Annotation of imach/src/imach.c, revision 1.323
1.323 ! brouard 1: /* $Id: imach.c,v 1.322 2022/07/22 12:27:48 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.323 ! brouard 4: Revision 1.322 2022/07/22 12:27:48 brouard
! 5: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
! 6:
1.322 brouard 7: Revision 1.321 2022/07/22 12:04:24 brouard
8: Summary: r28
9:
10: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
11:
1.321 brouard 12: Revision 1.320 2022/06/02 05:10:11 brouard
13: *** empty log message ***
14:
1.320 brouard 15: Revision 1.319 2022/06/02 04:45:11 brouard
16: * imach.c (Module): Adding the Wald tests from the log to the main
17: htm for better display of the maximum likelihood estimators.
18:
1.319 brouard 19: Revision 1.318 2022/05/24 08:10:59 brouard
20: * imach.c (Module): Some attempts to find a bug of wrong estimates
21: of confidencce intervals with product in the equation modelC
22:
1.318 brouard 23: Revision 1.317 2022/05/15 15:06:23 brouard
24: * imach.c (Module): Some minor improvements
25:
1.317 brouard 26: Revision 1.316 2022/05/11 15:11:31 brouard
27: Summary: r27
28:
1.316 brouard 29: Revision 1.315 2022/05/11 15:06:32 brouard
30: *** empty log message ***
31:
1.315 brouard 32: Revision 1.314 2022/04/13 17:43:09 brouard
33: * imach.c (Module): Adding link to text data files
34:
1.314 brouard 35: Revision 1.313 2022/04/11 15:57:42 brouard
36: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
37:
1.313 brouard 38: Revision 1.312 2022/04/05 21:24:39 brouard
39: *** empty log message ***
40:
1.312 brouard 41: Revision 1.311 2022/04/05 21:03:51 brouard
42: Summary: Fixed quantitative covariates
43:
44: Fixed covariates (dummy or quantitative)
45: with missing values have never been allowed but are ERRORS and
46: program quits. Standard deviations of fixed covariates were
47: wrongly computed. Mean and standard deviations of time varying
48: covariates are still not computed.
49:
1.311 brouard 50: Revision 1.310 2022/03/17 08:45:53 brouard
51: Summary: 99r25
52:
53: Improving detection of errors: result lines should be compatible with
54: the model.
55:
1.310 brouard 56: Revision 1.309 2021/05/20 12:39:14 brouard
57: Summary: Version 0.99r24
58:
1.309 brouard 59: Revision 1.308 2021/03/31 13:11:57 brouard
60: Summary: Version 0.99r23
61:
62:
63: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
64:
1.308 brouard 65: Revision 1.307 2021/03/08 18:11:32 brouard
66: Summary: 0.99r22 fixed bug on result:
67:
1.307 brouard 68: Revision 1.306 2021/02/20 15:44:02 brouard
69: Summary: Version 0.99r21
70:
71: * imach.c (Module): Fix bug on quitting after result lines!
72: (Module): Version 0.99r21
73:
1.306 brouard 74: Revision 1.305 2021/02/20 15:28:30 brouard
75: * imach.c (Module): Fix bug on quitting after result lines!
76:
1.305 brouard 77: Revision 1.304 2021/02/12 11:34:20 brouard
78: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
79:
1.304 brouard 80: Revision 1.303 2021/02/11 19:50:15 brouard
81: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
82:
1.303 brouard 83: Revision 1.302 2020/02/22 21:00:05 brouard
84: * (Module): imach.c Update mle=-3 (for computing Life expectancy
85: and life table from the data without any state)
86:
1.302 brouard 87: Revision 1.301 2019/06/04 13:51:20 brouard
88: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
89:
1.301 brouard 90: Revision 1.300 2019/05/22 19:09:45 brouard
91: Summary: version 0.99r19 of May 2019
92:
1.300 brouard 93: Revision 1.299 2019/05/22 18:37:08 brouard
94: Summary: Cleaned 0.99r19
95:
1.299 brouard 96: Revision 1.298 2019/05/22 18:19:56 brouard
97: *** empty log message ***
98:
1.298 brouard 99: Revision 1.297 2019/05/22 17:56:10 brouard
100: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
101:
1.297 brouard 102: Revision 1.296 2019/05/20 13:03:18 brouard
103: Summary: Projection syntax simplified
104:
105:
106: We can now start projections, forward or backward, from the mean date
107: of inteviews up to or down to a number of years of projection:
108: prevforecast=1 yearsfproj=15.3 mobil_average=0
109: or
110: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
111: or
112: prevbackcast=1 yearsbproj=12.3 mobil_average=1
113: or
114: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
115:
1.296 brouard 116: Revision 1.295 2019/05/18 09:52:50 brouard
117: Summary: doxygen tex bug
118:
1.295 brouard 119: Revision 1.294 2019/05/16 14:54:33 brouard
120: Summary: There was some wrong lines added
121:
1.294 brouard 122: Revision 1.293 2019/05/09 15:17:34 brouard
123: *** empty log message ***
124:
1.293 brouard 125: Revision 1.292 2019/05/09 14:17:20 brouard
126: Summary: Some updates
127:
1.292 brouard 128: Revision 1.291 2019/05/09 13:44:18 brouard
129: Summary: Before ncovmax
130:
1.291 brouard 131: Revision 1.290 2019/05/09 13:39:37 brouard
132: Summary: 0.99r18 unlimited number of individuals
133:
134: 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.
