG) (m+nrl-NR_END));
1976: }
1977:
1978: /******************* matrix *******************************/
1979: double **matrix(long nrl, long nrh, long ncl, long nch)
1980: {
1981: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1982: double **m;
1983:
1984: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1985: if (!m) nrerror("allocation failure 1 in matrix()");
1986: m += NR_END;
1987: m -= nrl;
1988:
1989: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1990: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1991: m[nrl] += NR_END;
1992: m[nrl] -= ncl;
1993:
1994: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1995: return m;
1.145 brouard 1996: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1997: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1998: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1999: */
2000: }
2001:
2002: /*************************free matrix ************************/
2003: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2004: {
2005: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2006: free((FREE_ARG)(m+nrl-NR_END));
2007: }
2008:
2009: /******************* ma3x *******************************/
2010: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2011: {
2012: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2013: double ***m;
2014:
2015: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2016: if (!m) nrerror("allocation failure 1 in matrix()");
2017: m += NR_END;
2018: m -= nrl;
2019:
2020: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2021: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2022: m[nrl] += NR_END;
2023: m[nrl] -= ncl;
2024:
2025: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2026:
2027: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2028: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2029: m[nrl][ncl] += NR_END;
2030: m[nrl][ncl] -= nll;
2031: for (j=ncl+1; j<=nch; j++)
2032: m[nrl][j]=m[nrl][j-1]+nlay;
2033:
2034: for (i=nrl+1; i<=nrh; i++) {
2035: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2036: for (j=ncl+1; j<=nch; j++)
2037: m[i][j]=m[i][j-1]+nlay;
2038: }
2039: return m;
2040: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2041: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2042: */
2043: }
2044:
2045: /*************************free ma3x ************************/
2046: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2047: {
2048: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2049: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2050: free((FREE_ARG)(m+nrl-NR_END));
2051: }
2052:
2053: /*************** function subdirf ***********/
2054: char *subdirf(char fileres[])
2055: {
2056: /* Caution optionfilefiname is hidden */
2057: strcpy(tmpout,optionfilefiname);
2058: strcat(tmpout,"/"); /* Add to the right */
2059: strcat(tmpout,fileres);
2060: return tmpout;
2061: }
2062:
2063: /*************** function subdirf2 ***********/
2064: char *subdirf2(char fileres[], char *preop)
2065: {
1.314 brouard 2066: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2067: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2068: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2069: /* Caution optionfilefiname is hidden */
2070: strcpy(tmpout,optionfilefiname);
2071: strcat(tmpout,"/");
2072: strcat(tmpout,preop);
2073: strcat(tmpout,fileres);
2074: return tmpout;
2075: }
2076:
2077: /*************** function subdirf3 ***********/
2078: char *subdirf3(char fileres[], char *preop, char *preop2)
2079: {
2080:
2081: /* Caution optionfilefiname is hidden */
2082: strcpy(tmpout,optionfilefiname);
2083: strcat(tmpout,"/");
2084: strcat(tmpout,preop);
2085: strcat(tmpout,preop2);
2086: strcat(tmpout,fileres);
2087: return tmpout;
2088: }
1.213 brouard 2089:
2090: /*************** function subdirfext ***********/
2091: char *subdirfext(char fileres[], char *preop, char *postop)
2092: {
2093:
2094: strcpy(tmpout,preop);
2095: strcat(tmpout,fileres);
2096: strcat(tmpout,postop);
2097: return tmpout;
2098: }
1.126 brouard 2099:
1.213 brouard 2100: /*************** function subdirfext3 ***********/
2101: char *subdirfext3(char fileres[], char *preop, char *postop)
2102: {
2103:
2104: /* Caution optionfilefiname is hidden */
2105: strcpy(tmpout,optionfilefiname);
2106: strcat(tmpout,"/");
2107: strcat(tmpout,preop);
2108: strcat(tmpout,fileres);
2109: strcat(tmpout,postop);
2110: return tmpout;
2111: }
2112:
1.162 brouard 2113: char *asc_diff_time(long time_sec, char ascdiff[])
2114: {
2115: long sec_left, days, hours, minutes;
2116: days = (time_sec) / (60*60*24);
2117: sec_left = (time_sec) % (60*60*24);
2118: hours = (sec_left) / (60*60) ;
2119: sec_left = (sec_left) %(60*60);
2120: minutes = (sec_left) /60;
2121: sec_left = (sec_left) % (60);
2122: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2123: return ascdiff;
2124: }
2125:
1.126 brouard 2126: /***************** f1dim *************************/
2127: extern int ncom;
2128: extern double *pcom,*xicom;
2129: extern double (*nrfunc)(double []);
2130:
2131: double f1dim(double x)
2132: {
2133: int j;
2134: double f;
2135: double *xt;
2136:
2137: xt=vector(1,ncom);
2138: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2139: f=(*nrfunc)(xt);
2140: free_vector(xt,1,ncom);
2141: return f;
2142: }
2143:
2144: /*****************brent *************************/
2145: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2146: {
2147: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2148: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2149: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2150: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2151: * returned function value.
2152: */
1.126 brouard 2153: int iter;
2154: double a,b,d,etemp;
1.159 brouard 2155: double fu=0,fv,fw,fx;
1.164 brouard 2156: double ftemp=0.;
1.126 brouard 2157: double p,q,r,tol1,tol2,u,v,w,x,xm;
2158: double e=0.0;
2159:
2160: a=(ax < cx ? ax : cx);
2161: b=(ax > cx ? ax : cx);
2162: x=w=v=bx;
2163: fw=fv=fx=(*f)(x);
2164: for (iter=1;iter<=ITMAX;iter++) {
2165: xm=0.5*(a+b);
2166: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2167: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2168: printf(".");fflush(stdout);
2169: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2170: #ifdef DEBUGBRENT
1.126 brouard 2171: 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);
2172: 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);
2173: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2174: #endif
2175: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2176: *xmin=x;
2177: return fx;
2178: }
2179: ftemp=fu;
2180: if (fabs(e) > tol1) {
2181: r=(x-w)*(fx-fv);
2182: q=(x-v)*(fx-fw);
2183: p=(x-v)*q-(x-w)*r;
2184: q=2.0*(q-r);
2185: if (q > 0.0) p = -p;
2186: q=fabs(q);
2187: etemp=e;
2188: e=d;
2189: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2190: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2191: else {
1.224 brouard 2192: d=p/q;
2193: u=x+d;
2194: if (u-a < tol2 || b-u < tol2)
2195: d=SIGN(tol1,xm-x);
1.126 brouard 2196: }
2197: } else {
2198: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2199: }
2200: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2201: fu=(*f)(u);
2202: if (fu <= fx) {
2203: if (u >= x) a=x; else b=x;
2204: SHFT(v,w,x,u)
1.183 brouard 2205: SHFT(fv,fw,fx,fu)
2206: } else {
2207: if (u < x) a=u; else b=u;
2208: if (fu <= fw || w == x) {
1.224 brouard 2209: v=w;
2210: w=u;
2211: fv=fw;
2212: fw=fu;
1.183 brouard 2213: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2214: v=u;
2215: fv=fu;
1.183 brouard 2216: }
2217: }
1.126 brouard 2218: }
2219: nrerror("Too many iterations in brent");
2220: *xmin=x;
2221: return fx;
2222: }
2223:
2224: /****************** mnbrak ***********************/
2225:
2226: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2227: double (*func)(double))
1.183 brouard 2228: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2229: the downhill direction (defined by the function as evaluated at the initial points) and returns
2230: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2231: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2232: */
1.126 brouard 2233: double ulim,u,r,q, dum;
2234: double fu;
1.187 brouard 2235:
2236: double scale=10.;
2237: int iterscale=0;
2238:
2239: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2240: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2241:
2242:
2243: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2244: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2245: /* *bx = *ax - (*ax - *bx)/scale; */
2246: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2247: /* } */
2248:
1.126 brouard 2249: if (*fb > *fa) {
2250: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2251: SHFT(dum,*fb,*fa,dum)
2252: }
1.126 brouard 2253: *cx=(*bx)+GOLD*(*bx-*ax);
2254: *fc=(*func)(*cx);
1.183 brouard 2255: #ifdef DEBUG
1.224 brouard 2256: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2257: 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 2258: #endif
1.224 brouard 2259: 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 2260: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2261: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2262: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2263: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2264: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2265: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2266: fu=(*func)(u);
1.163 brouard 2267: #ifdef DEBUG
2268: /* f(x)=A(x-u)**2+f(u) */
2269: double A, fparabu;
2270: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2271: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2272: 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);
2273: 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 2274: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2275: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2276: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2277: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2278: #endif
1.184 brouard 2279: #ifdef MNBRAKORIGINAL
1.183 brouard 2280: #else
1.191 brouard 2281: /* if (fu > *fc) { */
2282: /* #ifdef DEBUG */
2283: /* printf("mnbrak4 fu > fc \n"); */
2284: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2285: /* #endif */
2286: /* /\* 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 *\\/ *\/ */
2287: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2288: /* dum=u; /\* Shifting c and u *\/ */
2289: /* u = *cx; */
2290: /* *cx = dum; */
2291: /* dum = fu; */
2292: /* fu = *fc; */
2293: /* *fc =dum; */
2294: /* } else { /\* end *\/ */
2295: /* #ifdef DEBUG */
2296: /* printf("mnbrak3 fu < fc \n"); */
2297: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2298: /* #endif */
2299: /* dum=u; /\* Shifting c and u *\/ */
2300: /* u = *cx; */
2301: /* *cx = dum; */
2302: /* dum = fu; */
2303: /* fu = *fc; */
2304: /* *fc =dum; */
2305: /* } */
1.224 brouard 2306: #ifdef DEBUGMNBRAK
2307: double A, fparabu;
2308: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2309: fparabu= *fa - A*(*ax-u)*(*ax-u);
2310: 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);
2311: 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 2312: #endif
1.191 brouard 2313: dum=u; /* Shifting c and u */
2314: u = *cx;
2315: *cx = dum;
2316: dum = fu;
2317: fu = *fc;
2318: *fc =dum;
1.183 brouard 2319: #endif
1.162 brouard 2320: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2321: #ifdef DEBUG
1.224 brouard 2322: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2323: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2324: #endif
1.126 brouard 2325: fu=(*func)(u);
2326: if (fu < *fc) {
1.183 brouard 2327: #ifdef DEBUG
1.224 brouard 2328: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2329: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2330: #endif
2331: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2332: SHFT(*fb,*fc,fu,(*func)(u))
2333: #ifdef DEBUG
2334: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2335: #endif
2336: }
1.162 brouard 2337: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2338: #ifdef DEBUG
1.224 brouard 2339: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2340: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2341: #endif
1.126 brouard 2342: u=ulim;
2343: fu=(*func)(u);
1.183 brouard 2344: } else { /* u could be left to b (if r > q parabola has a maximum) */
2345: #ifdef DEBUG
1.224 brouard 2346: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2347: 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 2348: #endif
1.126 brouard 2349: u=(*cx)+GOLD*(*cx-*bx);
2350: fu=(*func)(u);
1.224 brouard 2351: #ifdef DEBUG
2352: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2353: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2354: #endif
1.183 brouard 2355: } /* end tests */
1.126 brouard 2356: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2357: SHFT(*fa,*fb,*fc,fu)
2358: #ifdef DEBUG
1.224 brouard 2359: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2360: 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 2361: #endif
2362: } /* 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 2363: }
2364:
2365: /*************** linmin ************************/
1.162 brouard 2366: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2367: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2368: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2369: the value of func at the returned location p . This is actually all accomplished by calling the
2370: routines mnbrak and brent .*/
1.126 brouard 2371: int ncom;
2372: double *pcom,*xicom;
2373: double (*nrfunc)(double []);
2374:
1.224 brouard 2375: #ifdef LINMINORIGINAL
1.126 brouard 2376: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2377: #else
2378: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2379: #endif
1.126 brouard 2380: {
2381: double brent(double ax, double bx, double cx,
2382: double (*f)(double), double tol, double *xmin);
2383: double f1dim(double x);
2384: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2385: double *fc, double (*func)(double));
2386: int j;
2387: double xx,xmin,bx,ax;
2388: double fx,fb,fa;
1.187 brouard 2389:
1.203 brouard 2390: #ifdef LINMINORIGINAL
2391: #else
2392: double scale=10., axs, xxs; /* Scale added for infinity */
2393: #endif
2394:
1.126 brouard 2395: ncom=n;
2396: pcom=vector(1,n);
2397: xicom=vector(1,n);
2398: nrfunc=func;
2399: for (j=1;j<=n;j++) {
2400: pcom[j]=p[j];
1.202 brouard 2401: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2402: }
1.187 brouard 2403:
1.203 brouard 2404: #ifdef LINMINORIGINAL
2405: xx=1.;
2406: #else
2407: axs=0.0;
2408: xxs=1.;
2409: do{
2410: xx= xxs;
2411: #endif
1.187 brouard 2412: ax=0.;
2413: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2414: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2415: /* 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)) */
2416: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2417: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2418: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2419: /* 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 2420: #ifdef LINMINORIGINAL
2421: #else
2422: if (fx != fx){
1.224 brouard 2423: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2424: printf("|");
2425: fprintf(ficlog,"|");
1.203 brouard 2426: #ifdef DEBUGLINMIN
1.224 brouard 2427: 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 2428: #endif
2429: }
1.224 brouard 2430: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2431: #endif
2432:
1.191 brouard 2433: #ifdef DEBUGLINMIN
2434: 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 2435: 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 2436: #endif
1.224 brouard 2437: #ifdef LINMINORIGINAL
2438: #else
1.317 brouard 2439: if(fb == fx){ /* Flat function in the direction */
2440: xmin=xx;
1.224 brouard 2441: *flat=1;
1.317 brouard 2442: }else{
1.224 brouard 2443: *flat=0;
2444: #endif
2445: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2446: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2447: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2448: /* fmin = f(p[j] + xmin * xi[j]) */
2449: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2450: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2451: #ifdef DEBUG
1.224 brouard 2452: 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);
2453: 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);
2454: #endif
2455: #ifdef LINMINORIGINAL
2456: #else
2457: }
1.126 brouard 2458: #endif
1.191 brouard 2459: #ifdef DEBUGLINMIN
2460: printf("linmin end ");
1.202 brouard 2461: fprintf(ficlog,"linmin end ");
1.191 brouard 2462: #endif
1.126 brouard 2463: for (j=1;j<=n;j++) {
1.203 brouard 2464: #ifdef LINMINORIGINAL
2465: xi[j] *= xmin;
2466: #else
2467: #ifdef DEBUGLINMIN
2468: if(xxs <1.0)
2469: printf(" before xi[%d]=%12.8f", j,xi[j]);
2470: #endif
2471: 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) */
2472: #ifdef DEBUGLINMIN
2473: if(xxs <1.0)
2474: 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 );
2475: #endif
2476: #endif
1.187 brouard 2477: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2478: }
1.191 brouard 2479: #ifdef DEBUGLINMIN
1.203 brouard 2480: printf("\n");
1.191 brouard 2481: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2482: 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 2483: for (j=1;j<=n;j++) {
1.202 brouard 2484: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2485: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2486: if(j % ncovmodel == 0){
1.191 brouard 2487: printf("\n");
1.202 brouard 2488: fprintf(ficlog,"\n");
2489: }
1.191 brouard 2490: }
1.203 brouard 2491: #else
1.191 brouard 2492: #endif
1.126 brouard 2493: free_vector(xicom,1,n);
2494: free_vector(pcom,1,n);
2495: }
2496:
2497:
2498: /*************** powell ************************/
1.162 brouard 2499: /*
1.317 brouard 2500: Minimization of a function func of n variables. Input consists in an initial starting point
2501: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2502: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2503: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2504: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2505: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2506: */
1.224 brouard 2507: #ifdef LINMINORIGINAL
2508: #else
2509: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2510: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2511: #endif
1.126 brouard 2512: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2513: double (*func)(double []))
2514: {
1.224 brouard 2515: #ifdef LINMINORIGINAL
2516: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2517: double (*func)(double []));
1.224 brouard 2518: #else
1.241 brouard 2519: void linmin(double p[], double xi[], int n, double *fret,
2520: double (*func)(double []),int *flat);
1.224 brouard 2521: #endif
1.239 brouard 2522: int i,ibig,j,jk,k;
1.126 brouard 2523: double del,t,*pt,*ptt,*xit;
1.181 brouard 2524: double directest;
1.126 brouard 2525: double fp,fptt;
2526: double *xits;
2527: int niterf, itmp;
2528:
2529: pt=vector(1,n);
2530: ptt=vector(1,n);
2531: xit=vector(1,n);
2532: xits=vector(1,n);
2533: *fret=(*func)(p);
2534: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2535: rcurr_time = time(NULL);
2536: fp=(*fret); /* Initialisation */
1.126 brouard 2537: for (*iter=1;;++(*iter)) {
2538: ibig=0;
2539: del=0.0;
1.157 brouard 2540: rlast_time=rcurr_time;
2541: /* (void) gettimeofday(&curr_time,&tzp); */
2542: rcurr_time = time(NULL);
2543: curr_time = *localtime(&rcurr_time);
1.337 brouard 2544: /* 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); */
2545: /* 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); */
2546: printf("\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2547: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
1.157 brouard 2548: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2549: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2550: for (i=1;i<=n;i++) {
1.126 brouard 2551: fprintf(ficrespow," %.12lf", p[i]);
2552: }
1.239 brouard 2553: fprintf(ficrespow,"\n");fflush(ficrespow);
2554: printf("\n#model= 1 + age ");
2555: fprintf(ficlog,"\n#model= 1 + age ");
2556: if(nagesqr==1){
1.241 brouard 2557: printf(" + age*age ");
2558: fprintf(ficlog," + age*age ");
1.239 brouard 2559: }
2560: for(j=1;j <=ncovmodel-2;j++){
2561: if(Typevar[j]==0) {
2562: printf(" + V%d ",Tvar[j]);
2563: fprintf(ficlog," + V%d ",Tvar[j]);
2564: }else if(Typevar[j]==1) {
2565: printf(" + V%d*age ",Tvar[j]);
2566: fprintf(ficlog," + V%d*age ",Tvar[j]);
2567: }else if(Typevar[j]==2) {
2568: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2569: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2570: }
2571: }
1.126 brouard 2572: printf("\n");
1.239 brouard 2573: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2574: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2575: fprintf(ficlog,"\n");
1.239 brouard 2576: for(i=1,jk=1; i <=nlstate; i++){
2577: for(k=1; k <=(nlstate+ndeath); k++){
2578: if (k != i) {
2579: printf("%d%d ",i,k);
2580: fprintf(ficlog,"%d%d ",i,k);
2581: for(j=1; j <=ncovmodel; j++){
2582: printf("%12.7f ",p[jk]);
2583: fprintf(ficlog,"%12.7f ",p[jk]);
2584: jk++;
2585: }
2586: printf("\n");
2587: fprintf(ficlog,"\n");
2588: }
2589: }
2590: }
1.241 brouard 2591: if(*iter <=3 && *iter >1){
1.157 brouard 2592: tml = *localtime(&rcurr_time);
2593: strcpy(strcurr,asctime(&tml));
2594: rforecast_time=rcurr_time;
1.126 brouard 2595: itmp = strlen(strcurr);
2596: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2597: strcurr[itmp-1]='\0';
1.162 brouard 2598: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2599: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2600: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2601: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2602: forecast_time = *localtime(&rforecast_time);
2603: strcpy(strfor,asctime(&forecast_time));
2604: itmp = strlen(strfor);
2605: if(strfor[itmp-1]=='\n')
2606: strfor[itmp-1]='\0';
2607: printf(" - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
2608: fprintf(ficlog," - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2609: }
2610: }
1.187 brouard 2611: for (i=1;i<=n;i++) { /* For each direction i */
2612: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2613: fptt=(*fret);
2614: #ifdef DEBUG
1.203 brouard 2615: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2616: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2617: #endif
1.203 brouard 2618: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2619: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2620: #ifdef LINMINORIGINAL
1.188 brouard 2621: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2622: #else
2623: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2624: flatdir[i]=flat; /* Function is vanishing in that direction i */
2625: #endif
2626: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2627: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2628: /* because that direction will be replaced unless the gain del is small */
2629: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2630: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2631: /* with the new direction. */
2632: del=fabs(fptt-(*fret));
2633: ibig=i;
1.126 brouard 2634: }
2635: #ifdef DEBUG
2636: printf("%d %.12e",i,(*fret));
2637: fprintf(ficlog,"%d %.12e",i,(*fret));
2638: for (j=1;j<=n;j++) {
1.224 brouard 2639: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2640: printf(" x(%d)=%.12e",j,xit[j]);
2641: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2642: }
2643: for(j=1;j<=n;j++) {
1.225 brouard 2644: printf(" p(%d)=%.12e",j,p[j]);
2645: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2646: }
2647: printf("\n");
2648: fprintf(ficlog,"\n");
2649: #endif
1.187 brouard 2650: } /* end loop on each direction i */
2651: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2652: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2653: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2654: for(j=1;j<=n;j++) {
2655: if(flatdir[j] >0){
2656: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2657: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2658: }
1.319 brouard 2659: /* printf("\n"); */
2660: /* fprintf(ficlog,"\n"); */
2661: }
1.243 brouard 2662: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2663: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2664: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2665: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2666: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2667: /* decreased of more than 3.84 */
2668: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2669: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2670: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2671:
1.188 brouard 2672: /* Starting the program with initial values given by a former maximization will simply change */
2673: /* the scales of the directions and the directions, because the are reset to canonical directions */
2674: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2675: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2676: #ifdef DEBUG
2677: int k[2],l;
2678: k[0]=1;
2679: k[1]=-1;
2680: printf("Max: %.12e",(*func)(p));
2681: fprintf(ficlog,"Max: %.12e",(*func)(p));
2682: for (j=1;j<=n;j++) {
2683: printf(" %.12e",p[j]);
2684: fprintf(ficlog," %.12e",p[j]);
2685: }
2686: printf("\n");
2687: fprintf(ficlog,"\n");
2688: for(l=0;l<=1;l++) {
2689: for (j=1;j<=n;j++) {
2690: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2691: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2692: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2693: }
2694: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2695: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2696: }
2697: #endif
2698:
2699: free_vector(xit,1,n);
2700: free_vector(xits,1,n);
2701: free_vector(ptt,1,n);
2702: free_vector(pt,1,n);
2703: return;
1.192 brouard 2704: } /* enough precision */
1.240 brouard 2705: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2706: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2707: ptt[j]=2.0*p[j]-pt[j];
2708: xit[j]=p[j]-pt[j];
2709: pt[j]=p[j];
2710: }
1.181 brouard 2711: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2712: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2713: if (*iter <=4) {
1.225 brouard 2714: #else
2715: #endif
1.224 brouard 2716: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2717: #else
1.161 brouard 2718: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2719: #endif
1.162 brouard 2720: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2721: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2722: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2723: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2724: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2725: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2726: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2727: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2728: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2729: /* Even if f3 <f1, directest can be negative and t >0 */
2730: /* mu² and del² are equal when f3=f1 */
2731: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2732: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2733: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2734: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2735: #ifdef NRCORIGINAL
2736: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2737: #else
2738: 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 2739: t= t- del*SQR(fp-fptt);
1.183 brouard 2740: #endif
1.202 brouard 2741: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2742: #ifdef DEBUG
1.181 brouard 2743: 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);
2744: 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 2745: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2746: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2747: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2748: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2749: 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);
2750: 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);
2751: #endif
1.183 brouard 2752: #ifdef POWELLORIGINAL
2753: if (t < 0.0) { /* Then we use it for new direction */
2754: #else
1.182 brouard 2755: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2756: 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 2757: 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 2758: 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 2759: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2760: }
1.181 brouard 2761: if (directest < 0.0) { /* Then we use it for new direction */
2762: #endif
1.191 brouard 2763: #ifdef DEBUGLINMIN
1.234 brouard 2764: printf("Before linmin in direction P%d-P0\n",n);
2765: for (j=1;j<=n;j++) {
2766: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2767: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2768: if(j % ncovmodel == 0){
2769: printf("\n");
2770: fprintf(ficlog,"\n");
2771: }
2772: }
1.224 brouard 2773: #endif
2774: #ifdef LINMINORIGINAL
1.234 brouard 2775: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2776: #else
1.234 brouard 2777: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2778: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2779: #endif
1.234 brouard 2780:
1.191 brouard 2781: #ifdef DEBUGLINMIN
1.234 brouard 2782: for (j=1;j<=n;j++) {
2783: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2784: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2785: if(j % ncovmodel == 0){
2786: printf("\n");
2787: fprintf(ficlog,"\n");
2788: }
2789: }
1.224 brouard 2790: #endif
1.234 brouard 2791: for (j=1;j<=n;j++) {
2792: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2793: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2794: }
1.224 brouard 2795: #ifdef LINMINORIGINAL
2796: #else
1.234 brouard 2797: for (j=1, flatd=0;j<=n;j++) {
2798: if(flatdir[j]>0)
2799: flatd++;
2800: }
2801: if(flatd >0){
1.255 brouard 2802: printf("%d flat directions: ",flatd);
2803: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2804: for (j=1;j<=n;j++) {
2805: if(flatdir[j]>0){
2806: printf("%d ",j);
2807: fprintf(ficlog,"%d ",j);
2808: }
2809: }
2810: printf("\n");
2811: fprintf(ficlog,"\n");
1.319 brouard 2812: #ifdef FLATSUP
2813: free_vector(xit,1,n);
2814: free_vector(xits,1,n);
2815: free_vector(ptt,1,n);
2816: free_vector(pt,1,n);
2817: return;
2818: #endif
1.234 brouard 2819: }
1.191 brouard 2820: #endif
1.234 brouard 2821: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2822: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2823:
1.126 brouard 2824: #ifdef DEBUG
1.234 brouard 2825: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2826: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2827: for(j=1;j<=n;j++){
2828: printf(" %lf",xit[j]);
2829: fprintf(ficlog," %lf",xit[j]);
2830: }
2831: printf("\n");
2832: fprintf(ficlog,"\n");
1.126 brouard 2833: #endif
1.192 brouard 2834: } /* end of t or directest negative */
1.224 brouard 2835: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2836: #else
1.234 brouard 2837: } /* end if (fptt < fp) */
1.192 brouard 2838: #endif
1.225 brouard 2839: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2840: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2841: #else
1.224 brouard 2842: #endif
1.234 brouard 2843: } /* loop iteration */
1.126 brouard 2844: }
1.234 brouard 2845:
1.126 brouard 2846: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2847:
1.235 brouard 2848: 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 2849: {
1.338 brouard 2850: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2851: * (and selected quantitative values in nres)
2852: * by left multiplying the unit
2853: * matrix by transitions matrix until convergence is reached with precision ftolpl
2854: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2855: * Wx is row vector: population in state 1, population in state 2, population dead
2856: * or prevalence in state 1, prevalence in state 2, 0
2857: * newm is the matrix after multiplications, its rows are identical at a factor.
2858: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2859: * Output is prlim.
2860: * Initial matrix pimij
2861: */
1.206 brouard 2862: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2863: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2864: /* 0, 0 , 1} */
2865: /*
2866: * and after some iteration: */
2867: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2868: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2869: /* 0, 0 , 1} */
2870: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2871: /* {0.51571254859325999, 0.4842874514067399, */
2872: /* 0.51326036147820708, 0.48673963852179264} */
2873: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2874:
1.332 brouard 2875: int i, ii,j,k, k1;
1.209 brouard 2876: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2877: /* double **matprod2(); */ /* test */
1.218 brouard 2878: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2879: double **newm;
1.209 brouard 2880: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2881: int ncvloop=0;
1.288 brouard 2882: int first=0;
1.169 brouard 2883:
1.209 brouard 2884: min=vector(1,nlstate);
2885: max=vector(1,nlstate);
2886: meandiff=vector(1,nlstate);
2887:
1.218 brouard 2888: /* Starting with matrix unity */
1.126 brouard 2889: for (ii=1;ii<=nlstate+ndeath;ii++)
2890: for (j=1;j<=nlstate+ndeath;j++){
2891: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2892: }
1.169 brouard 2893:
2894: cov[1]=1.;
2895:
2896: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2897: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2898: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2899: ncvloop++;
1.126 brouard 2900: newm=savm;
2901: /* Covariates have to be included here again */
1.138 brouard 2902: cov[2]=agefin;
1.319 brouard 2903: if(nagesqr==1){
2904: cov[3]= agefin*agefin;
2905: }
1.332 brouard 2906: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
2907: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
2908: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
2909: if(Typevar[k1]==1){ /* A product with age */
2910: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
2911: }else{
2912: cov[2+nagesqr+k1]=precov[nres][k1];
2913: }
2914: }/* End of loop on model equation */
2915:
2916: /* Start of old code (replaced by a loop on position in the model equation */
2917: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
2918: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
2919: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
2920: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
2921: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
2922: /* * k 1 2 3 4 5 6 7 8 */
2923: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
2924: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
2925: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
2926: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
2927: /* *nsd=3 (1) (2) (3) */
2928: /* *TvarsD[nsd] [1]=2 1 3 */
2929: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
2930: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
2931: /* *Tage[] [1]=1 [2]=2 [3]=3 */
2932: /* *Tvard[] [1][1]=1 [2][1]=1 */
2933: /* * [1][2]=3 [2][2]=2 */
2934: /* *Tprod[](=k) [1]=1 [2]=8 */
2935: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
2936: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
2937: /* *TvarsDpType */
2938: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
2939: /* * nsd=1 (1) (2) */
2940: /* *TvarsD[nsd] 3 2 */
2941: /* *TnsdVar (3)=1 (2)=2 */
2942: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
2943: /* *Tage[] [1]=2 [2]= 3 */
2944: /* *\/ */
2945: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
2946: /* /\* 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)); *\/ */
2947: /* } */
2948: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
2949: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
2950: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
2951: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
2952: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
2953: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2954: /* /\* 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]); *\/ */
2955: /* } */
2956: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
2957: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
2958: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
2959: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
2960: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
2961: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
2962: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2963: /* } */
2964: /* /\* 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]); *\/ */
2965: /* } */
2966: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
2967: /* /\* 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]); *\/ */
2968: /* if(Dummy[Tvard[k][1]]==0){ */
2969: /* if(Dummy[Tvard[k][2]]==0){ */
2970: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
2971: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
2972: /* }else{ */
2973: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
2974: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
2975: /* } */
2976: /* }else{ */
2977: /* if(Dummy[Tvard[k][2]]==0){ */
2978: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
2979: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
2980: /* }else{ */
2981: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
2982: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
2983: /* } */
2984: /* } */
2985: /* } /\* End product without age *\/ */
2986: /* ENd of old code */
1.138 brouard 2987: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2988: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2989: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2990: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2991: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2992: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2993: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2994:
1.126 brouard 2995: savm=oldm;
2996: oldm=newm;
1.209 brouard 2997:
2998: for(j=1; j<=nlstate; j++){
2999: max[j]=0.;
3000: min[j]=1.;
3001: }
3002: for(i=1;i<=nlstate;i++){
3003: sumnew=0;
3004: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3005: for(j=1; j<=nlstate; j++){
3006: prlim[i][j]= newm[i][j]/(1-sumnew);
3007: max[j]=FMAX(max[j],prlim[i][j]);
3008: min[j]=FMIN(min[j],prlim[i][j]);
3009: }
3010: }
3011:
1.126 brouard 3012: maxmax=0.;
1.209 brouard 3013: for(j=1; j<=nlstate; j++){
3014: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3015: maxmax=FMAX(maxmax,meandiff[j]);
3016: /* 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 3017: } /* j loop */
1.203 brouard 3018: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3019: /* 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 3020: if(maxmax < ftolpl){
1.209 brouard 3021: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3022: free_vector(min,1,nlstate);
3023: free_vector(max,1,nlstate);
3024: free_vector(meandiff,1,nlstate);
1.126 brouard 3025: return prlim;
3026: }
1.288 brouard 3027: } /* agefin loop */
1.208 brouard 3028: /* After some age loop it doesn't converge */
1.288 brouard 3029: if(!first){
3030: first=1;
3031: 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 3032: 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);
3033: }else if (first >=1 && first <10){
3034: 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);
3035: first++;
3036: }else if (first ==10){
3037: 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);
3038: 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");
3039: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3040: first++;
1.288 brouard 3041: }
3042:
1.209 brouard 3043: /* 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); */
3044: free_vector(min,1,nlstate);
3045: free_vector(max,1,nlstate);
3046: free_vector(meandiff,1,nlstate);
1.208 brouard 3047:
1.169 brouard 3048: return prlim; /* should not reach here */
1.126 brouard 3049: }
3050:
1.217 brouard 3051:
3052: /**** Back Prevalence limit (stable or period prevalence) ****************/
3053:
1.218 brouard 3054: /* 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) */
3055: /* 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 3056: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3057: {
1.264 brouard 3058: /* 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 3059: matrix by transitions matrix until convergence is reached with precision ftolpl */
3060: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3061: /* Wx is row vector: population in state 1, population in state 2, population dead */
3062: /* or prevalence in state 1, prevalence in state 2, 0 */
3063: /* newm is the matrix after multiplications, its rows are identical at a factor */
3064: /* Initial matrix pimij */
3065: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3066: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3067: /* 0, 0 , 1} */
3068: /*
3069: * and after some iteration: */
3070: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3071: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3072: /* 0, 0 , 1} */
3073: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3074: /* {0.51571254859325999, 0.4842874514067399, */
3075: /* 0.51326036147820708, 0.48673963852179264} */
3076: /* If we start from prlim again, prlim tends to a constant matrix */
3077:
1.332 brouard 3078: int i, ii,j,k, k1;
1.247 brouard 3079: int first=0;
1.217 brouard 3080: double *min, *max, *meandiff, maxmax,sumnew=0.;
3081: /* double **matprod2(); */ /* test */
3082: double **out, cov[NCOVMAX+1], **bmij();
3083: double **newm;
1.218 brouard 3084: double **dnewm, **doldm, **dsavm; /* for use */
3085: double **oldm, **savm; /* for use */
3086:
1.217 brouard 3087: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3088: int ncvloop=0;
3089:
3090: min=vector(1,nlstate);
3091: max=vector(1,nlstate);
3092: meandiff=vector(1,nlstate);
3093:
1.266 brouard 3094: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3095: oldm=oldms; savm=savms;
3096:
3097: /* Starting with matrix unity */
3098: for (ii=1;ii<=nlstate+ndeath;ii++)
3099: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3100: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3101: }
3102:
3103: cov[1]=1.;
3104:
3105: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3106: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3107: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3108: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3109: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3110: ncvloop++;
1.218 brouard 3111: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3112: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3113: /* Covariates have to be included here again */
3114: cov[2]=agefin;
1.319 brouard 3115: if(nagesqr==1){
1.217 brouard 3116: cov[3]= agefin*agefin;;
1.319 brouard 3117: }
1.332 brouard 3118: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3119: if(Typevar[k1]==1){ /* A product with age */
3120: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3121: }else{
1.332 brouard 3122: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3123: }
1.332 brouard 3124: }/* End of loop on model equation */
3125:
3126: /* Old code */
3127:
3128: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3129: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3130: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3131: /* /\* 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)); *\/ */
3132: /* } */
3133: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3134: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3135: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3136: /* /\* /\\* 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])]); *\\/ *\/ */
3137: /* /\* } *\/ */
3138: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3139: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3140: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3141: /* /\* 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]); *\/ */
3142: /* } */
3143: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3144: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3145: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3146: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3147: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3148: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3149: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3150: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3151: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3152: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3153: /* } */
3154: /* /\* 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]); *\/ */
3155: /* } */
3156: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3157: /* /\* 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]); *\/ */
3158: /* if(Dummy[Tvard[k][1]]==0){ */
3159: /* if(Dummy[Tvard[k][2]]==0){ */
3160: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3161: /* }else{ */
3162: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3163: /* } */
3164: /* }else{ */
3165: /* if(Dummy[Tvard[k][2]]==0){ */
3166: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3167: /* }else{ */
3168: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3169: /* } */
3170: /* } */
3171: /* } */
1.217 brouard 3172:
3173: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3174: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3175: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3176: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3177: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3178: /* ij should be linked to the correct index of cov */
3179: /* age and covariate values ij are in 'cov', but we need to pass
3180: * ij for the observed prevalence at age and status and covariate
3181: * number: prevacurrent[(int)agefin][ii][ij]
3182: */
3183: /* 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 *\/ */
3184: /* 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 *\/ */
3185: 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 3186: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3187: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3188: /* for(i=1; i<=nlstate+ndeath; i++) { */
3189: /* printf("%d newm= ",i); */
3190: /* for(j=1;j<=nlstate+ndeath;j++) { */
3191: /* printf("%f ",newm[i][j]); */
3192: /* } */
3193: /* printf("oldm * "); */
3194: /* for(j=1;j<=nlstate+ndeath;j++) { */
3195: /* printf("%f ",oldm[i][j]); */
3196: /* } */
1.268 brouard 3197: /* printf(" bmmij "); */
1.266 brouard 3198: /* for(j=1;j<=nlstate+ndeath;j++) { */
3199: /* printf("%f ",pmmij[i][j]); */
3200: /* } */
3201: /* printf("\n"); */
3202: /* } */
3203: /* } */
1.217 brouard 3204: savm=oldm;
3205: oldm=newm;
1.266 brouard 3206:
1.217 brouard 3207: for(j=1; j<=nlstate; j++){
3208: max[j]=0.;
3209: min[j]=1.;
3210: }
3211: for(j=1; j<=nlstate; j++){
3212: for(i=1;i<=nlstate;i++){
1.234 brouard 3213: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3214: bprlim[i][j]= newm[i][j];
3215: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3216: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3217: }
3218: }
1.218 brouard 3219:
1.217 brouard 3220: maxmax=0.;
3221: for(i=1; i<=nlstate; i++){
1.318 brouard 3222: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3223: maxmax=FMAX(maxmax,meandiff[i]);
3224: /* 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 3225: } /* i loop */
1.217 brouard 3226: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3227: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3228: if(maxmax < ftolpl){
1.220 brouard 3229: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3230: free_vector(min,1,nlstate);
3231: free_vector(max,1,nlstate);
3232: free_vector(meandiff,1,nlstate);
3233: return bprlim;
3234: }
1.288 brouard 3235: } /* agefin loop */
1.217 brouard 3236: /* After some age loop it doesn't converge */
1.288 brouard 3237: if(!first){
1.247 brouard 3238: first=1;
3239: 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\
3240: 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);
3241: }
3242: 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 3243: 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);
3244: /* 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); */
3245: free_vector(min,1,nlstate);
3246: free_vector(max,1,nlstate);
3247: free_vector(meandiff,1,nlstate);
3248:
3249: return bprlim; /* should not reach here */
3250: }
3251:
1.126 brouard 3252: /*************** transition probabilities ***************/
3253:
3254: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3255: {
1.138 brouard 3256: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3257: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3258: model to the ncovmodel covariates (including constant and age).
3259: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3260: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3261: ncth covariate in the global vector x is given by the formula:
3262: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3263: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3264: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3265: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3266: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3267: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3268: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3269: */
3270: double s1, lnpijopii;
1.126 brouard 3271: /*double t34;*/
1.164 brouard 3272: int i,j, nc, ii, jj;
1.126 brouard 3273:
1.223 brouard 3274: for(i=1; i<= nlstate; i++){
3275: for(j=1; j<i;j++){
3276: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3277: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3278: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3279: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3280: }
3281: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3282: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3283: }
3284: for(j=i+1; j<=nlstate+ndeath;j++){
3285: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3286: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3287: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3288: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3289: }
3290: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3291: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3292: }
3293: }
1.218 brouard 3294:
1.223 brouard 3295: for(i=1; i<= nlstate; i++){
3296: s1=0;
3297: for(j=1; j<i; j++){
1.339 brouard 3298: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3299: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3300: }
3301: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3302: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3303: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3304: }
3305: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3306: ps[i][i]=1./(s1+1.);
3307: /* Computing other pijs */
3308: for(j=1; j<i; j++)
1.325 brouard 3309: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3310: for(j=i+1; j<=nlstate+ndeath; j++)
3311: ps[i][j]= exp(ps[i][j])*ps[i][i];
3312: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3313: } /* end i */
1.218 brouard 3314:
1.223 brouard 3315: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3316: for(jj=1; jj<= nlstate+ndeath; jj++){
3317: ps[ii][jj]=0;
3318: ps[ii][ii]=1;
3319: }
3320: }
1.294 brouard 3321:
3322:
1.223 brouard 3323: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3324: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3325: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3326: /* } */
3327: /* printf("\n "); */
3328: /* } */
3329: /* printf("\n ");printf("%lf ",cov[2]);*/
3330: /*
3331: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3332: goto end;*/
1.266 brouard 3333: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3334: }
3335:
1.218 brouard 3336: /*************** backward transition probabilities ***************/
3337:
3338: /* 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 ) */
3339: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3340: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3341: {
1.302 brouard 3342: /* 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 3343: * 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 3344: */
1.218 brouard 3345: int i, ii, j,k;
1.222 brouard 3346:
3347: double **out, **pmij();
3348: double sumnew=0.;
1.218 brouard 3349: double agefin;
1.292 brouard 3350: 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 3351: double **dnewm, **dsavm, **doldm;
3352: double **bbmij;
3353:
1.218 brouard 3354: doldm=ddoldms; /* global pointers */
1.222 brouard 3355: dnewm=ddnewms;
3356: dsavm=ddsavms;
1.318 brouard 3357:
3358: /* Debug */
3359: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3360: agefin=cov[2];
1.268 brouard 3361: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3362: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3363: the observed prevalence (with this covariate ij) at beginning of transition */
3364: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3365:
3366: /* P_x */
1.325 brouard 3367: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3368: /* outputs pmmij which is a stochastic matrix in row */
3369:
3370: /* Diag(w_x) */
1.292 brouard 3371: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3372: sumnew=0.;
1.269 brouard 3373: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3374: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3375: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3376: sumnew+=prevacurrent[(int)agefin][ii][ij];
3377: }
3378: if(sumnew >0.01){ /* At least some value in the prevalence */
3379: for (ii=1;ii<=nlstate+ndeath;ii++){
3380: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3381: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3382: }
3383: }else{
3384: for (ii=1;ii<=nlstate+ndeath;ii++){
3385: for (j=1;j<=nlstate+ndeath;j++)
3386: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3387: }
3388: /* if(sumnew <0.9){ */
3389: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3390: /* } */
3391: }
3392: k3=0.0; /* We put the last diagonal to 0 */
3393: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3394: doldm[ii][ii]= k3;
3395: }
3396: /* End doldm, At the end doldm is diag[(w_i)] */
3397:
1.292 brouard 3398: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3399: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3400:
1.292 brouard 3401: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3402: /* 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 3403: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3404: sumnew=0.;
1.222 brouard 3405: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3406: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3407: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3408: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3409: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3410: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3411: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3412: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3413: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3414: /* }else */
1.268 brouard 3415: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3416: } /*End ii */
3417: } /* 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 */
3418:
1.292 brouard 3419: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3420: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3421: /* end bmij */
1.266 brouard 3422: return ps; /*pointer is unchanged */
1.218 brouard 3423: }
1.217 brouard 3424: /*************** transition probabilities ***************/
3425:
1.218 brouard 3426: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3427: {
3428: /* According to parameters values stored in x and the covariate's values stored in cov,
3429: computes the probability to be observed in state j being in state i by appying the
3430: model to the ncovmodel covariates (including constant and age).
3431: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3432: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3433: ncth covariate in the global vector x is given by the formula:
3434: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3435: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3436: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3437: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3438: Outputs ps[i][j] the probability to be observed in j being in j according to
3439: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3440: */
3441: double s1, lnpijopii;
3442: /*double t34;*/
3443: int i,j, nc, ii, jj;
3444:
1.234 brouard 3445: for(i=1; i<= nlstate; i++){
3446: for(j=1; j<i;j++){
3447: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3448: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3449: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3450: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3451: }
3452: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3453: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3454: }
3455: for(j=i+1; j<=nlstate+ndeath;j++){
3456: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3457: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3458: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3459: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3460: }
3461: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3462: }
3463: }
3464:
3465: for(i=1; i<= nlstate; i++){
3466: s1=0;
3467: for(j=1; j<i; j++){
3468: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3469: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3470: }
3471: for(j=i+1; j<=nlstate+ndeath; j++){
3472: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3473: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3474: }
3475: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3476: ps[i][i]=1./(s1+1.);
3477: /* Computing other pijs */
3478: for(j=1; j<i; j++)
3479: ps[i][j]= exp(ps[i][j])*ps[i][i];
3480: for(j=i+1; j<=nlstate+ndeath; j++)
3481: ps[i][j]= exp(ps[i][j])*ps[i][i];
3482: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3483: } /* end i */
3484:
3485: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3486: for(jj=1; jj<= nlstate+ndeath; jj++){
3487: ps[ii][jj]=0;
3488: ps[ii][ii]=1;
3489: }
3490: }
1.296 brouard 3491: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3492: for(jj=1; jj<= nlstate+ndeath; jj++){
3493: s1=0.;
3494: for(ii=1; ii<= nlstate+ndeath; ii++){
3495: s1+=ps[ii][jj];
3496: }
3497: for(ii=1; ii<= nlstate; ii++){
3498: ps[ii][jj]=ps[ii][jj]/s1;
3499: }
3500: }
3501: /* Transposition */
3502: for(jj=1; jj<= nlstate+ndeath; jj++){
3503: for(ii=jj; ii<= nlstate+ndeath; ii++){
3504: s1=ps[ii][jj];
3505: ps[ii][jj]=ps[jj][ii];
3506: ps[jj][ii]=s1;
3507: }
3508: }
3509: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3510: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3511: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3512: /* } */
3513: /* printf("\n "); */
3514: /* } */
3515: /* printf("\n ");printf("%lf ",cov[2]);*/
3516: /*
3517: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3518: goto end;*/
3519: return ps;
1.217 brouard 3520: }
3521:
3522:
1.126 brouard 3523: /**************** Product of 2 matrices ******************/
3524:
1.145 brouard 3525: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3526: {
3527: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3528: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3529: /* in, b, out are matrice of pointers which should have been initialized
3530: before: only the contents of out is modified. The function returns
3531: a pointer to pointers identical to out */
1.145 brouard 3532: int i, j, k;
1.126 brouard 3533: for(i=nrl; i<= nrh; i++)
1.145 brouard 3534: for(k=ncolol; k<=ncoloh; k++){
3535: out[i][k]=0.;
3536: for(j=ncl; j<=nch; j++)
3537: out[i][k] +=in[i][j]*b[j][k];
3538: }
1.126 brouard 3539: return out;
3540: }
3541:
3542:
3543: /************* Higher Matrix Product ***************/
3544:
1.235 brouard 3545: 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 3546: {
1.336 brouard 3547: /* Already optimized with precov.
3548: 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 3549: 'nhstepm*hstepm*stepm' months (i.e. until
3550: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3551: nhstepm*hstepm matrices.
3552: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3553: (typically every 2 years instead of every month which is too big
3554: for the memory).
3555: Model is determined by parameters x and covariates have to be
3556: included manually here.
3557:
3558: */
3559:
1.330 brouard 3560: int i, j, d, h, k, k1;
1.131 brouard 3561: double **out, cov[NCOVMAX+1];
1.126 brouard 3562: double **newm;
1.187 brouard 3563: double agexact;
1.214 brouard 3564: double agebegin, ageend;
1.126 brouard 3565:
3566: /* Hstepm could be zero and should return the unit matrix */
3567: for (i=1;i<=nlstate+ndeath;i++)
3568: for (j=1;j<=nlstate+ndeath;j++){
3569: oldm[i][j]=(i==j ? 1.0 : 0.0);
3570: po[i][j][0]=(i==j ? 1.0 : 0.0);
3571: }
3572: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3573: for(h=1; h <=nhstepm; h++){
3574: for(d=1; d <=hstepm; d++){
3575: newm=savm;
3576: /* Covariates have to be included here again */
3577: cov[1]=1.;
1.214 brouard 3578: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3579: cov[2]=agexact;
1.319 brouard 3580: if(nagesqr==1){
1.227 brouard 3581: cov[3]= agexact*agexact;
1.319 brouard 3582: }
1.330 brouard 3583: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3584: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3585: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.332 brouard 3586: if(Typevar[k1]==1){ /* A product with age */
3587: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3588: }else{
3589: cov[2+nagesqr+k1]=precov[nres][k1];
3590: }
3591: }/* End of loop on model equation */
3592: /* Old code */
3593: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3594: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3595: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3596: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3597: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3598: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3599: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3600: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3601: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3602: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3603: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3604: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3605: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3606: /* /\* 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]])); *\/ */
3607: /* 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); */
3608: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3609: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3610: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3611: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3612: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3613: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3614: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3615: /* 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]]); */
3616: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3617: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3618: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3619: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3620: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3621: /* 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]); */
3622: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3623:
3624: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3625: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3626: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3627: /* /\* *\/ */
1.330 brouard 3628: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3629: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3630: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3631: /* /\*cptcovage=2 1 2 *\/ */
3632: /* /\*Tage[k]= 5 8 *\/ */
3633: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3634: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3635: /* 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]]); */
3636: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3637: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3638: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3639: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3640: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3641: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3642: /* /\* 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); *\/ */
3643: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3644: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3645: /* /\* } *\/ */
3646: /* /\* 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]); *\/ */
3647: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3648: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3649: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3650: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3651: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3652: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3653: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3654: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3655: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3656:
1.332 brouard 3657: /* /\* 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])]); *\/ */
3658: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3659: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3660: /* 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]]); */
3661: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3662:
3663: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3664: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3665: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3666: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3667: /* /\* 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]])]; *\/ */
3668: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3669: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3670: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3671: /* /\* } *\/ */
3672: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3673: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3674: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3675: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3676: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3677: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3678: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3679: /* /\* } *\/ */
3680: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3681: /* }/\*end of products *\/ */
3682: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3683: /* for (k=1; k<=cptcovn;k++) */
3684: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3685: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3686: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3687: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3688: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3689:
3690:
1.126 brouard 3691: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3692: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3693: /* right multiplication of oldm by the current matrix */
1.126 brouard 3694: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3695: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3696: /* if((int)age == 70){ */
3697: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3698: /* for(i=1; i<=nlstate+ndeath; i++) { */
3699: /* printf("%d pmmij ",i); */
3700: /* for(j=1;j<=nlstate+ndeath;j++) { */
3701: /* printf("%f ",pmmij[i][j]); */
3702: /* } */
3703: /* printf(" oldm "); */
3704: /* for(j=1;j<=nlstate+ndeath;j++) { */
3705: /* printf("%f ",oldm[i][j]); */
3706: /* } */
3707: /* printf("\n"); */
3708: /* } */
3709: /* } */
1.126 brouard 3710: savm=oldm;
3711: oldm=newm;
3712: }
3713: for(i=1; i<=nlstate+ndeath; i++)
3714: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3715: po[i][j][h]=newm[i][j];
3716: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3717: }
1.128 brouard 3718: /*printf("h=%d ",h);*/
1.126 brouard 3719: } /* end h */
1.267 brouard 3720: /* printf("\n H=%d \n",h); */
1.126 brouard 3721: return po;
3722: }
3723:
1.217 brouard 3724: /************* Higher Back Matrix Product ***************/
1.218 brouard 3725: /* 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 3726: 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 3727: {
1.332 brouard 3728: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3729: computes the transition matrix starting at age 'age' over
1.217 brouard 3730: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3731: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3732: nhstepm*hstepm matrices.
3733: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3734: (typically every 2 years instead of every month which is too big
1.217 brouard 3735: for the memory).
1.218 brouard 3736: Model is determined by parameters x and covariates have to be
1.266 brouard 3737: included manually here. Then we use a call to bmij(x and cov)
3738: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3739: */
1.217 brouard 3740:
1.332 brouard 3741: int i, j, d, h, k, k1;
1.266 brouard 3742: double **out, cov[NCOVMAX+1], **bmij();
3743: double **newm, ***newmm;
1.217 brouard 3744: double agexact;
3745: double agebegin, ageend;
1.222 brouard 3746: double **oldm, **savm;
1.217 brouard 3747:
1.266 brouard 3748: newmm=po; /* To be saved */
3749: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3750: /* Hstepm could be zero and should return the unit matrix */
3751: for (i=1;i<=nlstate+ndeath;i++)
3752: for (j=1;j<=nlstate+ndeath;j++){
3753: oldm[i][j]=(i==j ? 1.0 : 0.0);
3754: po[i][j][0]=(i==j ? 1.0 : 0.0);
3755: }
3756: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3757: for(h=1; h <=nhstepm; h++){
3758: for(d=1; d <=hstepm; d++){
3759: newm=savm;
3760: /* Covariates have to be included here again */
3761: cov[1]=1.;
1.271 brouard 3762: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3763: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3764: /* Debug */
3765: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3766: cov[2]=agexact;
1.332 brouard 3767: if(nagesqr==1){
1.222 brouard 3768: cov[3]= agexact*agexact;
1.332 brouard 3769: }
3770: /** New code */
3771: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3772: if(Typevar[k1]==1){ /* A product with age */
3773: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3774: }else{
1.332 brouard 3775: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3776: }
1.332 brouard 3777: }/* End of loop on model equation */
3778: /** End of new code */
3779: /** This was old code */
3780: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3781: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3782: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3783: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3784: /* /\* 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)); *\/ */
3785: /* } */
3786: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3787: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3788: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3789: /* /\* 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]); *\/ */
3790: /* } */
3791: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3792: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3793: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3794: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3795: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3796: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3797: /* } */
3798: /* /\* 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]); *\/ */
3799: /* } */
3800: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3801: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3802: /* if(Dummy[Tvard[k][1]]==0){ */
3803: /* if(Dummy[Tvard[k][2]]==0){ */
3804: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3805: /* }else{ */
3806: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3807: /* } */
3808: /* }else{ */
3809: /* if(Dummy[Tvard[k][2]]==0){ */
3810: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3811: /* }else{ */
3812: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3813: /* } */
3814: /* } */
3815: /* } */
3816: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3817: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3818: /** End of old code */
3819:
1.218 brouard 3820: /* Careful transposed matrix */
1.266 brouard 3821: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3822: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3823: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3824: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3825: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3826: /* if((int)age == 70){ */
3827: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3828: /* for(i=1; i<=nlstate+ndeath; i++) { */
3829: /* printf("%d pmmij ",i); */
3830: /* for(j=1;j<=nlstate+ndeath;j++) { */
3831: /* printf("%f ",pmmij[i][j]); */
3832: /* } */
3833: /* printf(" oldm "); */
3834: /* for(j=1;j<=nlstate+ndeath;j++) { */
3835: /* printf("%f ",oldm[i][j]); */
3836: /* } */
3837: /* printf("\n"); */
3838: /* } */
3839: /* } */
3840: savm=oldm;
3841: oldm=newm;
3842: }
3843: for(i=1; i<=nlstate+ndeath; i++)
3844: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3845: po[i][j][h]=newm[i][j];
1.268 brouard 3846: /* if(h==nhstepm) */
3847: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3848: }
1.268 brouard 3849: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3850: } /* end h */
1.268 brouard 3851: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3852: return po;
3853: }
3854:
3855:
1.162 brouard 3856: #ifdef NLOPT
3857: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3858: double fret;
3859: double *xt;
3860: int j;
3861: myfunc_data *d2 = (myfunc_data *) pd;
3862: /* xt = (p1-1); */
3863: xt=vector(1,n);
3864: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3865:
3866: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3867: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3868: printf("Function = %.12lf ",fret);
3869: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3870: printf("\n");
3871: free_vector(xt,1,n);
3872: return fret;
3873: }
3874: #endif
1.126 brouard 3875:
3876: /*************** log-likelihood *************/
3877: double func( double *x)
3878: {
1.336 brouard 3879: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3880: int ioffset=0;
1.339 brouard 3881: int ipos=0,iposold=0,ncovv=0;
3882:
1.340 ! brouard 3883: double cotvarv, cotvarvold;
1.226 brouard 3884: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3885: double **out;
3886: double lli; /* Individual log likelihood */
3887: int s1, s2;
1.228 brouard 3888: 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 3889:
1.226 brouard 3890: double bbh, survp;
3891: double agexact;
1.336 brouard 3892: double agebegin, ageend;
1.226 brouard 3893: /*extern weight */
3894: /* We are differentiating ll according to initial status */
3895: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3896: /*for(i=1;i<imx;i++)
3897: printf(" %d\n",s[4][i]);
3898: */
1.162 brouard 3899:
1.226 brouard 3900: ++countcallfunc;
1.162 brouard 3901:
1.226 brouard 3902: cov[1]=1.;
1.126 brouard 3903:
1.226 brouard 3904: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3905: ioffset=0;
1.226 brouard 3906: if(mle==1){
3907: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3908: /* Computes the values of the ncovmodel covariates of the model
3909: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3910: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3911: to be observed in j being in i according to the model.
3912: */
1.243 brouard 3913: ioffset=2+nagesqr ;
1.233 brouard 3914: /* Fixed */
1.336 brouard 3915: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummu or quant or prod */
1.319 brouard 3916: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3917: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3918: /* 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 3919: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 3920: 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 3921: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3922: }
1.226 brouard 3923: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3924: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3925: has been calculated etc */
3926: /* For an individual i, wav[i] gives the number of effective waves */
3927: /* We compute the contribution to Likelihood of each effective transition
3928: mw[mi][i] is real wave of the mi th effectve wave */
3929: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3930: s2=s[mw[mi+1][i]][i];
1.340 ! brouard 3931: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv-ncovcol-nqv][i] because (-ncovcol-nqv) in the data
1.226 brouard 3932: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3933: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3934: */
1.336 brouard 3935: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
3936: /* Wave varying (but not age varying) */
1.339 brouard 3937: /* 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*\/ */
3938: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
3939: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
3940: /* } */
1.340 ! brouard 3941: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
! 3942: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
! 3943: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
! 3944: if(TvarFind[itv]==0){ /* Not a fixed covariate */
! 3945: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]-ncovcol-nqv][i]; /* cotvar[wav][ntv+iv][i] */
! 3946: }else{ /* fixed covariate */
! 3947: cotvarv=covar[Tvar[TvarFind[itv]]][i];
! 3948: }
1.339 brouard 3949: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 ! brouard 3950: cotvarvold=cotvarv;
! 3951: }else{ /* A second product */
! 3952: cotvarv=cotvarv*cotvarvold;
1.339 brouard 3953: }
3954: iposold=ipos;
1.340 ! brouard 3955: cov[ioffset+ipos]=cotvarv;
1.234 brouard 3956: }
1.339 brouard 3957: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
3958: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3959: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3960: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3961: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3962: /* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][TmodelInvind[itv]][i]=%f\n", i, mi, itv, TmodelInvind[itv],cotvar[mw[mi][i]][TmodelInvind[itv]][i]); */
3963: /* } */
3964: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
3965: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3966: /* /\* 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]); *\/ */
3967: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
3968: /* } */
3969: /* for products of time varying to be done */
1.234 brouard 3970: for (ii=1;ii<=nlstate+ndeath;ii++)
3971: for (j=1;j<=nlstate+ndeath;j++){
3972: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3973: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3974: }
1.336 brouard 3975:
3976: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3977: 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 3978: for(d=0; d<dh[mi][i]; d++){
3979: newm=savm;
3980: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3981: cov[2]=agexact;
3982: if(nagesqr==1)
3983: cov[3]= agexact*agexact; /* Should be changed here */
3984: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3985: if(!FixedV[Tvar[Tage[kk]]])
3986: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3987: else
1.340 ! brouard 3988: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact; /* -ntv because cotvar starts at ntv */
1.234 brouard 3989: }
3990: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3991: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3992: savm=oldm;
3993: oldm=newm;
3994: } /* end mult */
3995:
3996: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3997: /* But now since version 0.9 we anticipate for bias at large stepm.
3998: * If stepm is larger than one month (smallest stepm) and if the exact delay
3999: * (in months) between two waves is not a multiple of stepm, we rounded to
4000: * the nearest (and in case of equal distance, to the lowest) interval but now
4001: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4002: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4003: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4004: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4005: * -stepm/2 to stepm/2 .
4006: * For stepm=1 the results are the same as for previous versions of Imach.
4007: * For stepm > 1 the results are less biased than in previous versions.
4008: */
1.234 brouard 4009: s1=s[mw[mi][i]][i];
4010: s2=s[mw[mi+1][i]][i];
4011: bbh=(double)bh[mi][i]/(double)stepm;
4012: /* bias bh is positive if real duration
4013: * is higher than the multiple of stepm and negative otherwise.
4014: */
4015: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4016: if( s2 > nlstate){
4017: /* i.e. if s2 is a death state and if the date of death is known
4018: then the contribution to the likelihood is the probability to
4019: die between last step unit time and current step unit time,
4020: which is also equal to probability to die before dh
4021: minus probability to die before dh-stepm .
4022: In version up to 0.92 likelihood was computed
4023: as if date of death was unknown. Death was treated as any other
4024: health state: the date of the interview describes the actual state
4025: and not the date of a change in health state. The former idea was
4026: to consider that at each interview the state was recorded
4027: (healthy, disable or death) and IMaCh was corrected; but when we
4028: introduced the exact date of death then we should have modified
4029: the contribution of an exact death to the likelihood. This new
4030: contribution is smaller and very dependent of the step unit
4031: stepm. It is no more the probability to die between last interview
4032: and month of death but the probability to survive from last
4033: interview up to one month before death multiplied by the
4034: probability to die within a month. Thanks to Chris
4035: Jackson for correcting this bug. Former versions increased
4036: mortality artificially. The bad side is that we add another loop
4037: which slows down the processing. The difference can be up to 10%
4038: lower mortality.
4039: */
4040: /* If, at the beginning of the maximization mostly, the
4041: cumulative probability or probability to be dead is
4042: constant (ie = 1) over time d, the difference is equal to
4043: 0. out[s1][3] = savm[s1][3]: probability, being at state
4044: s1 at precedent wave, to be dead a month before current
4045: wave is equal to probability, being at state s1 at
4046: precedent wave, to be dead at mont of the current
4047: wave. Then the observed probability (that this person died)
4048: is null according to current estimated parameter. In fact,
4049: it should be very low but not zero otherwise the log go to
4050: infinity.
4051: */
1.183 brouard 4052: /* #ifdef INFINITYORIGINAL */
4053: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4054: /* #else */
4055: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4056: /* lli=log(mytinydouble); */
4057: /* else */
4058: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4059: /* #endif */
1.226 brouard 4060: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4061:
1.226 brouard 4062: } else if ( s2==-1 ) { /* alive */
4063: for (j=1,survp=0. ; j<=nlstate; j++)
4064: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4065: /*survp += out[s1][j]; */
4066: lli= log(survp);
4067: }
1.336 brouard 4068: /* else if (s2==-4) { */
4069: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4070: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4071: /* lli= log(survp); */
4072: /* } */
4073: /* else if (s2==-5) { */
4074: /* for (j=1,survp=0. ; j<=2; j++) */
4075: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4076: /* lli= log(survp); */
4077: /* } */
1.226 brouard 4078: else{
4079: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4080: /* 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 */
4081: }
4082: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4083: /*if(lli ==000.0)*/
1.340 ! brouard 4084: /* 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 4085: ipmx +=1;
4086: sw += weight[i];
4087: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4088: /* if (lli < log(mytinydouble)){ */
4089: /* 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); */
4090: /* 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]); */
4091: /* } */
4092: } /* end of wave */
4093: } /* end of individual */
4094: } else if(mle==2){
4095: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4096: ioffset=2+nagesqr ;
4097: for (k=1; k<=ncovf;k++)
4098: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4099: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4100: for(k=1; k <= ncovv ; k++){
1.340 ! brouard 4101: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; /* Cotvar starts at ntv */
1.319 brouard 4102: }
1.226 brouard 4103: for (ii=1;ii<=nlstate+ndeath;ii++)
4104: for (j=1;j<=nlstate+ndeath;j++){
4105: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4106: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4107: }
4108: for(d=0; d<=dh[mi][i]; d++){
4109: newm=savm;
4110: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4111: cov[2]=agexact;
4112: if(nagesqr==1)
4113: cov[3]= agexact*agexact;
4114: for (kk=1; kk<=cptcovage;kk++) {
4115: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4116: }
4117: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4118: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4119: savm=oldm;
4120: oldm=newm;
4121: } /* end mult */
4122:
4123: s1=s[mw[mi][i]][i];
4124: s2=s[mw[mi+1][i]][i];
4125: bbh=(double)bh[mi][i]/(double)stepm;
4126: 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 */
4127: ipmx +=1;
4128: sw += weight[i];
4129: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4130: } /* end of wave */
4131: } /* end of individual */
4132: } else if(mle==3){ /* exponential inter-extrapolation */
4133: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4134: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4135: for(mi=1; mi<= wav[i]-1; mi++){
4136: for (ii=1;ii<=nlstate+ndeath;ii++)
4137: for (j=1;j<=nlstate+ndeath;j++){
4138: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4139: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4140: }
4141: for(d=0; d<dh[mi][i]; d++){
4142: newm=savm;
4143: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4144: cov[2]=agexact;
4145: if(nagesqr==1)
4146: cov[3]= agexact*agexact;
4147: for (kk=1; kk<=cptcovage;kk++) {
1.340 ! brouard 4148: if(!FixedV[Tvar[Tage[kk]]])
! 4149: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
! 4150: else
! 4151: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact; /* -ntv because cotvar starts at ntv */
1.226 brouard 4152: }
4153: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4154: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4155: savm=oldm;
4156: oldm=newm;
4157: } /* end mult */
4158:
4159: s1=s[mw[mi][i]][i];
4160: s2=s[mw[mi+1][i]][i];
4161: bbh=(double)bh[mi][i]/(double)stepm;
4162: 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 */
4163: ipmx +=1;
4164: sw += weight[i];
4165: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4166: } /* end of wave */
4167: } /* end of individual */
4168: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4169: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4170: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4171: for(mi=1; mi<= wav[i]-1; mi++){
4172: for (ii=1;ii<=nlstate+ndeath;ii++)
4173: for (j=1;j<=nlstate+ndeath;j++){
4174: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4175: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4176: }
4177: for(d=0; d<dh[mi][i]; d++){
4178: newm=savm;
4179: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4180: cov[2]=agexact;
4181: if(nagesqr==1)
4182: cov[3]= agexact*agexact;
4183: for (kk=1; kk<=cptcovage;kk++) {
4184: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4185: }
1.126 brouard 4186:
1.226 brouard 4187: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4188: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4189: savm=oldm;
4190: oldm=newm;
4191: } /* end mult */
4192:
4193: s1=s[mw[mi][i]][i];
4194: s2=s[mw[mi+1][i]][i];
4195: if( s2 > nlstate){
4196: lli=log(out[s1][s2] - savm[s1][s2]);
4197: } else if ( s2==-1 ) { /* alive */
4198: for (j=1,survp=0. ; j<=nlstate; j++)
4199: survp += out[s1][j];
4200: lli= log(survp);
4201: }else{
4202: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4203: }
4204: ipmx +=1;
4205: sw += weight[i];
4206: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.340 ! brouard 4207: /* printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]); */
1.226 brouard 4208: } /* end of wave */
4209: } /* end of individual */
4210: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4211: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4212: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4213: for(mi=1; mi<= wav[i]-1; mi++){
4214: for (ii=1;ii<=nlstate+ndeath;ii++)
4215: for (j=1;j<=nlstate+ndeath;j++){
4216: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4217: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4218: }
4219: for(d=0; d<dh[mi][i]; d++){
4220: newm=savm;
4221: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4222: cov[2]=agexact;
4223: if(nagesqr==1)
4224: cov[3]= agexact*agexact;
4225: for (kk=1; kk<=cptcovage;kk++) {
1.340 ! brouard 4226: if(!FixedV[Tvar[Tage[kk]]])
! 4227: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
! 4228: else
! 4229: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact; /* -ntv because cotvar starts at ntv */
1.226 brouard 4230: }
1.126 brouard 4231:
1.226 brouard 4232: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4233: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4234: savm=oldm;
4235: oldm=newm;
4236: } /* end mult */
4237:
4238: s1=s[mw[mi][i]][i];
4239: s2=s[mw[mi+1][i]][i];
4240: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4241: ipmx +=1;
4242: sw += weight[i];
4243: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4244: /*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]);*/
4245: } /* end of wave */
4246: } /* end of individual */
4247: } /* End of if */
4248: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4249: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4250: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4251: return -l;
1.126 brouard 4252: }
4253:
4254: /*************** log-likelihood *************/
4255: double funcone( double *x)
4256: {
1.228 brouard 4257: /* Same as func but slower because of a lot of printf and if */
1.335 brouard 4258: int i, ii, j, k, mi, d, kk, kf=0;
1.228 brouard 4259: int ioffset=0;
1.339 brouard 4260: int ipos=0,iposold=0,ncovv=0;
4261:
1.340 ! brouard 4262: double cotvarv, cotvarvold;
1.131 brouard 4263: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4264: double **out;
4265: double lli; /* Individual log likelihood */
4266: double llt;
4267: int s1, s2;
1.228 brouard 4268: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4269:
1.126 brouard 4270: double bbh, survp;
1.187 brouard 4271: double agexact;
1.214 brouard 4272: double agebegin, ageend;
1.126 brouard 4273: /*extern weight */
4274: /* We are differentiating ll according to initial status */
4275: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4276: /*for(i=1;i<imx;i++)
4277: printf(" %d\n",s[4][i]);
4278: */
4279: cov[1]=1.;
4280:
4281: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4282: ioffset=0;
4283: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4284: /* Computes the values of the ncovmodel covariates of the model
4285: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4286: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4287: to be observed in j being in i according to the model.
4288: */
1.243 brouard 4289: /* ioffset=2+nagesqr+cptcovage; */
4290: ioffset=2+nagesqr;
1.232 brouard 4291: /* Fixed */
1.224 brouard 4292: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4293: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.335 brouard 4294: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 brouard 4295: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4296: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4297: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4298: 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 4299: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4300: /* cov[2+6]=covar[Tvar[6]][i]; */
4301: /* cov[2+6]=covar[2][i]; V2 */
4302: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4303: /* cov[2+7]=covar[Tvar[7]][i]; */
4304: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4305: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4306: /* cov[2+9]=covar[Tvar[9]][i]; */
4307: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4308: }
1.336 brouard 4309: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4310: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4311: has been calculated etc */
4312: /* For an individual i, wav[i] gives the number of effective waves */
4313: /* We compute the contribution to Likelihood of each effective transition
4314: mw[mi][i] is real wave of the mi th effectve wave */
4315: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4316: s2=s[mw[mi+1][i]][i];
1.340 ! brouard 4317: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][iv][i]
1.336 brouard 4318: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4319: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4320: */
4321: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4322: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4323: /* 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?)*\/ */
4324: /* } */
1.231 brouard 4325: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4326: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4327: /* } */
1.225 brouard 4328:
1.233 brouard 4329:
4330: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4331: /* 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 */
4332: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4333: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4334: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4335: /* } */
4336:
4337: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4338: /* model V1+V3+age*V1+age*V3+V1*V3 */
4339: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4340: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4341: /* We need the position of the time varying or product in the model */
4342: /* 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 */
4343: /* TvarVV gives the variable name */
1.340 ! brouard 4344: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
! 4345: * k= 1 2 3 4 5 6 7 8 9
! 4346: * varying 1 2 3 4 5
! 4347: * ncovv 1 2 3 4 5 6 7 8
! 4348: * TvarVV V3 5 1 3 3 5 1 5
! 4349: * TvarVVind 2 3 7 7 8 8 9 9
! 4350: * TvarFind[k] 1 0 0 0 0 0 0 0 0
! 4351: * cotvar starts at ntv=2 (because of V3 V4)
! 4352: */
! 4353: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
! 4354: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
! 4355: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
! 4356: if(TvarFind[itv]==0){ /* Not a fixed covariate */
! 4357: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]-ncovcol-nqv][i]; /* cotvar[wav][ntv+iv][i] */
! 4358: }else{ /* fixed covariate */
! 4359: cotvarv=covar[Tvar[TvarFind[itv]]][i];
! 4360: }
1.339 brouard 4361: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 ! brouard 4362: cotvarvold=cotvarv;
! 4363: }else{ /* A second product */
! 4364: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4365: }
4366: iposold=ipos;
1.340 ! brouard 4367: cov[ioffset+ipos]=cotvarv;
1.339 brouard 4368: /* For products */
4369: }
4370: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4371: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4372: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4373: /* /\* 1 2 3 4 5 *\/ */
4374: /* /\*itv 1 *\/ */
4375: /* /\* TvarVInd[1]= 2 *\/ */
4376: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4377: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4378: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4379: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4380: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4381: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4382: /* /\* 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]); *\/ */
4383: /* } */
1.232 brouard 4384: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4385: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4386: /* /\* 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]); *\/ */
4387: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4388: /* } */
1.126 brouard 4389: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4390: for (j=1;j<=nlstate+ndeath;j++){
4391: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4392: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4393: }
1.214 brouard 4394:
4395: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4396: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4397: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4398: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4399: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4400: and mw[mi+1][i]. dh depends on stepm.*/
4401: newm=savm;
1.247 brouard 4402: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4403: cov[2]=agexact;
4404: if(nagesqr==1)
4405: cov[3]= agexact*agexact;
4406: for (kk=1; kk<=cptcovage;kk++) {
4407: if(!FixedV[Tvar[Tage[kk]]])
4408: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4409: else
1.340 ! brouard 4410: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.242 brouard 4411: }
4412: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4413: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4414: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4415: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4416: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4417: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4418: savm=oldm;
4419: oldm=newm;
1.126 brouard 4420: } /* end mult */
1.336 brouard 4421: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4422: /* But now since version 0.9 we anticipate for bias at large stepm.
4423: * If stepm is larger than one month (smallest stepm) and if the exact delay
4424: * (in months) between two waves is not a multiple of stepm, we rounded to
4425: * the nearest (and in case of equal distance, to the lowest) interval but now
4426: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4427: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4428: * probability in order to take into account the bias as a fraction of the way
4429: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4430: * -stepm/2 to stepm/2 .
4431: * For stepm=1 the results are the same as for previous versions of Imach.
4432: * For stepm > 1 the results are less biased than in previous versions.
4433: */
1.126 brouard 4434: s1=s[mw[mi][i]][i];
4435: s2=s[mw[mi+1][i]][i];
1.217 brouard 4436: /* if(s2==-1){ */
1.268 brouard 4437: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4438: /* /\* exit(1); *\/ */
4439: /* } */
1.126 brouard 4440: bbh=(double)bh[mi][i]/(double)stepm;
4441: /* bias is positive if real duration
4442: * is higher than the multiple of stepm and negative otherwise.
4443: */
4444: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4445: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4446: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4447: for (j=1,survp=0. ; j<=nlstate; j++)
4448: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4449: lli= log(survp);
1.126 brouard 4450: }else if (mle==1){
1.242 brouard 4451: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4452: } else if(mle==2){
1.242 brouard 4453: 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 4454: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4455: 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 4456: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4457: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4458: } else{ /* mle=0 back to 1 */
1.242 brouard 4459: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4460: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4461: } /* End of if */
4462: ipmx +=1;
4463: sw += weight[i];
4464: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.340 ! brouard 4465: printf("Funcone num[i]=%ld i=%6d V= ", num[i], i);
! 4466: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
! 4467: printf("%g",covar[Tvar[TvarFind[kf]]][i]);
! 4468: }
! 4469: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
! 4470: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
! 4471: if(ipos!=iposold){ /* Not a product or first of a product */
! 4472: printf(" %g",cov[ioffset+ipos]);
! 4473: }else{
! 4474: printf("*");
! 4475: }
! 4476: iposold=ipos;
! 4477: }
! 4478: for (kk=1; kk<=cptcovage;kk++) {
! 4479: if(!FixedV[Tvar[Tage[kk]]])
! 4480: printf(" %g*age",covar[Tvar[Tage[kk]]][i]);
! 4481: else
! 4482: printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]);
! 4483: }
! 4484: printf(" s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.126 brouard 4485: if(globpr){
1.246 brouard 4486: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4487: %11.6f %11.6f %11.6f ", \
1.242 brouard 4488: 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 4489: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.335 brouard 4490: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4491: /* %11.6f %11.6f %11.6f ", \ */
4492: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4493: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4494: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4495: llt +=ll[k]*gipmx/gsw;
4496: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4497: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4498: }
4499: fprintf(ficresilk," %10.6f\n", -llt);
1.335 brouard 4500: /* printf(" %10.6f\n", -llt); */
1.126 brouard 4501: }
1.335 brouard 4502: } /* end of wave */
4503: } /* end of individual */
4504: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4505: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4506: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4507: if(globpr==0){ /* First time we count the contributions and weights */
4508: gipmx=ipmx;
4509: gsw=sw;
4510: }
1.232 brouard 4511: return -l;
1.126 brouard 4512: }
4513:
4514:
4515: /*************** function likelione ***********/
1.292 brouard 4516: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4517: {
4518: /* This routine should help understanding what is done with
4519: the selection of individuals/waves and
4520: to check the exact contribution to the likelihood.
4521: Plotting could be done.
4522: */
4523: int k;
4524:
4525: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4526: strcpy(fileresilk,"ILK_");
1.202 brouard 4527: strcat(fileresilk,fileresu);
1.126 brouard 4528: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4529: printf("Problem with resultfile: %s\n", fileresilk);
4530: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4531: }
1.214 brouard 4532: 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");
4533: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4534: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4535: for(k=1; k<=nlstate; k++)
4536: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4537: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4538: }
4539:
1.292 brouard 4540: *fretone=(*func)(p);
1.126 brouard 4541: if(*globpri !=0){
4542: fclose(ficresilk);
1.205 brouard 4543: if (mle ==0)
4544: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4545: else if(mle >=1)
4546: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4547: 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 4548: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4549:
4550: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4551: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Dot's sizes are related to corresponding weight: <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \
1.208 brouard 4552: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4553: }
1.207 brouard 4554: fprintf(fichtm,"<br>- The function drawn is -2Log(L) in Log scale: by state of origin <a href=\"%s-ori.png\">%s-ori.png</a><br> \
1.204 brouard 4555: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4556: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4557: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4558: fflush(fichtm);
1.205 brouard 4559: }
1.126 brouard 4560: return;
4561: }
4562:
4563:
4564: /*********** Maximum Likelihood Estimation ***************/
4565:
4566: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4567: {
1.319 brouard 4568: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4569: double **xi;
4570: double fret;
4571: double fretone; /* Only one call to likelihood */
4572: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4573:
4574: #ifdef NLOPT
4575: int creturn;
4576: nlopt_opt opt;
4577: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4578: double *lb;
4579: double minf; /* the minimum objective value, upon return */
4580: double * p1; /* Shifted parameters from 0 instead of 1 */
4581: myfunc_data dinst, *d = &dinst;
4582: #endif
4583:
4584:
1.126 brouard 4585: xi=matrix(1,npar,1,npar);
4586: for (i=1;i<=npar;i++)
4587: for (j=1;j<=npar;j++)
4588: xi[i][j]=(i==j ? 1.0 : 0.0);
4589: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4590: strcpy(filerespow,"POW_");
1.126 brouard 4591: strcat(filerespow,fileres);
4592: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4593: printf("Problem with resultfile: %s\n", filerespow);
4594: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4595: }
4596: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4597: for (i=1;i<=nlstate;i++)
4598: for(j=1;j<=nlstate+ndeath;j++)
4599: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4600: fprintf(ficrespow,"\n");
1.162 brouard 4601: #ifdef POWELL
1.319 brouard 4602: #ifdef LINMINORIGINAL
4603: #else /* LINMINORIGINAL */
4604:
4605: flatdir=ivector(1,npar);
4606: for (j=1;j<=npar;j++) flatdir[j]=0;
4607: #endif /*LINMINORIGINAL */
4608:
4609: #ifdef FLATSUP
4610: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4611: /* reorganizing p by suppressing flat directions */
4612: for(i=1, jk=1; i <=nlstate; i++){
4613: for(k=1; k <=(nlstate+ndeath); k++){
4614: if (k != i) {
4615: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4616: if(flatdir[jk]==1){
4617: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4618: }
4619: for(j=1; j <=ncovmodel; j++){
4620: printf("%12.7f ",p[jk]);
4621: jk++;
4622: }
4623: printf("\n");
4624: }
4625: }
4626: }
4627: /* skipping */
4628: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4629: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4630: for(k=1; k <=(nlstate+ndeath); k++){
4631: if (k != i) {
4632: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4633: if(flatdir[jk]==1){
4634: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4635: for(j=1; j <=ncovmodel; jk++,j++){
4636: printf(" p[%d]=%12.7f",jk, p[jk]);
4637: /*q[jjk]=p[jk];*/
4638: }
4639: }else{
4640: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4641: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4642: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4643: /*q[jjk]=p[jk];*/
4644: }
4645: }
4646: printf("\n");
4647: }
4648: fflush(stdout);
4649: }
4650: }
4651: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4652: #else /* FLATSUP */
1.126 brouard 4653: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4654: #endif /* FLATSUP */
4655:
4656: #ifdef LINMINORIGINAL
4657: #else
4658: free_ivector(flatdir,1,npar);
4659: #endif /* LINMINORIGINAL*/
4660: #endif /* POWELL */
1.126 brouard 4661:
1.162 brouard 4662: #ifdef NLOPT
4663: #ifdef NEWUOA
4664: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4665: #else
4666: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4667: #endif
4668: lb=vector(0,npar-1);
4669: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4670: nlopt_set_lower_bounds(opt, lb);
4671: nlopt_set_initial_step1(opt, 0.1);
4672:
4673: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4674: d->function = func;
4675: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4676: nlopt_set_min_objective(opt, myfunc, d);
4677: nlopt_set_xtol_rel(opt, ftol);
4678: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4679: printf("nlopt failed! %d\n",creturn);
4680: }
4681: else {
4682: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4683: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4684: iter=1; /* not equal */
4685: }
4686: nlopt_destroy(opt);
4687: #endif
1.319 brouard 4688: #ifdef FLATSUP
4689: /* npared = npar -flatd/ncovmodel; */
4690: /* xired= matrix(1,npared,1,npared); */
4691: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4692: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4693: /* free_matrix(xire,1,npared,1,npared); */
4694: #else /* FLATSUP */
4695: #endif /* FLATSUP */
1.126 brouard 4696: free_matrix(xi,1,npar,1,npar);
4697: fclose(ficrespow);
1.203 brouard 4698: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4699: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4700: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4701:
4702: }
4703:
4704: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4705: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4706: {
4707: double **a,**y,*x,pd;
1.203 brouard 4708: /* double **hess; */
1.164 brouard 4709: int i, j;
1.126 brouard 4710: int *indx;
4711:
4712: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4713: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4714: void lubksb(double **a, int npar, int *indx, double b[]) ;
4715: void ludcmp(double **a, int npar, int *indx, double *d) ;
4716: double gompertz(double p[]);
1.203 brouard 4717: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4718:
4719: printf("\nCalculation of the hessian matrix. Wait...\n");
4720: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4721: for (i=1;i<=npar;i++){
1.203 brouard 4722: printf("%d-",i);fflush(stdout);
4723: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4724:
4725: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4726:
4727: /* printf(" %f ",p[i]);
4728: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4729: }
4730:
4731: for (i=1;i<=npar;i++) {
4732: for (j=1;j<=npar;j++) {
4733: if (j>i) {
1.203 brouard 4734: printf(".%d-%d",i,j);fflush(stdout);
4735: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4736: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4737:
4738: hess[j][i]=hess[i][j];
4739: /*printf(" %lf ",hess[i][j]);*/
4740: }
4741: }
4742: }
4743: printf("\n");
4744: fprintf(ficlog,"\n");
4745:
4746: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4747: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4748:
4749: a=matrix(1,npar,1,npar);
4750: y=matrix(1,npar,1,npar);
4751: x=vector(1,npar);
4752: indx=ivector(1,npar);
4753: for (i=1;i<=npar;i++)
4754: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4755: ludcmp(a,npar,indx,&pd);
4756:
4757: for (j=1;j<=npar;j++) {
4758: for (i=1;i<=npar;i++) x[i]=0;
4759: x[j]=1;
4760: lubksb(a,npar,indx,x);
4761: for (i=1;i<=npar;i++){
4762: matcov[i][j]=x[i];
4763: }
4764: }
4765:
4766: printf("\n#Hessian matrix#\n");
4767: fprintf(ficlog,"\n#Hessian matrix#\n");
4768: for (i=1;i<=npar;i++) {
4769: for (j=1;j<=npar;j++) {
1.203 brouard 4770: printf("%.6e ",hess[i][j]);
4771: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4772: }
4773: printf("\n");
4774: fprintf(ficlog,"\n");
4775: }
4776:
1.203 brouard 4777: /* printf("\n#Covariance matrix#\n"); */
4778: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4779: /* for (i=1;i<=npar;i++) { */
4780: /* for (j=1;j<=npar;j++) { */
4781: /* printf("%.6e ",matcov[i][j]); */
4782: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4783: /* } */
4784: /* printf("\n"); */
4785: /* fprintf(ficlog,"\n"); */
4786: /* } */
4787:
1.126 brouard 4788: /* Recompute Inverse */
1.203 brouard 4789: /* for (i=1;i<=npar;i++) */
4790: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4791: /* ludcmp(a,npar,indx,&pd); */
4792:
4793: /* printf("\n#Hessian matrix recomputed#\n"); */
4794:
4795: /* for (j=1;j<=npar;j++) { */
4796: /* for (i=1;i<=npar;i++) x[i]=0; */
4797: /* x[j]=1; */
4798: /* lubksb(a,npar,indx,x); */
4799: /* for (i=1;i<=npar;i++){ */
4800: /* y[i][j]=x[i]; */
4801: /* printf("%.3e ",y[i][j]); */
4802: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4803: /* } */
4804: /* printf("\n"); */
4805: /* fprintf(ficlog,"\n"); */
4806: /* } */
4807:
4808: /* Verifying the inverse matrix */
4809: #ifdef DEBUGHESS
4810: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4811:
1.203 brouard 4812: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4813: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4814:
4815: for (j=1;j<=npar;j++) {
4816: for (i=1;i<=npar;i++){
1.203 brouard 4817: printf("%.2f ",y[i][j]);
4818: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4819: }
4820: printf("\n");
4821: fprintf(ficlog,"\n");
4822: }
1.203 brouard 4823: #endif
1.126 brouard 4824:
4825: free_matrix(a,1,npar,1,npar);
4826: free_matrix(y,1,npar,1,npar);
4827: free_vector(x,1,npar);
4828: free_ivector(indx,1,npar);
1.203 brouard 4829: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4830:
4831:
4832: }
4833:
4834: /*************** hessian matrix ****************/
4835: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4836: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4837: int i;
4838: int l=1, lmax=20;
1.203 brouard 4839: double k1,k2, res, fx;
1.132 brouard 4840: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4841: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4842: int k=0,kmax=10;
4843: double l1;
4844:
4845: fx=func(x);
4846: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4847: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4848: l1=pow(10,l);
4849: delts=delt;
4850: for(k=1 ; k <kmax; k=k+1){
4851: delt = delta*(l1*k);
4852: p2[theta]=x[theta] +delt;
1.145 brouard 4853: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4854: p2[theta]=x[theta]-delt;
4855: k2=func(p2)-fx;
4856: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4857: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4858:
1.203 brouard 4859: #ifdef DEBUGHESSII
1.126 brouard 4860: 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);
4861: 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);
4862: #endif
4863: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4864: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4865: k=kmax;
4866: }
4867: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4868: k=kmax; l=lmax*10;
1.126 brouard 4869: }
4870: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4871: delts=delt;
4872: }
1.203 brouard 4873: } /* End loop k */
1.126 brouard 4874: }
4875: delti[theta]=delts;
4876: return res;
4877:
4878: }
4879:
1.203 brouard 4880: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4881: {
4882: int i;
1.164 brouard 4883: int l=1, lmax=20;
1.126 brouard 4884: double k1,k2,k3,k4,res,fx;
1.132 brouard 4885: double p2[MAXPARM+1];
1.203 brouard 4886: int k, kmax=1;
4887: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4888:
4889: int firstime=0;
1.203 brouard 4890:
1.126 brouard 4891: fx=func(x);
1.203 brouard 4892: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4893: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4894: p2[thetai]=x[thetai]+delti[thetai]*k;
4895: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4896: k1=func(p2)-fx;
4897:
1.203 brouard 4898: p2[thetai]=x[thetai]+delti[thetai]*k;
4899: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4900: k2=func(p2)-fx;
4901:
1.203 brouard 4902: p2[thetai]=x[thetai]-delti[thetai]*k;
4903: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4904: k3=func(p2)-fx;
4905:
1.203 brouard 4906: p2[thetai]=x[thetai]-delti[thetai]*k;
4907: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4908: k4=func(p2)-fx;
1.203 brouard 4909: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4910: if(k1*k2*k3*k4 <0.){
1.208 brouard 4911: firstime=1;
1.203 brouard 4912: kmax=kmax+10;
1.208 brouard 4913: }
4914: if(kmax >=10 || firstime ==1){
1.246 brouard 4915: 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);
4916: 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 4917: 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);
4918: 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);
4919: }
4920: #ifdef DEBUGHESSIJ
4921: v1=hess[thetai][thetai];
4922: v2=hess[thetaj][thetaj];
4923: cv12=res;
4924: /* Computing eigen value of Hessian matrix */
4925: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4926: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4927: if ((lc2 <0) || (lc1 <0) ){
4928: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4929: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4930: 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);
4931: 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);
4932: }
1.126 brouard 4933: #endif
4934: }
4935: return res;
4936: }
4937:
1.203 brouard 4938: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4939: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4940: /* { */
4941: /* int i; */
4942: /* int l=1, lmax=20; */
4943: /* double k1,k2,k3,k4,res,fx; */
4944: /* double p2[MAXPARM+1]; */
4945: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4946: /* int k=0,kmax=10; */
4947: /* double l1; */
4948:
4949: /* fx=func(x); */
4950: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4951: /* l1=pow(10,l); */
4952: /* delts=delt; */
4953: /* for(k=1 ; k <kmax; k=k+1){ */
4954: /* delt = delti*(l1*k); */
4955: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4956: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4957: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4958: /* k1=func(p2)-fx; */
4959:
4960: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4961: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4962: /* k2=func(p2)-fx; */
4963:
4964: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4965: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4966: /* k3=func(p2)-fx; */
4967:
4968: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4969: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4970: /* k4=func(p2)-fx; */
4971: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4972: /* #ifdef DEBUGHESSIJ */
4973: /* 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); */
4974: /* 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); */
4975: /* #endif */
4976: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4977: /* k=kmax; */
4978: /* } */
4979: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4980: /* k=kmax; l=lmax*10; */
4981: /* } */
4982: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4983: /* delts=delt; */
4984: /* } */
4985: /* } /\* End loop k *\/ */
4986: /* } */
4987: /* delti[theta]=delts; */
4988: /* return res; */
4989: /* } */
4990:
4991:
1.126 brouard 4992: /************** Inverse of matrix **************/
4993: void ludcmp(double **a, int n, int *indx, double *d)
4994: {
4995: int i,imax,j,k;
4996: double big,dum,sum,temp;
4997: double *vv;
4998:
4999: vv=vector(1,n);
5000: *d=1.0;
5001: for (i=1;i<=n;i++) {
5002: big=0.0;
5003: for (j=1;j<=n;j++)
5004: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5005: if (big == 0.0){
5006: printf(" Singular Hessian matrix at row %d:\n",i);
5007: for (j=1;j<=n;j++) {
5008: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5009: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5010: }
5011: fflush(ficlog);
5012: fclose(ficlog);
5013: nrerror("Singular matrix in routine ludcmp");
5014: }
1.126 brouard 5015: vv[i]=1.0/big;
5016: }
5017: for (j=1;j<=n;j++) {
5018: for (i=1;i<j;i++) {
5019: sum=a[i][j];
5020: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5021: a[i][j]=sum;
5022: }
5023: big=0.0;
5024: for (i=j;i<=n;i++) {
5025: sum=a[i][j];
5026: for (k=1;k<j;k++)
5027: sum -= a[i][k]*a[k][j];
5028: a[i][j]=sum;
5029: if ( (dum=vv[i]*fabs(sum)) >= big) {
5030: big=dum;
5031: imax=i;
5032: }
5033: }
5034: if (j != imax) {
5035: for (k=1;k<=n;k++) {
5036: dum=a[imax][k];
5037: a[imax][k]=a[j][k];
5038: a[j][k]=dum;
5039: }
5040: *d = -(*d);
5041: vv[imax]=vv[j];
5042: }
5043: indx[j]=imax;
5044: if (a[j][j] == 0.0) a[j][j]=TINY;
5045: if (j != n) {
5046: dum=1.0/(a[j][j]);
5047: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5048: }
5049: }
5050: free_vector(vv,1,n); /* Doesn't work */
5051: ;
5052: }
5053:
5054: void lubksb(double **a, int n, int *indx, double b[])
5055: {
5056: int i,ii=0,ip,j;
5057: double sum;
5058:
5059: for (i=1;i<=n;i++) {
5060: ip=indx[i];
5061: sum=b[ip];
5062: b[ip]=b[i];
5063: if (ii)
5064: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5065: else if (sum) ii=i;
5066: b[i]=sum;
5067: }
5068: for (i=n;i>=1;i--) {
5069: sum=b[i];
5070: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5071: b[i]=sum/a[i][i];
5072: }
5073: }
5074:
5075: void pstamp(FILE *fichier)
5076: {
1.196 brouard 5077: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5078: }
5079:
1.297 brouard 5080: void date2dmy(double date,double *day, double *month, double *year){
5081: double yp=0., yp1=0., yp2=0.;
5082:
5083: yp1=modf(date,&yp);/* extracts integral of date in yp and
5084: fractional in yp1 */
5085: *year=yp;
5086: yp2=modf((yp1*12),&yp);
5087: *month=yp;
5088: yp1=modf((yp2*30.5),&yp);
5089: *day=yp;
5090: if(*day==0) *day=1;
5091: if(*month==0) *month=1;
5092: }
5093:
1.253 brouard 5094:
5095:
1.126 brouard 5096: /************ Frequencies ********************/
1.251 brouard 5097: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5098: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5099: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5100: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5101: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5102: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5103: int iind=0, iage=0;
5104: int mi; /* Effective wave */
5105: int first;
5106: double ***freq; /* Frequencies */
1.268 brouard 5107: 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 */
5108: 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 5109: double *meanq, *stdq, *idq;
1.226 brouard 5110: double **meanqt;
5111: double *pp, **prop, *posprop, *pospropt;
5112: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5113: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5114: double agebegin, ageend;
5115:
5116: pp=vector(1,nlstate);
1.251 brouard 5117: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5118: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5119: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5120: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5121: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5122: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5123: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5124: meanqt=matrix(1,lastpass,1,nqtveff);
5125: strcpy(fileresp,"P_");
5126: strcat(fileresp,fileresu);
5127: /*strcat(fileresphtm,fileresu);*/
5128: if((ficresp=fopen(fileresp,"w"))==NULL) {
5129: printf("Problem with prevalence resultfile: %s\n", fileresp);
5130: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5131: exit(0);
5132: }
1.240 brouard 5133:
1.226 brouard 5134: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5135: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5136: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5137: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5138: fflush(ficlog);
5139: exit(70);
5140: }
5141: else{
5142: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5143: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5144: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5145: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5146: }
1.319 brouard 5147: 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 5148:
1.226 brouard 5149: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5150: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5151: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5152: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5153: fflush(ficlog);
5154: exit(70);
1.240 brouard 5155: } else{
1.226 brouard 5156: 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 5157: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5158: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5159: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5160: }
1.319 brouard 5161: 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 5162:
1.253 brouard 5163: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5164: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5165: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5166: j1=0;
1.126 brouard 5167:
1.227 brouard 5168: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5169: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5170: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5171: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5172:
5173:
1.226 brouard 5174: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5175: reference=low_education V1=0,V2=0
5176: med_educ V1=1 V2=0,
5177: high_educ V1=0 V2=1
1.330 brouard 5178: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5179: */
1.249 brouard 5180: dateintsum=0;
5181: k2cpt=0;
5182:
1.253 brouard 5183: if(cptcoveff == 0 )
1.265 brouard 5184: nl=1; /* Constant and age model only */
1.253 brouard 5185: else
5186: nl=2;
1.265 brouard 5187:
5188: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5189: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5190: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5191: * freq[s1][s2][iage] =0.