135:
1.290 brouard 136: Revision 1.289 2018/12/13 09:16:26 brouard
137: Summary: Bug for young ages (<-30) will be in r17
138:
1.289 brouard 139: Revision 1.288 2018/05/02 20:58:27 brouard
140: Summary: Some bugs fixed
141:
1.288 brouard 142: Revision 1.287 2018/05/01 17:57:25 brouard
143: Summary: Bug fixed by providing frequencies only for non missing covariates
144:
1.287 brouard 145: Revision 1.286 2018/04/27 14:27:04 brouard
146: Summary: some minor bugs
147:
1.286 brouard 148: Revision 1.285 2018/04/21 21:02:16 brouard
149: Summary: Some bugs fixed, valgrind tested
150:
1.285 brouard 151: Revision 1.284 2018/04/20 05:22:13 brouard
152: Summary: Computing mean and stdeviation of fixed quantitative variables
153:
1.284 brouard 154: Revision 1.283 2018/04/19 14:49:16 brouard
155: Summary: Some minor bugs fixed
156:
1.283 brouard 157: Revision 1.282 2018/02/27 22:50:02 brouard
158: *** empty log message ***
159:
1.282 brouard 160: Revision 1.281 2018/02/27 19:25:23 brouard
161: Summary: Adding second argument for quitting
162:
1.281 brouard 163: Revision 1.280 2018/02/21 07:58:13 brouard
164: Summary: 0.99r15
165:
166: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
167:
1.280 brouard 168: Revision 1.279 2017/07/20 13:35:01 brouard
169: Summary: temporary working
170:
1.279 brouard 171: Revision 1.278 2017/07/19 14:09:02 brouard
172: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
173:
1.278 brouard 174: Revision 1.277 2017/07/17 08:53:49 brouard
175: Summary: BOM files can be read now
176:
1.277 brouard 177: Revision 1.276 2017/06/30 15:48:31 brouard
178: Summary: Graphs improvements
179:
1.276 brouard 180: Revision 1.275 2017/06/30 13:39:33 brouard
181: Summary: Saito's color
182:
1.275 brouard 183: Revision 1.274 2017/06/29 09:47:08 brouard
184: Summary: Version 0.99r14
185:
1.274 brouard 186: Revision 1.273 2017/06/27 11:06:02 brouard
187: Summary: More documentation on projections
188:
1.273 brouard 189: Revision 1.272 2017/06/27 10:22:40 brouard
190: Summary: Color of backprojection changed from 6 to 5(yellow)
191:
1.272 brouard 192: Revision 1.271 2017/06/27 10:17:50 brouard
193: Summary: Some bug with rint
194:
1.271 brouard 195: Revision 1.270 2017/05/24 05:45:29 brouard
196: *** empty log message ***
197:
1.270 brouard 198: Revision 1.269 2017/05/23 08:39:25 brouard
199: Summary: Code into subroutine, cleanings
200:
1.269 brouard 201: Revision 1.268 2017/05/18 20:09:32 brouard
202: Summary: backprojection and confidence intervals of backprevalence
203:
1.268 brouard 204: Revision 1.267 2017/05/13 10:25:05 brouard
205: Summary: temporary save for backprojection
206:
1.267 brouard 207: Revision 1.266 2017/05/13 07:26:12 brouard
208: Summary: Version 0.99r13 (improvements and bugs fixed)
209:
1.266 brouard 210: Revision 1.265 2017/04/26 16:22:11 brouard
211: Summary: imach 0.99r13 Some bugs fixed
212:
1.265 brouard 213: Revision 1.264 2017/04/26 06:01:29 brouard
214: Summary: Labels in graphs
215:
1.264 brouard 216: Revision 1.263 2017/04/24 15:23:15 brouard
217: Summary: to save
218:
1.263 brouard 219: Revision 1.262 2017/04/18 16:48:12 brouard
220: *** empty log message ***
221:
1.262 brouard 222: Revision 1.261 2017/04/05 10:14:09 brouard
223: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
224:
1.261 brouard 225: Revision 1.260 2017/04/04 17:46:59 brouard
226: Summary: Gnuplot indexations fixed (humm)
227:
1.260 brouard 228: Revision 1.259 2017/04/04 13:01:16 brouard
229: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
230:
1.259 brouard 231: Revision 1.258 2017/04/03 10:17:47 brouard
232: Summary: Version 0.99r12
233:
234: Some cleanings, conformed with updated documentation.