5192: * Loop on iind
5193: * ++freq[s1][s2][iage] weighted
5194: * end iind
5195: * if covariate and j!0
5196: * headers Variable on one line
5197: * endif cov j!=0
5198: * header of frequency table by age
5199: * Loop on age
5200: * pp[s1]+=freq[s1][s2][iage] weighted
5201: * pos+=freq[s1][s2][iage] weighted
5202: * Loop on s1 initial state
5203: * fprintf(ficresp
5204: * end s1
5205: * end age
5206: * if j!=0 computes starting values
5207: * end compute starting values
5208: * end j1
5209: * end nl
5210: */
1.253 brouard 5211: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5212: if(nj==1)
5213: j=0; /* First pass for the constant */
1.265 brouard 5214: else{
1.335 brouard 5215: 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 5216: }
1.251 brouard 5217: first=1;
1.332 brouard 5218: 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 5219: posproptt=0.;
1.330 brouard 5220: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5221: scanf("%d", i);*/
5222: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5223: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5224: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5225: freq[i][s2][m]=0;
1.251 brouard 5226:
5227: for (i=1; i<=nlstate; i++) {
1.240 brouard 5228: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5229: prop[i][m]=0;
5230: posprop[i]=0;
5231: pospropt[i]=0;
5232: }
1.283 brouard 5233: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5234: idq[z1]=0.;
5235: meanq[z1]=0.;
5236: stdq[z1]=0.;
1.283 brouard 5237: }
5238: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5239: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5240: /* meanqt[m][z1]=0.; */
5241: /* } */
5242: /* } */
1.251 brouard 5243: /* dateintsum=0; */
5244: /* k2cpt=0; */
5245:
1.265 brouard 5246: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5247: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5248: bool=1;
5249: if(j !=0){
5250: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5251: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5252: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5253: /* if(Tvaraff[z1] ==-20){ */
5254: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5255: /* }else if(Tvaraff[z1] ==-10){ */
5256: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5257: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5258: /* 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); */
5259: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5260: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5261: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5262: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5263: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5264: /* 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", */
5265: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5266: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5267: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5268: } /* Onlyf fixed */
5269: } /* end z1 */
1.335 brouard 5270: } /* cptcoveff > 0 */
1.251 brouard 5271: } /* end any */
5272: }/* end j==0 */
1.265 brouard 5273: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5274: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5275: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5276: m=mw[mi][iind];
5277: if(j!=0){
5278: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5279: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5280: if( Fixed[Tmodelind[z1]]==1){
1.340 ! brouard 5281: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /* Good */
1.332 brouard 5282: 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 5283: value is -1, we don't select. It differs from the
5284: constant and age model which counts them. */
5285: bool=0; /* not selected */
5286: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5287: /* i1=Tvaraff[z1]; */
5288: /* i2=TnsdVar[i1]; */
5289: /* i3=nbcode[i1][i2]; */
5290: /* i4=covar[i1][iind]; */
5291: /* if(i4 != i3){ */
5292: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5293: bool=0;
5294: }
5295: }
5296: }
5297: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5298: } /* end j==0 */
5299: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5300: if(bool==1){ /*Selected */
1.251 brouard 5301: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5302: and mw[mi+1][iind]. dh depends on stepm. */
5303: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5304: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5305: if(m >=firstpass && m <=lastpass){
5306: k2=anint[m][iind]+(mint[m][iind]/12.);
5307: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5308: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5309: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5310: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5311: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5312: if (m<lastpass) {
5313: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5314: /* 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]); */
5315: if(s[m][iind]==-1)
5316: 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.));
5317: 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 5318: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5319: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5320: idq[z1]=idq[z1]+weight[iind];
5321: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5322: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5323: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5324: }
1.284 brouard 5325: }
1.251 brouard 5326: /* if((int)agev[m][iind] == 55) */
5327: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5328: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5329: 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 5330: }
1.251 brouard 5331: } /* end if between passes */
5332: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5333: dateintsum=dateintsum+k2; /* on all covariates ?*/
5334: k2cpt++;
5335: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5336: }
1.251 brouard 5337: }else{
5338: bool=1;
5339: }/* end bool 2 */
5340: } /* end m */
1.284 brouard 5341: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5342: /* idq[z1]=idq[z1]+weight[iind]; */
5343: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5344: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5345: /* } */
1.251 brouard 5346: } /* end bool */
5347: } /* end iind = 1 to imx */
1.319 brouard 5348: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5349: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5350:
5351:
5352: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5353: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5354: pstamp(ficresp);
1.335 brouard 5355: if (cptcoveff>0 && j!=0){
1.265 brouard 5356: pstamp(ficresp);
1.251 brouard 5357: printf( "\n#********** Variable ");
5358: fprintf(ficresp, "\n#********** Variable ");
5359: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5360: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5361: fprintf(ficlog, "\n#********** Variable ");
1.340 ! brouard 5362: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5363: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5364: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5365: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5366: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5367: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5368: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5369: }else{
1.330 brouard 5370: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5371: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5372: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5373: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5374: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5375: }
5376: }
5377: printf( "**********\n#");
5378: fprintf(ficresp, "**********\n#");
5379: fprintf(ficresphtm, "**********</h3>\n");
5380: fprintf(ficresphtmfr, "**********</h3>\n");
5381: fprintf(ficlog, "**********\n");
5382: }
1.284 brouard 5383: /*
5384: Printing means of quantitative variables if any
5385: */
5386: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5387: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5388: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5389: if(weightopt==1){
5390: printf(" Weighted mean and standard deviation of");
5391: fprintf(ficlog," Weighted mean and standard deviation of");
5392: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5393: }
1.311 brouard 5394: /* mu = \frac{w x}{\sum w}
5395: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5396: */
5397: 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]));
5398: 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]));
5399: 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 5400: }
5401: /* for (z1=1; z1<= nqtveff; z1++) { */
5402: /* for(m=1;m<=lastpass;m++){ */
5403: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5404: /* } */
5405: /* } */
1.283 brouard 5406:
1.251 brouard 5407: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5408: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5409: fprintf(ficresp, " Age");
1.335 brouard 5410: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5411: 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]]);
5412: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5413: }
1.251 brouard 5414: for(i=1; i<=nlstate;i++) {
1.335 brouard 5415: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5416: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5417: }
1.335 brouard 5418: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5419: fprintf(ficresphtm, "\n");
5420:
5421: /* Header of frequency table by age */
5422: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5423: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5424: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5425: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5426: if(s2!=0 && m!=0)
5427: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5428: }
1.226 brouard 5429: }
1.251 brouard 5430: fprintf(ficresphtmfr, "\n");
5431:
5432: /* For each age */
5433: for(iage=iagemin; iage <= iagemax+3; iage++){
5434: fprintf(ficresphtm,"<tr>");
5435: if(iage==iagemax+1){
5436: fprintf(ficlog,"1");
5437: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5438: }else if(iage==iagemax+2){
5439: fprintf(ficlog,"0");
5440: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5441: }else if(iage==iagemax+3){
5442: fprintf(ficlog,"Total");
5443: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5444: }else{
1.240 brouard 5445: if(first==1){
1.251 brouard 5446: first=0;
5447: printf("See log file for details...\n");
5448: }
5449: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5450: fprintf(ficlog,"Age %d", iage);
5451: }
1.265 brouard 5452: for(s1=1; s1 <=nlstate ; s1++){
5453: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5454: pp[s1] += freq[s1][m][iage];
1.251 brouard 5455: }
1.265 brouard 5456: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5457: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5458: pos += freq[s1][m][iage];
5459: if(pp[s1]>=1.e-10){
1.251 brouard 5460: if(first==1){
1.265 brouard 5461: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5462: }
1.265 brouard 5463: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5464: }else{
5465: if(first==1)
1.265 brouard 5466: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5467: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5468: }
5469: }
5470:
1.265 brouard 5471: for(s1=1; s1 <=nlstate ; s1++){
5472: /* posprop[s1]=0; */
5473: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5474: pp[s1] += freq[s1][m][iage];
5475: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5476:
5477: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5478: pos += pp[s1]; /* pos is the total number of transitions until this age */
5479: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5480: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5481: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5482: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5483: }
5484:
5485: /* Writing ficresp */
1.335 brouard 5486: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5487: if( iage <= iagemax){
5488: fprintf(ficresp," %d",iage);
5489: }
5490: }else if( nj==2){
5491: if( iage <= iagemax){
5492: fprintf(ficresp," %d",iage);
1.335 brouard 5493: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5494: }
1.240 brouard 5495: }
1.265 brouard 5496: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5497: if(pos>=1.e-5){
1.251 brouard 5498: if(first==1)
1.265 brouard 5499: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5500: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5501: }else{
5502: if(first==1)
1.265 brouard 5503: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5504: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5505: }
5506: if( iage <= iagemax){
5507: if(pos>=1.e-5){
1.335 brouard 5508: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5509: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5510: }else if( nj==2){
5511: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5512: }
5513: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5514: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5515: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5516: } else{
1.335 brouard 5517: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5518: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5519: }
1.240 brouard 5520: }
1.265 brouard 5521: pospropt[s1] +=posprop[s1];
5522: } /* end loop s1 */
1.251 brouard 5523: /* pospropt=0.; */
1.265 brouard 5524: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5525: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5526: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5527: if(first==1){
1.265 brouard 5528: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5529: }
1.265 brouard 5530: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5531: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5532: }
1.265 brouard 5533: if(s1!=0 && m!=0)
5534: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5535: }
1.265 brouard 5536: } /* end loop s1 */
1.251 brouard 5537: posproptt=0.;
1.265 brouard 5538: for(s1=1; s1 <=nlstate; s1++){
5539: posproptt += pospropt[s1];
1.251 brouard 5540: }
5541: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5542: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5543: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5544: if(iage <= iagemax)
5545: fprintf(ficresp,"\n");
1.240 brouard 5546: }
1.251 brouard 5547: if(first==1)
5548: printf("Others in log...\n");
5549: fprintf(ficlog,"\n");
5550: } /* end loop age iage */
1.265 brouard 5551:
1.251 brouard 5552: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5553: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5554: if(posproptt < 1.e-5){
1.265 brouard 5555: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5556: }else{
1.265 brouard 5557: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5558: }
1.226 brouard 5559: }
1.251 brouard 5560: fprintf(ficresphtm,"</tr>\n");
5561: fprintf(ficresphtm,"</table>\n");
5562: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5563: if(posproptt < 1.e-5){
1.251 brouard 5564: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5565: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5566: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5567: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5568: invalidvarcomb[j1]=1;
1.226 brouard 5569: }else{
1.338 brouard 5570: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5571: invalidvarcomb[j1]=0;
1.226 brouard 5572: }
1.251 brouard 5573: fprintf(ficresphtmfr,"</table>\n");
5574: fprintf(ficlog,"\n");
5575: if(j!=0){
5576: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5577: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5578: for(k=1; k <=(nlstate+ndeath); k++){
5579: if (k != i) {
1.265 brouard 5580: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5581: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5582: if(j1==1){ /* All dummy covariates to zero */
5583: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5584: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5585: printf("%d%d ",i,k);
5586: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5587: 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]));
5588: 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]));
5589: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5590: }
1.253 brouard 5591: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5592: for(iage=iagemin; iage <= iagemax+3; iage++){
5593: x[iage]= (double)iage;
5594: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5595: /* 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 5596: }
1.268 brouard 5597: /* Some are not finite, but linreg will ignore these ages */
5598: no=0;
1.253 brouard 5599: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5600: pstart[s1]=b;
5601: pstart[s1-1]=a;
1.252 brouard 5602: }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 */
5603: 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]);
5604: 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 5605: 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 5606: printf("%d%d ",i,k);
5607: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5608: 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 5609: }else{ /* Other cases, like quantitative fixed or varying covariates */
5610: ;
5611: }
5612: /* printf("%12.7f )", param[i][jj][k]); */
5613: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5614: s1++;
1.251 brouard 5615: } /* end jj */
5616: } /* end k!= i */
5617: } /* end k */
1.265 brouard 5618: } /* end i, s1 */
1.251 brouard 5619: } /* end j !=0 */
5620: } /* end selected combination of covariate j1 */
5621: if(j==0){ /* We can estimate starting values from the occurences in each case */
5622: printf("#Freqsummary: Starting values for the constants:\n");
5623: fprintf(ficlog,"\n");
1.265 brouard 5624: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5625: for(k=1; k <=(nlstate+ndeath); k++){
5626: if (k != i) {
5627: printf("%d%d ",i,k);
5628: fprintf(ficlog,"%d%d ",i,k);
5629: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5630: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5631: if(jj==1){ /* Age has to be done */
1.265 brouard 5632: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5633: 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]));
5634: 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 5635: }
5636: /* printf("%12.7f )", param[i][jj][k]); */
5637: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5638: s1++;
1.250 brouard 5639: }
1.251 brouard 5640: printf("\n");
5641: fprintf(ficlog,"\n");
1.250 brouard 5642: }
5643: }
1.284 brouard 5644: } /* end of state i */
1.251 brouard 5645: printf("#Freqsummary\n");
5646: fprintf(ficlog,"\n");
1.265 brouard 5647: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5648: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5649: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5650: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5651: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5652: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5653: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5654: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5655: /* } */
5656: }
1.265 brouard 5657: } /* end loop s1 */
1.251 brouard 5658:
5659: printf("\n");
5660: fprintf(ficlog,"\n");
5661: } /* end j=0 */
1.249 brouard 5662: } /* end j */
1.252 brouard 5663:
1.253 brouard 5664: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5665: for(i=1, jk=1; i <=nlstate; i++){
5666: for(j=1; j <=nlstate+ndeath; j++){
5667: if(j!=i){
5668: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5669: printf("%1d%1d",i,j);
5670: fprintf(ficparo,"%1d%1d",i,j);
5671: for(k=1; k<=ncovmodel;k++){
5672: /* printf(" %lf",param[i][j][k]); */
5673: /* fprintf(ficparo," %lf",param[i][j][k]); */
5674: p[jk]=pstart[jk];
5675: printf(" %f ",pstart[jk]);
5676: fprintf(ficparo," %f ",pstart[jk]);
5677: jk++;
5678: }
5679: printf("\n");
5680: fprintf(ficparo,"\n");
5681: }
5682: }
5683: }
5684: } /* end mle=-2 */
1.226 brouard 5685: dateintmean=dateintsum/k2cpt;
1.296 brouard 5686: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5687:
1.226 brouard 5688: fclose(ficresp);
5689: fclose(ficresphtm);
5690: fclose(ficresphtmfr);
1.283 brouard 5691: free_vector(idq,1,nqfveff);
1.226 brouard 5692: free_vector(meanq,1,nqfveff);
1.284 brouard 5693: free_vector(stdq,1,nqfveff);
1.226 brouard 5694: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5695: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5696: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5697: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5698: free_vector(pospropt,1,nlstate);
5699: free_vector(posprop,1,nlstate);
1.251 brouard 5700: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5701: free_vector(pp,1,nlstate);
5702: /* End of freqsummary */
5703: }
1.126 brouard 5704:
1.268 brouard 5705: /* Simple linear regression */
5706: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5707:
5708: /* y=a+bx regression */
5709: double sumx = 0.0; /* sum of x */
5710: double sumx2 = 0.0; /* sum of x**2 */
5711: double sumxy = 0.0; /* sum of x * y */
5712: double sumy = 0.0; /* sum of y */
5713: double sumy2 = 0.0; /* sum of y**2 */
5714: double sume2 = 0.0; /* sum of square or residuals */
5715: double yhat;
5716:
5717: double denom=0;
5718: int i;
5719: int ne=*no;
5720:
5721: for ( i=ifi, ne=0;i<=ila;i++) {
5722: if(!isfinite(x[i]) || !isfinite(y[i])){
5723: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5724: continue;
5725: }
5726: ne=ne+1;
5727: sumx += x[i];
5728: sumx2 += x[i]*x[i];
5729: sumxy += x[i] * y[i];
5730: sumy += y[i];
5731: sumy2 += y[i]*y[i];
5732: denom = (ne * sumx2 - sumx*sumx);
5733: /* 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); */
5734: }
5735:
5736: denom = (ne * sumx2 - sumx*sumx);
5737: if (denom == 0) {
5738: // vertical, slope m is infinity
5739: *b = INFINITY;
5740: *a = 0;
5741: if (r) *r = 0;
5742: return 1;
5743: }
5744:
5745: *b = (ne * sumxy - sumx * sumy) / denom;
5746: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5747: if (r!=NULL) {
5748: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5749: sqrt((sumx2 - sumx*sumx/ne) *
5750: (sumy2 - sumy*sumy/ne));
5751: }
5752: *no=ne;
5753: for ( i=ifi, ne=0;i<=ila;i++) {
5754: if(!isfinite(x[i]) || !isfinite(y[i])){
5755: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5756: continue;
5757: }
5758: ne=ne+1;
5759: yhat = y[i] - *a -*b* x[i];
5760: sume2 += yhat * yhat ;
5761:
5762: denom = (ne * sumx2 - sumx*sumx);
5763: /* 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); */
5764: }
5765: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5766: *sa= *sb * sqrt(sumx2/ne);
5767:
5768: return 0;
5769: }
5770:
1.126 brouard 5771: /************ Prevalence ********************/
1.227 brouard 5772: 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)
5773: {
5774: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5775: in each health status at the date of interview (if between dateprev1 and dateprev2).
5776: We still use firstpass and lastpass as another selection.
5777: */
1.126 brouard 5778:
1.227 brouard 5779: int i, m, jk, j1, bool, z1,j, iv;
5780: int mi; /* Effective wave */
5781: int iage;
5782: double agebegin, ageend;
5783:
5784: double **prop;
5785: double posprop;
5786: double y2; /* in fractional years */
5787: int iagemin, iagemax;
5788: int first; /** to stop verbosity which is redirected to log file */
5789:
5790: iagemin= (int) agemin;
5791: iagemax= (int) agemax;
5792: /*pp=vector(1,nlstate);*/
1.251 brouard 5793: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5794: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5795: j1=0;
1.222 brouard 5796:
1.227 brouard 5797: /*j=cptcoveff;*/
5798: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5799:
1.288 brouard 5800: first=0;
1.335 brouard 5801: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 5802: for (i=1; i<=nlstate; i++)
1.251 brouard 5803: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5804: prop[i][iage]=0.0;
5805: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5806: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5807: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5808:
5809: for (i=1; i<=imx; i++) { /* Each individual */
5810: bool=1;
5811: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5812: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5813: m=mw[mi][i];
5814: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5815: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5816: for (z1=1; z1<=cptcoveff; z1++){
5817: if( Fixed[Tmodelind[z1]]==1){
5818: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.332 brouard 5819: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 5820: bool=0;
5821: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 5822: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 5823: bool=0;
5824: }
5825: }
5826: if(bool==1){ /* Otherwise we skip that wave/person */
5827: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5828: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5829: if(m >=firstpass && m <=lastpass){
5830: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5831: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5832: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5833: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5834: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5835: 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);
5836: exit(1);
5837: }
5838: if (s[m][i]>0 && s[m][i]<=nlstate) {
5839: /*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]]);*/
5840: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5841: prop[s[m][i]][iagemax+3] += weight[i];
5842: } /* end valid statuses */
5843: } /* end selection of dates */
5844: } /* end selection of waves */
5845: } /* end bool */
5846: } /* end wave */
5847: } /* end individual */
5848: for(i=iagemin; i <= iagemax+3; i++){
5849: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5850: posprop += prop[jk][i];
5851: }
5852:
5853: for(jk=1; jk <=nlstate ; jk++){
5854: if( i <= iagemax){
5855: if(posprop>=1.e-5){
5856: probs[i][jk][j1]= prop[jk][i]/posprop;
5857: } else{
1.288 brouard 5858: if(!first){
5859: first=1;
1.266 brouard 5860: 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]);
5861: }else{
1.288 brouard 5862: 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 5863: }
5864: }
5865: }
5866: }/* end jk */
5867: }/* end i */
1.222 brouard 5868: /*} *//* end i1 */
1.227 brouard 5869: } /* end j1 */
1.222 brouard 5870:
1.227 brouard 5871: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5872: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5873: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5874: } /* End of prevalence */
1.126 brouard 5875:
5876: /************* Waves Concatenation ***************/
5877:
5878: 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)
5879: {
1.298 brouard 5880: /* 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 5881: Death is a valid wave (if date is known).
5882: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5883: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5884: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5885: */
1.126 brouard 5886:
1.224 brouard 5887: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5888: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5889: double sum=0., jmean=0.;*/
1.224 brouard 5890: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5891: int j, k=0,jk, ju, jl;
5892: double sum=0.;
5893: first=0;
1.214 brouard 5894: firstwo=0;
1.217 brouard 5895: firsthree=0;
1.218 brouard 5896: firstfour=0;
1.164 brouard 5897: jmin=100000;
1.126 brouard 5898: jmax=-1;
5899: jmean=0.;
1.224 brouard 5900:
5901: /* Treating live states */
1.214 brouard 5902: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5903: mi=0; /* First valid wave */
1.227 brouard 5904: mli=0; /* Last valid wave */
1.309 brouard 5905: m=firstpass; /* Loop on waves */
5906: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5907: 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 */
5908: mli=m-1;/* mw[++mi][i]=m-1; */
5909: }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 5910: 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 5911: mli=m;
1.224 brouard 5912: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5913: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5914: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5915: }
1.309 brouard 5916: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5917: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5918: break;
1.224 brouard 5919: #else
1.317 brouard 5920: 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 5921: if(firsthree == 0){
1.302 brouard 5922: 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 5923: firsthree=1;
1.317 brouard 5924: }else if(firsthree >=1 && firsthree < 10){
5925: 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);
5926: firsthree++;
5927: }else if(firsthree == 10){
5928: printf("Information, too many Information flags: no more reported to log either\n");
5929: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5930: firsthree++;
5931: }else{
5932: firsthree++;
1.227 brouard 5933: }
1.309 brouard 5934: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5935: mli=m;
5936: }
5937: if(s[m][i]==-2){ /* Vital status is really unknown */
5938: nbwarn++;
1.309 brouard 5939: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5940: 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);
5941: 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);
5942: }
5943: break;
5944: }
5945: break;
1.224 brouard 5946: #endif
1.227 brouard 5947: }/* End m >= lastpass */
1.126 brouard 5948: }/* end while */
1.224 brouard 5949:
1.227 brouard 5950: /* 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 5951: /* After last pass */
1.224 brouard 5952: /* Treating death states */
1.214 brouard 5953: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5954: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5955: /* } */
1.126 brouard 5956: mi++; /* Death is another wave */
5957: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5958: /* Only death is a correct wave */
1.126 brouard 5959: mw[mi][i]=m;
1.257 brouard 5960: } /* else not in a death state */
1.224 brouard 5961: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5962: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5963: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5964: 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 5965: nbwarn++;
5966: if(firstfiv==0){
1.309 brouard 5967: 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 5968: firstfiv=1;
5969: }else{
1.309 brouard 5970: 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 5971: }
1.309 brouard 5972: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5973: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5974: nberr++;
5975: if(firstwo==0){
1.309 brouard 5976: 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 5977: firstwo=1;
5978: }
1.309 brouard 5979: 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 5980: }
1.257 brouard 5981: }else{ /* if date of interview is unknown */
1.227 brouard 5982: /* death is known but not confirmed by death status at any wave */
5983: if(firstfour==0){
1.309 brouard 5984: 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 5985: firstfour=1;
5986: }
1.309 brouard 5987: 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 5988: }
1.224 brouard 5989: } /* end if date of death is known */
5990: #endif
1.309 brouard 5991: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5992: /* wav[i]=mw[mi][i]; */
1.126 brouard 5993: if(mi==0){
5994: nbwarn++;
5995: if(first==0){
1.227 brouard 5996: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5997: first=1;
1.126 brouard 5998: }
5999: if(first==1){
1.227 brouard 6000: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6001: }
6002: } /* end mi==0 */
6003: } /* End individuals */
1.214 brouard 6004: /* wav and mw are no more changed */
1.223 brouard 6005:
1.317 brouard 6006: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6007: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6008:
6009:
1.126 brouard 6010: for(i=1; i<=imx; i++){
6011: for(mi=1; mi<wav[i];mi++){
6012: if (stepm <=0)
1.227 brouard 6013: dh[mi][i]=1;
1.126 brouard 6014: else{
1.260 brouard 6015: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6016: if (agedc[i] < 2*AGESUP) {
6017: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6018: if(j==0) j=1; /* Survives at least one month after exam */
6019: else if(j<0){
6020: nberr++;
6021: 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]);
6022: j=1; /* Temporary Dangerous patch */
6023: 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);
6024: 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]);
6025: 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);
6026: }
6027: k=k+1;
6028: if (j >= jmax){
6029: jmax=j;
6030: ijmax=i;
6031: }
6032: if (j <= jmin){
6033: jmin=j;
6034: ijmin=i;
6035: }
6036: sum=sum+j;
6037: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6038: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6039: }
6040: }
6041: else{
6042: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6043: /* 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 6044:
1.227 brouard 6045: k=k+1;
6046: if (j >= jmax) {
6047: jmax=j;
6048: ijmax=i;
6049: }
6050: else if (j <= jmin){
6051: jmin=j;
6052: ijmin=i;
6053: }
6054: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6055: /*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]);*/
6056: if(j<0){
6057: nberr++;
6058: 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]);
6059: 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]);
6060: }
6061: sum=sum+j;
6062: }
6063: jk= j/stepm;
6064: jl= j -jk*stepm;
6065: ju= j -(jk+1)*stepm;
6066: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6067: if(jl==0){
6068: dh[mi][i]=jk;
6069: bh[mi][i]=0;
6070: }else{ /* We want a negative bias in order to only have interpolation ie
6071: * to avoid the price of an extra matrix product in likelihood */
6072: dh[mi][i]=jk+1;
6073: bh[mi][i]=ju;
6074: }
6075: }else{
6076: if(jl <= -ju){
6077: dh[mi][i]=jk;
6078: bh[mi][i]=jl; /* bias is positive if real duration
6079: * is higher than the multiple of stepm and negative otherwise.
6080: */
6081: }
6082: else{
6083: dh[mi][i]=jk+1;
6084: bh[mi][i]=ju;
6085: }
6086: if(dh[mi][i]==0){
6087: dh[mi][i]=1; /* At least one step */
6088: bh[mi][i]=ju; /* At least one step */
6089: /* 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);*/
6090: }
6091: } /* end if mle */
1.126 brouard 6092: }
6093: } /* end wave */
6094: }
6095: jmean=sum/k;
6096: 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 6097: 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 6098: }
1.126 brouard 6099:
6100: /*********** Tricode ****************************/
1.220 brouard 6101: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6102: {
6103: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6104: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6105: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6106: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6107: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6108: */
1.130 brouard 6109:
1.242 brouard 6110: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6111: int modmaxcovj=0; /* Modality max of covariates j */
6112: int cptcode=0; /* Modality max of covariates j */
6113: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6114:
6115:
1.242 brouard 6116: /* cptcoveff=0; */
6117: /* *cptcov=0; */
1.126 brouard 6118:
1.242 brouard 6119: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6120: for (k=1; k <= maxncov; k++)
6121: for(j=1; j<=2; j++)
6122: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6123:
1.242 brouard 6124: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6125: 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 6126: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.339 brouard 6127: printf("Testing k=%d, cptcovt=%d\n",k, cptcovt);
6128: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 6129: switch(Fixed[k]) {
6130: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6131: modmaxcovj=0;
6132: modmincovj=0;
1.242 brouard 6133: 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 6134: /* 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 6135: ij=(int)(covar[Tvar[k]][i]);
6136: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6137: * If product of Vn*Vm, still boolean *:
6138: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6139: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6140: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6141: modality of the nth covariate of individual i. */
6142: if (ij > modmaxcovj)
6143: modmaxcovj=ij;
6144: else if (ij < modmincovj)
6145: modmincovj=ij;
1.287 brouard 6146: if (ij <0 || ij >1 ){
1.311 brouard 6147: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6148: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6149: fflush(ficlog);
6150: exit(1);
1.287 brouard 6151: }
6152: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6153: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6154: exit(1);
6155: }else
6156: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6157: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6158: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6159: /* getting the maximum value of the modality of the covariate
6160: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6161: female ies 1, then modmaxcovj=1.
6162: */
6163: } /* end for loop on individuals i */
6164: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6165: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6166: cptcode=modmaxcovj;
6167: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6168: /*for (i=0; i<=cptcode; i++) {*/
6169: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6170: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6171: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6172: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6173: if( j != -1){
6174: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6175: covariate for which somebody answered excluding
6176: undefined. Usually 2: 0 and 1. */
6177: }
6178: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6179: covariate for which somebody answered including
6180: undefined. Usually 3: -1, 0 and 1. */
6181: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6182: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6183: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6184:
1.242 brouard 6185: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6186: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6187: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6188: /* modmincovj=3; modmaxcovj = 7; */
6189: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6190: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6191: /* defining two dummy variables: variables V1_1 and V1_2.*/
6192: /* nbcode[Tvar[j]][ij]=k; */
6193: /* nbcode[Tvar[j]][1]=0; */
6194: /* nbcode[Tvar[j]][2]=1; */
6195: /* nbcode[Tvar[j]][3]=2; */
6196: /* To be continued (not working yet). */
6197: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6198:
6199: /* 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*/
6200: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6201: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6202: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6203: /*, could be restored in the future */
6204: 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 6205: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6206: break;
6207: }
6208: ij++;
1.287 brouard 6209: 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 6210: cptcode = ij; /* New max modality for covar j */
6211: } /* end of loop on modality i=-1 to 1 or more */
6212: break;
6213: case 1: /* Testing on varying covariate, could be simple and
6214: * should look at waves or product of fixed *
6215: * varying. No time to test -1, assuming 0 and 1 only */
6216: ij=0;
6217: for(i=0; i<=1;i++){
6218: nbcode[Tvar[k]][++ij]=i;
6219: }
6220: break;
6221: default:
6222: break;
6223: } /* end switch */
6224: } /* end dummy test */
1.334 brouard 6225: if(Dummy[k]==1 && Typevar[k] !=1){ /* Quantitative covariate and not age product */
1.311 brouard 6226: 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 6227: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6228: printf("Error k=%d \n",k);
6229: exit(1);
6230: }
1.311 brouard 6231: if(isnan(covar[Tvar[k]][i])){
6232: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6233: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6234: fflush(ficlog);
6235: exit(1);
6236: }
6237: }
1.335 brouard 6238: } /* end Quanti */
1.287 brouard 6239: } /* 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 6240:
6241: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6242: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6243: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6244: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6245: 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 */
6246: 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 */
6247: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6248: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6249:
6250: ij=0;
6251: /* 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 6252: 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 */
6253: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6254: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6255: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6256: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6257: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6258: /* 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 6259: /* If product not in single variable we don't print results */
6260: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6261: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6262: /* k= 1 2 3 4 5 6 7 8 9 */
6263: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6264: /* ij 1 2 3 */
6265: /* Tvaraff[ij]= 4 3 1 */
6266: /* Tmodelind[ij]=2 3 9 */
6267: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6268: 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*/
6269: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6270: 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 */
6271: if(Fixed[k]!=0)
6272: anyvaryingduminmodel=1;
6273: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6274: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6275: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6276: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6277: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6278: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6279: }
6280: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6281: /* ij--; */
6282: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6283: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6284: * because they can be excluded from the model and real
6285: * if in the model but excluded because missing values, but how to get k from ij?*/
6286: for(j=ij+1; j<= cptcovt; j++){
6287: Tvaraff[j]=0;
6288: Tmodelind[j]=0;
6289: }
6290: for(j=ntveff+1; j<= cptcovt; j++){
6291: TmodelInvind[j]=0;
6292: }
6293: /* To be sorted */
6294: ;
6295: }
1.126 brouard 6296:
1.145 brouard 6297:
1.126 brouard 6298: /*********** Health Expectancies ****************/
6299:
1.235 brouard 6300: 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 6301:
6302: {
6303: /* Health expectancies, no variances */
1.329 brouard 6304: /* cij is the combination in the list of combination of dummy covariates */
6305: /* strstart is a string of time at start of computing */
1.164 brouard 6306: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6307: int nhstepma, nstepma; /* Decreasing with age */
6308: double age, agelim, hf;
6309: double ***p3mat;
6310: double eip;
6311:
1.238 brouard 6312: /* pstamp(ficreseij); */
1.126 brouard 6313: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6314: fprintf(ficreseij,"# Age");
6315: for(i=1; i<=nlstate;i++){
6316: for(j=1; j<=nlstate;j++){
6317: fprintf(ficreseij," e%1d%1d ",i,j);
6318: }
6319: fprintf(ficreseij," e%1d. ",i);
6320: }
6321: fprintf(ficreseij,"\n");
6322:
6323:
6324: if(estepm < stepm){
6325: printf ("Problem %d lower than %d\n",estepm, stepm);
6326: }
6327: else hstepm=estepm;
6328: /* We compute the life expectancy from trapezoids spaced every estepm months
6329: * This is mainly to measure the difference between two models: for example
6330: * if stepm=24 months pijx are given only every 2 years and by summing them
6331: * we are calculating an estimate of the Life Expectancy assuming a linear
6332: * progression in between and thus overestimating or underestimating according
6333: * to the curvature of the survival function. If, for the same date, we
6334: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6335: * to compare the new estimate of Life expectancy with the same linear
6336: * hypothesis. A more precise result, taking into account a more precise
6337: * curvature will be obtained if estepm is as small as stepm. */
6338:
6339: /* For example we decided to compute the life expectancy with the smallest unit */
6340: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6341: nhstepm is the number of hstepm from age to agelim
6342: nstepm is the number of stepm from age to agelin.
1.270 brouard 6343: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6344: and note for a fixed period like estepm months */
6345: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6346: survival function given by stepm (the optimization length). Unfortunately it
6347: means that if the survival funtion is printed only each two years of age and if
6348: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6349: results. So we changed our mind and took the option of the best precision.
6350: */
6351: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6352:
6353: agelim=AGESUP;
6354: /* If stepm=6 months */
6355: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6356: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6357:
6358: /* nhstepm age range expressed in number of stepm */
6359: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6360: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6361: /* if (stepm >= YEARM) hstepm=1;*/
6362: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6363: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6364:
6365: for (age=bage; age<=fage; age ++){
6366: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6367: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6368: /* if (stepm >= YEARM) hstepm=1;*/
6369: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6370:
6371: /* If stepm=6 months */
6372: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6373: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6374: /* 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 6375: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6376:
6377: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6378:
6379: printf("%d|",(int)age);fflush(stdout);
6380: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6381:
6382: /* Computing expectancies */
6383: for(i=1; i<=nlstate;i++)
6384: for(j=1; j<=nlstate;j++)
6385: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6386: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6387:
6388: /* 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]);*/
6389:
6390: }
6391:
6392: fprintf(ficreseij,"%3.0f",age );
6393: for(i=1; i<=nlstate;i++){
6394: eip=0;
6395: for(j=1; j<=nlstate;j++){
6396: eip +=eij[i][j][(int)age];
6397: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6398: }
6399: fprintf(ficreseij,"%9.4f", eip );
6400: }
6401: fprintf(ficreseij,"\n");
6402:
6403: }
6404: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6405: printf("\n");
6406: fprintf(ficlog,"\n");
6407:
6408: }
6409:
1.235 brouard 6410: 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 6411:
6412: {
6413: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6414: to initial status i, ei. .
1.126 brouard 6415: */
1.336 brouard 6416: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6417: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6418: int nhstepma, nstepma; /* Decreasing with age */
6419: double age, agelim, hf;
6420: double ***p3matp, ***p3matm, ***varhe;
6421: double **dnewm,**doldm;
6422: double *xp, *xm;
6423: double **gp, **gm;
6424: double ***gradg, ***trgradg;
6425: int theta;
6426:
6427: double eip, vip;
6428:
6429: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6430: xp=vector(1,npar);
6431: xm=vector(1,npar);
6432: dnewm=matrix(1,nlstate*nlstate,1,npar);
6433: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6434:
6435: pstamp(ficresstdeij);
6436: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6437: fprintf(ficresstdeij,"# Age");
6438: for(i=1; i<=nlstate;i++){
6439: for(j=1; j<=nlstate;j++)
6440: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6441: fprintf(ficresstdeij," e%1d. ",i);
6442: }
6443: fprintf(ficresstdeij,"\n");
6444:
6445: pstamp(ficrescveij);
6446: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6447: fprintf(ficrescveij,"# Age");
6448: for(i=1; i<=nlstate;i++)
6449: for(j=1; j<=nlstate;j++){
6450: cptj= (j-1)*nlstate+i;
6451: for(i2=1; i2<=nlstate;i2++)
6452: for(j2=1; j2<=nlstate;j2++){
6453: cptj2= (j2-1)*nlstate+i2;
6454: if(cptj2 <= cptj)
6455: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6456: }
6457: }
6458: fprintf(ficrescveij,"\n");
6459:
6460: if(estepm < stepm){
6461: printf ("Problem %d lower than %d\n",estepm, stepm);
6462: }
6463: else hstepm=estepm;
6464: /* We compute the life expectancy from trapezoids spaced every estepm months
6465: * This is mainly to measure the difference between two models: for example
6466: * if stepm=24 months pijx are given only every 2 years and by summing them
6467: * we are calculating an estimate of the Life Expectancy assuming a linear
6468: * progression in between and thus overestimating or underestimating according
6469: * to the curvature of the survival function. If, for the same date, we
6470: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6471: * to compare the new estimate of Life expectancy with the same linear
6472: * hypothesis. A more precise result, taking into account a more precise
6473: * curvature will be obtained if estepm is as small as stepm. */
6474:
6475: /* For example we decided to compute the life expectancy with the smallest unit */
6476: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6477: nhstepm is the number of hstepm from age to agelim
6478: nstepm is the number of stepm from age to agelin.
6479: Look at hpijx to understand the reason of that which relies in memory size
6480: and note for a fixed period like estepm months */
6481: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6482: survival function given by stepm (the optimization length). Unfortunately it
6483: means that if the survival funtion is printed only each two years of age and if
6484: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6485: results. So we changed our mind and took the option of the best precision.
6486: */
6487: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6488:
6489: /* If stepm=6 months */
6490: /* nhstepm age range expressed in number of stepm */
6491: agelim=AGESUP;
6492: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6493: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6494: /* if (stepm >= YEARM) hstepm=1;*/
6495: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6496:
6497: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6498: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6499: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6500: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6501: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6502: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6503:
6504: for (age=bage; age<=fage; age ++){
6505: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6506: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6507: /* if (stepm >= YEARM) hstepm=1;*/
6508: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6509:
1.126 brouard 6510: /* If stepm=6 months */
6511: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6512: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6513:
6514: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6515:
1.126 brouard 6516: /* Computing Variances of health expectancies */
6517: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6518: decrease memory allocation */
6519: for(theta=1; theta <=npar; theta++){
6520: for(i=1; i<=npar; i++){
1.222 brouard 6521: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6522: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6523: }
1.235 brouard 6524: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6525: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6526:
1.126 brouard 6527: for(j=1; j<= nlstate; j++){
1.222 brouard 6528: for(i=1; i<=nlstate; i++){
6529: for(h=0; h<=nhstepm-1; h++){
6530: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6531: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6532: }
6533: }
1.126 brouard 6534: }
1.218 brouard 6535:
1.126 brouard 6536: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6537: for(h=0; h<=nhstepm-1; h++){
6538: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6539: }
1.126 brouard 6540: }/* End theta */
6541:
6542:
6543: for(h=0; h<=nhstepm-1; h++)
6544: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6545: for(theta=1; theta <=npar; theta++)
6546: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6547:
1.218 brouard 6548:
1.222 brouard 6549: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6550: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6551: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6552:
1.222 brouard 6553: printf("%d|",(int)age);fflush(stdout);
6554: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6555: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6556: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6557: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6558: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6559: for(ij=1;ij<=nlstate*nlstate;ij++)
6560: for(ji=1;ji<=nlstate*nlstate;ji++)
6561: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6562: }
6563: }
1.320 brouard 6564: /* if((int)age ==50){ */
6565: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6566: /* } */
1.126 brouard 6567: /* Computing expectancies */
1.235 brouard 6568: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6569: for(i=1; i<=nlstate;i++)
6570: for(j=1; j<=nlstate;j++)
1.222 brouard 6571: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6572: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6573:
1.222 brouard 6574: /* 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 6575:
1.222 brouard 6576: }
1.269 brouard 6577:
6578: /* Standard deviation of expectancies ij */
1.126 brouard 6579: fprintf(ficresstdeij,"%3.0f",age );
6580: for(i=1; i<=nlstate;i++){
6581: eip=0.;
6582: vip=0.;
6583: for(j=1; j<=nlstate;j++){
1.222 brouard 6584: eip += eij[i][j][(int)age];
6585: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6586: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6587: 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 6588: }
6589: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6590: }
6591: fprintf(ficresstdeij,"\n");
1.218 brouard 6592:
1.269 brouard 6593: /* Variance of expectancies ij */
1.126 brouard 6594: fprintf(ficrescveij,"%3.0f",age );
6595: for(i=1; i<=nlstate;i++)
6596: for(j=1; j<=nlstate;j++){
1.222 brouard 6597: cptj= (j-1)*nlstate+i;
6598: for(i2=1; i2<=nlstate;i2++)
6599: for(j2=1; j2<=nlstate;j2++){
6600: cptj2= (j2-1)*nlstate+i2;
6601: if(cptj2 <= cptj)
6602: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6603: }
1.126 brouard 6604: }
6605: fprintf(ficrescveij,"\n");
1.218 brouard 6606:
1.126 brouard 6607: }
6608: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6609: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6610: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6611: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6612: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6613: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6614: printf("\n");
6615: fprintf(ficlog,"\n");
1.218 brouard 6616:
1.126 brouard 6617: free_vector(xm,1,npar);
6618: free_vector(xp,1,npar);
6619: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6620: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6621: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6622: }
1.218 brouard 6623:
1.126 brouard 6624: /************ Variance ******************/
1.235 brouard 6625: 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 6626: {
1.279 brouard 6627: /** Variance of health expectancies
6628: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6629: * double **newm;
6630: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6631: */
1.218 brouard 6632:
6633: /* int movingaverage(); */
6634: double **dnewm,**doldm;
6635: double **dnewmp,**doldmp;
6636: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6637: int first=0;
1.218 brouard 6638: int k;
6639: double *xp;
1.279 brouard 6640: double **gp, **gm; /**< for var eij */
6641: double ***gradg, ***trgradg; /**< for var eij */
6642: double **gradgp, **trgradgp; /**< for var p point j */
6643: double *gpp, *gmp; /**< for var p point j */
6644: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6645: double ***p3mat;
6646: double age,agelim, hf;
6647: /* double ***mobaverage; */
6648: int theta;
6649: char digit[4];
6650: char digitp[25];
6651:
6652: char fileresprobmorprev[FILENAMELENGTH];
6653:
6654: if(popbased==1){
6655: if(mobilav!=0)
6656: strcpy(digitp,"-POPULBASED-MOBILAV_");
6657: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6658: }
6659: else
6660: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6661:
1.218 brouard 6662: /* if (mobilav!=0) { */
6663: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6664: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6665: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6666: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6667: /* } */
6668: /* } */
6669:
6670: strcpy(fileresprobmorprev,"PRMORPREV-");
6671: sprintf(digit,"%-d",ij);
6672: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6673: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6674: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6675: strcat(fileresprobmorprev,fileresu);
6676: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6677: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6678: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6679: }
6680: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6681: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6682: pstamp(ficresprobmorprev);
6683: 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 6684: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 6685:
6686: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
6687: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
6688: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
6689: /* } */
6690: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
6691: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 6692: }
1.337 brouard 6693: /* for(j=1;j<=cptcoveff;j++) */
6694: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 6695: fprintf(ficresprobmorprev,"\n");
6696:
1.218 brouard 6697: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6698: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6699: fprintf(ficresprobmorprev," p.%-d SE",j);
6700: for(i=1; i<=nlstate;i++)
6701: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6702: }
6703: fprintf(ficresprobmorprev,"\n");
6704:
6705: fprintf(ficgp,"\n# Routine varevsij");
6706: fprintf(ficgp,"\nunset title \n");
6707: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6708: 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");
6709: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6710:
1.218 brouard 6711: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6712: pstamp(ficresvij);
6713: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6714: if(popbased==1)
6715: 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);
6716: else
6717: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6718: fprintf(ficresvij,"# Age");
6719: for(i=1; i<=nlstate;i++)
6720: for(j=1; j<=nlstate;j++)
6721: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6722: fprintf(ficresvij,"\n");
6723:
6724: xp=vector(1,npar);
6725: dnewm=matrix(1,nlstate,1,npar);
6726: doldm=matrix(1,nlstate,1,nlstate);
6727: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6728: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6729:
6730: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6731: gpp=vector(nlstate+1,nlstate+ndeath);
6732: gmp=vector(nlstate+1,nlstate+ndeath);
6733: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6734:
1.218 brouard 6735: if(estepm < stepm){
6736: printf ("Problem %d lower than %d\n",estepm, stepm);
6737: }
6738: else hstepm=estepm;
6739: /* For example we decided to compute the life expectancy with the smallest unit */
6740: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6741: nhstepm is the number of hstepm from age to agelim
6742: nstepm is the number of stepm from age to agelim.
6743: Look at function hpijx to understand why because of memory size limitations,
6744: we decided (b) to get a life expectancy respecting the most precise curvature of the
6745: survival function given by stepm (the optimization length). Unfortunately it
6746: means that if the survival funtion is printed every two years of age and if
6747: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6748: results. So we changed our mind and took the option of the best precision.
6749: */
6750: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6751: agelim = AGESUP;
6752: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6753: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6754: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6755: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6756: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6757: gp=matrix(0,nhstepm,1,nlstate);
6758: gm=matrix(0,nhstepm,1,nlstate);
6759:
6760:
6761: for(theta=1; theta <=npar; theta++){
6762: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6763: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6764: }
1.279 brouard 6765: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6766: * returns into prlim .
1.288 brouard 6767: */
1.242 brouard 6768: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6769:
6770: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6771: if (popbased==1) {
6772: if(mobilav ==0){
6773: for(i=1; i<=nlstate;i++)
6774: prlim[i][i]=probs[(int)age][i][ij];
6775: }else{ /* mobilav */
6776: for(i=1; i<=nlstate;i++)
6777: prlim[i][i]=mobaverage[(int)age][i][ij];
6778: }
6779: }
1.295 brouard 6780: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6781: */
6782: 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 6783: /**< 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 6784: * at horizon h in state j including mortality.
6785: */
1.218 brouard 6786: for(j=1; j<= nlstate; j++){
6787: for(h=0; h<=nhstepm; h++){
6788: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6789: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6790: }
6791: }
1.279 brouard 6792: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6793: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6794: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6795: */
6796: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6797: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6798: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6799: }
6800:
6801: /* Again with minus shift */
1.218 brouard 6802:
6803: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6804: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6805:
1.242 brouard 6806: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6807:
6808: if (popbased==1) {
6809: if(mobilav ==0){
6810: for(i=1; i<=nlstate;i++)
6811: prlim[i][i]=probs[(int)age][i][ij];
6812: }else{ /* mobilav */
6813: for(i=1; i<=nlstate;i++)
6814: prlim[i][i]=mobaverage[(int)age][i][ij];
6815: }
6816: }
6817:
1.235 brouard 6818: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6819:
6820: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6821: for(h=0; h<=nhstepm; h++){
6822: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6823: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6824: }
6825: }
6826: /* This for computing probability of death (h=1 means
6827: computed over hstepm matrices product = hstepm*stepm months)
6828: as a weighted average of prlim.
6829: */
6830: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6831: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6832: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6833: }
1.279 brouard 6834: /* end shifting computations */
6835:
6836: /**< Computing gradient matrix at horizon h
6837: */
1.218 brouard 6838: for(j=1; j<= nlstate; j++) /* vareij */
6839: for(h=0; h<=nhstepm; h++){
6840: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6841: }
1.279 brouard 6842: /**< Gradient of overall mortality p.3 (or p.j)
6843: */
6844: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6845: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6846: }
6847:
6848: } /* End theta */
1.279 brouard 6849:
6850: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6851: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6852:
6853: for(h=0; h<=nhstepm; h++) /* veij */
6854: for(j=1; j<=nlstate;j++)
6855: for(theta=1; theta <=npar; theta++)
6856: trgradg[h][j][theta]=gradg[h][theta][j];
6857:
6858: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6859: for(theta=1; theta <=npar; theta++)
6860: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6861: /**< as well as its transposed matrix
6862: */
1.218 brouard 6863:
6864: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6865: for(i=1;i<=nlstate;i++)
6866: for(j=1;j<=nlstate;j++)
6867: vareij[i][j][(int)age] =0.;
1.279 brouard 6868:
6869: /* Computing trgradg by matcov by gradg at age and summing over h
6870: * and k (nhstepm) formula 15 of article
6871: * Lievre-Brouard-Heathcote
6872: */
6873:
1.218 brouard 6874: for(h=0;h<=nhstepm;h++){
6875: for(k=0;k<=nhstepm;k++){
6876: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6877: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6878: for(i=1;i<=nlstate;i++)
6879: for(j=1;j<=nlstate;j++)
6880: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6881: }
6882: }
6883:
1.279 brouard 6884: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6885: * p.j overall mortality formula 49 but computed directly because
6886: * we compute the grad (wix pijx) instead of grad (pijx),even if
6887: * wix is independent of theta.
6888: */
1.218 brouard 6889: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6890: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6891: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6892: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6893: varppt[j][i]=doldmp[j][i];
6894: /* end ppptj */
6895: /* x centered again */
6896:
1.242 brouard 6897: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6898:
6899: if (popbased==1) {
6900: if(mobilav ==0){
6901: for(i=1; i<=nlstate;i++)
6902: prlim[i][i]=probs[(int)age][i][ij];
6903: }else{ /* mobilav */
6904: for(i=1; i<=nlstate;i++)
6905: prlim[i][i]=mobaverage[(int)age][i][ij];
6906: }
6907: }
6908:
6909: /* This for computing probability of death (h=1 means
6910: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6911: as a weighted average of prlim.
6912: */
1.235 brouard 6913: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6914: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6915: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6916: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6917: }
6918: /* end probability of death */
6919:
6920: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6921: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6922: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6923: for(i=1; i<=nlstate;i++){
6924: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6925: }
6926: }
6927: fprintf(ficresprobmorprev,"\n");
6928:
6929: fprintf(ficresvij,"%.0f ",age );
6930: for(i=1; i<=nlstate;i++)
6931: for(j=1; j<=nlstate;j++){
6932: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6933: }
6934: fprintf(ficresvij,"\n");
6935: free_matrix(gp,0,nhstepm,1,nlstate);
6936: free_matrix(gm,0,nhstepm,1,nlstate);
6937: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6938: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6939: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6940: } /* End age */
6941: free_vector(gpp,nlstate+1,nlstate+ndeath);
6942: free_vector(gmp,nlstate+1,nlstate+ndeath);
6943: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6944: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6945: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6946: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6947: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6948: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6949: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6950: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6951: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6952: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6953: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6954: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6955: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6956: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6957: 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);
6958: /* 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 6959: */
1.218 brouard 6960: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6961: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6962:
1.218 brouard 6963: free_vector(xp,1,npar);
6964: free_matrix(doldm,1,nlstate,1,nlstate);
6965: free_matrix(dnewm,1,nlstate,1,npar);
6966: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6967: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6968: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6969: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6970: fclose(ficresprobmorprev);
6971: fflush(ficgp);
6972: fflush(fichtm);
6973: } /* end varevsij */
1.126 brouard 6974:
6975: /************ Variance of prevlim ******************/
1.269 brouard 6976: 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 6977: {
1.205 brouard 6978: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6979: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6980:
1.268 brouard 6981: double **dnewmpar,**doldm;
1.126 brouard 6982: int i, j, nhstepm, hstepm;
6983: double *xp;
6984: double *gp, *gm;
6985: double **gradg, **trgradg;
1.208 brouard 6986: double **mgm, **mgp;
1.126 brouard 6987: double age,agelim;
6988: int theta;
6989:
6990: pstamp(ficresvpl);
1.288 brouard 6991: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6992: fprintf(ficresvpl,"# Age ");
6993: if(nresult >=1)
6994: fprintf(ficresvpl," Result# ");
1.126 brouard 6995: for(i=1; i<=nlstate;i++)
6996: fprintf(ficresvpl," %1d-%1d",i,i);
6997: fprintf(ficresvpl,"\n");
6998:
6999: xp=vector(1,npar);
1.268 brouard 7000: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7001: doldm=matrix(1,nlstate,1,nlstate);
7002:
7003: hstepm=1*YEARM; /* Every year of age */
7004: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7005: agelim = AGESUP;
7006: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7007: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7008: if (stepm >= YEARM) hstepm=1;
7009: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7010: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7011: mgp=matrix(1,npar,1,nlstate);
7012: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7013: gp=vector(1,nlstate);
7014: gm=vector(1,nlstate);
7015:
7016: for(theta=1; theta <=npar; theta++){
7017: for(i=1; i<=npar; i++){ /* Computes gradient */
7018: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7019: }
1.288 brouard 7020: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7021: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7022: /* else */
7023: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7024: for(i=1;i<=nlstate;i++){
1.126 brouard 7025: gp[i] = prlim[i][i];
1.208 brouard 7026: mgp[theta][i] = prlim[i][i];
7027: }
1.126 brouard 7028: for(i=1; i<=npar; i++) /* Computes gradient */
7029: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7030: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7031: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7032: /* else */
7033: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7034: for(i=1;i<=nlstate;i++){
1.126 brouard 7035: gm[i] = prlim[i][i];
1.208 brouard 7036: mgm[theta][i] = prlim[i][i];
7037: }
1.126 brouard 7038: for(i=1;i<=nlstate;i++)
7039: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7040: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7041: } /* End theta */
7042:
7043: trgradg =matrix(1,nlstate,1,npar);
7044:
7045: for(j=1; j<=nlstate;j++)
7046: for(theta=1; theta <=npar; theta++)
7047: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7048: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7049: /* printf("\nmgm mgp %d ",(int)age); */
7050: /* for(j=1; j<=nlstate;j++){ */
7051: /* printf(" %d ",j); */
7052: /* for(theta=1; theta <=npar; theta++) */
7053: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7054: /* printf("\n "); */
7055: /* } */
7056: /* } */
7057: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7058: /* printf("\n gradg %d ",(int)age); */
7059: /* for(j=1; j<=nlstate;j++){ */
7060: /* printf("%d ",j); */
7061: /* for(theta=1; theta <=npar; theta++) */
7062: /* printf("%d %lf ",theta,gradg[theta][j]); */
7063: /* printf("\n "); */
7064: /* } */
7065: /* } */
1.126 brouard 7066:
7067: for(i=1;i<=nlstate;i++)
7068: varpl[i][(int)age] =0.;
1.209 brouard 7069: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7070: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7071: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7072: }else{
1.268 brouard 7073: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7074: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7075: }
1.126 brouard 7076: for(i=1;i<=nlstate;i++)
7077: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7078:
7079: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7080: if(nresult >=1)
7081: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7082: for(i=1; i<=nlstate;i++){
1.126 brouard 7083: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7084: /* for(j=1;j<=nlstate;j++) */
7085: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7086: }
1.126 brouard 7087: fprintf(ficresvpl,"\n");
7088: free_vector(gp,1,nlstate);
7089: free_vector(gm,1,nlstate);
1.208 brouard 7090: free_matrix(mgm,1,npar,1,nlstate);
7091: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7092: free_matrix(gradg,1,npar,1,nlstate);
7093: free_matrix(trgradg,1,nlstate,1,npar);
7094: } /* End age */
7095:
7096: free_vector(xp,1,npar);
7097: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7098: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7099:
7100: }
7101:
7102:
7103: /************ Variance of backprevalence limit ******************/
1.269 brouard 7104: 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 7105: {
7106: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7107: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7108:
7109: double **dnewmpar,**doldm;
7110: int i, j, nhstepm, hstepm;
7111: double *xp;
7112: double *gp, *gm;
7113: double **gradg, **trgradg;
7114: double **mgm, **mgp;
7115: double age,agelim;
7116: int theta;
7117:
7118: pstamp(ficresvbl);
7119: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7120: fprintf(ficresvbl,"# Age ");
7121: if(nresult >=1)
7122: fprintf(ficresvbl," Result# ");
7123: for(i=1; i<=nlstate;i++)
7124: fprintf(ficresvbl," %1d-%1d",i,i);
7125: fprintf(ficresvbl,"\n");
7126:
7127: xp=vector(1,npar);
7128: dnewmpar=matrix(1,nlstate,1,npar);
7129: doldm=matrix(1,nlstate,1,nlstate);
7130:
7131: hstepm=1*YEARM; /* Every year of age */
7132: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7133: agelim = AGEINF;
7134: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7135: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7136: if (stepm >= YEARM) hstepm=1;
7137: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7138: gradg=matrix(1,npar,1,nlstate);
7139: mgp=matrix(1,npar,1,nlstate);
7140: mgm=matrix(1,npar,1,nlstate);
7141: gp=vector(1,nlstate);
7142: gm=vector(1,nlstate);
7143:
7144: for(theta=1; theta <=npar; theta++){
7145: for(i=1; i<=npar; i++){ /* Computes gradient */
7146: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7147: }
7148: if(mobilavproj > 0 )
7149: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7150: else
7151: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7152: for(i=1;i<=nlstate;i++){
7153: gp[i] = bprlim[i][i];
7154: mgp[theta][i] = bprlim[i][i];
7155: }
7156: for(i=1; i<=npar; i++) /* Computes gradient */
7157: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7158: if(mobilavproj > 0 )
7159: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7160: else
7161: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7162: for(i=1;i<=nlstate;i++){
7163: gm[i] = bprlim[i][i];
7164: mgm[theta][i] = bprlim[i][i];
7165: }
7166: for(i=1;i<=nlstate;i++)
7167: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7168: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7169: } /* End theta */
7170:
7171: trgradg =matrix(1,nlstate,1,npar);
7172:
7173: for(j=1; j<=nlstate;j++)
7174: for(theta=1; theta <=npar; theta++)
7175: trgradg[j][theta]=gradg[theta][j];
7176: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7177: /* printf("\nmgm mgp %d ",(int)age); */
7178: /* for(j=1; j<=nlstate;j++){ */
7179: /* printf(" %d ",j); */
7180: /* for(theta=1; theta <=npar; theta++) */
7181: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7182: /* printf("\n "); */
7183: /* } */
7184: /* } */
7185: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7186: /* printf("\n gradg %d ",(int)age); */
7187: /* for(j=1; j<=nlstate;j++){ */
7188: /* printf("%d ",j); */
7189: /* for(theta=1; theta <=npar; theta++) */
7190: /* printf("%d %lf ",theta,gradg[theta][j]); */
7191: /* printf("\n "); */
7192: /* } */
7193: /* } */
7194:
7195: for(i=1;i<=nlstate;i++)
7196: varbpl[i][(int)age] =0.;
7197: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7198: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7199: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7200: }else{
7201: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7202: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7203: }
7204: for(i=1;i<=nlstate;i++)
7205: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7206:
7207: fprintf(ficresvbl,"%.0f ",age );
7208: if(nresult >=1)
7209: fprintf(ficresvbl,"%d ",nres );
7210: for(i=1; i<=nlstate;i++)
7211: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7212: fprintf(ficresvbl,"\n");
7213: free_vector(gp,1,nlstate);
7214: free_vector(gm,1,nlstate);
7215: free_matrix(mgm,1,npar,1,nlstate);
7216: free_matrix(mgp,1,npar,1,nlstate);
7217: free_matrix(gradg,1,npar,1,nlstate);
7218: free_matrix(trgradg,1,nlstate,1,npar);
7219: } /* End age */
7220:
7221: free_vector(xp,1,npar);
7222: free_matrix(doldm,1,nlstate,1,npar);
7223: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7224:
7225: }
7226:
7227: /************ Variance of one-step probabilities ******************/
7228: 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 7229: {
7230: int i, j=0, k1, l1, tj;
7231: int k2, l2, j1, z1;
7232: int k=0, l;
7233: int first=1, first1, first2;
1.326 brouard 7234: int nres=0; /* New */
1.222 brouard 7235: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7236: double **dnewm,**doldm;
7237: double *xp;
7238: double *gp, *gm;
7239: double **gradg, **trgradg;
7240: double **mu;
7241: double age, cov[NCOVMAX+1];
7242: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7243: int theta;
7244: char fileresprob[FILENAMELENGTH];
7245: char fileresprobcov[FILENAMELENGTH];
7246: char fileresprobcor[FILENAMELENGTH];
7247: double ***varpij;
7248:
7249: strcpy(fileresprob,"PROB_");
7250: strcat(fileresprob,fileres);
7251: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7252: printf("Problem with resultfile: %s\n", fileresprob);
7253: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7254: }
7255: strcpy(fileresprobcov,"PROBCOV_");
7256: strcat(fileresprobcov,fileresu);
7257: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7258: printf("Problem with resultfile: %s\n", fileresprobcov);
7259: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7260: }
7261: strcpy(fileresprobcor,"PROBCOR_");
7262: strcat(fileresprobcor,fileresu);
7263: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7264: printf("Problem with resultfile: %s\n", fileresprobcor);
7265: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7266: }
7267: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7268: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7269: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7270: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7271: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7272: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7273: pstamp(ficresprob);
7274: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7275: fprintf(ficresprob,"# Age");
7276: pstamp(ficresprobcov);
7277: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7278: fprintf(ficresprobcov,"# Age");
7279: pstamp(ficresprobcor);
7280: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7281: fprintf(ficresprobcor,"# Age");
1.126 brouard 7282:
7283:
1.222 brouard 7284: for(i=1; i<=nlstate;i++)
7285: for(j=1; j<=(nlstate+ndeath);j++){
7286: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7287: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7288: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7289: }
7290: /* fprintf(ficresprob,"\n");
7291: fprintf(ficresprobcov,"\n");
7292: fprintf(ficresprobcor,"\n");
7293: */
7294: xp=vector(1,npar);
7295: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7296: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7297: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7298: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7299: first=1;
7300: fprintf(ficgp,"\n# Routine varprob");
7301: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7302: fprintf(fichtm,"\n");
7303:
1.288 brouard 7304: 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 7305: 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);
7306: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7307: and drawn. It helps understanding how is the covariance between two incidences.\
7308: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7309: 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 7310: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7311: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7312: standard deviations wide on each axis. <br>\
7313: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7314: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7315: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7316:
1.222 brouard 7317: cov[1]=1;
7318: /* tj=cptcoveff; */
1.225 brouard 7319: tj = (int) pow(2,cptcoveff);
1.222 brouard 7320: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7321: j1=0;
1.332 brouard 7322:
7323: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7324: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.334 brouard 7325: 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 7326: if(tj != 1 && TKresult[nres]!= j1)
7327: continue;
7328:
7329: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7330: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7331: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7332: if (cptcovn>0) {
1.334 brouard 7333: fprintf(ficresprob, "\n#********** Variable ");
7334: fprintf(ficresprobcov, "\n#********** Variable ");
7335: fprintf(ficgp, "\n#********** Variable ");
7336: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7337: fprintf(ficresprobcor, "\n#********** Variable ");
7338:
7339: /* Including quantitative variables of the resultline to be done */
7340: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.338 brouard 7341: printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7342: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7343: /* 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 7344: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7345: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7346: 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 */
7347: 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 */
7348: 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 */
7349: 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 */
7350: 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 */
7351: fprintf(ficresprob,"fixed ");
7352: fprintf(ficresprobcov,"fixed ");
7353: fprintf(ficgp,"fixed ");
7354: fprintf(fichtmcov,"fixed ");
7355: fprintf(ficresprobcor,"fixed ");
7356: }else{
7357: fprintf(ficresprob,"varyi ");
7358: fprintf(ficresprobcov,"varyi ");
7359: fprintf(ficgp,"varyi ");
7360: fprintf(fichtmcov,"varyi ");
7361: fprintf(ficresprobcor,"varyi ");
7362: }
7363: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7364: /* For each selected (single) quantitative value */
1.337 brouard 7365: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7366: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7367: fprintf(ficresprob,"fixed ");
7368: fprintf(ficresprobcov,"fixed ");
7369: fprintf(ficgp,"fixed ");
7370: fprintf(fichtmcov,"fixed ");
7371: fprintf(ficresprobcor,"fixed ");
7372: }else{
7373: fprintf(ficresprob,"varyi ");
7374: fprintf(ficresprobcov,"varyi ");
7375: fprintf(ficgp,"varyi ");
7376: fprintf(fichtmcov,"varyi ");
7377: fprintf(ficresprobcor,"varyi ");
7378: }
7379: }else{
7380: 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 */
7381: 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 */
7382: exit(1);
7383: }
7384: } /* End loop on variable of this resultline */
7385: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7386: fprintf(ficresprob, "**********\n#\n");
7387: fprintf(ficresprobcov, "**********\n#\n");
7388: fprintf(ficgp, "**********\n#\n");
7389: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7390: fprintf(ficresprobcor, "**********\n#");
7391: if(invalidvarcomb[j1]){
7392: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7393: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7394: continue;
7395: }
7396: }
7397: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7398: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7399: gp=vector(1,(nlstate)*(nlstate+ndeath));
7400: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7401: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7402: cov[2]=age;
7403: if(nagesqr==1)
7404: cov[3]= age*age;
1.334 brouard 7405: /* New code end of combination but for each resultline */
7406: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
7407: if(Typevar[k1]==1){ /* A product with age */
7408: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7409: }else{
1.334 brouard 7410: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7411: }
1.334 brouard 7412: }/* End of loop on model equation */
7413: /* Old code */
7414: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7415: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7416: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7417: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7418: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7419: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7420: /* * 1 1 1 1 1 */
7421: /* * 2 2 1 1 1 */
7422: /* * 3 1 2 1 1 */
7423: /* *\/ */
7424: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7425: /* } */
7426: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7427: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7428: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7429: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7430: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7431: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7432: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7433: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7434: /* 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]); */
7435: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7436: /* /\* exit(1); *\/ */
7437: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7438: /* } */
7439: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7440: /* } */
7441: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7442: /* if(Dummy[Tvard[k][1]]==0){ */
7443: /* if(Dummy[Tvard[k][2]]==0){ */
7444: /* 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]])]; */
7445: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7446: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7447: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7448: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7449: /* } */
7450: /* }else{ */
7451: /* if(Dummy[Tvard[k][2]]==0){ */
7452: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7453: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7454: /* }else{ */
7455: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7456: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7457: /* } */
7458: /* } */
7459: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7460: /* } */
1.326 brouard 7461: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7462: for(theta=1; theta <=npar; theta++){
7463: for(i=1; i<=npar; i++)
7464: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7465:
1.222 brouard 7466: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7467:
1.222 brouard 7468: k=0;
7469: for(i=1; i<= (nlstate); i++){
7470: for(j=1; j<=(nlstate+ndeath);j++){
7471: k=k+1;
7472: gp[k]=pmmij[i][j];
7473: }
7474: }
1.220 brouard 7475:
1.222 brouard 7476: for(i=1; i<=npar; i++)
7477: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7478:
1.222 brouard 7479: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7480: k=0;
7481: for(i=1; i<=(nlstate); i++){
7482: for(j=1; j<=(nlstate+ndeath);j++){
7483: k=k+1;
7484: gm[k]=pmmij[i][j];
7485: }
7486: }
1.220 brouard 7487:
1.222 brouard 7488: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7489: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7490: }
1.126 brouard 7491:
1.222 brouard 7492: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7493: for(theta=1; theta <=npar; theta++)
7494: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7495:
1.222 brouard 7496: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7497: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7498:
1.222 brouard 7499: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7500:
1.222 brouard 7501: k=0;
7502: for(i=1; i<=(nlstate); i++){
7503: for(j=1; j<=(nlstate+ndeath);j++){
7504: k=k+1;
7505: mu[k][(int) age]=pmmij[i][j];
7506: }
7507: }
7508: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7509: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7510: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7511:
1.222 brouard 7512: /*printf("\n%d ",(int)age);
7513: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7514: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7515: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7516: }*/
1.220 brouard 7517:
1.222 brouard 7518: fprintf(ficresprob,"\n%d ",(int)age);
7519: fprintf(ficresprobcov,"\n%d ",(int)age);
7520: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7521:
1.222 brouard 7522: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7523: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7524: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7525: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7526: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7527: }
7528: i=0;
7529: for (k=1; k<=(nlstate);k++){
7530: for (l=1; l<=(nlstate+ndeath);l++){
7531: i++;
7532: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7533: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7534: for (j=1; j<=i;j++){
7535: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7536: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7537: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7538: }
7539: }
7540: }/* end of loop for state */
7541: } /* end of loop for age */
7542: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7543: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7544: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7545: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7546:
7547: /* Confidence intervalle of pij */
7548: /*
7549: fprintf(ficgp,"\nunset parametric;unset label");
7550: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7551: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7552: 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);
7553: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7554: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7555: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7556: */
7557:
7558: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7559: first1=1;first2=2;
7560: for (k2=1; k2<=(nlstate);k2++){
7561: for (l2=1; l2<=(nlstate+ndeath);l2++){
7562: if(l2==k2) continue;
7563: j=(k2-1)*(nlstate+ndeath)+l2;
7564: for (k1=1; k1<=(nlstate);k1++){
7565: for (l1=1; l1<=(nlstate+ndeath);l1++){
7566: if(l1==k1) continue;
7567: i=(k1-1)*(nlstate+ndeath)+l1;
7568: if(i<=j) continue;
7569: for (age=bage; age<=fage; age ++){
7570: if ((int)age %5==0){
7571: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7572: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7573: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7574: mu1=mu[i][(int) age]/stepm*YEARM ;
7575: mu2=mu[j][(int) age]/stepm*YEARM;
7576: c12=cv12/sqrt(v1*v2);
7577: /* Computing eigen value of matrix of covariance */
7578: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7579: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7580: if ((lc2 <0) || (lc1 <0) ){
7581: if(first2==1){
7582: first1=0;
7583: 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);
7584: }
7585: 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);
7586: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7587: /* lc2=fabs(lc2); */
7588: }
1.220 brouard 7589:
1.222 brouard 7590: /* Eigen vectors */
1.280 brouard 7591: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7592: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7593: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7594: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7595: }else
7596: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7597: /*v21=sqrt(1.-v11*v11); *//* error */
7598: v21=(lc1-v1)/cv12*v11;
7599: v12=-v21;
7600: v22=v11;
7601: tnalp=v21/v11;
7602: if(first1==1){
7603: first1=0;
7604: 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);
7605: }
7606: 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);
7607: /*printf(fignu*/
7608: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7609: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7610: if(first==1){
7611: first=0;
7612: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7613: fprintf(ficgp,"\nset parametric;unset label");
7614: 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);
7615: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7616: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7617: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7618: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7619: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7620: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7621: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7622: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7623: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7624: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7625: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7626: 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 7627: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7628: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7629: }else{
7630: first=0;
7631: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7632: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7633: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7634: 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 7635: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7636: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7637: }/* if first */
7638: } /* age mod 5 */
7639: } /* end loop age */
7640: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7641: first=1;
7642: } /*l12 */
7643: } /* k12 */
7644: } /*l1 */
7645: }/* k1 */
1.332 brouard 7646: } /* loop on combination of covariates j1 */
1.326 brouard 7647: } /* loop on nres */
1.222 brouard 7648: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7649: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7650: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7651: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7652: free_vector(xp,1,npar);
7653: fclose(ficresprob);
7654: fclose(ficresprobcov);
7655: fclose(ficresprobcor);
7656: fflush(ficgp);
7657: fflush(fichtmcov);
7658: }
1.126 brouard 7659:
7660:
7661: /******************* Printing html file ***********/
1.201 brouard 7662: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7663: int lastpass, int stepm, int weightopt, char model[],\
7664: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7665: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7666: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7667: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7668: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7669: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7670: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7671: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7672: </ul>");
1.319 brouard 7673: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7674: /* </ul>", model); */
1.214 brouard 7675: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7676: 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",
7677: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 7678: 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 7679: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7680: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7681: fprintf(fichtm,"\
7682: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7683: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7684: fprintf(fichtm,"\
1.217 brouard 7685: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7686: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7687: fprintf(fichtm,"\
1.288 brouard 7688: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7689: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7690: fprintf(fichtm,"\
1.288 brouard 7691: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7692: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7693: fprintf(fichtm,"\
1.211 brouard 7694: - (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 7695: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7696: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7697: if(prevfcast==1){
7698: fprintf(fichtm,"\
7699: - Prevalence projections by age and states: \
1.201 brouard 7700: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7701: }
1.126 brouard 7702:
7703:
1.225 brouard 7704: m=pow(2,cptcoveff);
1.222 brouard 7705: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7706:
1.317 brouard 7707: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7708:
7709: jj1=0;
7710:
7711: fprintf(fichtm," \n<ul>");
1.337 brouard 7712: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7713: /* k1=nres; */
1.338 brouard 7714: k1=TKresult[nres];
7715: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 7716: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7717: /* if(m != 1 && TKresult[nres]!= k1) */
7718: /* continue; */
1.264 brouard 7719: jj1++;
7720: if (cptcovn > 0) {
7721: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 7722: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
7723: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7724: }
1.337 brouard 7725: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7726: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7727: /* } */
7728: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7729: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7730: /* } */
1.264 brouard 7731: fprintf(fichtm,"\">");
7732:
7733: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7734: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7735: for (cpt=1; cpt<=cptcovs;cpt++){
7736: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7737: }
1.337 brouard 7738: /* fprintf(fichtm,"************ Results for covariates"); */
7739: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7740: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7741: /* } */
7742: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7743: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7744: /* } */
1.264 brouard 7745: if(invalidvarcomb[k1]){
7746: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7747: continue;
7748: }
7749: fprintf(fichtm,"</a></li>");
7750: } /* cptcovn >0 */
7751: }
1.317 brouard 7752: fprintf(fichtm," \n</ul>");
1.264 brouard 7753:
1.222 brouard 7754: jj1=0;
1.237 brouard 7755:
1.337 brouard 7756: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7757: /* k1=nres; */
1.338 brouard 7758: k1=TKresult[nres];
7759: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7760: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7761: /* if(m != 1 && TKresult[nres]!= k1) */
7762: /* continue; */
1.220 brouard 7763:
1.222 brouard 7764: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7765: jj1++;
7766: if (cptcovn > 0) {
1.264 brouard 7767: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 7768: for (cpt=1; cpt<=cptcovs;cpt++){
7769: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7770: }
1.337 brouard 7771: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7772: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7773: /* } */
1.264 brouard 7774: fprintf(fichtm,"\"</a>");
7775:
1.222 brouard 7776: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7777: for (cpt=1; cpt<=cptcovs;cpt++){
7778: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7779: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7780: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7781: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7782: }
1.230 brouard 7783: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 7784: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7785: if(invalidvarcomb[k1]){
7786: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7787: printf("\nCombination (%d) ignored because no cases \n",k1);
7788: continue;
7789: }
7790: }
7791: /* aij, bij */
1.259 brouard 7792: 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 7793: <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 7794: /* Pij */
1.241 brouard 7795: 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> \
7796: <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 7797: /* Quasi-incidences */
7798: 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 7799: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7800: 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 7801: 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> \
7802: <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 7803: /* Survival functions (period) in state j */
7804: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7805: 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);
7806: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7807: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7808: }
7809: /* State specific survival functions (period) */
7810: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7811: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7812: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 7813: <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);
7814: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7815: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7816: }
1.288 brouard 7817: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7818: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7819: 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 7820: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 7821: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7822: }
1.296 brouard 7823: if(prevbcast==1){
1.288 brouard 7824: /* Backward prevalence in each health state */
1.222 brouard 7825: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 7826: 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);
7827: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
7828: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 7829: }
1.217 brouard 7830: }
1.222 brouard 7831: if(prevfcast==1){
1.288 brouard 7832: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7833: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7834: 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);
7835: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7836: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7837: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7838: }
7839: }
1.296 brouard 7840: if(prevbcast==1){
1.268 brouard 7841: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7842: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7843: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7844: 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 \
7845: 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 7846: 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);
7847: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7848: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7849: }
7850: }
1.220 brouard 7851:
1.222 brouard 7852: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7853: 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);
7854: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7855: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7856: }
7857: /* } /\* end i1 *\/ */
1.337 brouard 7858: }/* End k1=nres */
1.222 brouard 7859: fprintf(fichtm,"</ul>");
1.126 brouard 7860:
1.222 brouard 7861: fprintf(fichtm,"\
1.126 brouard 7862: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7863: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7864: - 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 7865: But because parameters are usually highly correlated (a higher incidence of disability \
7866: and a higher incidence of recovery can give very close observed transition) it might \
7867: be very useful to look not only at linear confidence intervals estimated from the \
7868: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7869: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7870: covariance matrix of the one-step probabilities. \
7871: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7872:
1.222 brouard 7873: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7874: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7875: fprintf(fichtm,"\
1.126 brouard 7876: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7877: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7878:
1.222 brouard 7879: fprintf(fichtm,"\
1.126 brouard 7880: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7881: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7882: fprintf(fichtm,"\
1.126 brouard 7883: - 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): \
7884: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7885: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7886: fprintf(fichtm,"\
1.126 brouard 7887: - (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): \
7888: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7889: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7890: fprintf(fichtm,"\
1.288 brouard 7891: - 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 7892: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7893: fprintf(fichtm,"\
1.128 brouard 7894: - 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 7895: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7896: fprintf(fichtm,"\
1.288 brouard 7897: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7898: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7899:
7900: /* if(popforecast==1) fprintf(fichtm,"\n */
7901: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7902: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7903: /* <br>",fileres,fileres,fileres,fileres); */
7904: /* else */
1.338 brouard 7905: /* 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 7906: fflush(fichtm);
1.126 brouard 7907:
1.225 brouard 7908: m=pow(2,cptcoveff);
1.222 brouard 7909: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7910:
1.317 brouard 7911: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7912:
7913: jj1=0;
7914:
7915: fprintf(fichtm," \n<ul>");
1.337 brouard 7916: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7917: /* k1=nres; */
1.338 brouard 7918: k1=TKresult[nres];
1.337 brouard 7919: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7920: /* if(m != 1 && TKresult[nres]!= k1) */
7921: /* continue; */
1.317 brouard 7922: jj1++;
7923: if (cptcovn > 0) {
7924: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 7925: for (cpt=1; cpt<=cptcovs;cpt++){
7926: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7927: }
7928: fprintf(fichtm,"\">");
7929:
7930: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7931: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7932: for (cpt=1; cpt<=cptcovs;cpt++){
7933: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7934: }
7935: if(invalidvarcomb[k1]){
7936: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7937: continue;
7938: }
7939: fprintf(fichtm,"</a></li>");
7940: } /* cptcovn >0 */
1.337 brouard 7941: } /* End nres */
1.317 brouard 7942: fprintf(fichtm," \n</ul>");
7943:
1.222 brouard 7944: jj1=0;
1.237 brouard 7945:
1.241 brouard 7946: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 7947: /* k1=nres; */
1.338 brouard 7948: k1=TKresult[nres];
7949: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7950: /* for(k1=1; k1<=m;k1++){ */
7951: /* if(m != 1 && TKresult[nres]!= k1) */
7952: /* continue; */
1.222 brouard 7953: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7954: jj1++;
1.126 brouard 7955: if (cptcovn > 0) {
1.317 brouard 7956: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 7957: for (cpt=1; cpt<=cptcovs;cpt++){
7958: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7959: }
7960: fprintf(fichtm,"\"</a>");
7961:
1.126 brouard 7962: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7963: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
7964: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7965: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7966: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7967: }
1.237 brouard 7968:
1.338 brouard 7969: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7970:
1.222 brouard 7971: if(invalidvarcomb[k1]){
7972: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7973: continue;
7974: }
1.337 brouard 7975: } /* If cptcovn >0 */
1.126 brouard 7976: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7977: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7978: 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);
7979: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7980: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7981: }
7982: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7983: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7984: true period expectancies (those weighted with period prevalences are also\
7985: drawn in addition to the population based expectancies computed using\
1.314 brouard 7986: 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);
7987: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7988: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7989: /* } /\* end i1 *\/ */
1.241 brouard 7990: }/* End nres */
1.222 brouard 7991: fprintf(fichtm,"</ul>");
7992: fflush(fichtm);
1.126 brouard 7993: }
7994:
7995: /******************* Gnuplot file **************/
1.296 brouard 7996: 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 7997:
7998: char dirfileres[132],optfileres[132];
1.264 brouard 7999: char gplotcondition[132], gplotlabel[132];
1.237 brouard 8000: int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,ij=0, ijp=0, l=0;
1.211 brouard 8001: int lv=0, vlv=0, kl=0;
1.130 brouard 8002: int ng=0;
1.201 brouard 8003: int vpopbased;
1.223 brouard 8004: int ioffset; /* variable offset for columns */
1.270 brouard 8005: int iyearc=1; /* variable column for year of projection */
8006: int iagec=1; /* variable column for age of projection */
1.235 brouard 8007: int nres=0; /* Index of resultline */
1.266 brouard 8008: int istart=1; /* For starting graphs in projections */
1.219 brouard 8009:
1.126 brouard 8010: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8011: /* printf("Problem with file %s",optionfilegnuplot); */
8012: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8013: /* } */
8014:
8015: /*#ifdef windows */
8016: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8017: /*#endif */
1.225 brouard 8018: m=pow(2,cptcoveff);
1.126 brouard 8019:
1.274 brouard 8020: /* diagram of the model */
8021: fprintf(ficgp,"\n#Diagram of the model \n");
8022: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8023: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8024: 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);
8025:
8026: fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=1:%d] arrow (%d+1)*10+i from cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.80*(cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) ), -0.80*(sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) + yoff ) ls 4\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
8027: fprintf(ficgp,"\n#show arrow\nunset label\n");
8028: 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);
8029: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8030: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8031: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8032: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8033:
1.202 brouard 8034: /* Contribution to likelihood */
8035: /* Plot the probability implied in the likelihood */
1.223 brouard 8036: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8037: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8038: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8039: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8040: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8041: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8042: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8043: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8044: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8045: 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));
8046: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8047: 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));
8048: for (i=1; i<= nlstate ; i ++) {
8049: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8050: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8051: 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);
8052: for (j=2; j<= nlstate+ndeath ; j ++) {
8053: 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);
8054: }
8055: fprintf(ficgp,";\nset out; unset ylabel;\n");
8056: }
8057: /* 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 */
8058: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8059: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8060: fprintf(ficgp,"\nset out;unset log\n");
8061: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8062:
1.126 brouard 8063: strcpy(dirfileres,optionfilefiname);
8064: strcpy(optfileres,"vpl");
1.223 brouard 8065: /* 1eme*/
1.238 brouard 8066: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8067: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8068: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8069: k1=TKresult[nres];
1.338 brouard 8070: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8071: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8072: /* if(m != 1 && TKresult[nres]!= k1) */
8073: /* continue; */
1.238 brouard 8074: /* We are interested in selected combination by the resultline */
1.246 brouard 8075: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8076: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8077: strcpy(gplotlabel,"(");
1.337 brouard 8078: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8079: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8080: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8081:
8082: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8083: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8084: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8085: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8086: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8087: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8088: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8089: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8090: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8091: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8092: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8093: /* } */
8094: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8095: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8096: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8097: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8098: }
8099: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8100: /* printf("\n#\n"); */
1.238 brouard 8101: fprintf(ficgp,"\n#\n");
8102: if(invalidvarcomb[k1]){
1.260 brouard 8103: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8104: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8105: continue;
8106: }
1.235 brouard 8107:
1.241 brouard 8108: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8109: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8110: /* 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 8111: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8112: 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);
8113: /* 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); */
8114: /* k1-1 error should be nres-1*/
1.238 brouard 8115: for (i=1; i<= nlstate ; i ++) {
8116: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8117: else fprintf(ficgp," %%*lf (%%*lf)");
8118: }
1.288 brouard 8119: 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 8120: for (i=1; i<= nlstate ; i ++) {
8121: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8122: else fprintf(ficgp," %%*lf (%%*lf)");
8123: }
1.260 brouard 8124: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8125: for (i=1; i<= nlstate ; i ++) {
8126: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8127: else fprintf(ficgp," %%*lf (%%*lf)");
8128: }
1.265 brouard 8129: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8130:
8131: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8132: if(cptcoveff ==0){
1.271 brouard 8133: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8134: }else{
8135: kl=0;
8136: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8137: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8138: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8139: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8140: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8141: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8142: vlv= nbcode[Tvaraff[k]][lv];
8143: kl++;
8144: /* 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 *\/ */
8145: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8146: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8147: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8148: if(k==cptcoveff){
8149: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8150: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8151: }else{
8152: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8153: kl++;
8154: }
8155: } /* end covariate */
8156: } /* end if no covariate */
8157:
1.296 brouard 8158: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8159: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8160: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8161: if(cptcoveff ==0){
1.245 brouard 8162: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8163: }else{
8164: kl=0;
8165: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8166: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8167: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8168: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8169: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8170: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8171: /* vlv= nbcode[Tvaraff[k]][lv]; */
8172: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8173: kl++;
1.238 brouard 8174: /* 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 *\/ */
8175: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8176: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8177: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8178: if(k==cptcoveff){
1.245 brouard 8179: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8180: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8181: }else{
1.332 brouard 8182: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8183: kl++;
8184: }
8185: } /* end covariate */
8186: } /* end if no covariate */
1.296 brouard 8187: if(prevbcast == 1){
1.268 brouard 8188: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8189: /* k1-1 error should be nres-1*/
8190: for (i=1; i<= nlstate ; i ++) {
8191: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8192: else fprintf(ficgp," %%*lf (%%*lf)");
8193: }
1.271 brouard 8194: 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 8195: for (i=1; i<= nlstate ; i ++) {
8196: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8197: else fprintf(ficgp," %%*lf (%%*lf)");
8198: }
1.276 brouard 8199: 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 8200: for (i=1; i<= nlstate ; i ++) {
8201: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8202: else fprintf(ficgp," %%*lf (%%*lf)");
8203: }
1.274 brouard 8204: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8205: } /* end if backprojcast */
1.296 brouard 8206: } /* end if prevbcast */
1.276 brouard 8207: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8208: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8209: } /* nres */
1.337 brouard 8210: /* } /\* k1 *\/ */
1.201 brouard 8211: } /* cpt */
1.235 brouard 8212:
8213:
1.126 brouard 8214: /*2 eme*/
1.337 brouard 8215: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8216: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8217: k1=TKresult[nres];
1.338 brouard 8218: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8219: /* if(m != 1 && TKresult[nres]!= k1) */
8220: /* continue; */
1.238 brouard 8221: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8222: strcpy(gplotlabel,"(");
1.337 brouard 8223: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8224: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8225: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8226: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8227: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8228: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8229: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8230: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8231: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8232: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8233: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8234: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8235: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8236: /* } */
8237: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8238: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8239: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8240: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8241: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8242: }
1.264 brouard 8243: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8244: fprintf(ficgp,"\n#\n");
1.223 brouard 8245: if(invalidvarcomb[k1]){
8246: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8247: continue;
8248: }
1.219 brouard 8249:
1.241 brouard 8250: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8251: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8252: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8253: if(vpopbased==0){
1.238 brouard 8254: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8255: }else
1.238 brouard 8256: fprintf(ficgp,"\nreplot ");
8257: for (i=1; i<= nlstate+1 ; i ++) {
8258: k=2*i;
1.261 brouard 8259: 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 8260: for (j=1; j<= nlstate+1 ; j ++) {
8261: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8262: else fprintf(ficgp," %%*lf (%%*lf)");
8263: }
8264: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8265: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8266: 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 8267: for (j=1; j<= nlstate+1 ; j ++) {
8268: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8269: else fprintf(ficgp," %%*lf (%%*lf)");
8270: }
8271: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8272: 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 8273: for (j=1; j<= nlstate+1 ; j ++) {
8274: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8275: else fprintf(ficgp," %%*lf (%%*lf)");
8276: }
8277: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8278: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8279: } /* state */
8280: } /* vpopbased */
1.264 brouard 8281: 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 8282: } /* end nres */
1.337 brouard 8283: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8284:
8285:
8286: /*3eme*/
1.337 brouard 8287: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8288: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8289: k1=TKresult[nres];
1.338 brouard 8290: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8291: /* if(m != 1 && TKresult[nres]!= k1) */
8292: /* continue; */
1.238 brouard 8293:
1.332 brouard 8294: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8295: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8296: strcpy(gplotlabel,"(");
1.337 brouard 8297: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8298: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8299: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8300: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8301: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8302: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8303: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8304: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8305: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8306: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8307: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8308: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8309: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8310: /* } */
8311: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8312: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8313: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8314: }
1.264 brouard 8315: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8316: fprintf(ficgp,"\n#\n");
8317: if(invalidvarcomb[k1]){
8318: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8319: continue;
8320: }
8321:
8322: /* k=2+nlstate*(2*cpt-2); */
8323: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8324: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8325: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8326: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8327: 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 8328: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8329: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8330: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8331: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8332: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8333: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8334:
1.238 brouard 8335: */
8336: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8337: 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 8338: /* 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 8339:
1.238 brouard 8340: }
1.261 brouard 8341: 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 8342: }
1.264 brouard 8343: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8344: } /* end nres */
1.337 brouard 8345: /* } /\* end kl 3eme *\/ */
1.126 brouard 8346:
1.223 brouard 8347: /* 4eme */
1.201 brouard 8348: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8349: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8350: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8351: k1=TKresult[nres];
1.338 brouard 8352: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8353: /* if(m != 1 && TKresult[nres]!= k1) */
8354: /* continue; */
1.238 brouard 8355: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8356: strcpy(gplotlabel,"(");
1.337 brouard 8357: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8358: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8359: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8360: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8361: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8362: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8363: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8364: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8365: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8366: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8367: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8368: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8369: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8370: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8371: /* } */
8372: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8373: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8374: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8375: }
1.264 brouard 8376: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8377: fprintf(ficgp,"\n#\n");
8378: if(invalidvarcomb[k1]){
8379: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8380: continue;
1.223 brouard 8381: }
1.238 brouard 8382:
1.241 brouard 8383: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8384: 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 8385: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8386: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8387: k=3;
8388: for (i=1; i<= nlstate ; i ++){
8389: if(i==1){
8390: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8391: }else{
8392: fprintf(ficgp,", '' ");
8393: }
8394: l=(nlstate+ndeath)*(i-1)+1;
8395: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8396: for (j=2; j<= nlstate+ndeath ; j ++)
8397: fprintf(ficgp,"+$%d",k+l+j-1);
8398: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8399: } /* nlstate */
1.264 brouard 8400: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8401: } /* end cpt state*/
8402: } /* end nres */
1.337 brouard 8403: /* } /\* end covariate k1 *\/ */
1.238 brouard 8404:
1.220 brouard 8405: /* 5eme */
1.201 brouard 8406: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8407: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8408: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8409: k1=TKresult[nres];
1.338 brouard 8410: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8411: /* if(m != 1 && TKresult[nres]!= k1) */
8412: /* continue; */
1.238 brouard 8413: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8414: strcpy(gplotlabel,"(");
1.238 brouard 8415: 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 8416: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8417: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8418: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8419: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8420: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8421: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8422: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8423: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8424: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8425: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8426: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8427: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8428: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8429: /* } */
8430: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8431: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8432: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8433: }
1.264 brouard 8434: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8435: fprintf(ficgp,"\n#\n");
8436: if(invalidvarcomb[k1]){
8437: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8438: continue;
8439: }
1.227 brouard 8440:
1.241 brouard 8441: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8442: 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 8443: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8444: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8445: k=3;
8446: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8447: if(j==1)
8448: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8449: else
8450: fprintf(ficgp,", '' ");
8451: l=(nlstate+ndeath)*(cpt-1) +j;
8452: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8453: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8454: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8455: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8456: } /* nlstate */
8457: fprintf(ficgp,", '' ");
8458: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8459: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8460: l=(nlstate+ndeath)*(cpt-1) +j;
8461: if(j < nlstate)
8462: fprintf(ficgp,"$%d +",k+l);
8463: else
8464: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8465: }
1.264 brouard 8466: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8467: } /* end cpt state*/
1.337 brouard 8468: /* } /\* end covariate *\/ */
1.238 brouard 8469: } /* end nres */
1.227 brouard 8470:
1.220 brouard 8471: /* 6eme */
1.202 brouard 8472: /* CV preval stable (period) for each covariate */
1.337 brouard 8473: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8474: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8475: k1=TKresult[nres];
1.338 brouard 8476: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8477: /* if(m != 1 && TKresult[nres]!= k1) */
8478: /* continue; */
1.255 brouard 8479: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8480: strcpy(gplotlabel,"(");
1.288 brouard 8481: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8482: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8483: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8484: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8485: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8486: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8487: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8488: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8489: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8490: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8491: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8492: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8493: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8494: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8495: /* } */
8496: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8497: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8498: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8499: }
1.264 brouard 8500: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8501: fprintf(ficgp,"\n#\n");
1.223 brouard 8502: if(invalidvarcomb[k1]){
1.227 brouard 8503: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8504: continue;
1.223 brouard 8505: }
1.227 brouard 8506:
1.241 brouard 8507: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8508: 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 8509: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8510: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8511: k=3; /* Offset */
1.255 brouard 8512: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8513: if(i==1)
8514: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8515: else
8516: fprintf(ficgp,", '' ");
1.255 brouard 8517: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8518: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8519: for (j=2; j<= nlstate ; j ++)
8520: fprintf(ficgp,"+$%d",k+l+j-1);
8521: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8522: } /* nlstate */
1.264 brouard 8523: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8524: } /* end cpt state*/
8525: } /* end covariate */
1.227 brouard 8526:
8527:
1.220 brouard 8528: /* 7eme */
1.296 brouard 8529: if(prevbcast == 1){
1.288 brouard 8530: /* CV backward prevalence for each covariate */
1.337 brouard 8531: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8532: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8533: k1=TKresult[nres];
1.338 brouard 8534: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8535: /* if(m != 1 && TKresult[nres]!= k1) */
8536: /* continue; */
1.268 brouard 8537: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8538: strcpy(gplotlabel,"(");
1.288 brouard 8539: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8540: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8541: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8542: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8543: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8544: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8545: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8546: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8547: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8548: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8549: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8550: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8551: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8552: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8553: /* } */
8554: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8555: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8556: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8557: }
1.264 brouard 8558: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8559: fprintf(ficgp,"\n#\n");
8560: if(invalidvarcomb[k1]){
8561: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8562: continue;
8563: }
8564:
1.241 brouard 8565: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8566: 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 8567: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8568: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8569: k=3; /* Offset */
1.268 brouard 8570: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8571: if(i==1)
8572: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8573: else
8574: fprintf(ficgp,", '' ");
8575: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8576: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8577: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8578: /* 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 8579: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8580: /* for (j=2; j<= nlstate ; j ++) */
8581: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8582: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8583: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8584: } /* nlstate */
1.264 brouard 8585: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8586: } /* end cpt state*/
8587: } /* end covariate */
1.296 brouard 8588: } /* End if prevbcast */
1.218 brouard 8589:
1.223 brouard 8590: /* 8eme */
1.218 brouard 8591: if(prevfcast==1){
1.288 brouard 8592: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8593:
1.337 brouard 8594: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8595: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8596: k1=TKresult[nres];
1.338 brouard 8597: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8598: /* if(m != 1 && TKresult[nres]!= k1) */
8599: /* continue; */
1.211 brouard 8600: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8601: strcpy(gplotlabel,"(");
1.288 brouard 8602: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8603: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8604: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8605: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8606: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8607: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8608: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8609: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8610: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8611: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8612: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8613: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8614: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8615: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8616: /* } */
8617: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8618: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8619: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8620: }
1.264 brouard 8621: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8622: fprintf(ficgp,"\n#\n");
8623: if(invalidvarcomb[k1]){
8624: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8625: continue;
8626: }
8627:
8628: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8629: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8630: 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 8631: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8632: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8633:
8634: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8635: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8636: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8637: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8638: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8639: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8640: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8641: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8642: if(i==istart){
1.227 brouard 8643: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8644: }else{
8645: fprintf(ficgp,",\\\n '' ");
8646: }
8647: if(cptcoveff ==0){ /* No covariate */
8648: ioffset=2; /* Age is in 2 */
8649: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8650: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8651: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8652: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8653: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8654: if(i==nlstate+1){
1.270 brouard 8655: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8656: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8657: fprintf(ficgp,",\\\n '' ");
8658: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8659: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8660: offyear, \
1.268 brouard 8661: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8662: }else
1.227 brouard 8663: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8664: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8665: }else{ /* more than 2 covariates */
1.270 brouard 8666: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8667: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8668: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8669: iyearc=ioffset-1;
8670: iagec=ioffset;
1.227 brouard 8671: fprintf(ficgp," u %d:(",ioffset);
8672: kl=0;
8673: strcpy(gplotcondition,"(");
8674: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 8675: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8676: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8677: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8678: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8679: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8680: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8681: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8682: kl++;
8683: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8684: kl++;
8685: if(k <cptcoveff && cptcoveff>1)
8686: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8687: }
8688: strcpy(gplotcondition+strlen(gplotcondition),")");
8689: /* 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 *\/ */
8690: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8691: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8692: /* '' 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*/
8693: if(i==nlstate+1){
1.270 brouard 8694: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8695: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8696: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8697: fprintf(ficgp," u %d:(",iagec);
8698: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8699: iyearc, iagec, offyear, \
8700: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8701: /* '' 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 8702: }else{
8703: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8704: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8705: }
8706: } /* end if covariate */
8707: } /* nlstate */
1.264 brouard 8708: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8709: } /* end cpt state*/
8710: } /* end covariate */
8711: } /* End if prevfcast */
1.227 brouard 8712:
1.296 brouard 8713: if(prevbcast==1){
1.268 brouard 8714: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8715:
1.337 brouard 8716: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 8717: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8718: k1=TKresult[nres];
1.338 brouard 8719: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8720: /* if(m != 1 && TKresult[nres]!= k1) */
8721: /* continue; */
1.268 brouard 8722: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8723: strcpy(gplotlabel,"(");
8724: 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 8725: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8726: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8727: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8728: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8729: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8730: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8731: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8732: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8733: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8734: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8735: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8736: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8737: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8738: /* } */
8739: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8740: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8741: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 8742: }
8743: strcpy(gplotlabel+strlen(gplotlabel),")");
8744: fprintf(ficgp,"\n#\n");
8745: if(invalidvarcomb[k1]){
8746: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8747: continue;
8748: }
8749:
8750: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8751: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8752: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8753: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8754: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8755:
8756: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8757: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8758: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8759: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8760: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8761: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8762: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8763: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8764: if(i==istart){
8765: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8766: }else{
8767: fprintf(ficgp,",\\\n '' ");
8768: }
8769: if(cptcoveff ==0){ /* No covariate */
8770: ioffset=2; /* Age is in 2 */
8771: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8772: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8773: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8774: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8775: fprintf(ficgp," u %d:(", ioffset);
8776: if(i==nlstate+1){
1.270 brouard 8777: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8778: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8779: fprintf(ficgp,",\\\n '' ");
8780: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8781: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8782: offbyear, \
8783: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8784: }else
8785: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8786: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8787: }else{ /* more than 2 covariates */
1.270 brouard 8788: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8789: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8790: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8791: iyearc=ioffset-1;
8792: iagec=ioffset;
1.268 brouard 8793: fprintf(ficgp," u %d:(",ioffset);
8794: kl=0;
8795: strcpy(gplotcondition,"(");
1.337 brouard 8796: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 8797: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 8798: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
8799: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8800: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8801: lv=Tvresult[nres][k];
8802: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
8803: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8804: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8805: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8806: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8807: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8808: kl++;
8809: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
8810: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
8811: kl++;
1.338 brouard 8812: if(k <cptcovs && cptcovs>1)
1.337 brouard 8813: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8814: }
1.268 brouard 8815: }
8816: strcpy(gplotcondition+strlen(gplotcondition),")");
8817: /* 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 *\/ */
8818: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8819: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8820: /* '' 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*/
8821: if(i==nlstate+1){
1.270 brouard 8822: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8823: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8824: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8825: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8826: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8827: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8828: iyearc,iagec,offbyear, \
8829: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8830: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8831: }else{
8832: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8833: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8834: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8835: }
8836: } /* end if covariate */
8837: } /* nlstate */
8838: fprintf(ficgp,"\nset out; unset label;\n");
8839: } /* end cpt state*/
8840: } /* end covariate */
1.296 brouard 8841: } /* End if prevbcast */
1.268 brouard 8842:
1.227 brouard 8843:
1.238 brouard 8844: /* 9eme writing MLE parameters */
8845: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8846: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8847: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8848: for(k=1; k <=(nlstate+ndeath); k++){
8849: if (k != i) {
1.227 brouard 8850: fprintf(ficgp,"# current state %d\n",k);
8851: for(j=1; j <=ncovmodel; j++){
8852: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8853: jk++;
8854: }
8855: fprintf(ficgp,"\n");
1.126 brouard 8856: }
8857: }
1.223 brouard 8858: }
1.187 brouard 8859: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8860:
1.145 brouard 8861: /*goto avoid;*/
1.238 brouard 8862: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8863: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8864: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8865: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8866: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8867: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8868: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8869: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8870: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8871: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8872: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8873: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8874: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8875: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8876: fprintf(ficgp,"#\n");
1.223 brouard 8877: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8878: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 8879: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 8880: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8881: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
1.337 brouard 8882: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 8883: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8884: /* k1=nres; */
1.338 brouard 8885: k1=TKresult[nres];
8886: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8887: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 8888: strcpy(gplotlabel,"(");
1.276 brouard 8889: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 8890: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8891: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
8892: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
8893: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8894: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8895: }
8896: /* if(m != 1 && TKresult[nres]!= k1) */
8897: /* continue; */
8898: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
8899: /* strcpy(gplotlabel,"("); */
8900: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
8901: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8902: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8903: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8904: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8905: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8906: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8907: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8908: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8909: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8910: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8911: /* } */
8912: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8913: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8914: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8915: /* } */
1.264 brouard 8916: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8917: fprintf(ficgp,"\n#\n");
1.264 brouard 8918: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8919: fprintf(ficgp,"\nset key outside ");
8920: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8921: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8922: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8923: if (ng==1){
8924: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8925: fprintf(ficgp,"\nunset log y");
8926: }else if (ng==2){
8927: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8928: fprintf(ficgp,"\nset log y");
8929: }else if (ng==3){
8930: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8931: fprintf(ficgp,"\nset log y");
8932: }else
8933: fprintf(ficgp,"\nunset title ");
8934: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8935: i=1;
8936: for(k2=1; k2<=nlstate; k2++) {
8937: k3=i;
8938: for(k=1; k<=(nlstate+ndeath); k++) {
8939: if (k != k2){
8940: switch( ng) {
8941: case 1:
8942: if(nagesqr==0)
8943: fprintf(ficgp," p%d+p%d*x",i,i+1);
8944: else /* nagesqr =1 */
8945: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8946: break;
8947: case 2: /* ng=2 */
8948: if(nagesqr==0)
8949: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8950: else /* nagesqr =1 */
8951: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8952: break;
8953: case 3:
8954: if(nagesqr==0)
8955: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8956: else /* nagesqr =1 */
8957: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8958: break;
8959: }
8960: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8961: ijp=1; /* product no age */
8962: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8963: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8964: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 8965: switch(Typevar[j]){
8966: case 1:
8967: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8968: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
8969: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8970: if(DummyV[j]==0){/* Bug valgrind */
8971: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8972: }else{ /* quantitative */
8973: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8974: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8975: }
8976: ij++;
1.268 brouard 8977: }
1.237 brouard 8978: }
1.329 brouard 8979: }
8980: break;
8981: case 2:
8982: if(cptcovprod >0){
8983: if(j==Tprod[ijp]) { /* */
8984: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8985: if(ijp <=cptcovprod) { /* Product */
8986: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8987: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8988: /* 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)]); */
8989: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8990: }else{ /* Vn is dummy and Vm is quanti */
8991: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8992: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8993: }
8994: }else{ /* Vn*Vm Vn is quanti */
8995: if(DummyV[Tvard[ijp][2]]==0){
8996: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8997: }else{ /* Both quanti */
8998: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8999: }
1.268 brouard 9000: }
1.329 brouard 9001: ijp++;
1.237 brouard 9002: }
1.329 brouard 9003: } /* end Tprod */
9004: }
9005: break;
9006: case 0:
9007: /* simple covariate */
1.264 brouard 9008: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9009: if(Dummy[j]==0){
9010: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9011: }else{ /* quantitative */
9012: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9013: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9014: }
1.329 brouard 9015: /* end simple */
9016: break;
9017: default:
9018: break;
9019: } /* end switch */
1.237 brouard 9020: } /* end j */
1.329 brouard 9021: }else{ /* k=k2 */
9022: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9023: fprintf(ficgp," (1.");i=i-ncovmodel;
9024: }else
9025: i=i-ncovmodel;
1.223 brouard 9026: }
1.227 brouard 9027:
1.223 brouard 9028: if(ng != 1){
9029: fprintf(ficgp,")/(1");
1.227 brouard 9030:
1.264 brouard 9031: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9032: if(nagesqr==0)
1.264 brouard 9033: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9034: else /* nagesqr =1 */
1.264 brouard 9035: 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 9036:
1.223 brouard 9037: ij=1;
1.329 brouard 9038: ijp=1;
9039: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9040: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9041: switch(Typevar[j]){
9042: case 1:
9043: if(cptcovage >0){
9044: if(j==Tage[ij]) { /* Bug valgrind */
9045: if(ij <=cptcovage) { /* Bug valgrind */
9046: if(DummyV[j]==0){/* Bug valgrind */
9047: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9048: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9049: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9050: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9051: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9052: }else{ /* quantitative */
9053: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9054: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9055: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9056: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9057: }
9058: ij++;
9059: }
9060: }
9061: }
9062: break;
9063: case 2:
9064: if(cptcovprod >0){
9065: if(j==Tprod[ijp]) { /* */
9066: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9067: if(ijp <=cptcovprod) { /* Product */
9068: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9069: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9070: /* 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)]); */
9071: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9072: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9073: }else{ /* Vn is dummy and Vm is quanti */
9074: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9075: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9076: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9077: }
9078: }else{ /* Vn*Vm Vn is quanti */
9079: if(DummyV[Tvard[ijp][2]]==0){
9080: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9081: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9082: }else{ /* Both quanti */
9083: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9084: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9085: }
9086: }
9087: ijp++;
9088: }
9089: } /* end Tprod */
9090: } /* end if */
9091: break;
9092: case 0:
9093: /* simple covariate */
9094: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9095: if(Dummy[j]==0){
9096: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9097: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9098: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9099: }else{ /* quantitative */
9100: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9101: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9102: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9103: }
9104: /* end simple */
9105: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9106: break;
9107: default:
9108: break;
9109: } /* end switch */
1.223 brouard 9110: }
9111: fprintf(ficgp,")");
9112: }
9113: fprintf(ficgp,")");
9114: if(ng ==2)
1.276 brouard 9115: 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 9116: else /* ng= 3 */
1.276 brouard 9117: 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 9118: }else{ /* end ng <> 1 */
1.223 brouard 9119: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9120: 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 9121: }
9122: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9123: fprintf(ficgp,",");
9124: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9125: fprintf(ficgp,",");
9126: i=i+ncovmodel;
9127: } /* end k */
9128: } /* end k2 */
1.276 brouard 9129: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9130: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9131: } /* end resultline */
1.223 brouard 9132: } /* end ng */
9133: /* avoid: */
9134: fflush(ficgp);
1.126 brouard 9135: } /* end gnuplot */
9136:
9137:
9138: /*************** Moving average **************/
1.219 brouard 9139: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9140: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9141:
1.222 brouard 9142: int i, cpt, cptcod;
9143: int modcovmax =1;
9144: int mobilavrange, mob;
9145: int iage=0;
1.288 brouard 9146: int firstA1=0, firstA2=0;
1.222 brouard 9147:
1.266 brouard 9148: double sum=0., sumr=0.;
1.222 brouard 9149: double age;
1.266 brouard 9150: double *sumnewp, *sumnewm, *sumnewmr;
9151: double *agemingood, *agemaxgood;
9152: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9153:
9154:
1.278 brouard 9155: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9156: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9157:
9158: sumnewp = vector(1,ncovcombmax);
9159: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9160: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9161: agemingood = vector(1,ncovcombmax);
1.266 brouard 9162: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9163: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9164: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9165:
9166: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9167: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9168: sumnewp[cptcod]=0.;
1.266 brouard 9169: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9170: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9171: }
9172: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9173:
1.266 brouard 9174: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9175: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9176: else mobilavrange=mobilav;
9177: for (age=bage; age<=fage; age++)
9178: for (i=1; i<=nlstate;i++)
9179: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9180: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9181: /* We keep the original values on the extreme ages bage, fage and for
9182: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9183: we use a 5 terms etc. until the borders are no more concerned.
9184: */
9185: for (mob=3;mob <=mobilavrange;mob=mob+2){
9186: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9187: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9188: sumnewm[cptcod]=0.;
9189: for (i=1; i<=nlstate;i++){
1.222 brouard 9190: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9191: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9192: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9193: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9194: }
9195: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9196: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9197: } /* end i */
9198: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9199: } /* end cptcod */
1.222 brouard 9200: }/* end age */
9201: }/* end mob */
1.266 brouard 9202: }else{
9203: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9204: return -1;
1.266 brouard 9205: }
9206:
9207: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9208: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9209: if(invalidvarcomb[cptcod]){
9210: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9211: continue;
9212: }
1.219 brouard 9213:
1.266 brouard 9214: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9215: sumnewm[cptcod]=0.;
9216: sumnewmr[cptcod]=0.;
9217: for (i=1; i<=nlstate;i++){
9218: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9219: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9220: }
9221: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9222: agemingoodr[cptcod]=age;
9223: }
9224: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9225: agemingood[cptcod]=age;
9226: }
9227: } /* age */
9228: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9229: sumnewm[cptcod]=0.;
1.266 brouard 9230: sumnewmr[cptcod]=0.;
1.222 brouard 9231: for (i=1; i<=nlstate;i++){
9232: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9233: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9234: }
9235: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9236: agemaxgoodr[cptcod]=age;
1.222 brouard 9237: }
9238: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9239: agemaxgood[cptcod]=age;
9240: }
9241: } /* age */
9242: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9243: /* but they will change */
1.288 brouard 9244: firstA1=0;firstA2=0;
1.266 brouard 9245: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9246: sumnewm[cptcod]=0.;
9247: sumnewmr[cptcod]=0.;
9248: for (i=1; i<=nlstate;i++){
9249: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9250: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9251: }
9252: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9253: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9254: agemaxgoodr[cptcod]=age; /* age min */
9255: for (i=1; i<=nlstate;i++)
9256: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9257: }else{ /* bad we change the value with the values of good ages */
9258: for (i=1; i<=nlstate;i++){
9259: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9260: } /* i */
9261: } /* end bad */
9262: }else{
9263: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9264: agemaxgood[cptcod]=age;
9265: }else{ /* bad we change the value with the values of good ages */
9266: for (i=1; i<=nlstate;i++){
9267: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9268: } /* i */
9269: } /* end bad */
9270: }/* end else */
9271: sum=0.;sumr=0.;
9272: for (i=1; i<=nlstate;i++){
9273: sum+=mobaverage[(int)age][i][cptcod];
9274: sumr+=probs[(int)age][i][cptcod];
9275: }
9276: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9277: if(!firstA1){
9278: firstA1=1;
9279: 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);
9280: }
9281: 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 9282: } /* end bad */
9283: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9284: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9285: if(!firstA2){
9286: firstA2=1;
9287: 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);
9288: }
9289: 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 9290: } /* end bad */
9291: }/* age */
1.266 brouard 9292:
9293: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9294: sumnewm[cptcod]=0.;
1.266 brouard 9295: sumnewmr[cptcod]=0.;
1.222 brouard 9296: for (i=1; i<=nlstate;i++){
9297: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9298: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9299: }
9300: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9301: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9302: agemingoodr[cptcod]=age;
9303: for (i=1; i<=nlstate;i++)
9304: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9305: }else{ /* bad we change the value with the values of good ages */
9306: for (i=1; i<=nlstate;i++){
9307: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9308: } /* i */
9309: } /* end bad */
9310: }else{
9311: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9312: agemingood[cptcod]=age;
9313: }else{ /* bad */
9314: for (i=1; i<=nlstate;i++){
9315: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9316: } /* i */
9317: } /* end bad */
9318: }/* end else */
9319: sum=0.;sumr=0.;
9320: for (i=1; i<=nlstate;i++){
9321: sum+=mobaverage[(int)age][i][cptcod];
9322: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9323: }
1.266 brouard 9324: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9325: 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 9326: } /* end bad */
9327: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9328: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9329: 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 9330: } /* end bad */
9331: }/* age */
1.266 brouard 9332:
1.222 brouard 9333:
9334: for (age=bage; age<=fage; age++){
1.235 brouard 9335: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9336: sumnewp[cptcod]=0.;
9337: sumnewm[cptcod]=0.;
9338: for (i=1; i<=nlstate;i++){
9339: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9340: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9341: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9342: }
9343: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9344: }
9345: /* printf("\n"); */
9346: /* } */
1.266 brouard 9347:
1.222 brouard 9348: /* brutal averaging */
1.266 brouard 9349: /* for (i=1; i<=nlstate;i++){ */
9350: /* for (age=1; age<=bage; age++){ */
9351: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9352: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9353: /* } */
9354: /* for (age=fage; age<=AGESUP; age++){ */
9355: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9356: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9357: /* } */
9358: /* } /\* end i status *\/ */
9359: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9360: /* for (age=1; age<=AGESUP; age++){ */
9361: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9362: /* mobaverage[(int)age][i][cptcod]=0.; */
9363: /* } */
9364: /* } */
1.222 brouard 9365: }/* end cptcod */
1.266 brouard 9366: free_vector(agemaxgoodr,1, ncovcombmax);
9367: free_vector(agemaxgood,1, ncovcombmax);
9368: free_vector(agemingood,1, ncovcombmax);
9369: free_vector(agemingoodr,1, ncovcombmax);
9370: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9371: free_vector(sumnewm,1, ncovcombmax);
9372: free_vector(sumnewp,1, ncovcombmax);
9373: return 0;
9374: }/* End movingaverage */
1.218 brouard 9375:
1.126 brouard 9376:
1.296 brouard 9377:
1.126 brouard 9378: /************** Forecasting ******************/
1.296 brouard 9379: /* 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)*/
9380: 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){
9381: /* dateintemean, mean date of interviews
9382: dateprojd, year, month, day of starting projection
9383: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9384: agemin, agemax range of age
9385: dateprev1 dateprev2 range of dates during which prevalence is computed
9386: */
1.296 brouard 9387: /* double anprojd, mprojd, jprojd; */
9388: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9389: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9390: double agec; /* generic age */
1.296 brouard 9391: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9392: double *popeffectif,*popcount;
9393: double ***p3mat;
1.218 brouard 9394: /* double ***mobaverage; */
1.126 brouard 9395: char fileresf[FILENAMELENGTH];
9396:
9397: agelim=AGESUP;
1.211 brouard 9398: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9399: in each health status at the date of interview (if between dateprev1 and dateprev2).
9400: We still use firstpass and lastpass as another selection.
9401: */
1.214 brouard 9402: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9403: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9404:
1.201 brouard 9405: strcpy(fileresf,"F_");
9406: strcat(fileresf,fileresu);
1.126 brouard 9407: if((ficresf=fopen(fileresf,"w"))==NULL) {
9408: printf("Problem with forecast resultfile: %s\n", fileresf);
9409: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9410: }
1.235 brouard 9411: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9412: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9413:
1.225 brouard 9414: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9415:
9416:
9417: stepsize=(int) (stepm+YEARM-1)/YEARM;
9418: if (stepm<=12) stepsize=1;
9419: if(estepm < stepm){
9420: printf ("Problem %d lower than %d\n",estepm, stepm);
9421: }
1.270 brouard 9422: else{
9423: hstepm=estepm;
9424: }
9425: if(estepm > stepm){ /* Yes every two year */
9426: stepsize=2;
9427: }
1.296 brouard 9428: hstepm=hstepm/stepm;
1.126 brouard 9429:
1.296 brouard 9430:
9431: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9432: /* fractional in yp1 *\/ */
9433: /* aintmean=yp; */
9434: /* yp2=modf((yp1*12),&yp); */
9435: /* mintmean=yp; */
9436: /* yp1=modf((yp2*30.5),&yp); */
9437: /* jintmean=yp; */
9438: /* if(jintmean==0) jintmean=1; */
9439: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9440:
1.296 brouard 9441:
9442: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9443: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9444: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9445: i1=pow(2,cptcoveff);
1.126 brouard 9446: if (cptcovn < 1){i1=1;}
9447:
1.296 brouard 9448: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9449:
9450: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9451:
1.126 brouard 9452: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9453: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9454: for(k=1; k<=i1;k++){ /* We want to find the combination k corresponding to the values of the dummies given in this resut line (to be cleaned one day) */
1.253 brouard 9455: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9456: continue;
1.227 brouard 9457: if(invalidvarcomb[k]){
9458: printf("\nCombination (%d) projection ignored because no cases \n",k);
9459: continue;
9460: }
9461: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9462: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9463: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
9464: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9465: }
1.235 brouard 9466: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9467: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9468: }
1.227 brouard 9469: fprintf(ficresf," yearproj age");
9470: for(j=1; j<=nlstate+ndeath;j++){
9471: for(i=1; i<=nlstate;i++)
9472: fprintf(ficresf," p%d%d",i,j);
9473: fprintf(ficresf," wp.%d",j);
9474: }
1.296 brouard 9475: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9476: fprintf(ficresf,"\n");
1.296 brouard 9477: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9478: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9479: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9480: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9481: nhstepm = nhstepm/hstepm;
9482: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9483: oldm=oldms;savm=savms;
1.268 brouard 9484: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9485: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9486: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9487: for (h=0; h<=nhstepm; h++){
9488: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9489: break;
9490: }
9491: }
9492: fprintf(ficresf,"\n");
9493: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9494: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
9495: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9496: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9497:
9498: for(j=1; j<=nlstate+ndeath;j++) {
9499: ppij=0.;
9500: for(i=1; i<=nlstate;i++) {
1.278 brouard 9501: if (mobilav>=1)
9502: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9503: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9504: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9505: }
1.268 brouard 9506: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9507: } /* end i */
9508: fprintf(ficresf," %.3f", ppij);
9509: }/* end j */
1.227 brouard 9510: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9511: } /* end agec */
1.266 brouard 9512: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9513: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9514: } /* end yearp */
9515: } /* end k */
1.219 brouard 9516:
1.126 brouard 9517: fclose(ficresf);
1.215 brouard 9518: printf("End of Computing forecasting \n");
9519: fprintf(ficlog,"End of Computing forecasting\n");
9520:
1.126 brouard 9521: }
9522:
1.269 brouard 9523: /************** Back Forecasting ******************/
1.296 brouard 9524: /* 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){ */
9525: 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){
9526: /* back1, year, month, day of starting backprojection
1.267 brouard 9527: agemin, agemax range of age
9528: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9529: anback2 year of end of backprojection (same day and month as back1).
9530: prevacurrent and prev are prevalences.
1.267 brouard 9531: */
9532: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9533: double agec; /* generic age */
1.302 brouard 9534: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 9535: double *popeffectif,*popcount;
9536: double ***p3mat;
9537: /* double ***mobaverage; */
9538: char fileresfb[FILENAMELENGTH];
9539:
1.268 brouard 9540: agelim=AGEINF;
1.267 brouard 9541: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9542: in each health status at the date of interview (if between dateprev1 and dateprev2).
9543: We still use firstpass and lastpass as another selection.
9544: */
9545: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9546: /* firstpass, lastpass, stepm, weightopt, model); */
9547:
9548: /*Do we need to compute prevalence again?*/
9549:
9550: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9551:
9552: strcpy(fileresfb,"FB_");
9553: strcat(fileresfb,fileresu);
9554: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9555: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9556: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9557: }
9558: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9559: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9560:
9561: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9562:
9563:
9564: stepsize=(int) (stepm+YEARM-1)/YEARM;
9565: if (stepm<=12) stepsize=1;
9566: if(estepm < stepm){
9567: printf ("Problem %d lower than %d\n",estepm, stepm);
9568: }
1.270 brouard 9569: else{
9570: hstepm=estepm;
9571: }
9572: if(estepm >= stepm){ /* Yes every two year */
9573: stepsize=2;
9574: }
1.267 brouard 9575:
9576: hstepm=hstepm/stepm;
1.296 brouard 9577: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9578: /* fractional in yp1 *\/ */
9579: /* aintmean=yp; */
9580: /* yp2=modf((yp1*12),&yp); */
9581: /* mintmean=yp; */
9582: /* yp1=modf((yp2*30.5),&yp); */
9583: /* jintmean=yp; */
9584: /* if(jintmean==0) jintmean=1; */
9585: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9586:
9587: i1=pow(2,cptcoveff);
9588: if (cptcovn < 1){i1=1;}
9589:
1.296 brouard 9590: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9591: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9592:
9593: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9594:
9595: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9596: for(k=1; k<=i1;k++){
9597: if(i1 != 1 && TKresult[nres]!= k)
9598: continue;
9599: if(invalidvarcomb[k]){
9600: printf("\nCombination (%d) projection ignored because no cases \n",k);
9601: continue;
9602: }
1.268 brouard 9603: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9604: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9605: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 9606: }
9607: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9608: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9609: }
9610: fprintf(ficresfb," yearbproj age");
9611: for(j=1; j<=nlstate+ndeath;j++){
9612: for(i=1; i<=nlstate;i++)
1.268 brouard 9613: fprintf(ficresfb," b%d%d",i,j);
9614: fprintf(ficresfb," b.%d",j);
1.267 brouard 9615: }
1.296 brouard 9616: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9617: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9618: fprintf(ficresfb,"\n");
1.296 brouard 9619: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9620: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9621: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9622: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9623: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9624: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9625: nhstepm = nhstepm/hstepm;
9626: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9627: oldm=oldms;savm=savms;
1.268 brouard 9628: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9629: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9630: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9631: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9632: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9633: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9634: for (h=0; h<=nhstepm; h++){
1.268 brouard 9635: if (h*hstepm/YEARM*stepm ==-yearp) {
9636: break;
9637: }
9638: }
9639: fprintf(ficresfb,"\n");
9640: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9641: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 9642: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9643: for(i=1; i<=nlstate+ndeath;i++) {
9644: ppij=0.;ppi=0.;
9645: for(j=1; j<=nlstate;j++) {
9646: /* if (mobilav==1) */
1.269 brouard 9647: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9648: ppi=ppi+prevacurrent[(int)agec][j][k];
9649: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9650: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9651: /* else { */
9652: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9653: /* } */
1.268 brouard 9654: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9655: } /* end j */
9656: if(ppi <0.99){
9657: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9658: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9659: }
9660: fprintf(ficresfb," %.3f", ppij);
9661: }/* end j */
1.267 brouard 9662: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9663: } /* end agec */
9664: } /* end yearp */
9665: } /* end k */
1.217 brouard 9666:
1.267 brouard 9667: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9668:
1.267 brouard 9669: fclose(ficresfb);
9670: printf("End of Computing Back forecasting \n");
9671: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9672:
1.267 brouard 9673: }
1.217 brouard 9674:
1.269 brouard 9675: /* Variance of prevalence limit: varprlim */
9676: 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 9677: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9678:
9679: char fileresvpl[FILENAMELENGTH];
9680: FILE *ficresvpl;
9681: double **oldm, **savm;
9682: double **varpl; /* Variances of prevalence limits by age */
9683: int i1, k, nres, j ;
9684:
9685: strcpy(fileresvpl,"VPL_");
9686: strcat(fileresvpl,fileresu);
9687: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9688: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9689: exit(0);
9690: }
1.288 brouard 9691: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9692: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9693:
9694: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9695: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9696:
9697: i1=pow(2,cptcoveff);
9698: if (cptcovn < 1){i1=1;}
9699:
1.337 brouard 9700: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9701: k=TKresult[nres];
1.338 brouard 9702: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9703: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 9704: if(i1 != 1 && TKresult[nres]!= k)
9705: continue;
9706: fprintf(ficresvpl,"\n#****** ");
9707: printf("\n#****** ");
9708: fprintf(ficlog,"\n#****** ");
1.337 brouard 9709: for(j=1;j<=cptcovs;j++) {
9710: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9711: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9712: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9713: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9714: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 9715: }
1.337 brouard 9716: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9717: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9718: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9719: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9720: /* } */
1.269 brouard 9721: fprintf(ficresvpl,"******\n");
9722: printf("******\n");
9723: fprintf(ficlog,"******\n");
9724:
9725: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9726: oldm=oldms;savm=savms;
9727: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9728: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9729: /*}*/
9730: }
9731:
9732: fclose(ficresvpl);
1.288 brouard 9733: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9734: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9735:
9736: }
9737: /* Variance of back prevalence: varbprlim */
9738: 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){
9739: /*------- Variance of back (stable) prevalence------*/
9740:
9741: char fileresvbl[FILENAMELENGTH];
9742: FILE *ficresvbl;
9743:
9744: double **oldm, **savm;
9745: double **varbpl; /* Variances of back prevalence limits by age */
9746: int i1, k, nres, j ;
9747:
9748: strcpy(fileresvbl,"VBL_");
9749: strcat(fileresvbl,fileresu);
9750: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9751: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9752: exit(0);
9753: }
9754: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9755: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9756:
9757:
9758: i1=pow(2,cptcoveff);
9759: if (cptcovn < 1){i1=1;}
9760:
1.337 brouard 9761: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9762: k=TKresult[nres];
1.338 brouard 9763: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9764: /* for(k=1; k<=i1;k++){ */
9765: /* if(i1 != 1 && TKresult[nres]!= k) */
9766: /* continue; */
1.269 brouard 9767: fprintf(ficresvbl,"\n#****** ");
9768: printf("\n#****** ");
9769: fprintf(ficlog,"\n#****** ");
1.337 brouard 9770: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 9771: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
9772: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
9773: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 9774: /* for(j=1;j<=cptcoveff;j++) { */
9775: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9776: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9777: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9778: /* } */
9779: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9780: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9781: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9782: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 9783: }
9784: fprintf(ficresvbl,"******\n");
9785: printf("******\n");
9786: fprintf(ficlog,"******\n");
9787:
9788: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9789: oldm=oldms;savm=savms;
9790:
9791: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9792: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9793: /*}*/
9794: }
9795:
9796: fclose(ficresvbl);
9797: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9798: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9799:
9800: } /* End of varbprlim */
9801:
1.126 brouard 9802: /************** Forecasting *****not tested NB*************/
1.227 brouard 9803: /* 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 9804:
1.227 brouard 9805: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9806: /* int *popage; */
9807: /* double calagedatem, agelim, kk1, kk2; */
9808: /* double *popeffectif,*popcount; */
9809: /* double ***p3mat,***tabpop,***tabpopprev; */
9810: /* /\* double ***mobaverage; *\/ */
9811: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9812:
1.227 brouard 9813: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9814: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9815: /* agelim=AGESUP; */
9816: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9817:
1.227 brouard 9818: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9819:
9820:
1.227 brouard 9821: /* strcpy(filerespop,"POP_"); */
9822: /* strcat(filerespop,fileresu); */
9823: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9824: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9825: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9826: /* } */
9827: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9828: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9829:
1.227 brouard 9830: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9831:
1.227 brouard 9832: /* /\* if (mobilav!=0) { *\/ */
9833: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9834: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9835: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9836: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9837: /* /\* } *\/ */
9838: /* /\* } *\/ */
1.126 brouard 9839:
1.227 brouard 9840: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9841: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9842:
1.227 brouard 9843: /* agelim=AGESUP; */
1.126 brouard 9844:
1.227 brouard 9845: /* hstepm=1; */
9846: /* hstepm=hstepm/stepm; */
1.218 brouard 9847:
1.227 brouard 9848: /* if (popforecast==1) { */
9849: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9850: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9851: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9852: /* } */
9853: /* popage=ivector(0,AGESUP); */
9854: /* popeffectif=vector(0,AGESUP); */
9855: /* popcount=vector(0,AGESUP); */
1.126 brouard 9856:
1.227 brouard 9857: /* i=1; */
9858: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9859:
1.227 brouard 9860: /* imx=i; */
9861: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9862: /* } */
1.218 brouard 9863:
1.227 brouard 9864: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9865: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9866: /* k=k+1; */
9867: /* fprintf(ficrespop,"\n#******"); */
9868: /* for(j=1;j<=cptcoveff;j++) { */
9869: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9870: /* } */
9871: /* fprintf(ficrespop,"******\n"); */
9872: /* fprintf(ficrespop,"# Age"); */
9873: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9874: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9875:
1.227 brouard 9876: /* for (cpt=0; cpt<=0;cpt++) { */
9877: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9878:
1.227 brouard 9879: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9880: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9881: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9882:
1.227 brouard 9883: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9884: /* oldm=oldms;savm=savms; */
9885: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9886:
1.227 brouard 9887: /* for (h=0; h<=nhstepm; h++){ */
9888: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9889: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9890: /* } */
9891: /* for(j=1; j<=nlstate+ndeath;j++) { */
9892: /* kk1=0.;kk2=0; */
9893: /* for(i=1; i<=nlstate;i++) { */
9894: /* if (mobilav==1) */
9895: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9896: /* else { */
9897: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9898: /* } */
9899: /* } */
9900: /* if (h==(int)(calagedatem+12*cpt)){ */
9901: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9902: /* /\*fprintf(ficrespop," %.3f", kk1); */
9903: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9904: /* } */
9905: /* } */
9906: /* for(i=1; i<=nlstate;i++){ */
9907: /* kk1=0.; */
9908: /* for(j=1; j<=nlstate;j++){ */
9909: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9910: /* } */
9911: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9912: /* } */
1.218 brouard 9913:
1.227 brouard 9914: /* if (h==(int)(calagedatem+12*cpt)) */
9915: /* for(j=1; j<=nlstate;j++) */
9916: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9917: /* } */
9918: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9919: /* } */
9920: /* } */
1.218 brouard 9921:
1.227 brouard 9922: /* /\******\/ */
1.218 brouard 9923:
1.227 brouard 9924: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9925: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9926: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9927: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9928: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9929:
1.227 brouard 9930: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9931: /* oldm=oldms;savm=savms; */
9932: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9933: /* for (h=0; h<=nhstepm; h++){ */
9934: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9935: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9936: /* } */
9937: /* for(j=1; j<=nlstate+ndeath;j++) { */
9938: /* kk1=0.;kk2=0; */
9939: /* for(i=1; i<=nlstate;i++) { */
9940: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9941: /* } */
9942: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9943: /* } */
9944: /* } */
9945: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9946: /* } */
9947: /* } */
9948: /* } */
9949: /* } */
1.218 brouard 9950:
1.227 brouard 9951: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9952:
1.227 brouard 9953: /* if (popforecast==1) { */
9954: /* free_ivector(popage,0,AGESUP); */
9955: /* free_vector(popeffectif,0,AGESUP); */
9956: /* free_vector(popcount,0,AGESUP); */
9957: /* } */
9958: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9959: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9960: /* fclose(ficrespop); */
9961: /* } /\* End of popforecast *\/ */
1.218 brouard 9962:
1.126 brouard 9963: int fileappend(FILE *fichier, char *optionfich)
9964: {
9965: if((fichier=fopen(optionfich,"a"))==NULL) {
9966: printf("Problem with file: %s\n", optionfich);
9967: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9968: return (0);
9969: }
9970: fflush(fichier);
9971: return (1);
9972: }
9973:
9974:
9975: /**************** function prwizard **********************/
9976: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9977: {
9978:
9979: /* Wizard to print covariance matrix template */
9980:
1.164 brouard 9981: char ca[32], cb[32];
9982: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9983: int numlinepar;
9984:
9985: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9986: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9987: for(i=1; i <=nlstate; i++){
9988: jj=0;
9989: for(j=1; j <=nlstate+ndeath; j++){
9990: if(j==i) continue;
9991: jj++;
9992: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9993: printf("%1d%1d",i,j);
9994: fprintf(ficparo,"%1d%1d",i,j);
9995: for(k=1; k<=ncovmodel;k++){
9996: /* printf(" %lf",param[i][j][k]); */
9997: /* fprintf(ficparo," %lf",param[i][j][k]); */
9998: printf(" 0.");
9999: fprintf(ficparo," 0.");
10000: }
10001: printf("\n");
10002: fprintf(ficparo,"\n");
10003: }
10004: }
10005: printf("# Scales (for hessian or gradient estimation)\n");
10006: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10007: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10008: for(i=1; i <=nlstate; i++){
10009: jj=0;
10010: for(j=1; j <=nlstate+ndeath; j++){
10011: if(j==i) continue;
10012: jj++;
10013: fprintf(ficparo,"%1d%1d",i,j);
10014: printf("%1d%1d",i,j);
10015: fflush(stdout);
10016: for(k=1; k<=ncovmodel;k++){
10017: /* printf(" %le",delti3[i][j][k]); */
10018: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10019: printf(" 0.");
10020: fprintf(ficparo," 0.");
10021: }
10022: numlinepar++;
10023: printf("\n");
10024: fprintf(ficparo,"\n");
10025: }
10026: }
10027: printf("# Covariance matrix\n");
10028: /* # 121 Var(a12)\n\ */
10029: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10030: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10031: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10032: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10033: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10034: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10035: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10036: fflush(stdout);
10037: fprintf(ficparo,"# Covariance matrix\n");
10038: /* # 121 Var(a12)\n\ */
10039: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10040: /* # ...\n\ */
10041: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10042:
10043: for(itimes=1;itimes<=2;itimes++){
10044: jj=0;
10045: for(i=1; i <=nlstate; i++){
10046: for(j=1; j <=nlstate+ndeath; j++){
10047: if(j==i) continue;
10048: for(k=1; k<=ncovmodel;k++){
10049: jj++;
10050: ca[0]= k+'a'-1;ca[1]='\0';
10051: if(itimes==1){
10052: printf("#%1d%1d%d",i,j,k);
10053: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10054: }else{
10055: printf("%1d%1d%d",i,j,k);
10056: fprintf(ficparo,"%1d%1d%d",i,j,k);
10057: /* printf(" %.5le",matcov[i][j]); */
10058: }
10059: ll=0;
10060: for(li=1;li <=nlstate; li++){
10061: for(lj=1;lj <=nlstate+ndeath; lj++){
10062: if(lj==li) continue;
10063: for(lk=1;lk<=ncovmodel;lk++){
10064: ll++;
10065: if(ll<=jj){
10066: cb[0]= lk +'a'-1;cb[1]='\0';
10067: if(ll<jj){
10068: if(itimes==1){
10069: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10070: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10071: }else{
10072: printf(" 0.");
10073: fprintf(ficparo," 0.");
10074: }
10075: }else{
10076: if(itimes==1){
10077: printf(" Var(%s%1d%1d)",ca,i,j);
10078: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10079: }else{
10080: printf(" 0.");
10081: fprintf(ficparo," 0.");
10082: }
10083: }
10084: }
10085: } /* end lk */
10086: } /* end lj */
10087: } /* end li */
10088: printf("\n");
10089: fprintf(ficparo,"\n");
10090: numlinepar++;
10091: } /* end k*/
10092: } /*end j */
10093: } /* end i */
10094: } /* end itimes */
10095:
10096: } /* end of prwizard */
10097: /******************* Gompertz Likelihood ******************************/
10098: double gompertz(double x[])
10099: {
1.302 brouard 10100: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10101: int i,n=0; /* n is the size of the sample */
10102:
1.220 brouard 10103: for (i=1;i<=imx ; i++) {
1.126 brouard 10104: sump=sump+weight[i];
10105: /* sump=sump+1;*/
10106: num=num+1;
10107: }
1.302 brouard 10108: L=0.0;
10109: /* agegomp=AGEGOMP; */
1.126 brouard 10110: /* for (i=0; i<=imx; i++)
10111: 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]);*/
10112:
1.302 brouard 10113: for (i=1;i<=imx ; i++) {
10114: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10115: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10116: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10117: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10118: * +
10119: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10120: */
10121: if (wav[i] > 1 || agedc[i] < AGESUP) {
10122: if (cens[i] == 1){
10123: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10124: } else if (cens[i] == 0){
1.126 brouard 10125: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10126: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10127: } else
10128: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10129: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10130: L=L+A*weight[i];
1.126 brouard 10131: /* 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 10132: }
10133: }
1.126 brouard 10134:
1.302 brouard 10135: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10136:
10137: return -2*L*num/sump;
10138: }
10139:
1.136 brouard 10140: #ifdef GSL
10141: /******************* Gompertz_f Likelihood ******************************/
10142: double gompertz_f(const gsl_vector *v, void *params)
10143: {
1.302 brouard 10144: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10145: double *x= (double *) v->data;
10146: int i,n=0; /* n is the size of the sample */
10147:
10148: for (i=0;i<=imx-1 ; i++) {
10149: sump=sump+weight[i];
10150: /* sump=sump+1;*/
10151: num=num+1;
10152: }
10153:
10154:
10155: /* for (i=0; i<=imx; i++)
10156: 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]);*/
10157: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10158: for (i=1;i<=imx ; i++)
10159: {
10160: if (cens[i] == 1 && wav[i]>1)
10161: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10162:
10163: if (cens[i] == 0 && wav[i]>1)
10164: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10165: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10166:
10167: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10168: if (wav[i] > 1 ) { /* ??? */
10169: LL=LL+A*weight[i];
10170: /* 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]);*/
10171: }
10172: }
10173:
10174: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10175: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10176:
10177: return -2*LL*num/sump;
10178: }
10179: #endif
10180:
1.126 brouard 10181: /******************* Printing html file ***********/
1.201 brouard 10182: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10183: int lastpass, int stepm, int weightopt, char model[],\
10184: int imx, double p[],double **matcov,double agemortsup){
10185: int i,k;
10186:
10187: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10188: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10189: for (i=1;i<=2;i++)
10190: 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 10191: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10192: fprintf(fichtm,"</ul>");
10193:
10194: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10195:
10196: 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>");
10197:
10198: for (k=agegomp;k<(agemortsup-2);k++)
10199: 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]);
10200:
10201:
10202: fflush(fichtm);
10203: }
10204:
10205: /******************* Gnuplot file **************/
1.201 brouard 10206: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10207:
10208: char dirfileres[132],optfileres[132];
1.164 brouard 10209:
1.126 brouard 10210: int ng;
10211:
10212:
10213: /*#ifdef windows */
10214: fprintf(ficgp,"cd \"%s\" \n",pathc);
10215: /*#endif */
10216:
10217:
10218: strcpy(dirfileres,optionfilefiname);
10219: strcpy(optfileres,"vpl");
1.199 brouard 10220: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10221: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10222: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10223: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10224: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10225:
10226: }
10227:
1.136 brouard 10228: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10229: {
1.126 brouard 10230:
1.136 brouard 10231: /*-------- data file ----------*/
10232: FILE *fic;
10233: char dummy[]=" ";
1.240 brouard 10234: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10235: int lstra;
1.136 brouard 10236: int linei, month, year,iout;
1.302 brouard 10237: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10238: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10239: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10240: char *stratrunc;
1.223 brouard 10241:
1.240 brouard 10242: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
10243: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 10244: for(v=1;v<NCOVMAX;v++){
10245: DummyV[v]=0;
10246: FixedV[v]=0;
10247: }
1.126 brouard 10248:
1.240 brouard 10249: for(v=1; v <=ncovcol;v++){
10250: DummyV[v]=0;
10251: FixedV[v]=0;
10252: }
10253: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
10254: DummyV[v]=1;
10255: FixedV[v]=0;
10256: }
10257: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
10258: DummyV[v]=0;
10259: FixedV[v]=1;
10260: }
10261: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
10262: DummyV[v]=1;
10263: FixedV[v]=1;
10264: }
10265: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
10266: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
10267: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
10268: }
1.339 brouard 10269:
10270: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10271:
1.136 brouard 10272: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10273: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10274: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10275: }
1.126 brouard 10276:
1.302 brouard 10277: /* Is it a BOM UTF-8 Windows file? */
10278: /* First data line */
10279: linei=0;
10280: while(fgets(line, MAXLINE, fic)) {
10281: noffset=0;
10282: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10283: {
10284: noffset=noffset+3;
10285: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10286: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10287: fflush(ficlog); return 1;
10288: }
10289: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10290: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10291: {
10292: noffset=noffset+2;
1.304 brouard 10293: 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);
10294: 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 10295: fflush(ficlog); return 1;
10296: }
10297: else if( line[0] == 0 && line[1] == 0)
10298: {
10299: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10300: noffset=noffset+4;
1.304 brouard 10301: 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);
10302: 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 10303: fflush(ficlog); return 1;
10304: }
10305: } else{
10306: ;/*printf(" Not a BOM file\n");*/
10307: }
10308: /* If line starts with a # it is a comment */
10309: if (line[noffset] == '#') {
10310: linei=linei+1;
10311: break;
10312: }else{
10313: break;
10314: }
10315: }
10316: fclose(fic);
10317: if((fic=fopen(datafile,"r"))==NULL) {
10318: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10319: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10320: }
10321: /* Not a Bom file */
10322:
1.136 brouard 10323: i=1;
10324: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10325: linei=linei+1;
10326: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10327: if(line[j] == '\t')
10328: line[j] = ' ';
10329: }
10330: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10331: ;
10332: };
10333: line[j+1]=0; /* Trims blanks at end of line */
10334: if(line[0]=='#'){
10335: fprintf(ficlog,"Comment line\n%s\n",line);
10336: printf("Comment line\n%s\n",line);
10337: continue;
10338: }
10339: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10340: strcpy(line, linetmp);
1.223 brouard 10341:
10342: /* Loops on waves */
10343: for (j=maxwav;j>=1;j--){
10344: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10345: cutv(stra, strb, line, ' ');
10346: if(strb[0]=='.') { /* Missing value */
10347: lval=-1;
10348: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
10349: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
10350: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10351: 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);
10352: 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);
10353: return 1;
10354: }
10355: }else{
10356: errno=0;
10357: /* what_kind_of_number(strb); */
10358: dval=strtod(strb,&endptr);
10359: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10360: /* if(strb != endptr && *endptr == '\0') */
10361: /* dval=dlval; */
10362: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10363: if( strb[0]=='\0' || (*endptr != '\0')){
10364: 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);
10365: 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);
10366: return 1;
10367: }
10368: cotqvar[j][iv][i]=dval;
10369: cotvar[j][ntv+iv][i]=dval;
10370: }
10371: strcpy(line,stra);
1.223 brouard 10372: }/* end loop ntqv */
1.225 brouard 10373:
1.223 brouard 10374: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10375: cutv(stra, strb, line, ' ');
10376: if(strb[0]=='.') { /* Missing value */
10377: lval=-1;
10378: }else{
10379: errno=0;
10380: lval=strtol(strb,&endptr,10);
10381: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10382: if( strb[0]=='\0' || (*endptr != '\0')){
10383: 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);
10384: 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);
10385: return 1;
10386: }
10387: }
10388: if(lval <-1 || lval >1){
10389: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10390: 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 10391: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10392: For example, for multinomial values like 1, 2 and 3,\n \
10393: build V1=0 V2=0 for the reference value (1),\n \
10394: V1=1 V2=0 for (2) \n \
1.223 brouard 10395: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10396: output of IMaCh is often meaningless.\n \
1.319 brouard 10397: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10398: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10399: 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 10400: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10401: For example, for multinomial values like 1, 2 and 3,\n \
10402: build V1=0 V2=0 for the reference value (1),\n \
10403: V1=1 V2=0 for (2) \n \
1.223 brouard 10404: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10405: output of IMaCh is often meaningless.\n \
1.319 brouard 10406: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10407: return 1;
10408: }
10409: cotvar[j][iv][i]=(double)(lval);
10410: strcpy(line,stra);
1.223 brouard 10411: }/* end loop ntv */
1.225 brouard 10412:
1.223 brouard 10413: /* Statuses at wave */
1.137 brouard 10414: cutv(stra, strb, line, ' ');
1.223 brouard 10415: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10416: lval=-1;
1.136 brouard 10417: }else{
1.238 brouard 10418: errno=0;
10419: lval=strtol(strb,&endptr,10);
10420: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10421: if( strb[0]=='\0' || (*endptr != '\0')){
10422: 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);
10423: 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);
10424: return 1;
10425: }
1.136 brouard 10426: }
1.225 brouard 10427:
1.136 brouard 10428: s[j][i]=lval;
1.225 brouard 10429:
1.223 brouard 10430: /* Date of Interview */
1.136 brouard 10431: strcpy(line,stra);
10432: cutv(stra, strb,line,' ');
1.169 brouard 10433: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10434: }
1.169 brouard 10435: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10436: month=99;
10437: year=9999;
1.136 brouard 10438: }else{
1.225 brouard 10439: 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);
10440: 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);
10441: return 1;
1.136 brouard 10442: }
10443: anint[j][i]= (double) year;
1.302 brouard 10444: mint[j][i]= (double)month;
10445: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10446: /* 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]); */
10447: /* 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]); */
10448: /* } */
1.136 brouard 10449: strcpy(line,stra);
1.223 brouard 10450: } /* End loop on waves */
1.225 brouard 10451:
1.223 brouard 10452: /* Date of death */
1.136 brouard 10453: cutv(stra, strb,line,' ');
1.169 brouard 10454: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10455: }
1.169 brouard 10456: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10457: month=99;
10458: year=9999;
10459: }else{
1.141 brouard 10460: 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 10461: 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);
10462: return 1;
1.136 brouard 10463: }
10464: andc[i]=(double) year;
10465: moisdc[i]=(double) month;
10466: strcpy(line,stra);
10467:
1.223 brouard 10468: /* Date of birth */
1.136 brouard 10469: cutv(stra, strb,line,' ');
1.169 brouard 10470: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10471: }
1.169 brouard 10472: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10473: month=99;
10474: year=9999;
10475: }else{
1.141 brouard 10476: 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);
10477: 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 10478: return 1;
1.136 brouard 10479: }
10480: if (year==9999) {
1.141 brouard 10481: 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);
10482: 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 10483: return 1;
10484:
1.136 brouard 10485: }
10486: annais[i]=(double)(year);
1.302 brouard 10487: moisnais[i]=(double)(month);
10488: for (j=1;j<=maxwav;j++){
10489: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10490: 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]);
10491: 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]);
10492: }
10493: }
10494:
1.136 brouard 10495: strcpy(line,stra);
1.225 brouard 10496:
1.223 brouard 10497: /* Sample weight */
1.136 brouard 10498: cutv(stra, strb,line,' ');
10499: errno=0;
10500: dval=strtod(strb,&endptr);
10501: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10502: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10503: 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 10504: fflush(ficlog);
10505: return 1;
10506: }
10507: weight[i]=dval;
10508: strcpy(line,stra);
1.225 brouard 10509:
1.223 brouard 10510: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10511: cutv(stra, strb, line, ' ');
10512: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10513: lval=-1;
1.311 brouard 10514: coqvar[iv][i]=NAN;
10515: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10516: }else{
1.225 brouard 10517: errno=0;
10518: /* what_kind_of_number(strb); */
10519: dval=strtod(strb,&endptr);
10520: /* if(strb != endptr && *endptr == '\0') */
10521: /* dval=dlval; */
10522: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10523: if( strb[0]=='\0' || (*endptr != '\0')){
10524: 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);
10525: 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);
10526: return 1;
10527: }
10528: coqvar[iv][i]=dval;
1.226 brouard 10529: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10530: }
10531: strcpy(line,stra);
10532: }/* end loop nqv */
1.136 brouard 10533:
1.223 brouard 10534: /* Covariate values */
1.136 brouard 10535: for (j=ncovcol;j>=1;j--){
10536: cutv(stra, strb,line,' ');
1.223 brouard 10537: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10538: lval=-1;
1.136 brouard 10539: }else{
1.225 brouard 10540: errno=0;
10541: lval=strtol(strb,&endptr,10);
10542: if( strb[0]=='\0' || (*endptr != '\0')){
10543: 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);
10544: 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);
10545: return 1;
10546: }
1.136 brouard 10547: }
10548: if(lval <-1 || lval >1){
1.225 brouard 10549: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10550: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10551: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10552: For example, for multinomial values like 1, 2 and 3,\n \
10553: build V1=0 V2=0 for the reference value (1),\n \
10554: V1=1 V2=0 for (2) \n \
1.136 brouard 10555: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10556: output of IMaCh is often meaningless.\n \
1.136 brouard 10557: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 10558: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10559: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10560: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10561: For example, for multinomial values like 1, 2 and 3,\n \
10562: build V1=0 V2=0 for the reference value (1),\n \
10563: V1=1 V2=0 for (2) \n \
1.136 brouard 10564: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10565: output of IMaCh is often meaningless.\n \
1.136 brouard 10566: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10567: return 1;
1.136 brouard 10568: }
10569: covar[j][i]=(double)(lval);
10570: strcpy(line,stra);
10571: }
10572: lstra=strlen(stra);
1.225 brouard 10573:
1.136 brouard 10574: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10575: stratrunc = &(stra[lstra-9]);
10576: num[i]=atol(stratrunc);
10577: }
10578: else
10579: num[i]=atol(stra);
10580: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10581: 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;}*/
10582:
10583: i=i+1;
10584: } /* End loop reading data */
1.225 brouard 10585:
1.136 brouard 10586: *imax=i-1; /* Number of individuals */
10587: fclose(fic);
1.225 brouard 10588:
1.136 brouard 10589: return (0);
1.164 brouard 10590: /* endread: */
1.225 brouard 10591: printf("Exiting readdata: ");
10592: fclose(fic);
10593: return (1);
1.223 brouard 10594: }
1.126 brouard 10595:
1.234 brouard 10596: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10597: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10598: while (*p2 == ' ')
1.234 brouard 10599: p2++;
10600: /* while ((*p1++ = *p2++) !=0) */
10601: /* ; */
10602: /* do */
10603: /* while (*p2 == ' ') */
10604: /* p2++; */
10605: /* while (*p1++ == *p2++); */
10606: *stri=p2;
1.145 brouard 10607: }
10608:
1.330 brouard 10609: int decoderesult( char resultline[], int nres)
1.230 brouard 10610: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10611: {
1.235 brouard 10612: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10613: char resultsav[MAXLINE];
1.330 brouard 10614: /* int resultmodel[MAXLINE]; */
1.334 brouard 10615: /* int modelresult[MAXLINE]; */
1.230 brouard 10616: char stra[80], strb[80], strc[80], strd[80],stre[80];
10617:
1.234 brouard 10618: removefirstspace(&resultline);
1.332 brouard 10619: printf("decoderesult:%s\n",resultline);
1.230 brouard 10620:
1.332 brouard 10621: strcpy(resultsav,resultline);
10622: printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline);
1.230 brouard 10623: if (strlen(resultsav) >1){
1.334 brouard 10624: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 10625: }
1.253 brouard 10626: if(j == 0){ /* Resultline but no = */
10627: TKresult[nres]=0; /* Combination for the nresult and the model */
10628: return (0);
10629: }
1.234 brouard 10630: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 10631: printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, %s.\n",j, cptcovs, model);
10632: fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, %s.\n",j, cptcovs, model);
1.332 brouard 10633: /* return 1;*/
1.234 brouard 10634: }
1.334 brouard 10635: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 10636: if(nbocc(resultsav,'=') >1){
1.318 brouard 10637: 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 10638: /* 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 10639: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 10640: /* If a blank, then strc="V4=" and strd='\0' */
10641: if(strc[0]=='\0'){
10642: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
10643: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
10644: return 1;
10645: }
1.234 brouard 10646: }else
10647: cutl(strc,strd,resultsav,'=');
1.318 brouard 10648: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10649:
1.230 brouard 10650: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10651: 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 10652: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10653: /* cptcovsel++; */
10654: if (nbocc(stra,'=') >0)
10655: strcpy(resultsav,stra); /* and analyzes it */
10656: }
1.235 brouard 10657: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10658: /* 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 10659: 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 10660: if(Typevar[k1]==0){ /* Single covariate in model */
10661: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10662: match=0;
1.318 brouard 10663: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10664: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10665: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10666: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10667: break;
10668: }
10669: }
10670: if(match == 0){
1.338 brouard 10671: 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]);
10672: 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 10673: return 1;
1.234 brouard 10674: }
1.332 brouard 10675: }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*/
10676: /* We feed resultmodel[k1]=k2; */
10677: match=0;
10678: 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 */
10679: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10680: 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 10681: resultmodel[nres][k1]=k2; /* Added here */
10682: printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]);
10683: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10684: break;
10685: }
10686: }
10687: if(match == 0){
1.338 brouard 10688: 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]);
10689: 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 10690: return 1;
10691: }
10692: }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/
10693: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
10694: match=0;
10695: 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]);
10696: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10697: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10698: /* modelresult[k2]=k1; */
10699: printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]);
10700: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10701: }
10702: }
10703: if(match == 0){
1.338 brouard 10704: printf("Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
10705: fprintf(ficlog,"Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 10706: return 1;
10707: }
10708: match=0;
10709: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10710: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10711: /* modelresult[k2]=k1;*/
10712: printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]);
10713: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10714: break;
10715: }
10716: }
10717: if(match == 0){
1.338 brouard 10718: printf("Error in result line (Product without age second variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
10719: fprintf(ficlog,"Error in result line (Product without age second variable): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 10720: return 1;
10721: }
10722: }/* End of testing */
1.333 brouard 10723: }/* End loop cptcovt */
1.235 brouard 10724: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10725: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 10726: 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)
10727: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 10728: match=0;
1.318 brouard 10729: 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 10730: if(Typevar[k1]==0){ /* Single only */
1.237 brouard 10731: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.330 brouard 10732: 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 10733: 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 10734: ++match;
10735: }
10736: }
10737: }
10738: if(match == 0){
1.338 brouard 10739: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
10740: 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 10741: return 1;
1.234 brouard 10742: }else if(match > 1){
1.338 brouard 10743: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
10744: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 10745: return 1;
1.234 brouard 10746: }
10747: }
1.334 brouard 10748: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 10749: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10750: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 10751: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10752: /* 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*/
10753: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 10754: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10755: /* 1 0 0 0 */
10756: /* 2 1 0 0 */
10757: /* 3 0 1 0 */
1.330 brouard 10758: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 10759: /* 5 0 0 1 */
1.330 brouard 10760: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 10761: /* 7 0 1 1 */
10762: /* 8 1 1 1 */
1.237 brouard 10763: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10764: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10765: /* V5*age V5 known which value for nres? */
10766: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 10767: 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.
10768: * loop on position k1 in the MODEL LINE */
1.331 brouard 10769: /* k counting number of combination of single dummies in the equation model */
10770: /* k4 counting single dummies in the equation model */
10771: /* k4q counting single quantitatives in the equation model */
1.334 brouard 10772: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, k1 is sorting according to MODEL, but k3 to resultline */
10773: /* 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 10774: /* 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 10775: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 10776: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
10777: /* k3 is the position in the nres result line of the k1th variable of the model equation */
10778: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
10779: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
10780: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 10781: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 10782: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 10783: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 10784: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
10785: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
10786: 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 10787: 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 10788: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 10789: /* Tinvresult[nres][4]=1 */
1.334 brouard 10790: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
10791: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
10792: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
10793: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 10794: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 10795: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.332 brouard 10796: 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 10797: k4++;;
1.331 brouard 10798: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 10799: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 10800: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 10801: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 10802: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
10803: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
10804: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 10805: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
10806: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
10807: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
10808: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10809: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
10810: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 10811: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 10812: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 10813: precov[nres][k1]=Tvalsel[k3q];
10814: 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 10815: k4q++;;
1.331 brouard 10816: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
10817: /* Tvar[k1]; */ /* Age variable */
1.332 brouard 10818: /* Wrong we want the value of variable name Tvar[k1] */
10819:
10820: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
1.331 brouard 10821: k2=(int)Tvarsel[k3]; /* nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
1.334 brouard 10822: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
1.332 brouard 10823: precov[nres][k1]=Tvalsel[k3];
10824: 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 10825: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.332 brouard 10826: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.331 brouard 10827: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 10828: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
1.332 brouard 10829: precov[nres][k1]=Tvalsel[k3q];
1.334 brouard 10830: printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
1.331 brouard 10831: }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
1.332 brouard 10832: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
10833: 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 10834: }else{
1.332 brouard 10835: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
10836: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 10837: }
10838: }
1.234 brouard 10839:
1.334 brouard 10840: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 10841: return (0);
10842: }
1.235 brouard 10843:
1.230 brouard 10844: int decodemodel( char model[], int lastobs)
10845: /**< This routine decodes the model and returns:
1.224 brouard 10846: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10847: * - nagesqr = 1 if age*age in the model, otherwise 0.
10848: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10849: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10850: * - cptcovage number of covariates with age*products =2
10851: * - cptcovs number of simple covariates
1.339 brouard 10852: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 10853: * - 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 10854: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 10855: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10856: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10857: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10858: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10859: */
1.319 brouard 10860: /* 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 10861: {
1.238 brouard 10862: int i, j, k, ks, v;
1.227 brouard 10863: int j1, k1, k2, k3, k4;
1.136 brouard 10864: char modelsav[80];
1.145 brouard 10865: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10866: char *strpt;
1.136 brouard 10867:
1.145 brouard 10868: /*removespace(model);*/
1.136 brouard 10869: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10870: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10871: if (strstr(model,"AGE") !=0){
1.192 brouard 10872: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10873: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10874: return 1;
10875: }
1.141 brouard 10876: if (strstr(model,"v") !=0){
1.338 brouard 10877: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
10878: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 10879: return 1;
10880: }
1.187 brouard 10881: strcpy(modelsav,model);
10882: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 10883: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 10884: if(strpt != model){
1.338 brouard 10885: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10886: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10887: corresponding column of parameters.\n",model);
1.338 brouard 10888: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10889: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10890: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10891: return 1;
1.225 brouard 10892: }
1.187 brouard 10893: nagesqr=1;
10894: if (strstr(model,"+age*age") !=0)
1.234 brouard 10895: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10896: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10897: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10898: else
1.234 brouard 10899: substrchaine(modelsav, model, "age*age");
1.187 brouard 10900: }else
10901: nagesqr=0;
10902: if (strlen(modelsav) >1){
10903: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10904: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10905: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10906: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10907: * cst, age and age*age
10908: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10909: /* including age products which are counted in cptcovage.
10910: * but the covariates which are products must be treated
10911: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10912: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10913: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10914:
10915:
1.187 brouard 10916: /* Design
10917: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10918: * < ncovcol=8 >
10919: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10920: * k= 1 2 3 4 5 6 7 8
10921: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10922: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10923: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10924: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10925: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10926: * Tage[++cptcovage]=k
10927: * if products, new covar are created after ncovcol with k1
10928: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10929: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10930: * 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
10931: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10932: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10933: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10934: * < ncovcol=8 >
10935: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10936: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10937: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10938: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10939: * p Tprod[1]@2={ 6, 5}
10940: *p Tvard[1][1]@4= {7, 8, 5, 6}
10941: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10942: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10943: *How to reorganize? Tvars(orted)
1.187 brouard 10944: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10945: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10946: * {2, 1, 4, 8, 5, 6, 3, 7}
10947: * Struct []
10948: */
1.225 brouard 10949:
1.187 brouard 10950: /* This loop fills the array Tvar from the string 'model'.*/
10951: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10952: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10953: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10954: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10955: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10956: /* k=1 Tvar[1]=2 (from V2) */
10957: /* k=5 Tvar[5] */
10958: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10959: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10960: /* } */
1.198 brouard 10961: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10962: /*
10963: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10964: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10965: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10966: }
1.187 brouard 10967: cptcovage=0;
1.319 brouard 10968: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10969: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10970: 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" */
10971: if (nbocc(modelsav,'+')==0)
10972: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10973: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10974: /*scanf("%d",i);*/
1.319 brouard 10975: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10976: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
1.234 brouard 10977: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10978: /* covar is not filled and then is empty */
10979: cptcovprod--;
10980: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10981: Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
1.234 brouard 10982: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10983: cptcovage++; /* Counts the number of covariates which include age as a product */
10984: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.234 brouard 10985: /*printf("stre=%s ", stre);*/
10986: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10987: cptcovprod--;
10988: cutl(stre,strb,strc,'V');
10989: Tvar[k]=atoi(stre);
10990: Typevar[k]=1; /* 1 for age product */
10991: cptcovage++;
10992: Tage[cptcovage]=k;
10993: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10994: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10995: cptcovn++;
10996: cptcovprodnoage++;k1++;
10997: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.339 brouard 10998: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
1.234 brouard 10999: because this model-covariate is a construction we invent a new column
11000: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.335 brouard 11001: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
1.319 brouard 11002: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
1.339 brouard 11003: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
1.335 brouard 11004: /* Please remark that the new variables are model dependent */
11005: /* If we have 4 variable but the model uses only 3, like in
11006: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11007: * k= 1 2 3 4 5 6 7 8
11008: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11009: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11010: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11011: */
1.339 brouard 11012: Typevar[k]=2; /* 2 for product */
1.234 brouard 11013: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11014: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 11015: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 11016: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
1.330 brouard 11017: Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
1.234 brouard 11018: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
1.330 brouard 11019: Tvardk[k][2] =atoi(stre); /* n 4 for V4*/
1.234 brouard 11020: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11021: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11022: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 11023: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 11024: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
1.339 brouard 11025: 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 */
11026: for (i=1; i<=lastobs;i++){/* For fixed product */
1.234 brouard 11027: /* Computes the new covariate which is a product of
11028: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
1.339 brouard 11029: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11030: }
11031: } /*End of FixedV */
1.234 brouard 11032: } /* End age is not in the model */
11033: } /* End if model includes a product */
1.319 brouard 11034: else { /* not a product */
1.234 brouard 11035: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11036: /* scanf("%d",i);*/
11037: cutl(strd,strc,strb,'V');
11038: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11039: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11040: Tvar[k]=atoi(strd);
11041: Typevar[k]=0; /* 0 for simple covariates */
11042: }
11043: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11044: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11045: scanf("%d",i);*/
1.187 brouard 11046: } /* end of loop + on total covariates */
11047: } /* end if strlen(modelsave == 0) age*age might exist */
11048: } /* end if strlen(model == 0) */
1.136 brouard 11049:
11050: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11051: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11052:
1.136 brouard 11053: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11054: printf("cptcovprod=%d ", cptcovprod);
11055: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11056: scanf("%d ",i);*/
11057:
11058:
1.230 brouard 11059: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11060: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11061: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11062: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11063: k = 1 2 3 4 5 6 7 8 9
11064: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11065: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11066: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11067: Dummy[k] 1 0 0 0 3 1 1 2 3
11068: Tmodelind[combination of covar]=k;
1.225 brouard 11069: */
11070: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11071: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11072: /* 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 11073: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11074: printf("Model=1+age+%s\n\
1.227 brouard 11075: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11076: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11077: 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 11078: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 11079: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11080: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11081: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.285 brouard 11082: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.339 brouard 11083: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt */
1.234 brouard 11084: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11085: Fixed[k]= 0;
11086: Dummy[k]= 0;
1.225 brouard 11087: ncoveff++;
1.232 brouard 11088: ncovf++;
1.234 brouard 11089: nsd++;
11090: modell[k].maintype= FTYPE;
11091: TvarsD[nsd]=Tvar[k];
11092: TvarsDind[nsd]=k;
1.330 brouard 11093: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11094: TvarF[ncovf]=Tvar[k];
11095: TvarFind[ncovf]=k;
11096: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11097: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11098: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
11099: }else if( Tposprod[k]>0 && Typevar[k]==2 && FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol */
1.234 brouard 11100: Fixed[k]= 0;
11101: Dummy[k]= 0;
11102: ncoveff++;
11103: ncovf++;
11104: modell[k].maintype= FTYPE;
11105: TvarF[ncovf]=Tvar[k];
1.330 brouard 11106: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
1.234 brouard 11107: TvarFind[ncovf]=k;
1.230 brouard 11108: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 11109: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 11110: }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 11111: Fixed[k]= 0;
11112: Dummy[k]= 1;
1.230 brouard 11113: nqfveff++;
1.234 brouard 11114: modell[k].maintype= FTYPE;
11115: modell[k].subtype= FQ;
11116: nsq++;
1.334 brouard 11117: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11118: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11119: ncovf++;
1.234 brouard 11120: TvarF[ncovf]=Tvar[k];
11121: TvarFind[ncovf]=k;
1.231 brouard 11122: 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 11123: 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 11124: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11125: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11126: /* model V1+V3+age*V1+age*V3+V1*V3 */
11127: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11128: ncovvt++;
11129: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11130: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11131:
1.227 brouard 11132: Fixed[k]= 1;
11133: Dummy[k]= 0;
1.225 brouard 11134: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11135: modell[k].maintype= VTYPE;
11136: modell[k].subtype= VD;
11137: nsd++;
11138: TvarsD[nsd]=Tvar[k];
11139: TvarsDind[nsd]=k;
1.330 brouard 11140: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11141: ncovv++; /* Only simple time varying variables */
11142: TvarV[ncovv]=Tvar[k];
1.242 brouard 11143: 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 11144: 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 */
11145: 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 11146: 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);
11147: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11148: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11149: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11150: /* model V1+V3+age*V1+age*V3+V1*V3 */
11151: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11152: ncovvt++;
11153: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11154: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11155:
1.234 brouard 11156: Fixed[k]= 1;
11157: Dummy[k]= 1;
11158: nqtveff++;
11159: modell[k].maintype= VTYPE;
11160: modell[k].subtype= VQ;
11161: ncovv++; /* Only simple time varying variables */
11162: nsq++;
1.334 brouard 11163: 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) */
11164: 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 11165: TvarV[ncovv]=Tvar[k];
1.242 brouard 11166: 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 11167: 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 */
11168: 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 11169: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11170: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
11171: printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%d,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv);
1.228 brouard 11172: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 11173: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11174: ncova++;
11175: TvarA[ncova]=Tvar[k];
11176: TvarAind[ncova]=k;
1.231 brouard 11177: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11178: Fixed[k]= 2;
11179: Dummy[k]= 2;
11180: modell[k].maintype= ATYPE;
11181: modell[k].subtype= APFD;
11182: /* ncoveff++; */
1.227 brouard 11183: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11184: Fixed[k]= 2;
11185: Dummy[k]= 3;
11186: modell[k].maintype= ATYPE;
11187: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
11188: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11189: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11190: Fixed[k]= 3;
11191: Dummy[k]= 2;
11192: modell[k].maintype= ATYPE;
11193: modell[k].subtype= APVD; /* Product age * varying dummy */
11194: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11195: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11196: Fixed[k]= 3;
11197: Dummy[k]= 3;
11198: modell[k].maintype= ATYPE;
11199: modell[k].subtype= APVQ; /* Product age * varying quantitative */
11200: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11201: }
1.339 brouard 11202: }else if (Typevar[k] == 2) { /* product Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
11203: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11204: /* model V1+V3+age*V1+age*V3+V1*V3 */
11205: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11206: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1} k1=1 first product but second time varying because of V3 */
11207: ncovvt++;
11208: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11209: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11210: ncovvt++;
11211: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11212: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11213:
11214:
11215: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11216: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.240 brouard 11217: Fixed[k]= 1;
11218: Dummy[k]= 0;
11219: modell[k].maintype= FTYPE;
11220: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11221: ncovf++; /* Fixed variables without age */
11222: TvarF[ncovf]=Tvar[k];
11223: TvarFind[ncovf]=k;
1.339 brouard 11224: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11225: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11226: Dummy[k]= 1;
11227: modell[k].maintype= FTYPE;
11228: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11229: ncovf++; /* Varying variables without age */
11230: TvarF[ncovf]=Tvar[k];
11231: TvarFind[ncovf]=k;
1.339 brouard 11232: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.240 brouard 11233: Fixed[k]= 1;
11234: Dummy[k]= 0;
11235: modell[k].maintype= VTYPE;
11236: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11237: ncovv++; /* Varying variables without age */
1.339 brouard 11238: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11239: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11240: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.240 brouard 11241: Fixed[k]= 1;
11242: Dummy[k]= 1;
11243: modell[k].maintype= VTYPE;
11244: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11245: ncovv++; /* Varying variables without age */
11246: TvarV[ncovv]=Tvar[k];
11247: TvarVind[ncovv]=k;
11248: }
1.339 brouard 11249: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11250: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11251: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11252: Dummy[k]= 1;
11253: modell[k].maintype= FTYPE;
11254: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11255: ncovf++; /* Fixed variables without age */
11256: TvarF[ncovf]=Tvar[k];
11257: TvarFind[ncovf]=k;
1.339 brouard 11258: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.240 brouard 11259: Fixed[k]= 1;
11260: Dummy[k]= 1;
11261: modell[k].maintype= VTYPE;
11262: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11263: ncovv++; /* Varying variables without age */
11264: TvarV[ncovv]=Tvar[k];
11265: TvarVind[ncovv]=k;
1.339 brouard 11266: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.240 brouard 11267: Fixed[k]= 1;
11268: Dummy[k]= 1;
11269: modell[k].maintype= VTYPE;
11270: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11271: ncovv++; /* Varying variables without age */
11272: TvarV[ncovv]=Tvar[k];
11273: TvarVind[ncovv]=k;
11274: ncovv++; /* Varying variables without age */
11275: TvarV[ncovv]=Tvar[k];
11276: TvarVind[ncovv]=k;
11277: }
1.339 brouard 11278: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 11279: if(Tvard[k1][2] <=ncovcol){
11280: Fixed[k]= 1;
11281: Dummy[k]= 1;
11282: modell[k].maintype= VTYPE;
11283: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11284: ncovv++; /* Varying variables without age */
11285: TvarV[ncovv]=Tvar[k];
11286: TvarVind[ncovv]=k;
11287: }else if(Tvard[k1][2] <=ncovcol+nqv){
11288: Fixed[k]= 1;
11289: Dummy[k]= 1;
11290: modell[k].maintype= VTYPE;
11291: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11292: ncovv++; /* Varying variables without age */
11293: TvarV[ncovv]=Tvar[k];
11294: TvarVind[ncovv]=k;
11295: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11296: Fixed[k]= 1;
11297: Dummy[k]= 0;
11298: modell[k].maintype= VTYPE;
11299: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
11300: ncovv++; /* Varying variables without age */
11301: TvarV[ncovv]=Tvar[k];
11302: TvarVind[ncovv]=k;
11303: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11304: Fixed[k]= 1;
11305: Dummy[k]= 1;
11306: modell[k].maintype= VTYPE;
11307: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
11308: ncovv++; /* Varying variables without age */
11309: TvarV[ncovv]=Tvar[k];
11310: TvarVind[ncovv]=k;
11311: }
1.339 brouard 11312: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 11313: if(Tvard[k1][2] <=ncovcol){
11314: Fixed[k]= 1;
11315: Dummy[k]= 1;
11316: modell[k].maintype= VTYPE;
11317: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
11318: ncovv++; /* Varying variables without age */
11319: TvarV[ncovv]=Tvar[k];
11320: TvarVind[ncovv]=k;
11321: }else if(Tvard[k1][2] <=ncovcol+nqv){
11322: Fixed[k]= 1;
11323: Dummy[k]= 1;
11324: modell[k].maintype= VTYPE;
11325: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
11326: ncovv++; /* Varying variables without age */
11327: TvarV[ncovv]=Tvar[k];
11328: TvarVind[ncovv]=k;
11329: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11330: Fixed[k]= 1;
11331: Dummy[k]= 1;
11332: modell[k].maintype= VTYPE;
11333: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
11334: ncovv++; /* Varying variables without age */
11335: TvarV[ncovv]=Tvar[k];
11336: TvarVind[ncovv]=k;
11337: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11338: Fixed[k]= 1;
11339: Dummy[k]= 1;
11340: modell[k].maintype= VTYPE;
11341: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
11342: ncovv++; /* Varying variables without age */
11343: TvarV[ncovv]=Tvar[k];
11344: TvarVind[ncovv]=k;
11345: }
1.227 brouard 11346: }else{
1.240 brouard 11347: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11348: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11349: } /*end k1*/
1.225 brouard 11350: }else{
1.226 brouard 11351: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
11352: 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 11353: }
1.227 brouard 11354: printf("Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[k],Dummy[k]);
1.231 brouard 11355: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 11356: 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]);
11357: }
11358: /* Searching for doublons in the model */
11359: for(k1=1; k1<= cptcovt;k1++){
11360: for(k2=1; k2 <k1;k2++){
1.285 brouard 11361: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
11362: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 11363: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
11364: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 11365: 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]);
11366: 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 11367: return(1);
11368: }
11369: }else if (Typevar[k1] ==2){
11370: k3=Tposprod[k1];
11371: k4=Tposprod[k2];
11372: 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 11373: 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]]);
11374: 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 11375: return(1);
11376: }
11377: }
1.227 brouard 11378: }
11379: }
1.225 brouard 11380: }
11381: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
11382: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 11383: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
11384: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 11385: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 11386: /*endread:*/
1.225 brouard 11387: printf("Exiting decodemodel: ");
11388: return (1);
1.136 brouard 11389: }
11390:
1.169 brouard 11391: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 11392: {/* Check ages at death */
1.136 brouard 11393: int i, m;
1.218 brouard 11394: int firstone=0;
11395:
1.136 brouard 11396: for (i=1; i<=imx; i++) {
11397: for(m=2; (m<= maxwav); m++) {
11398: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
11399: anint[m][i]=9999;
1.216 brouard 11400: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
11401: s[m][i]=-1;
1.136 brouard 11402: }
11403: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 11404: *nberr = *nberr + 1;
1.218 brouard 11405: if(firstone == 0){
11406: firstone=1;
1.260 brouard 11407: 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 11408: }
1.262 brouard 11409: 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 11410: s[m][i]=-1; /* Droping the death status */
1.136 brouard 11411: }
11412: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 11413: (*nberr)++;
1.259 brouard 11414: 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 11415: 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 11416: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 11417: }
11418: }
11419: }
11420:
11421: for (i=1; i<=imx; i++) {
11422: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
11423: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 11424: 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 11425: if (s[m][i] >= nlstate+1) {
1.169 brouard 11426: if(agedc[i]>0){
11427: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 11428: agev[m][i]=agedc[i];
1.214 brouard 11429: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 11430: }else {
1.136 brouard 11431: if ((int)andc[i]!=9999){
11432: nbwarn++;
11433: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
11434: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
11435: agev[m][i]=-1;
11436: }
11437: }
1.169 brouard 11438: } /* agedc > 0 */
1.214 brouard 11439: } /* end if */
1.136 brouard 11440: else if(s[m][i] !=9){ /* Standard case, age in fractional
11441: years but with the precision of a month */
11442: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
11443: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
11444: agev[m][i]=1;
11445: else if(agev[m][i] < *agemin){
11446: *agemin=agev[m][i];
11447: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
11448: }
11449: else if(agev[m][i] >*agemax){
11450: *agemax=agev[m][i];
1.156 brouard 11451: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 11452: }
11453: /*agev[m][i]=anint[m][i]-annais[i];*/
11454: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 11455: } /* en if 9*/
1.136 brouard 11456: else { /* =9 */
1.214 brouard 11457: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 11458: agev[m][i]=1;
11459: s[m][i]=-1;
11460: }
11461: }
1.214 brouard 11462: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 11463: agev[m][i]=1;
1.214 brouard 11464: else{
11465: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11466: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11467: agev[m][i]=0;
11468: }
11469: } /* End for lastpass */
11470: }
1.136 brouard 11471:
11472: for (i=1; i<=imx; i++) {
11473: for(m=firstpass; (m<=lastpass); m++){
11474: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 11475: (*nberr)++;
1.136 brouard 11476: 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);
11477: 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);
11478: return 1;
11479: }
11480: }
11481: }
11482:
11483: /*for (i=1; i<=imx; i++){
11484: for (m=firstpass; (m<lastpass); m++){
11485: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
11486: }
11487:
11488: }*/
11489:
11490:
1.139 brouard 11491: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
11492: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 11493:
11494: return (0);
1.164 brouard 11495: /* endread:*/
1.136 brouard 11496: printf("Exiting calandcheckages: ");
11497: return (1);
11498: }
11499:
1.172 brouard 11500: #if defined(_MSC_VER)
11501: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11502: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11503: //#include "stdafx.h"
11504: //#include <stdio.h>
11505: //#include <tchar.h>
11506: //#include <windows.h>
11507: //#include <iostream>
11508: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
11509:
11510: LPFN_ISWOW64PROCESS fnIsWow64Process;
11511:
11512: BOOL IsWow64()
11513: {
11514: BOOL bIsWow64 = FALSE;
11515:
11516: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
11517: // (HANDLE, PBOOL);
11518:
11519: //LPFN_ISWOW64PROCESS fnIsWow64Process;
11520:
11521: HMODULE module = GetModuleHandle(_T("kernel32"));
11522: const char funcName[] = "IsWow64Process";
11523: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
11524: GetProcAddress(module, funcName);
11525:
11526: if (NULL != fnIsWow64Process)
11527: {
11528: if (!fnIsWow64Process(GetCurrentProcess(),
11529: &bIsWow64))
11530: //throw std::exception("Unknown error");
11531: printf("Unknown error\n");
11532: }
11533: return bIsWow64 != FALSE;
11534: }
11535: #endif
1.177 brouard 11536:
1.191 brouard 11537: void syscompilerinfo(int logged)
1.292 brouard 11538: {
11539: #include <stdint.h>
11540:
11541: /* #include "syscompilerinfo.h"*/
1.185 brouard 11542: /* command line Intel compiler 32bit windows, XP compatible:*/
11543: /* /GS /W3 /Gy
11544: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
11545: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
11546: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 11547: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
11548: */
11549: /* 64 bits */
1.185 brouard 11550: /*
11551: /GS /W3 /Gy
11552: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
11553: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
11554: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
11555: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
11556: /* Optimization are useless and O3 is slower than O2 */
11557: /*
11558: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
11559: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
11560: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
11561: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
11562: */
1.186 brouard 11563: /* Link is */ /* /OUT:"visual studio
1.185 brouard 11564: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
11565: /PDB:"visual studio
11566: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
11567: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
11568: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
11569: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
11570: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
11571: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
11572: uiAccess='false'"
11573: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
11574: /NOLOGO /TLBID:1
11575: */
1.292 brouard 11576:
11577:
1.177 brouard 11578: #if defined __INTEL_COMPILER
1.178 brouard 11579: #if defined(__GNUC__)
11580: struct utsname sysInfo; /* For Intel on Linux and OS/X */
11581: #endif
1.177 brouard 11582: #elif defined(__GNUC__)
1.179 brouard 11583: #ifndef __APPLE__
1.174 brouard 11584: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 11585: #endif
1.177 brouard 11586: struct utsname sysInfo;
1.178 brouard 11587: int cross = CROSS;
11588: if (cross){
11589: printf("Cross-");
1.191 brouard 11590: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 11591: }
1.174 brouard 11592: #endif
11593:
1.191 brouard 11594: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 11595: #if defined(__clang__)
1.191 brouard 11596: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 11597: #endif
11598: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 11599: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 11600: #endif
11601: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 11602: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 11603: #endif
11604: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 11605: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 11606: #endif
11607: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 11608: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 11609: #endif
11610: #if defined(_MSC_VER)
1.191 brouard 11611: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 11612: #endif
11613: #if defined(__PGI)
1.191 brouard 11614: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 11615: #endif
11616: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 11617: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 11618: #endif
1.191 brouard 11619: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 11620:
1.167 brouard 11621: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
11622: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
11623: // Windows (x64 and x86)
1.191 brouard 11624: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 11625: #elif __unix__ // all unices, not all compilers
11626: // Unix
1.191 brouard 11627: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 11628: #elif __linux__
11629: // linux
1.191 brouard 11630: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 11631: #elif __APPLE__
1.174 brouard 11632: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 11633: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 11634: #endif
11635:
11636: /* __MINGW32__ */
11637: /* __CYGWIN__ */
11638: /* __MINGW64__ */
11639: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
11640: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
11641: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
11642: /* _WIN64 // Defined for applications for Win64. */
11643: /* _M_X64 // Defined for compilations that target x64 processors. */
11644: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 11645:
1.167 brouard 11646: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 11647: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 11648: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 11649: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 11650: #else
1.191 brouard 11651: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 11652: #endif
11653:
1.169 brouard 11654: #if defined(__GNUC__)
11655: # if defined(__GNUC_PATCHLEVEL__)
11656: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11657: + __GNUC_MINOR__ * 100 \
11658: + __GNUC_PATCHLEVEL__)
11659: # else
11660: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11661: + __GNUC_MINOR__ * 100)
11662: # endif
1.174 brouard 11663: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 11664: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 11665:
11666: if (uname(&sysInfo) != -1) {
11667: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 11668: 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 11669: }
11670: else
11671: perror("uname() error");
1.179 brouard 11672: //#ifndef __INTEL_COMPILER
11673: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 11674: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 11675: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 11676: #endif
1.169 brouard 11677: #endif
1.172 brouard 11678:
1.286 brouard 11679: // void main ()
1.172 brouard 11680: // {
1.169 brouard 11681: #if defined(_MSC_VER)
1.174 brouard 11682: if (IsWow64()){
1.191 brouard 11683: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
11684: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 11685: }
11686: else{
1.191 brouard 11687: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
11688: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 11689: }
1.172 brouard 11690: // printf("\nPress Enter to continue...");
11691: // getchar();
11692: // }
11693:
1.169 brouard 11694: #endif
11695:
1.167 brouard 11696:
1.219 brouard 11697: }
1.136 brouard 11698:
1.219 brouard 11699: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 11700: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 11701: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 11702: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 11703: /* double ftolpl = 1.e-10; */
1.180 brouard 11704: double age, agebase, agelim;
1.203 brouard 11705: double tot;
1.180 brouard 11706:
1.202 brouard 11707: strcpy(filerespl,"PL_");
11708: strcat(filerespl,fileresu);
11709: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 11710: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
11711: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11712: }
1.288 brouard 11713: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11714: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11715: pstamp(ficrespl);
1.288 brouard 11716: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11717: fprintf(ficrespl,"#Age ");
11718: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11719: fprintf(ficrespl,"\n");
1.180 brouard 11720:
1.219 brouard 11721: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11722:
1.219 brouard 11723: agebase=ageminpar;
11724: agelim=agemaxpar;
1.180 brouard 11725:
1.227 brouard 11726: /* i1=pow(2,ncoveff); */
1.234 brouard 11727: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11728: if (cptcovn < 1){i1=1;}
1.180 brouard 11729:
1.337 brouard 11730: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 11731: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 11732: k=TKresult[nres];
1.338 brouard 11733: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11734: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
11735: /* continue; */
1.235 brouard 11736:
1.238 brouard 11737: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11738: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11739: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11740: /* k=k+1; */
11741: /* to clean */
1.332 brouard 11742: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11743: fprintf(ficrespl,"#******");
11744: printf("#******");
11745: fprintf(ficlog,"#******");
1.337 brouard 11746: 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 11747: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 11748: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11749: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11750: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11751: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11752: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11753: }
11754: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11755: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11756: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11757: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11758: /* } */
1.238 brouard 11759: fprintf(ficrespl,"******\n");
11760: printf("******\n");
11761: fprintf(ficlog,"******\n");
11762: if(invalidvarcomb[k]){
11763: printf("\nCombination (%d) ignored because no case \n",k);
11764: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
11765: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
11766: continue;
11767: }
1.219 brouard 11768:
1.238 brouard 11769: fprintf(ficrespl,"#Age ");
1.337 brouard 11770: /* for(j=1;j<=cptcoveff;j++) { */
11771: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11772: /* } */
11773: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
11774: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11775: }
11776: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
11777: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 11778:
1.238 brouard 11779: for (age=agebase; age<=agelim; age++){
11780: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 11781: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
11782: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 11783: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 11784: /* for(j=1;j<=cptcoveff;j++) */
11785: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11786: for(j=1;j<=cptcovs;j++)
11787: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11788: tot=0.;
11789: for(i=1; i<=nlstate;i++){
11790: tot += prlim[i][i];
11791: fprintf(ficrespl," %.5f", prlim[i][i]);
11792: }
11793: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
11794: } /* Age */
11795: /* was end of cptcod */
1.337 brouard 11796: } /* nres */
11797: /* } /\* for each combination *\/ */
1.219 brouard 11798: return 0;
1.180 brouard 11799: }
11800:
1.218 brouard 11801: 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 11802: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 11803:
11804: /* Computes the back prevalence limit for any combination of covariate values
11805: * at any age between ageminpar and agemaxpar
11806: */
1.235 brouard 11807: int i, j, k, i1, nres=0 ;
1.217 brouard 11808: /* double ftolpl = 1.e-10; */
11809: double age, agebase, agelim;
11810: double tot;
1.218 brouard 11811: /* double ***mobaverage; */
11812: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 11813:
11814: strcpy(fileresplb,"PLB_");
11815: strcat(fileresplb,fileresu);
11816: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 11817: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
11818: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 11819: }
1.288 brouard 11820: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
11821: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 11822: pstamp(ficresplb);
1.288 brouard 11823: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 11824: fprintf(ficresplb,"#Age ");
11825: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
11826: fprintf(ficresplb,"\n");
11827:
1.218 brouard 11828:
11829: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
11830:
11831: agebase=ageminpar;
11832: agelim=agemaxpar;
11833:
11834:
1.227 brouard 11835: i1=pow(2,cptcoveff);
1.218 brouard 11836: if (cptcovn < 1){i1=1;}
1.227 brouard 11837:
1.238 brouard 11838: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 11839: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
11840: k=TKresult[nres];
11841: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11842: /* if(i1 != 1 && TKresult[nres]!= k) */
11843: /* continue; */
11844: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 11845: fprintf(ficresplb,"#******");
11846: printf("#******");
11847: fprintf(ficlog,"#******");
1.338 brouard 11848: 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) */
11849: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11850: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11851: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11852: }
1.338 brouard 11853: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
11854: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11855: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11856: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11857: /* } */
11858: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11859: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11860: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11861: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11862: /* } */
1.238 brouard 11863: fprintf(ficresplb,"******\n");
11864: printf("******\n");
11865: fprintf(ficlog,"******\n");
11866: if(invalidvarcomb[k]){
11867: printf("\nCombination (%d) ignored because no cases \n",k);
11868: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
11869: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
11870: continue;
11871: }
1.218 brouard 11872:
1.238 brouard 11873: fprintf(ficresplb,"#Age ");
1.338 brouard 11874: for(j=1;j<=cptcovs;j++) {
11875: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11876: }
11877: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
11878: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 11879:
11880:
1.238 brouard 11881: for (age=agebase; age<=agelim; age++){
11882: /* for (age=agebase; age<=agebase; age++){ */
11883: if(mobilavproj > 0){
11884: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11885: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11886: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11887: }else if (mobilavproj == 0){
11888: 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);
11889: 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);
11890: exit(1);
11891: }else{
11892: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11893: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11894: /* printf("TOTOT\n"); */
11895: /* exit(1); */
1.238 brouard 11896: }
11897: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 11898: for(j=1;j<=cptcovs;j++)
11899: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11900: tot=0.;
11901: for(i=1; i<=nlstate;i++){
11902: tot += bprlim[i][i];
11903: fprintf(ficresplb," %.5f", bprlim[i][i]);
11904: }
11905: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11906: } /* Age */
11907: /* was end of cptcod */
1.255 brouard 11908: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 11909: /* } /\* end of any combination *\/ */
1.238 brouard 11910: } /* end of nres */
1.218 brouard 11911: /* hBijx(p, bage, fage); */
11912: /* fclose(ficrespijb); */
11913:
11914: return 0;
1.217 brouard 11915: }
1.218 brouard 11916:
1.180 brouard 11917: int hPijx(double *p, int bage, int fage){
11918: /*------------- h Pij x at various ages ------------*/
1.336 brouard 11919: /* to be optimized with precov */
1.180 brouard 11920: int stepsize;
11921: int agelim;
11922: int hstepm;
11923: int nhstepm;
1.235 brouard 11924: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11925:
11926: double agedeb;
11927: double ***p3mat;
11928:
1.337 brouard 11929: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
11930: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11931: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11932: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11933: }
11934: printf("Computing pij: result on file '%s' \n", filerespij);
11935: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11936:
11937: stepsize=(int) (stepm+YEARM-1)/YEARM;
11938: /*if (stepm<=24) stepsize=2;*/
11939:
11940: agelim=AGESUP;
11941: hstepm=stepsize*YEARM; /* Every year of age */
11942: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11943:
11944: /* hstepm=1; aff par mois*/
11945: pstamp(ficrespij);
11946: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
11947: i1= pow(2,cptcoveff);
11948: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11949: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11950: /* k=k+1; */
11951: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11952: k=TKresult[nres];
1.338 brouard 11953: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11954: /* for(k=1; k<=i1;k++){ */
11955: /* if(i1 != 1 && TKresult[nres]!= k) */
11956: /* continue; */
11957: fprintf(ficrespij,"\n#****** ");
11958: for(j=1;j<=cptcovs;j++){
11959: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11960: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11961: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11962: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11963: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11964: }
11965: fprintf(ficrespij,"******\n");
11966:
11967: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11968: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11969: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11970:
11971: /* nhstepm=nhstepm*YEARM; aff par mois*/
11972:
11973: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11974: oldm=oldms;savm=savms;
11975: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
11976: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11977: for(i=1; i<=nlstate;i++)
11978: for(j=1; j<=nlstate+ndeath;j++)
11979: fprintf(ficrespij," %1d-%1d",i,j);
11980: fprintf(ficrespij,"\n");
11981: for (h=0; h<=nhstepm; h++){
11982: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11983: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 11984: for(i=1; i<=nlstate;i++)
11985: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 11986: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 11987: fprintf(ficrespij,"\n");
11988: }
1.337 brouard 11989: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11990: fprintf(ficrespij,"\n");
1.180 brouard 11991: }
1.337 brouard 11992: }
11993: /*}*/
11994: return 0;
1.180 brouard 11995: }
1.218 brouard 11996:
11997: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11998: /*------------- h Bij x at various ages ------------*/
1.336 brouard 11999: /* To be optimized with precov */
1.217 brouard 12000: int stepsize;
1.218 brouard 12001: /* int agelim; */
12002: int ageminl;
1.217 brouard 12003: int hstepm;
12004: int nhstepm;
1.238 brouard 12005: int h, i, i1, j, k, nres;
1.218 brouard 12006:
1.217 brouard 12007: double agedeb;
12008: double ***p3mat;
1.218 brouard 12009:
12010: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12011: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12012: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12013: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12014: }
12015: printf("Computing pij back: result on file '%s' \n", filerespijb);
12016: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12017:
12018: stepsize=(int) (stepm+YEARM-1)/YEARM;
12019: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12020:
1.218 brouard 12021: /* agelim=AGESUP; */
1.289 brouard 12022: ageminl=AGEINF; /* was 30 */
1.218 brouard 12023: hstepm=stepsize*YEARM; /* Every year of age */
12024: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12025:
12026: /* hstepm=1; aff par mois*/
12027: pstamp(ficrespijb);
1.255 brouard 12028: 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 12029: i1= pow(2,cptcoveff);
1.218 brouard 12030: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12031: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12032: /* k=k+1; */
1.238 brouard 12033: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12034: k=TKresult[nres];
1.338 brouard 12035: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12036: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12037: /* if(i1 != 1 && TKresult[nres]!= k) */
12038: /* continue; */
12039: fprintf(ficrespijb,"\n#****** ");
12040: for(j=1;j<=cptcovs;j++){
1.338 brouard 12041: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12042: /* for(j=1;j<=cptcoveff;j++) */
12043: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12044: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12045: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12046: }
12047: fprintf(ficrespijb,"******\n");
12048: if(invalidvarcomb[k]){ /* Is it necessary here? */
12049: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12050: continue;
12051: }
12052:
12053: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12054: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12055: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12056: 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 */
12057: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12058:
12059: /* nhstepm=nhstepm*YEARM; aff par mois*/
12060:
12061: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12062: /* and memory limitations if stepm is small */
12063:
12064: /* oldm=oldms;savm=savms; */
12065: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12066: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12067: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12068: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12069: for(i=1; i<=nlstate;i++)
12070: for(j=1; j<=nlstate+ndeath;j++)
12071: fprintf(ficrespijb," %1d-%1d",i,j);
12072: fprintf(ficrespijb,"\n");
12073: for (h=0; h<=nhstepm; h++){
12074: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12075: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12076: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12077: for(i=1; i<=nlstate;i++)
12078: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12079: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12080: fprintf(ficrespijb,"\n");
1.337 brouard 12081: }
12082: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12083: fprintf(ficrespijb,"\n");
12084: } /* end age deb */
12085: /* } /\* end combination *\/ */
1.238 brouard 12086: } /* end nres */
1.218 brouard 12087: return 0;
12088: } /* hBijx */
1.217 brouard 12089:
1.180 brouard 12090:
1.136 brouard 12091: /***********************************************/
12092: /**************** Main Program *****************/
12093: /***********************************************/
12094:
12095: int main(int argc, char *argv[])
12096: {
12097: #ifdef GSL
12098: const gsl_multimin_fminimizer_type *T;
12099: size_t iteri = 0, it;
12100: int rval = GSL_CONTINUE;
12101: int status = GSL_SUCCESS;
12102: double ssval;
12103: #endif
12104: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12105: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12106: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12107: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12108: int jj, ll, li, lj, lk;
1.136 brouard 12109: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12110: int num_filled;
1.136 brouard 12111: int itimes;
12112: int NDIM=2;
12113: int vpopbased=0;
1.235 brouard 12114: int nres=0;
1.258 brouard 12115: int endishere=0;
1.277 brouard 12116: int noffset=0;
1.274 brouard 12117: int ncurrv=0; /* Temporary variable */
12118:
1.164 brouard 12119: char ca[32], cb[32];
1.136 brouard 12120: /* FILE *fichtm; *//* Html File */
12121: /* FILE *ficgp;*/ /*Gnuplot File */
12122: struct stat info;
1.191 brouard 12123: double agedeb=0.;
1.194 brouard 12124:
12125: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 12126: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 12127:
1.165 brouard 12128: double fret;
1.191 brouard 12129: double dum=0.; /* Dummy variable */
1.136 brouard 12130: double ***p3mat;
1.218 brouard 12131: /* double ***mobaverage; */
1.319 brouard 12132: double wald;
1.164 brouard 12133:
12134: char line[MAXLINE];
1.197 brouard 12135: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
12136:
1.234 brouard 12137: char modeltemp[MAXLINE];
1.332 brouard 12138: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 12139:
1.136 brouard 12140: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 12141: char *tok, *val; /* pathtot */
1.334 brouard 12142: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 12143: int c, h , cpt, c2;
1.191 brouard 12144: int jl=0;
12145: int i1, j1, jk, stepsize=0;
1.194 brouard 12146: int count=0;
12147:
1.164 brouard 12148: int *tab;
1.136 brouard 12149: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 12150: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
12151: /* double anprojf, mprojf, jprojf; */
12152: /* double jintmean,mintmean,aintmean; */
12153: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12154: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12155: double yrfproj= 10.0; /* Number of years of forward projections */
12156: double yrbproj= 10.0; /* Number of years of backward projections */
12157: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 12158: int mobilav=0,popforecast=0;
1.191 brouard 12159: int hstepm=0, nhstepm=0;
1.136 brouard 12160: int agemortsup;
12161: float sumlpop=0.;
12162: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
12163: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
12164:
1.191 brouard 12165: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 12166: double ftolpl=FTOL;
12167: double **prlim;
1.217 brouard 12168: double **bprlim;
1.317 brouard 12169: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
12170: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 12171: double ***paramstart; /* Matrix of starting parameter values */
12172: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 12173: double **matcov; /* Matrix of covariance */
1.203 brouard 12174: double **hess; /* Hessian matrix */
1.136 brouard 12175: double ***delti3; /* Scale */
12176: double *delti; /* Scale */
12177: double ***eij, ***vareij;
12178: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 12179:
1.136 brouard 12180: double *epj, vepp;
1.164 brouard 12181:
1.273 brouard 12182: double dateprev1, dateprev2;
1.296 brouard 12183: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
12184: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
12185:
1.217 brouard 12186:
1.136 brouard 12187: double **ximort;
1.145 brouard 12188: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 12189: int *dcwave;
12190:
1.164 brouard 12191: char z[1]="c";
1.136 brouard 12192:
12193: /*char *strt;*/
12194: char strtend[80];
1.126 brouard 12195:
1.164 brouard 12196:
1.126 brouard 12197: /* setlocale (LC_ALL, ""); */
12198: /* bindtextdomain (PACKAGE, LOCALEDIR); */
12199: /* textdomain (PACKAGE); */
12200: /* setlocale (LC_CTYPE, ""); */
12201: /* setlocale (LC_MESSAGES, ""); */
12202:
12203: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 12204: rstart_time = time(NULL);
12205: /* (void) gettimeofday(&start_time,&tzp);*/
12206: start_time = *localtime(&rstart_time);
1.126 brouard 12207: curr_time=start_time;
1.157 brouard 12208: /*tml = *localtime(&start_time.tm_sec);*/
12209: /* strcpy(strstart,asctime(&tml)); */
12210: strcpy(strstart,asctime(&start_time));
1.126 brouard 12211:
12212: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 12213: /* tp.tm_sec = tp.tm_sec +86400; */
12214: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 12215: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
12216: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
12217: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 12218: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 12219: /* strt=asctime(&tmg); */
12220: /* printf("Time(after) =%s",strstart); */
12221: /* (void) time (&time_value);
12222: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
12223: * tm = *localtime(&time_value);
12224: * strstart=asctime(&tm);
12225: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
12226: */
12227:
12228: nberr=0; /* Number of errors and warnings */
12229: nbwarn=0;
1.184 brouard 12230: #ifdef WIN32
12231: _getcwd(pathcd, size);
12232: #else
1.126 brouard 12233: getcwd(pathcd, size);
1.184 brouard 12234: #endif
1.191 brouard 12235: syscompilerinfo(0);
1.196 brouard 12236: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 12237: if(argc <=1){
12238: printf("\nEnter the parameter file name: ");
1.205 brouard 12239: if(!fgets(pathr,FILENAMELENGTH,stdin)){
12240: printf("ERROR Empty parameter file name\n");
12241: goto end;
12242: }
1.126 brouard 12243: i=strlen(pathr);
12244: if(pathr[i-1]=='\n')
12245: pathr[i-1]='\0';
1.156 brouard 12246: i=strlen(pathr);
1.205 brouard 12247: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 12248: pathr[i-1]='\0';
1.205 brouard 12249: }
12250: i=strlen(pathr);
12251: if( i==0 ){
12252: printf("ERROR Empty parameter file name\n");
12253: goto end;
12254: }
12255: for (tok = pathr; tok != NULL; ){
1.126 brouard 12256: printf("Pathr |%s|\n",pathr);
12257: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
12258: printf("val= |%s| pathr=%s\n",val,pathr);
12259: strcpy (pathtot, val);
12260: if(pathr[0] == '\0') break; /* Dirty */
12261: }
12262: }
1.281 brouard 12263: else if (argc<=2){
12264: strcpy(pathtot,argv[1]);
12265: }
1.126 brouard 12266: else{
12267: strcpy(pathtot,argv[1]);
1.281 brouard 12268: strcpy(z,argv[2]);
12269: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 12270: }
12271: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
12272: /*cygwin_split_path(pathtot,path,optionfile);
12273: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
12274: /* cutv(path,optionfile,pathtot,'\\');*/
12275:
12276: /* Split argv[0], imach program to get pathimach */
12277: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
12278: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12279: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12280: /* strcpy(pathimach,argv[0]); */
12281: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
12282: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
12283: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 12284: #ifdef WIN32
12285: _chdir(path); /* Can be a relative path */
12286: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
12287: #else
1.126 brouard 12288: chdir(path); /* Can be a relative path */
1.184 brouard 12289: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
12290: #endif
12291: printf("Current directory %s!\n",pathcd);
1.126 brouard 12292: strcpy(command,"mkdir ");
12293: strcat(command,optionfilefiname);
12294: if((outcmd=system(command)) != 0){
1.169 brouard 12295: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 12296: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
12297: /* fclose(ficlog); */
12298: /* exit(1); */
12299: }
12300: /* if((imk=mkdir(optionfilefiname))<0){ */
12301: /* perror("mkdir"); */
12302: /* } */
12303:
12304: /*-------- arguments in the command line --------*/
12305:
1.186 brouard 12306: /* Main Log file */
1.126 brouard 12307: strcat(filelog, optionfilefiname);
12308: strcat(filelog,".log"); /* */
12309: if((ficlog=fopen(filelog,"w"))==NULL) {
12310: printf("Problem with logfile %s\n",filelog);
12311: goto end;
12312: }
12313: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 12314: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 12315: fprintf(ficlog,"\nEnter the parameter file name: \n");
12316: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
12317: path=%s \n\
12318: optionfile=%s\n\
12319: optionfilext=%s\n\
1.156 brouard 12320: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 12321:
1.197 brouard 12322: syscompilerinfo(1);
1.167 brouard 12323:
1.126 brouard 12324: printf("Local time (at start):%s",strstart);
12325: fprintf(ficlog,"Local time (at start): %s",strstart);
12326: fflush(ficlog);
12327: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 12328: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 12329:
12330: /* */
12331: strcpy(fileres,"r");
12332: strcat(fileres, optionfilefiname);
1.201 brouard 12333: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 12334: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 12335: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 12336:
1.186 brouard 12337: /* Main ---------arguments file --------*/
1.126 brouard 12338:
12339: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 12340: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
12341: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 12342: fflush(ficlog);
1.149 brouard 12343: /* goto end; */
12344: exit(70);
1.126 brouard 12345: }
12346:
12347: strcpy(filereso,"o");
1.201 brouard 12348: strcat(filereso,fileresu);
1.126 brouard 12349: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
12350: printf("Problem with Output resultfile: %s\n", filereso);
12351: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
12352: fflush(ficlog);
12353: goto end;
12354: }
1.278 brouard 12355: /*-------- Rewriting parameter file ----------*/
12356: strcpy(rfileres,"r"); /* "Rparameterfile */
12357: strcat(rfileres,optionfilefiname); /* Parameter file first name */
12358: strcat(rfileres,"."); /* */
12359: strcat(rfileres,optionfilext); /* Other files have txt extension */
12360: if((ficres =fopen(rfileres,"w"))==NULL) {
12361: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
12362: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
12363: fflush(ficlog);
12364: goto end;
12365: }
12366: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 12367:
1.278 brouard 12368:
1.126 brouard 12369: /* Reads comments: lines beginning with '#' */
12370: numlinepar=0;
1.277 brouard 12371: /* Is it a BOM UTF-8 Windows file? */
12372: /* First parameter line */
1.197 brouard 12373: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 12374: noffset=0;
12375: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12376: {
12377: noffset=noffset+3;
12378: printf("# File is an UTF8 Bom.\n"); // 0xBF
12379: }
1.302 brouard 12380: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12381: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 12382: {
12383: noffset=noffset+2;
12384: printf("# File is an UTF16BE BOM file\n");
12385: }
12386: else if( line[0] == 0 && line[1] == 0)
12387: {
12388: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12389: noffset=noffset+4;
12390: printf("# File is an UTF16BE BOM file\n");
12391: }
12392: } else{
12393: ;/*printf(" Not a BOM file\n");*/
12394: }
12395:
1.197 brouard 12396: /* If line starts with a # it is a comment */
1.277 brouard 12397: if (line[noffset] == '#') {
1.197 brouard 12398: numlinepar++;
12399: fputs(line,stdout);
12400: fputs(line,ficparo);
1.278 brouard 12401: fputs(line,ficres);
1.197 brouard 12402: fputs(line,ficlog);
12403: continue;
12404: }else
12405: break;
12406: }
12407: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
12408: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
12409: if (num_filled != 5) {
12410: printf("Should be 5 parameters\n");
1.283 brouard 12411: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 12412: }
1.126 brouard 12413: numlinepar++;
1.197 brouard 12414: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 12415: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12416: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12417: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 12418: }
12419: /* Second parameter line */
12420: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 12421: /* while(fscanf(ficpar,"%[^\n]", line)) { */
12422: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 12423: if (line[0] == '#') {
12424: numlinepar++;
1.283 brouard 12425: printf("%s",line);
12426: fprintf(ficres,"%s",line);
12427: fprintf(ficparo,"%s",line);
12428: fprintf(ficlog,"%s",line);
1.197 brouard 12429: continue;
12430: }else
12431: break;
12432: }
1.223 brouard 12433: 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", \
12434: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
12435: if (num_filled != 11) {
12436: 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 12437: printf("but line=%s\n",line);
1.283 brouard 12438: 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");
12439: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 12440: }
1.286 brouard 12441: if( lastpass > maxwav){
12442: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12443: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12444: fflush(ficlog);
12445: goto end;
12446: }
12447: 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 12448: 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 12449: 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 12450: 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 12451: }
1.203 brouard 12452: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 12453: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 12454: /* Third parameter line */
12455: while(fgets(line, MAXLINE, ficpar)) {
12456: /* If line starts with a # it is a comment */
12457: if (line[0] == '#') {
12458: numlinepar++;
1.283 brouard 12459: printf("%s",line);
12460: fprintf(ficres,"%s",line);
12461: fprintf(ficparo,"%s",line);
12462: fprintf(ficlog,"%s",line);
1.197 brouard 12463: continue;
12464: }else
12465: break;
12466: }
1.201 brouard 12467: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 12468: if (num_filled != 1){
1.302 brouard 12469: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
12470: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 12471: model[0]='\0';
12472: goto end;
12473: }
12474: else{
12475: if (model[0]=='+'){
12476: for(i=1; i<=strlen(model);i++)
12477: modeltemp[i-1]=model[i];
1.201 brouard 12478: strcpy(model,modeltemp);
1.197 brouard 12479: }
12480: }
1.338 brouard 12481: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 12482: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 12483: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
12484: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
12485: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 12486: }
12487: /* 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); */
12488: /* numlinepar=numlinepar+3; /\* In general *\/ */
12489: /* 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 12490: /* 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); */
12491: /* 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 12492: fflush(ficlog);
1.190 brouard 12493: /* if(model[0]=='#'|| model[0]== '\0'){ */
12494: if(model[0]=='#'){
1.279 brouard 12495: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
12496: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
12497: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 12498: if(mle != -1){
1.279 brouard 12499: 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 12500: exit(1);
12501: }
12502: }
1.126 brouard 12503: while((c=getc(ficpar))=='#' && c!= EOF){
12504: ungetc(c,ficpar);
12505: fgets(line, MAXLINE, ficpar);
12506: numlinepar++;
1.195 brouard 12507: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
12508: z[0]=line[1];
12509: }
12510: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 12511: fputs(line, stdout);
12512: //puts(line);
1.126 brouard 12513: fputs(line,ficparo);
12514: fputs(line,ficlog);
12515: }
12516: ungetc(c,ficpar);
12517:
12518:
1.290 brouard 12519: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
12520: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
12521: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
12522: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.340 ! brouard 12523: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /\**< Might be better *\/ */
1.136 brouard 12524: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
12525: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
12526: v1+v2*age+v2*v3 makes cptcovn = 3
12527: */
12528: if (strlen(model)>1)
1.187 brouard 12529: 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 12530: else
1.187 brouard 12531: ncovmodel=2; /* Constant and age */
1.133 brouard 12532: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
12533: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 12534: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
12535: 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);
12536: 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);
12537: fflush(stdout);
12538: fclose (ficlog);
12539: goto end;
12540: }
1.126 brouard 12541: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12542: delti=delti3[1][1];
12543: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
12544: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 12545: /* We could also provide initial parameters values giving by simple logistic regression
12546: * only one way, that is without matrix product. We will have nlstate maximizations */
12547: /* for(i=1;i<nlstate;i++){ */
12548: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12549: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12550: /* } */
1.126 brouard 12551: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 12552: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
12553: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12554: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12555: fclose (ficparo);
12556: fclose (ficlog);
12557: goto end;
12558: exit(0);
1.220 brouard 12559: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 12560: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 12561: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
12562: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12563: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12564: matcov=matrix(1,npar,1,npar);
1.203 brouard 12565: hess=matrix(1,npar,1,npar);
1.220 brouard 12566: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 12567: /* Read guessed parameters */
1.126 brouard 12568: /* Reads comments: lines beginning with '#' */
12569: while((c=getc(ficpar))=='#' && c!= EOF){
12570: ungetc(c,ficpar);
12571: fgets(line, MAXLINE, ficpar);
12572: numlinepar++;
1.141 brouard 12573: fputs(line,stdout);
1.126 brouard 12574: fputs(line,ficparo);
12575: fputs(line,ficlog);
12576: }
12577: ungetc(c,ficpar);
12578:
12579: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 12580: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 12581: for(i=1; i <=nlstate; i++){
1.234 brouard 12582: j=0;
1.126 brouard 12583: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 12584: if(jj==i) continue;
12585: j++;
1.292 brouard 12586: while((c=getc(ficpar))=='#' && c!= EOF){
12587: ungetc(c,ficpar);
12588: fgets(line, MAXLINE, ficpar);
12589: numlinepar++;
12590: fputs(line,stdout);
12591: fputs(line,ficparo);
12592: fputs(line,ficlog);
12593: }
12594: ungetc(c,ficpar);
1.234 brouard 12595: fscanf(ficpar,"%1d%1d",&i1,&j1);
12596: if ((i1 != i) || (j1 != jj)){
12597: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 12598: It might be a problem of design; if ncovcol and the model are correct\n \
12599: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 12600: exit(1);
12601: }
12602: fprintf(ficparo,"%1d%1d",i1,j1);
12603: if(mle==1)
12604: printf("%1d%1d",i,jj);
12605: fprintf(ficlog,"%1d%1d",i,jj);
12606: for(k=1; k<=ncovmodel;k++){
12607: fscanf(ficpar," %lf",¶m[i][j][k]);
12608: if(mle==1){
12609: printf(" %lf",param[i][j][k]);
12610: fprintf(ficlog," %lf",param[i][j][k]);
12611: }
12612: else
12613: fprintf(ficlog," %lf",param[i][j][k]);
12614: fprintf(ficparo," %lf",param[i][j][k]);
12615: }
12616: fscanf(ficpar,"\n");
12617: numlinepar++;
12618: if(mle==1)
12619: printf("\n");
12620: fprintf(ficlog,"\n");
12621: fprintf(ficparo,"\n");
1.126 brouard 12622: }
12623: }
12624: fflush(ficlog);
1.234 brouard 12625:
1.251 brouard 12626: /* Reads parameters values */
1.126 brouard 12627: p=param[1][1];
1.251 brouard 12628: pstart=paramstart[1][1];
1.126 brouard 12629:
12630: /* Reads comments: lines beginning with '#' */
12631: while((c=getc(ficpar))=='#' && c!= EOF){
12632: ungetc(c,ficpar);
12633: fgets(line, MAXLINE, ficpar);
12634: numlinepar++;
1.141 brouard 12635: fputs(line,stdout);
1.126 brouard 12636: fputs(line,ficparo);
12637: fputs(line,ficlog);
12638: }
12639: ungetc(c,ficpar);
12640:
12641: for(i=1; i <=nlstate; i++){
12642: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 12643: fscanf(ficpar,"%1d%1d",&i1,&j1);
12644: if ( (i1-i) * (j1-j) != 0){
12645: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
12646: exit(1);
12647: }
12648: printf("%1d%1d",i,j);
12649: fprintf(ficparo,"%1d%1d",i1,j1);
12650: fprintf(ficlog,"%1d%1d",i1,j1);
12651: for(k=1; k<=ncovmodel;k++){
12652: fscanf(ficpar,"%le",&delti3[i][j][k]);
12653: printf(" %le",delti3[i][j][k]);
12654: fprintf(ficparo," %le",delti3[i][j][k]);
12655: fprintf(ficlog," %le",delti3[i][j][k]);
12656: }
12657: fscanf(ficpar,"\n");
12658: numlinepar++;
12659: printf("\n");
12660: fprintf(ficparo,"\n");
12661: fprintf(ficlog,"\n");
1.126 brouard 12662: }
12663: }
12664: fflush(ficlog);
1.234 brouard 12665:
1.145 brouard 12666: /* Reads covariance matrix */
1.126 brouard 12667: delti=delti3[1][1];
1.220 brouard 12668:
12669:
1.126 brouard 12670: /* 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 12671:
1.126 brouard 12672: /* Reads comments: lines beginning with '#' */
12673: while((c=getc(ficpar))=='#' && c!= EOF){
12674: ungetc(c,ficpar);
12675: fgets(line, MAXLINE, ficpar);
12676: numlinepar++;
1.141 brouard 12677: fputs(line,stdout);
1.126 brouard 12678: fputs(line,ficparo);
12679: fputs(line,ficlog);
12680: }
12681: ungetc(c,ficpar);
1.220 brouard 12682:
1.126 brouard 12683: matcov=matrix(1,npar,1,npar);
1.203 brouard 12684: hess=matrix(1,npar,1,npar);
1.131 brouard 12685: for(i=1; i <=npar; i++)
12686: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 12687:
1.194 brouard 12688: /* Scans npar lines */
1.126 brouard 12689: for(i=1; i <=npar; i++){
1.226 brouard 12690: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 12691: if(count != 3){
1.226 brouard 12692: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12693: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12694: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12695: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12696: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12697: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12698: exit(1);
1.220 brouard 12699: }else{
1.226 brouard 12700: if(mle==1)
12701: printf("%1d%1d%d",i1,j1,jk);
12702: }
12703: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
12704: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 12705: for(j=1; j <=i; j++){
1.226 brouard 12706: fscanf(ficpar," %le",&matcov[i][j]);
12707: if(mle==1){
12708: printf(" %.5le",matcov[i][j]);
12709: }
12710: fprintf(ficlog," %.5le",matcov[i][j]);
12711: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 12712: }
12713: fscanf(ficpar,"\n");
12714: numlinepar++;
12715: if(mle==1)
1.220 brouard 12716: printf("\n");
1.126 brouard 12717: fprintf(ficlog,"\n");
12718: fprintf(ficparo,"\n");
12719: }
1.194 brouard 12720: /* End of read covariance matrix npar lines */
1.126 brouard 12721: for(i=1; i <=npar; i++)
12722: for(j=i+1;j<=npar;j++)
1.226 brouard 12723: matcov[i][j]=matcov[j][i];
1.126 brouard 12724:
12725: if(mle==1)
12726: printf("\n");
12727: fprintf(ficlog,"\n");
12728:
12729: fflush(ficlog);
12730:
12731: } /* End of mle != -3 */
1.218 brouard 12732:
1.186 brouard 12733: /* Main data
12734: */
1.290 brouard 12735: nobs=lastobs-firstobs+1; /* was = lastobs;*/
12736: /* num=lvector(1,n); */
12737: /* moisnais=vector(1,n); */
12738: /* annais=vector(1,n); */
12739: /* moisdc=vector(1,n); */
12740: /* andc=vector(1,n); */
12741: /* weight=vector(1,n); */
12742: /* agedc=vector(1,n); */
12743: /* cod=ivector(1,n); */
12744: /* for(i=1;i<=n;i++){ */
12745: num=lvector(firstobs,lastobs);
12746: moisnais=vector(firstobs,lastobs);
12747: annais=vector(firstobs,lastobs);
12748: moisdc=vector(firstobs,lastobs);
12749: andc=vector(firstobs,lastobs);
12750: weight=vector(firstobs,lastobs);
12751: agedc=vector(firstobs,lastobs);
12752: cod=ivector(firstobs,lastobs);
12753: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12754: num[i]=0;
12755: moisnais[i]=0;
12756: annais[i]=0;
12757: moisdc[i]=0;
12758: andc[i]=0;
12759: agedc[i]=0;
12760: cod[i]=0;
12761: weight[i]=1.0; /* Equal weights, 1 by default */
12762: }
1.290 brouard 12763: mint=matrix(1,maxwav,firstobs,lastobs);
12764: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 12765: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 12766: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 12767: tab=ivector(1,NCOVMAX);
1.144 brouard 12768: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 12769: 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 12770:
1.136 brouard 12771: /* Reads data from file datafile */
12772: if (readdata(datafile, firstobs, lastobs, &imx)==1)
12773: goto end;
12774:
12775: /* Calculation of the number of parameters from char model */
1.234 brouard 12776: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 12777: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
12778: k=3 V4 Tvar[k=3]= 4 (from V4)
12779: k=2 V1 Tvar[k=2]= 1 (from V1)
12780: k=1 Tvar[1]=2 (from V2)
1.234 brouard 12781: */
12782:
12783: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
12784: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 12785: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 12786: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 12787: TvarsD=ivector(1,NCOVMAX); /* */
12788: TvarsQind=ivector(1,NCOVMAX); /* */
12789: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 12790: TvarF=ivector(1,NCOVMAX); /* */
12791: TvarFind=ivector(1,NCOVMAX); /* */
12792: TvarV=ivector(1,NCOVMAX); /* */
12793: TvarVind=ivector(1,NCOVMAX); /* */
12794: TvarA=ivector(1,NCOVMAX); /* */
12795: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 12796: TvarFD=ivector(1,NCOVMAX); /* */
12797: TvarFDind=ivector(1,NCOVMAX); /* */
12798: TvarFQ=ivector(1,NCOVMAX); /* */
12799: TvarFQind=ivector(1,NCOVMAX); /* */
12800: TvarVD=ivector(1,NCOVMAX); /* */
12801: TvarVDind=ivector(1,NCOVMAX); /* */
12802: TvarVQ=ivector(1,NCOVMAX); /* */
12803: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 12804: TvarVV=ivector(1,NCOVMAX); /* */
12805: TvarVVind=ivector(1,NCOVMAX); /* */
1.231 brouard 12806:
1.230 brouard 12807: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 12808: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 12809: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
12810: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
12811: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 12812: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
12813: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
12814: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
12815: */
12816: /* For model-covariate k tells which data-covariate to use but
12817: because this model-covariate is a construction we invent a new column
12818: ncovcol + k1
12819: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
12820: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 12821: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
12822: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 12823: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
12824: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 12825: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 12826: */
1.145 brouard 12827: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
12828: 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 12829: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
12830: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.330 brouard 12831: Tvardk=imatrix(1,NCOVMAX,1,2);
1.145 brouard 12832: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 12833: 4 covariates (3 plus signs)
12834: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 12835: */
12836: for(i=1;i<NCOVMAX;i++)
12837: Tage[i]=0;
1.230 brouard 12838: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 12839: * individual dummy, fixed or varying:
12840: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
12841: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 12842: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
12843: * V1 df, V2 qf, V3 & V4 dv, V5 qv
12844: * Tmodelind[1]@9={9,0,3,2,}*/
12845: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
12846: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 12847: * individual quantitative, fixed or varying:
12848: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
12849: * 3, 1, 0, 0, 0, 0, 0, 0},
12850: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 12851: /* Main decodemodel */
12852:
1.187 brouard 12853:
1.223 brouard 12854: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 12855: goto end;
12856:
1.137 brouard 12857: if((double)(lastobs-imx)/(double)imx > 1.10){
12858: nbwarn++;
12859: 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);
12860: 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);
12861: }
1.136 brouard 12862: /* if(mle==1){*/
1.137 brouard 12863: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
12864: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 12865: }
12866:
12867: /*-calculation of age at interview from date of interview and age at death -*/
12868: agev=matrix(1,maxwav,1,imx);
12869:
12870: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
12871: goto end;
12872:
1.126 brouard 12873:
1.136 brouard 12874: agegomp=(int)agemin;
1.290 brouard 12875: free_vector(moisnais,firstobs,lastobs);
12876: free_vector(annais,firstobs,lastobs);
1.126 brouard 12877: /* free_matrix(mint,1,maxwav,1,n);
12878: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 12879: /* free_vector(moisdc,1,n); */
12880: /* free_vector(andc,1,n); */
1.145 brouard 12881: /* */
12882:
1.126 brouard 12883: wav=ivector(1,imx);
1.214 brouard 12884: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
12885: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
12886: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
12887: 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.*/
12888: bh=imatrix(1,lastpass-firstpass+2,1,imx);
12889: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 12890:
12891: /* Concatenates waves */
1.214 brouard 12892: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
12893: Death is a valid wave (if date is known).
12894: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
12895: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
12896: and mw[mi+1][i]. dh depends on stepm.
12897: */
12898:
1.126 brouard 12899: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12900: /* Concatenates waves */
1.145 brouard 12901:
1.290 brouard 12902: free_vector(moisdc,firstobs,lastobs);
12903: free_vector(andc,firstobs,lastobs);
1.215 brouard 12904:
1.126 brouard 12905: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12906: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12907: ncodemax[1]=1;
1.145 brouard 12908: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12909: cptcoveff=0;
1.220 brouard 12910: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 12911: 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 12912: }
12913:
12914: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 12915: invalidvarcomb=ivector(0, ncovcombmax);
12916: for(i=0;i<ncovcombmax;i++)
1.227 brouard 12917: invalidvarcomb[i]=0;
12918:
1.211 brouard 12919: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12920: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12921: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12922:
1.200 brouard 12923: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12924: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12925: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12926: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12927: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12928: * (currently 0 or 1) in the data.
12929: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12930: * corresponding modality (h,j).
12931: */
12932:
1.145 brouard 12933: h=0;
12934: /*if (cptcovn > 0) */
1.126 brouard 12935: m=pow(2,cptcoveff);
12936:
1.144 brouard 12937: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12938: * For k=4 covariates, h goes from 1 to m=2**k
12939: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12940: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 12941: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
12942: *______________________________ *______________________
12943: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
12944: * 2 2 1 1 1 * 1 0 0 0 1
12945: * 3 i=2 1 2 1 1 * 2 0 0 1 0
12946: * 4 2 2 1 1 * 3 0 0 1 1
12947: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
12948: * 6 2 1 2 1 * 5 0 1 0 1
12949: * 7 i=4 1 2 2 1 * 6 0 1 1 0
12950: * 8 2 2 2 1 * 7 0 1 1 1
12951: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
12952: * 10 2 1 1 2 * 9 1 0 0 1
12953: * 11 i=6 1 2 1 2 * 10 1 0 1 0
12954: * 12 2 2 1 2 * 11 1 0 1 1
12955: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
12956: * 14 2 1 2 2 * 13 1 1 0 1
12957: * 15 i=8 1 2 2 2 * 14 1 1 1 0
12958: * 16 2 2 2 2 * 15 1 1 1 1
12959: */
1.212 brouard 12960: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12961: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12962: * and the value of each covariate?
12963: * V1=1, V2=1, V3=2, V4=1 ?
12964: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12965: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12966: * In order to get the real value in the data, we use nbcode
12967: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12968: * We are keeping this crazy system in order to be able (in the future?)
12969: * to have more than 2 values (0 or 1) for a covariate.
12970: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12971: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12972: * bbbbbbbb
12973: * 76543210
12974: * h-1 00000101 (6-1=5)
1.219 brouard 12975: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12976: * &
12977: * 1 00000001 (1)
1.219 brouard 12978: * 00000000 = 1 & ((h-1) >> (k-1))
12979: * +1= 00000001 =1
1.211 brouard 12980: *
12981: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12982: * h' 1101 =2^3+2^2+0x2^1+2^0
12983: * >>k' 11
12984: * & 00000001
12985: * = 00000001
12986: * +1 = 00000010=2 = codtabm(14,3)
12987: * Reverse h=6 and m=16?
12988: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12989: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12990: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12991: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12992: * V3=decodtabm(14,3,2**4)=2
12993: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12994: *(h-1) >> (j-1) 0011 =13 >> 2
12995: * &1 000000001
12996: * = 000000001
12997: * +1= 000000010 =2
12998: * 2211
12999: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13000: * V3=2
1.220 brouard 13001: * codtabm and decodtabm are identical
1.211 brouard 13002: */
13003:
1.145 brouard 13004:
13005: free_ivector(Ndum,-1,NCOVMAX);
13006:
13007:
1.126 brouard 13008:
1.186 brouard 13009: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13010: strcpy(optionfilegnuplot,optionfilefiname);
13011: if(mle==-3)
1.201 brouard 13012: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13013: strcat(optionfilegnuplot,".gp");
13014:
13015: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13016: printf("Problem with file %s",optionfilegnuplot);
13017: }
13018: else{
1.204 brouard 13019: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13020: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13021: //fprintf(ficgp,"set missing 'NaNq'\n");
13022: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13023: }
13024: /* fclose(ficgp);*/
1.186 brouard 13025:
13026:
13027: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13028:
13029: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13030: if(mle==-3)
1.201 brouard 13031: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13032: strcat(optionfilehtm,".htm");
13033: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13034: printf("Problem with %s \n",optionfilehtm);
13035: exit(0);
1.126 brouard 13036: }
13037:
13038: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13039: strcat(optionfilehtmcov,"-cov.htm");
13040: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13041: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13042: }
13043: else{
13044: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13045: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13046: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13047: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13048: }
13049:
1.335 brouard 13050: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13051: <title>IMaCh %s</title></head>\n\
13052: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13053: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13054: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13055: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13056: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13057:
13058: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13059: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13060: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13061: 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 13062: \n\
13063: <hr size=\"2\" color=\"#EC5E5E\">\
13064: <ul><li><h4>Parameter files</h4>\n\
13065: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13066: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13067: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13068: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13069: - Date and time at start: %s</ul>\n",\
1.335 brouard 13070: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13071: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13072: fileres,fileres,\
13073: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13074: fflush(fichtm);
13075:
13076: strcpy(pathr,path);
13077: strcat(pathr,optionfilefiname);
1.184 brouard 13078: #ifdef WIN32
13079: _chdir(optionfilefiname); /* Move to directory named optionfile */
13080: #else
1.126 brouard 13081: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 13082: #endif
13083:
1.126 brouard 13084:
1.220 brouard 13085: /* Calculates basic frequencies. Computes observed prevalence at single age
13086: and for any valid combination of covariates
1.126 brouard 13087: and prints on file fileres'p'. */
1.251 brouard 13088: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 13089: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 13090:
13091: fprintf(fichtm,"\n");
1.286 brouard 13092: 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 13093: ftol, stepm);
13094: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
13095: ncurrv=1;
13096: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
13097: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
13098: ncurrv=i;
13099: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13100: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 13101: ncurrv=i;
13102: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13103: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 13104: ncurrv=i;
13105: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
13106: 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", \
13107: nlstate, ndeath, maxwav, mle, weightopt);
13108:
13109: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
13110: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
13111:
13112:
1.317 brouard 13113: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 13114: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
13115: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 13116: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 13117: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 13118: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13119: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13120: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13121: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 13122:
1.126 brouard 13123: /* For Powell, parameters are in a vector p[] starting at p[1]
13124: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
13125: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
13126:
13127: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 13128: /* For mortality only */
1.126 brouard 13129: if (mle==-3){
1.136 brouard 13130: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 13131: for(i=1;i<=NDIM;i++)
13132: for(j=1;j<=NDIM;j++)
13133: ximort[i][j]=0.;
1.186 brouard 13134: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 13135: cens=ivector(firstobs,lastobs);
13136: ageexmed=vector(firstobs,lastobs);
13137: agecens=vector(firstobs,lastobs);
13138: dcwave=ivector(firstobs,lastobs);
1.223 brouard 13139:
1.126 brouard 13140: for (i=1; i<=imx; i++){
13141: dcwave[i]=-1;
13142: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 13143: if (s[m][i]>nlstate) {
13144: dcwave[i]=m;
13145: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
13146: break;
13147: }
1.126 brouard 13148: }
1.226 brouard 13149:
1.126 brouard 13150: for (i=1; i<=imx; i++) {
13151: if (wav[i]>0){
1.226 brouard 13152: ageexmed[i]=agev[mw[1][i]][i];
13153: j=wav[i];
13154: agecens[i]=1.;
13155:
13156: if (ageexmed[i]> 1 && wav[i] > 0){
13157: agecens[i]=agev[mw[j][i]][i];
13158: cens[i]= 1;
13159: }else if (ageexmed[i]< 1)
13160: cens[i]= -1;
13161: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
13162: cens[i]=0 ;
1.126 brouard 13163: }
13164: else cens[i]=-1;
13165: }
13166:
13167: for (i=1;i<=NDIM;i++) {
13168: for (j=1;j<=NDIM;j++)
1.226 brouard 13169: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 13170: }
13171:
1.302 brouard 13172: p[1]=0.0268; p[NDIM]=0.083;
13173: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 13174:
13175:
1.136 brouard 13176: #ifdef GSL
13177: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 13178: #else
1.126 brouard 13179: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 13180: #endif
1.201 brouard 13181: strcpy(filerespow,"POW-MORT_");
13182: strcat(filerespow,fileresu);
1.126 brouard 13183: if((ficrespow=fopen(filerespow,"w"))==NULL) {
13184: printf("Problem with resultfile: %s\n", filerespow);
13185: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
13186: }
1.136 brouard 13187: #ifdef GSL
13188: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 13189: #else
1.126 brouard 13190: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 13191: #endif
1.126 brouard 13192: /* for (i=1;i<=nlstate;i++)
13193: for(j=1;j<=nlstate+ndeath;j++)
13194: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
13195: */
13196: fprintf(ficrespow,"\n");
1.136 brouard 13197: #ifdef GSL
13198: /* gsl starts here */
13199: T = gsl_multimin_fminimizer_nmsimplex;
13200: gsl_multimin_fminimizer *sfm = NULL;
13201: gsl_vector *ss, *x;
13202: gsl_multimin_function minex_func;
13203:
13204: /* Initial vertex size vector */
13205: ss = gsl_vector_alloc (NDIM);
13206:
13207: if (ss == NULL){
13208: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
13209: }
13210: /* Set all step sizes to 1 */
13211: gsl_vector_set_all (ss, 0.001);
13212:
13213: /* Starting point */
1.126 brouard 13214:
1.136 brouard 13215: x = gsl_vector_alloc (NDIM);
13216:
13217: if (x == NULL){
13218: gsl_vector_free(ss);
13219: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
13220: }
13221:
13222: /* Initialize method and iterate */
13223: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 13224: /* gsl_vector_set(x, 0, 0.0268); */
13225: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 13226: gsl_vector_set(x, 0, p[1]);
13227: gsl_vector_set(x, 1, p[2]);
13228:
13229: minex_func.f = &gompertz_f;
13230: minex_func.n = NDIM;
13231: minex_func.params = (void *)&p; /* ??? */
13232:
13233: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
13234: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
13235:
13236: printf("Iterations beginning .....\n\n");
13237: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
13238:
13239: iteri=0;
13240: while (rval == GSL_CONTINUE){
13241: iteri++;
13242: status = gsl_multimin_fminimizer_iterate(sfm);
13243:
13244: if (status) printf("error: %s\n", gsl_strerror (status));
13245: fflush(0);
13246:
13247: if (status)
13248: break;
13249:
13250: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
13251: ssval = gsl_multimin_fminimizer_size (sfm);
13252:
13253: if (rval == GSL_SUCCESS)
13254: printf ("converged to a local maximum at\n");
13255:
13256: printf("%5d ", iteri);
13257: for (it = 0; it < NDIM; it++){
13258: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
13259: }
13260: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
13261: }
13262:
13263: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
13264:
13265: gsl_vector_free(x); /* initial values */
13266: gsl_vector_free(ss); /* inital step size */
13267: for (it=0; it<NDIM; it++){
13268: p[it+1]=gsl_vector_get(sfm->x,it);
13269: fprintf(ficrespow," %.12lf", p[it]);
13270: }
13271: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
13272: #endif
13273: #ifdef POWELL
13274: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
13275: #endif
1.126 brouard 13276: fclose(ficrespow);
13277:
1.203 brouard 13278: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 13279:
13280: for(i=1; i <=NDIM; i++)
13281: for(j=i+1;j<=NDIM;j++)
1.220 brouard 13282: matcov[i][j]=matcov[j][i];
1.126 brouard 13283:
13284: printf("\nCovariance matrix\n ");
1.203 brouard 13285: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 13286: for(i=1; i <=NDIM; i++) {
13287: for(j=1;j<=NDIM;j++){
1.220 brouard 13288: printf("%f ",matcov[i][j]);
13289: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 13290: }
1.203 brouard 13291: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 13292: }
13293:
13294: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 13295: for (i=1;i<=NDIM;i++) {
1.126 brouard 13296: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 13297: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
13298: }
1.302 brouard 13299: lsurv=vector(agegomp,AGESUP);
13300: lpop=vector(agegomp,AGESUP);
13301: tpop=vector(agegomp,AGESUP);
1.126 brouard 13302: lsurv[agegomp]=100000;
13303:
13304: for (k=agegomp;k<=AGESUP;k++) {
13305: agemortsup=k;
13306: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
13307: }
13308:
13309: for (k=agegomp;k<agemortsup;k++)
13310: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
13311:
13312: for (k=agegomp;k<agemortsup;k++){
13313: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
13314: sumlpop=sumlpop+lpop[k];
13315: }
13316:
13317: tpop[agegomp]=sumlpop;
13318: for (k=agegomp;k<(agemortsup-3);k++){
13319: /* tpop[k+1]=2;*/
13320: tpop[k+1]=tpop[k]-lpop[k];
13321: }
13322:
13323:
13324: printf("\nAge lx qx dx Lx Tx e(x)\n");
13325: for (k=agegomp;k<(agemortsup-2);k++)
13326: 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]);
13327:
13328:
13329: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 13330: ageminpar=50;
13331: agemaxpar=100;
1.194 brouard 13332: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
13333: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13334: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13335: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
13336: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13337: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13338: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13339: }else{
13340: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
13341: 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 13342: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 13343: }
1.201 brouard 13344: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 13345: stepm, weightopt,\
13346: model,imx,p,matcov,agemortsup);
13347:
1.302 brouard 13348: free_vector(lsurv,agegomp,AGESUP);
13349: free_vector(lpop,agegomp,AGESUP);
13350: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 13351: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 13352: free_ivector(dcwave,firstobs,lastobs);
13353: free_vector(agecens,firstobs,lastobs);
13354: free_vector(ageexmed,firstobs,lastobs);
13355: free_ivector(cens,firstobs,lastobs);
1.220 brouard 13356: #ifdef GSL
1.136 brouard 13357: #endif
1.186 brouard 13358: } /* Endof if mle==-3 mortality only */
1.205 brouard 13359: /* Standard */
13360: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
13361: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13362: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 13363: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 13364: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
13365: for (k=1; k<=npar;k++)
13366: printf(" %d %8.5f",k,p[k]);
13367: printf("\n");
1.205 brouard 13368: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
13369: /* mlikeli uses func not funcone */
1.247 brouard 13370: /* for(i=1;i<nlstate;i++){ */
13371: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13372: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13373: /* } */
1.205 brouard 13374: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
13375: }
13376: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
13377: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13378: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
13379: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13380: }
13381: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 13382: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13383: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 13384: /* exit(0); */
1.126 brouard 13385: for (k=1; k<=npar;k++)
13386: printf(" %d %8.5f",k,p[k]);
13387: printf("\n");
13388:
13389: /*--------- results files --------------*/
1.283 brouard 13390: /* 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 13391:
13392:
13393: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13394: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 13395: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13396:
13397: printf("#model= 1 + age ");
13398: fprintf(ficres,"#model= 1 + age ");
13399: fprintf(ficlog,"#model= 1 + age ");
13400: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
13401: </ul>", model);
13402:
13403: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
13404: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
13405: if(nagesqr==1){
13406: printf(" + age*age ");
13407: fprintf(ficres," + age*age ");
13408: fprintf(ficlog," + age*age ");
13409: fprintf(fichtm, "<th>+ age*age</th>");
13410: }
13411: for(j=1;j <=ncovmodel-2;j++){
13412: if(Typevar[j]==0) {
13413: printf(" + V%d ",Tvar[j]);
13414: fprintf(ficres," + V%d ",Tvar[j]);
13415: fprintf(ficlog," + V%d ",Tvar[j]);
13416: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13417: }else if(Typevar[j]==1) {
13418: printf(" + V%d*age ",Tvar[j]);
13419: fprintf(ficres," + V%d*age ",Tvar[j]);
13420: fprintf(ficlog," + V%d*age ",Tvar[j]);
13421: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13422: }else if(Typevar[j]==2) {
13423: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13424: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13425: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13426: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13427: }
13428: }
13429: printf("\n");
13430: fprintf(ficres,"\n");
13431: fprintf(ficlog,"\n");
13432: fprintf(fichtm, "</tr>");
13433: fprintf(fichtm, "\n");
13434:
13435:
1.126 brouard 13436: for(i=1,jk=1; i <=nlstate; i++){
13437: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 13438: if (k != i) {
1.319 brouard 13439: fprintf(fichtm, "<tr>");
1.225 brouard 13440: printf("%d%d ",i,k);
13441: fprintf(ficlog,"%d%d ",i,k);
13442: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 13443: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13444: for(j=1; j <=ncovmodel; j++){
13445: printf("%12.7f ",p[jk]);
13446: fprintf(ficlog,"%12.7f ",p[jk]);
13447: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 13448: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 13449: jk++;
13450: }
13451: printf("\n");
13452: fprintf(ficlog,"\n");
13453: fprintf(ficres,"\n");
1.319 brouard 13454: fprintf(fichtm, "</tr>\n");
1.225 brouard 13455: }
1.126 brouard 13456: }
13457: }
1.319 brouard 13458: /* fprintf(fichtm,"</tr>\n"); */
13459: fprintf(fichtm,"</table>\n");
13460: fprintf(fichtm, "\n");
13461:
1.203 brouard 13462: if(mle != 0){
13463: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 13464: ftolhess=ftol; /* Usually correct */
1.203 brouard 13465: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
13466: 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");
13467: 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 13468: 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 13469: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
13470: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
13471: if(nagesqr==1){
13472: printf(" + age*age ");
13473: fprintf(ficres," + age*age ");
13474: fprintf(ficlog," + age*age ");
13475: fprintf(fichtm, "<th>+ age*age</th>");
13476: }
13477: for(j=1;j <=ncovmodel-2;j++){
13478: if(Typevar[j]==0) {
13479: printf(" + V%d ",Tvar[j]);
13480: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13481: }else if(Typevar[j]==1) {
13482: printf(" + V%d*age ",Tvar[j]);
13483: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13484: }else if(Typevar[j]==2) {
13485: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13486: }
13487: }
13488: fprintf(fichtm, "</tr>\n");
13489:
1.203 brouard 13490: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 13491: for(k=1; k <=(nlstate+ndeath); k++){
13492: if (k != i) {
1.319 brouard 13493: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 13494: printf("%d%d ",i,k);
13495: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 13496: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13497: for(j=1; j <=ncovmodel; j++){
1.319 brouard 13498: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 13499: 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]));
13500: 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 13501: if(fabs(wald) > 1.96){
1.321 brouard 13502: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 13503: }else{
13504: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
13505: }
1.324 brouard 13506: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 13507: 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 13508: jk++;
13509: }
13510: printf("\n");
13511: fprintf(ficlog,"\n");
1.319 brouard 13512: fprintf(fichtm, "</tr>\n");
1.225 brouard 13513: }
13514: }
1.193 brouard 13515: }
1.203 brouard 13516: } /* end of hesscov and Wald tests */
1.319 brouard 13517: fprintf(fichtm,"</table>\n");
1.225 brouard 13518:
1.203 brouard 13519: /* */
1.126 brouard 13520: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
13521: printf("# Scales (for hessian or gradient estimation)\n");
13522: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
13523: for(i=1,jk=1; i <=nlstate; i++){
13524: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 13525: if (j!=i) {
13526: fprintf(ficres,"%1d%1d",i,j);
13527: printf("%1d%1d",i,j);
13528: fprintf(ficlog,"%1d%1d",i,j);
13529: for(k=1; k<=ncovmodel;k++){
13530: printf(" %.5e",delti[jk]);
13531: fprintf(ficlog," %.5e",delti[jk]);
13532: fprintf(ficres," %.5e",delti[jk]);
13533: jk++;
13534: }
13535: printf("\n");
13536: fprintf(ficlog,"\n");
13537: fprintf(ficres,"\n");
13538: }
1.126 brouard 13539: }
13540: }
13541:
13542: fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
1.203 brouard 13543: if(mle >= 1) /* To big for the screen */
1.126 brouard 13544: 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");
13545: 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");
13546: /* # 121 Var(a12)\n\ */
13547: /* # 122 Cov(b12,a12) Var(b12)\n\ */
13548: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
13549: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
13550: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
13551: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
13552: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
13553: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
13554:
13555:
13556: /* Just to have a covariance matrix which will be more understandable
13557: even is we still don't want to manage dictionary of variables
13558: */
13559: for(itimes=1;itimes<=2;itimes++){
13560: jj=0;
13561: for(i=1; i <=nlstate; i++){
1.225 brouard 13562: for(j=1; j <=nlstate+ndeath; j++){
13563: if(j==i) continue;
13564: for(k=1; k<=ncovmodel;k++){
13565: jj++;
13566: ca[0]= k+'a'-1;ca[1]='\0';
13567: if(itimes==1){
13568: if(mle>=1)
13569: printf("#%1d%1d%d",i,j,k);
13570: fprintf(ficlog,"#%1d%1d%d",i,j,k);
13571: fprintf(ficres,"#%1d%1d%d",i,j,k);
13572: }else{
13573: if(mle>=1)
13574: printf("%1d%1d%d",i,j,k);
13575: fprintf(ficlog,"%1d%1d%d",i,j,k);
13576: fprintf(ficres,"%1d%1d%d",i,j,k);
13577: }
13578: ll=0;
13579: for(li=1;li <=nlstate; li++){
13580: for(lj=1;lj <=nlstate+ndeath; lj++){
13581: if(lj==li) continue;
13582: for(lk=1;lk<=ncovmodel;lk++){
13583: ll++;
13584: if(ll<=jj){
13585: cb[0]= lk +'a'-1;cb[1]='\0';
13586: if(ll<jj){
13587: if(itimes==1){
13588: if(mle>=1)
13589: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13590: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13591: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13592: }else{
13593: if(mle>=1)
13594: printf(" %.5e",matcov[jj][ll]);
13595: fprintf(ficlog," %.5e",matcov[jj][ll]);
13596: fprintf(ficres," %.5e",matcov[jj][ll]);
13597: }
13598: }else{
13599: if(itimes==1){
13600: if(mle>=1)
13601: printf(" Var(%s%1d%1d)",ca,i,j);
13602: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
13603: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
13604: }else{
13605: if(mle>=1)
13606: printf(" %.7e",matcov[jj][ll]);
13607: fprintf(ficlog," %.7e",matcov[jj][ll]);
13608: fprintf(ficres," %.7e",matcov[jj][ll]);
13609: }
13610: }
13611: }
13612: } /* end lk */
13613: } /* end lj */
13614: } /* end li */
13615: if(mle>=1)
13616: printf("\n");
13617: fprintf(ficlog,"\n");
13618: fprintf(ficres,"\n");
13619: numlinepar++;
13620: } /* end k*/
13621: } /*end j */
1.126 brouard 13622: } /* end i */
13623: } /* end itimes */
13624:
13625: fflush(ficlog);
13626: fflush(ficres);
1.225 brouard 13627: while(fgets(line, MAXLINE, ficpar)) {
13628: /* If line starts with a # it is a comment */
13629: if (line[0] == '#') {
13630: numlinepar++;
13631: fputs(line,stdout);
13632: fputs(line,ficparo);
13633: fputs(line,ficlog);
1.299 brouard 13634: fputs(line,ficres);
1.225 brouard 13635: continue;
13636: }else
13637: break;
13638: }
13639:
1.209 brouard 13640: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
13641: /* ungetc(c,ficpar); */
13642: /* fgets(line, MAXLINE, ficpar); */
13643: /* fputs(line,stdout); */
13644: /* fputs(line,ficparo); */
13645: /* } */
13646: /* ungetc(c,ficpar); */
1.126 brouard 13647:
13648: estepm=0;
1.209 brouard 13649: 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 13650:
13651: if (num_filled != 6) {
13652: 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);
13653: 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);
13654: goto end;
13655: }
13656: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
13657: }
13658: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
13659: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
13660:
1.209 brouard 13661: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 13662: if (estepm==0 || estepm < stepm) estepm=stepm;
13663: if (fage <= 2) {
13664: bage = ageminpar;
13665: fage = agemaxpar;
13666: }
13667:
13668: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 13669: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
13670: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 13671:
1.186 brouard 13672: /* Other stuffs, more or less useful */
1.254 brouard 13673: while(fgets(line, MAXLINE, ficpar)) {
13674: /* If line starts with a # it is a comment */
13675: if (line[0] == '#') {
13676: numlinepar++;
13677: fputs(line,stdout);
13678: fputs(line,ficparo);
13679: fputs(line,ficlog);
1.299 brouard 13680: fputs(line,ficres);
1.254 brouard 13681: continue;
13682: }else
13683: break;
13684: }
13685:
13686: 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){
13687:
13688: if (num_filled != 7) {
13689: 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);
13690: 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);
13691: goto end;
13692: }
13693: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
13694: 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);
13695: 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);
13696: 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 13697: }
1.254 brouard 13698:
13699: while(fgets(line, MAXLINE, ficpar)) {
13700: /* If line starts with a # it is a comment */
13701: if (line[0] == '#') {
13702: numlinepar++;
13703: fputs(line,stdout);
13704: fputs(line,ficparo);
13705: fputs(line,ficlog);
1.299 brouard 13706: fputs(line,ficres);
1.254 brouard 13707: continue;
13708: }else
13709: break;
1.126 brouard 13710: }
13711:
13712:
13713: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
13714: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
13715:
1.254 brouard 13716: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
13717: if (num_filled != 1) {
13718: 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);
13719: 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);
13720: goto end;
13721: }
13722: printf("pop_based=%d\n",popbased);
13723: fprintf(ficlog,"pop_based=%d\n",popbased);
13724: fprintf(ficparo,"pop_based=%d\n",popbased);
13725: fprintf(ficres,"pop_based=%d\n",popbased);
13726: }
13727:
1.258 brouard 13728: /* Results */
1.332 brouard 13729: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
13730: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
13731: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 13732: endishere=0;
1.258 brouard 13733: nresult=0;
1.308 brouard 13734: parameterline=0;
1.258 brouard 13735: do{
13736: if(!fgets(line, MAXLINE, ficpar)){
13737: endishere=1;
1.308 brouard 13738: parameterline=15;
1.258 brouard 13739: }else if (line[0] == '#') {
13740: /* If line starts with a # it is a comment */
1.254 brouard 13741: numlinepar++;
13742: fputs(line,stdout);
13743: fputs(line,ficparo);
13744: fputs(line,ficlog);
1.299 brouard 13745: fputs(line,ficres);
1.254 brouard 13746: continue;
1.258 brouard 13747: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
13748: parameterline=11;
1.296 brouard 13749: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 13750: parameterline=12;
1.307 brouard 13751: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 13752: parameterline=13;
1.307 brouard 13753: }
1.258 brouard 13754: else{
13755: parameterline=14;
1.254 brouard 13756: }
1.308 brouard 13757: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13758: case 11:
1.296 brouard 13759: 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)){
13760: 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 13761: 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);
13762: 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);
13763: 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);
13764: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 13765: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
13766: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 13767: prvforecast = 1;
13768: }
13769: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 13770: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13771: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13772: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 13773: prvforecast = 2;
13774: }
13775: else {
13776: 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);
13777: 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);
13778: goto end;
1.258 brouard 13779: }
1.254 brouard 13780: break;
1.258 brouard 13781: case 12:
1.296 brouard 13782: 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)){
13783: 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);
13784: 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);
13785: 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);
13786: 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);
13787: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 13788: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
13789: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 13790: prvbackcast = 1;
13791: }
13792: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 13793: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13794: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13795: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 13796: prvbackcast = 2;
13797: }
13798: else {
13799: 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);
13800: 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);
13801: goto end;
1.258 brouard 13802: }
1.230 brouard 13803: break;
1.258 brouard 13804: case 13:
1.332 brouard 13805: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 13806: nresult++; /* Sum of resultlines */
1.332 brouard 13807: printf("Result %d: result:%s\n",nresult, resultlineori);
13808: /* removefirstspace(&resultlineori); */
13809:
13810: if(strstr(resultlineori,"v") !=0){
13811: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
13812: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
13813: return 1;
13814: }
13815: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
13816: printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori);
1.318 brouard 13817: if(nresult > MAXRESULTLINESPONE-1){
13818: 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);
13819: 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 13820: goto end;
13821: }
1.332 brouard 13822:
1.310 brouard 13823: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 13824: fprintf(ficparo,"result: %s\n",resultline);
13825: fprintf(ficres,"result: %s\n",resultline);
13826: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 13827: } else
13828: goto end;
1.307 brouard 13829: break;
13830: case 14:
13831: printf("Error: Unknown command '%s'\n",line);
13832: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 13833: if(line[0] == ' ' || line[0] == '\n'){
13834: printf("It should not be an empty line '%s'\n",line);
13835: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
13836: }
1.307 brouard 13837: if(ncovmodel >=2 && nresult==0 ){
13838: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
13839: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 13840: }
1.307 brouard 13841: /* goto end; */
13842: break;
1.308 brouard 13843: case 15:
13844: printf("End of resultlines.\n");
13845: fprintf(ficlog,"End of resultlines.\n");
13846: break;
13847: default: /* parameterline =0 */
1.307 brouard 13848: nresult=1;
13849: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 13850: } /* End switch parameterline */
13851: }while(endishere==0); /* End do */
1.126 brouard 13852:
1.230 brouard 13853: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 13854: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 13855:
13856: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 13857: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 13858: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13859: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13860: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 13861: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13862: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13863: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13864: }else{
1.270 brouard 13865: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 13866: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
13867: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
13868: if(prvforecast==1){
13869: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
13870: jprojd=jproj1;
13871: mprojd=mproj1;
13872: anprojd=anproj1;
13873: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
13874: jprojf=jproj2;
13875: mprojf=mproj2;
13876: anprojf=anproj2;
13877: } else if(prvforecast == 2){
13878: dateprojd=dateintmean;
13879: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
13880: dateprojf=dateintmean+yrfproj;
13881: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
13882: }
13883: if(prvbackcast==1){
13884: datebackd=(jback1+12*mback1+365*anback1)/365;
13885: jbackd=jback1;
13886: mbackd=mback1;
13887: anbackd=anback1;
13888: datebackf=(jback2+12*mback2+365*anback2)/365;
13889: jbackf=jback2;
13890: mbackf=mback2;
13891: anbackf=anback2;
13892: } else if(prvbackcast == 2){
13893: datebackd=dateintmean;
13894: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
13895: datebackf=dateintmean-yrbproj;
13896: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
13897: }
13898:
13899: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 13900: }
13901: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 13902: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
13903: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 13904:
1.225 brouard 13905: /*------------ free_vector -------------*/
13906: /* chdir(path); */
1.220 brouard 13907:
1.215 brouard 13908: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
13909: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
13910: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
13911: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 13912: free_lvector(num,firstobs,lastobs);
13913: free_vector(agedc,firstobs,lastobs);
1.126 brouard 13914: /*free_matrix(covar,0,NCOVMAX,1,n);*/
13915: /*free_matrix(covar,1,NCOVMAX,1,n);*/
13916: fclose(ficparo);
13917: fclose(ficres);
1.220 brouard 13918:
13919:
1.186 brouard 13920: /* Other results (useful)*/
1.220 brouard 13921:
13922:
1.126 brouard 13923: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13924: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13925: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 13926: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 13927: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13928: fclose(ficrespl);
13929:
13930: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13931: /*#include "hpijx.h"*/
1.332 brouard 13932: /** 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?*/
13933: /* calls hpxij with combination k */
1.180 brouard 13934: hPijx(p, bage, fage);
1.145 brouard 13935: fclose(ficrespij);
1.227 brouard 13936:
1.220 brouard 13937: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 13938: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 13939: k=1;
1.126 brouard 13940: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13941:
1.269 brouard 13942: /* Prevalence for each covariate combination in probs[age][status][cov] */
13943: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13944: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13945: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13946: for(k=1;k<=ncovcombmax;k++)
13947: probs[i][j][k]=0.;
1.269 brouard 13948: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13949: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13950: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13951: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13952: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13953: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13954: for(k=1;k<=ncovcombmax;k++)
13955: mobaverages[i][j][k]=0.;
1.219 brouard 13956: mobaverage=mobaverages;
13957: if (mobilav!=0) {
1.235 brouard 13958: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13959: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13960: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13961: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13962: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13963: }
1.269 brouard 13964: } else if (mobilavproj !=0) {
1.235 brouard 13965: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13966: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13967: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13968: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13969: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13970: }
1.269 brouard 13971: }else{
13972: printf("Internal error moving average\n");
13973: fflush(stdout);
13974: exit(1);
1.219 brouard 13975: }
13976: }/* end if moving average */
1.227 brouard 13977:
1.126 brouard 13978: /*---------- Forecasting ------------------*/
1.296 brouard 13979: if(prevfcast==1){
13980: /* /\* if(stepm ==1){*\/ */
13981: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13982: /*This done previously after freqsummary.*/
13983: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13984: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13985:
13986: /* } else if (prvforecast==2){ */
13987: /* /\* if(stepm ==1){*\/ */
13988: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13989: /* } */
13990: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13991: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13992: }
1.269 brouard 13993:
1.296 brouard 13994: /* Prevbcasting */
13995: if(prevbcast==1){
1.219 brouard 13996: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13997: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13998: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13999:
14000: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14001:
14002: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14003:
1.219 brouard 14004: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14005: fclose(ficresplb);
14006:
1.222 brouard 14007: hBijx(p, bage, fage, mobaverage);
14008: fclose(ficrespijb);
1.219 brouard 14009:
1.296 brouard 14010: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14011: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14012: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14013: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14014: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14015: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14016:
14017:
1.269 brouard 14018: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14019:
14020:
1.269 brouard 14021: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14022: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14023: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14024: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14025: } /* end Prevbcasting */
1.268 brouard 14026:
1.186 brouard 14027:
14028: /* ------ Other prevalence ratios------------ */
1.126 brouard 14029:
1.215 brouard 14030: free_ivector(wav,1,imx);
14031: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14032: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14033: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14034:
14035:
1.127 brouard 14036: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14037:
1.201 brouard 14038: strcpy(filerese,"E_");
14039: strcat(filerese,fileresu);
1.126 brouard 14040: if((ficreseij=fopen(filerese,"w"))==NULL) {
14041: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14042: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14043: }
1.208 brouard 14044: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14045: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14046:
14047: pstamp(ficreseij);
1.219 brouard 14048:
1.235 brouard 14049: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14050: if (cptcovn < 1){i1=1;}
14051:
14052: for(nres=1; nres <= nresult; nres++) /* For each resultline */
14053: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 14054: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 14055: continue;
1.219 brouard 14056: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14057: printf("\n#****** ");
1.225 brouard 14058: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 14059: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
14060: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 14061: }
14062: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14063: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14064: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 14065: }
14066: fprintf(ficreseij,"******\n");
1.235 brouard 14067: printf("******\n");
1.219 brouard 14068:
14069: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14070: oldm=oldms;savm=savms;
1.330 brouard 14071: /* 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 14072: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 14073:
1.219 brouard 14074: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 14075: }
14076: fclose(ficreseij);
1.208 brouard 14077: printf("done evsij\n");fflush(stdout);
14078: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 14079:
1.218 brouard 14080:
1.227 brouard 14081: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 14082: /* Should be moved in a function */
1.201 brouard 14083: strcpy(filerest,"T_");
14084: strcat(filerest,fileresu);
1.127 brouard 14085: if((ficrest=fopen(filerest,"w"))==NULL) {
14086: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
14087: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
14088: }
1.208 brouard 14089: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
14090: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 14091: strcpy(fileresstde,"STDE_");
14092: strcat(fileresstde,fileresu);
1.126 brouard 14093: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 14094: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
14095: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 14096: }
1.227 brouard 14097: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
14098: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 14099:
1.201 brouard 14100: strcpy(filerescve,"CVE_");
14101: strcat(filerescve,fileresu);
1.126 brouard 14102: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 14103: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
14104: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 14105: }
1.227 brouard 14106: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
14107: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 14108:
1.201 brouard 14109: strcpy(fileresv,"V_");
14110: strcat(fileresv,fileresu);
1.126 brouard 14111: if((ficresvij=fopen(fileresv,"w"))==NULL) {
14112: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
14113: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
14114: }
1.227 brouard 14115: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
14116: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 14117:
1.235 brouard 14118: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14119: if (cptcovn < 1){i1=1;}
14120:
1.334 brouard 14121: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
14122: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
14123: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
14124: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
14125: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
14126: /* */
14127: 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 14128: continue;
1.321 brouard 14129: printf("\n# model %s \n#****** Result for:", model);
14130: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
14131: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 14132: /* It might not be a good idea to mix dummies and quantitative */
14133: /* 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 *\/ */
14134: 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 */
14135: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
14136: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
14137: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
14138: * (V5 is quanti) V4 and V3 are dummies
14139: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
14140: * l=1 l=2
14141: * k=1 1 1 0 0
14142: * k=2 2 1 1 0
14143: * k=3 [1] [2] 0 1
14144: * k=4 2 2 1 1
14145: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
14146: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
14147: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
14148: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
14149: */
14150: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
14151: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
14152: /* We give up with the combinations!! */
14153: 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 */
14154:
14155: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
1.337 brouard 14156: 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 */
14157: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
14158: fprintf(ficrest,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
1.334 brouard 14159: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14160: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14161: }else{
14162: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14163: }
14164: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14165: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14166: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
14167: /* For each selected (single) quantitative value */
1.337 brouard 14168: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14169: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14170: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 14171: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14172: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14173: }else{
14174: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14175: }
14176: }else{
14177: 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 */
14178: 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 */
14179: exit(1);
14180: }
1.335 brouard 14181: } /* End loop for each variable in the resultline */
1.334 brouard 14182: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14183: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
14184: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14185: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14186: /* } */
1.208 brouard 14187: fprintf(ficrest,"******\n");
1.227 brouard 14188: fprintf(ficlog,"******\n");
14189: printf("******\n");
1.208 brouard 14190:
14191: fprintf(ficresstdeij,"\n#****** ");
14192: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 14193: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
14194: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 14195: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 14196: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14197: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14198: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14199: }
14200: 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 14201: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
14202: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 14203: }
1.208 brouard 14204: fprintf(ficresstdeij,"******\n");
14205: fprintf(ficrescveij,"******\n");
14206:
14207: fprintf(ficresvij,"\n#****** ");
1.238 brouard 14208: /* pstamp(ficresvij); */
1.225 brouard 14209: for(j=1;j<=cptcoveff;j++)
1.335 brouard 14210: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14211: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 14212: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 14213: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 14214: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 14215: }
1.208 brouard 14216: fprintf(ficresvij,"******\n");
14217:
14218: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14219: oldm=oldms;savm=savms;
1.235 brouard 14220: printf(" cvevsij ");
14221: fprintf(ficlog, " cvevsij ");
14222: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 14223: printf(" end cvevsij \n ");
14224: fprintf(ficlog, " end cvevsij \n ");
14225:
14226: /*
14227: */
14228: /* goto endfree; */
14229:
14230: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14231: pstamp(ficrest);
14232:
1.269 brouard 14233: epj=vector(1,nlstate+1);
1.208 brouard 14234: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 14235: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
14236: cptcod= 0; /* To be deleted */
14237: printf("varevsij vpopbased=%d \n",vpopbased);
14238: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 14239: 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 14240: 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 ");
14241: if(vpopbased==1)
14242: 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);
14243: else
1.288 brouard 14244: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 14245: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 14246: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
14247: fprintf(ficrest,"\n");
14248: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 14249: printf("Computing age specific forward period (stable) prevalences in each health state \n");
14250: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 14251: for(age=bage; age <=fage ;age++){
1.235 brouard 14252: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 14253: if (vpopbased==1) {
14254: if(mobilav ==0){
14255: for(i=1; i<=nlstate;i++)
14256: prlim[i][i]=probs[(int)age][i][k];
14257: }else{ /* mobilav */
14258: for(i=1; i<=nlstate;i++)
14259: prlim[i][i]=mobaverage[(int)age][i][k];
14260: }
14261: }
1.219 brouard 14262:
1.227 brouard 14263: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
14264: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
14265: /* printf(" age %4.0f ",age); */
14266: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
14267: for(i=1, epj[j]=0.;i <=nlstate;i++) {
14268: epj[j] += prlim[i][i]*eij[i][j][(int)age];
14269: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
14270: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
14271: }
14272: epj[nlstate+1] +=epj[j];
14273: }
14274: /* printf(" age %4.0f \n",age); */
1.219 brouard 14275:
1.227 brouard 14276: for(i=1, vepp=0.;i <=nlstate;i++)
14277: for(j=1;j <=nlstate;j++)
14278: vepp += vareij[i][j][(int)age];
14279: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
14280: for(j=1;j <=nlstate;j++){
14281: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
14282: }
14283: fprintf(ficrest,"\n");
14284: }
1.208 brouard 14285: } /* End vpopbased */
1.269 brouard 14286: free_vector(epj,1,nlstate+1);
1.208 brouard 14287: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
14288: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 14289: printf("done selection\n");fflush(stdout);
14290: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 14291:
1.335 brouard 14292: } /* End k selection or end covariate selection for nres */
1.227 brouard 14293:
14294: printf("done State-specific expectancies\n");fflush(stdout);
14295: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
14296:
1.335 brouard 14297: /* variance-covariance of forward period prevalence */
1.269 brouard 14298: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14299:
1.227 brouard 14300:
1.290 brouard 14301: free_vector(weight,firstobs,lastobs);
1.330 brouard 14302: free_imatrix(Tvardk,1,NCOVMAX,1,2);
1.227 brouard 14303: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 14304: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
14305: free_matrix(anint,1,maxwav,firstobs,lastobs);
14306: free_matrix(mint,1,maxwav,firstobs,lastobs);
14307: free_ivector(cod,firstobs,lastobs);
1.227 brouard 14308: free_ivector(tab,1,NCOVMAX);
14309: fclose(ficresstdeij);
14310: fclose(ficrescveij);
14311: fclose(ficresvij);
14312: fclose(ficrest);
14313: fclose(ficpar);
14314:
14315:
1.126 brouard 14316: /*---------- End : free ----------------*/
1.219 brouard 14317: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 14318: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
14319: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 14320: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
14321: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 14322: } /* mle==-3 arrives here for freeing */
1.227 brouard 14323: /* endfree:*/
14324: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
14325: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
14326: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 14327: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
14328: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
14329: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
14330: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 14331: free_matrix(matcov,1,npar,1,npar);
14332: free_matrix(hess,1,npar,1,npar);
14333: /*free_vector(delti,1,npar);*/
14334: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14335: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 14336: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 14337: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14338:
14339: free_ivector(ncodemax,1,NCOVMAX);
14340: free_ivector(ncodemaxwundef,1,NCOVMAX);
14341: free_ivector(Dummy,-1,NCOVMAX);
14342: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 14343: free_ivector(DummyV,1,NCOVMAX);
14344: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 14345: free_ivector(Typevar,-1,NCOVMAX);
14346: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 14347: free_ivector(TvarsQ,1,NCOVMAX);
14348: free_ivector(TvarsQind,1,NCOVMAX);
14349: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 14350: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 14351: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 14352: free_ivector(TvarFD,1,NCOVMAX);
14353: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 14354: free_ivector(TvarF,1,NCOVMAX);
14355: free_ivector(TvarFind,1,NCOVMAX);
14356: free_ivector(TvarV,1,NCOVMAX);
14357: free_ivector(TvarVind,1,NCOVMAX);
14358: free_ivector(TvarA,1,NCOVMAX);
14359: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 14360: free_ivector(TvarFQ,1,NCOVMAX);
14361: free_ivector(TvarFQind,1,NCOVMAX);
14362: free_ivector(TvarVD,1,NCOVMAX);
14363: free_ivector(TvarVDind,1,NCOVMAX);
14364: free_ivector(TvarVQ,1,NCOVMAX);
14365: free_ivector(TvarVQind,1,NCOVMAX);
1.339 brouard 14366: free_ivector(TvarVV,1,NCOVMAX);
14367: free_ivector(TvarVVind,1,NCOVMAX);
14368:
1.230 brouard 14369: free_ivector(Tvarsel,1,NCOVMAX);
14370: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 14371: free_ivector(Tposprod,1,NCOVMAX);
14372: free_ivector(Tprod,1,NCOVMAX);
14373: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 14374: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 14375: free_ivector(Tage,1,NCOVMAX);
14376: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 14377: free_ivector(TmodelInvind,1,NCOVMAX);
14378: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 14379:
14380: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
14381:
1.227 brouard 14382: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
14383: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 14384: fflush(fichtm);
14385: fflush(ficgp);
14386:
1.227 brouard 14387:
1.126 brouard 14388: if((nberr >0) || (nbwarn>0)){
1.216 brouard 14389: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
14390: 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 14391: }else{
14392: printf("End of Imach\n");
14393: fprintf(ficlog,"End of Imach\n");
14394: }
14395: printf("See log file on %s\n",filelog);
14396: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 14397: /*(void) gettimeofday(&end_time,&tzp);*/
14398: rend_time = time(NULL);
14399: end_time = *localtime(&rend_time);
14400: /* tml = *localtime(&end_time.tm_sec); */
14401: strcpy(strtend,asctime(&end_time));
1.126 brouard 14402: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
14403: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 14404: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 14405:
1.157 brouard 14406: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
14407: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
14408: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 14409: /* printf("Total time was %d uSec.\n", total_usecs);*/
14410: /* if(fileappend(fichtm,optionfilehtm)){ */
14411: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14412: fclose(fichtm);
14413: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14414: fclose(fichtmcov);
14415: fclose(ficgp);
14416: fclose(ficlog);
14417: /*------ End -----------*/
1.227 brouard 14418:
1.281 brouard 14419:
14420: /* Executes gnuplot */
1.227 brouard 14421:
14422: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 14423: #ifdef WIN32
1.227 brouard 14424: if (_chdir(pathcd) != 0)
14425: printf("Can't move to directory %s!\n",path);
14426: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 14427: #else
1.227 brouard 14428: if(chdir(pathcd) != 0)
14429: printf("Can't move to directory %s!\n", path);
14430: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 14431: #endif
1.126 brouard 14432: printf("Current directory %s!\n",pathcd);
14433: /*strcat(plotcmd,CHARSEPARATOR);*/
14434: sprintf(plotcmd,"gnuplot");
1.157 brouard 14435: #ifdef _WIN32
1.126 brouard 14436: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
14437: #endif
14438: if(!stat(plotcmd,&info)){
1.158 brouard 14439: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14440: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 14441: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 14442: }else
14443: strcpy(pplotcmd,plotcmd);
1.157 brouard 14444: #ifdef __unix
1.126 brouard 14445: strcpy(plotcmd,GNUPLOTPROGRAM);
14446: if(!stat(plotcmd,&info)){
1.158 brouard 14447: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14448: }else
14449: strcpy(pplotcmd,plotcmd);
14450: #endif
14451: }else
14452: strcpy(pplotcmd,plotcmd);
14453:
14454: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 14455: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 14456: strcpy(pplotcmd,plotcmd);
1.227 brouard 14457:
1.126 brouard 14458: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 14459: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 14460: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 14461: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 14462: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 14463: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 14464: strcpy(plotcmd,pplotcmd);
14465: }
1.126 brouard 14466: }
1.158 brouard 14467: printf(" Successful, please wait...");
1.126 brouard 14468: while (z[0] != 'q') {
14469: /* chdir(path); */
1.154 brouard 14470: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 14471: scanf("%s",z);
14472: /* if (z[0] == 'c') system("./imach"); */
14473: if (z[0] == 'e') {
1.158 brouard 14474: #ifdef __APPLE__
1.152 brouard 14475: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 14476: #elif __linux
14477: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 14478: #else
1.152 brouard 14479: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 14480: #endif
14481: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
14482: system(pplotcmd);
1.126 brouard 14483: }
14484: else if (z[0] == 'g') system(plotcmd);
14485: else if (z[0] == 'q') exit(0);
14486: }
1.227 brouard 14487: end:
1.126 brouard 14488: while (z[0] != 'q') {
1.195 brouard 14489: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 14490: scanf("%s",z);
14491: }
1.283 brouard 14492: printf("End\n");
1.282 brouard 14493: exit(0);
1.126 brouard 14494: }
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