235:
1.258 brouard 236: Revision 1.257 2017/03/29 16:53:30 brouard
237: Summary: Temp
238:
1.257 brouard 239: Revision 1.256 2017/03/27 05:50:23 brouard
240: Summary: Temporary
241:
1.256 brouard 242: Revision 1.255 2017/03/08 16:02:28 brouard
243: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
244:
1.255 brouard 245: Revision 1.254 2017/03/08 07:13:00 brouard
246: Summary: Fixing data parameter line
247:
1.254 brouard 248: Revision 1.253 2016/12/15 11:59:41 brouard
249: Summary: 0.99 in progress
250:
1.253 brouard 251: Revision 1.252 2016/09/15 21:15:37 brouard
252: *** empty log message ***
253:
1.252 brouard 254: Revision 1.251 2016/09/15 15:01:13 brouard
255: Summary: not working
256:
1.251 brouard 257: Revision 1.250 2016/09/08 16:07:27 brouard
258: Summary: continue
259:
1.250 brouard 260: Revision 1.249 2016/09/07 17:14:18 brouard
261: Summary: Starting values from frequencies
262:
1.249 brouard 263: Revision 1.248 2016/09/07 14:10:18 brouard
264: *** empty log message ***
265:
1.248 brouard 266: Revision 1.247 2016/09/02 11:11:21 brouard
267: *** empty log message ***
268:
1.247 brouard 269: Revision 1.246 2016/09/02 08:49:22 brouard
270: *** empty log message ***
271:
1.246 brouard 272: Revision 1.245 2016/09/02 07:25:01 brouard
273: *** empty log message ***
274:
1.245 brouard 275: Revision 1.244 2016/09/02 07:17:34 brouard
276: *** empty log message ***
277:
1.244 brouard 278: Revision 1.243 2016/09/02 06:45:35 brouard
279: *** empty log message ***
280:
1.243 brouard 281: Revision 1.242 2016/08/30 15:01:20 brouard
282: Summary: Fixing a lots
283:
1.242 brouard 284: Revision 1.241 2016/08/29 17:17:25 brouard
285: Summary: gnuplot problem in Back projection to fix
286:
1.241 brouard 287: Revision 1.240 2016/08/29 07:53:18 brouard
288: Summary: Better
289:
1.240 brouard 290: Revision 1.239 2016/08/26 15:51:03 brouard
291: Summary: Improvement in Powell output in order to copy and paste
292:
293: Author:
294:
1.239 brouard 295: Revision 1.238 2016/08/26 14:23:35 brouard
296: Summary: Starting tests of 0.99
297:
1.238 brouard 298: Revision 1.237 2016/08/26 09:20:19 brouard
299: Summary: to valgrind
300:
1.237 brouard 301: Revision 1.236 2016/08/25 10:50:18 brouard
302: *** empty log message ***
303:
1.236 brouard 304: Revision 1.235 2016/08/25 06:59:23 brouard
305: *** empty log message ***
306:
1.235 brouard 307: Revision 1.234 2016/08/23 16:51:20 brouard
308: *** empty log message ***
309:
1.234 brouard 310: Revision 1.233 2016/08/23 07:40:50 brouard
311: Summary: not working
312:
1.233 brouard 313: Revision 1.232 2016/08/22 14:20:21 brouard
314: Summary: not working
315:
1.232 brouard 316: Revision 1.231 2016/08/22 07:17:15 brouard
317: Summary: not working
318:
1.231 brouard 319: Revision 1.230 2016/08/22 06:55:53 brouard
320: Summary: Not working
321:
1.230 brouard 322: Revision 1.229 2016/07/23 09:45:53 brouard
323: Summary: Completing for func too
324:
1.229 brouard 325: Revision 1.228 2016/07/22 17:45:30 brouard
326: Summary: Fixing some arrays, still debugging
327:
1.227 brouard 328: Revision 1.226 2016/07/12 18:42:34 brouard
329: Summary: temp
330:
1.226 brouard 331: Revision 1.225 2016/07/12 08:40:03 brouard
332: Summary: saving but not running
333:
1.225 brouard 334: Revision 1.224 2016/07/01 13:16:01 brouard
335: Summary: Fixes
336:
1.224 brouard 337: Revision 1.223 2016/02/19 09:23:35 brouard
338: Summary: temporary
339:
1.223 brouard 340: Revision 1.222 2016/02/17 08:14:50 brouard
341: Summary: Probably last 0.98 stable version 0.98r6
342:
1.222 brouard 343: Revision 1.221 2016/02/15 23:35:36 brouard
344: Summary: minor bug
345:
1.220 brouard 346: Revision 1.219 2016/02/15 00:48:12 brouard
347: *** empty log message ***
348:
1.219 brouard 349: Revision 1.218 2016/02/12 11:29:23 brouard
350: Summary: 0.99 Back projections
351:
1.218 brouard 352: Revision 1.217 2015/12/23 17:18:31 brouard
353: Summary: Experimental backcast
354:
1.217 brouard 355: Revision 1.216 2015/12/18 17:32:11 brouard
356: Summary: 0.98r4 Warning and status=-2
357:
358: Version 0.98r4 is now:
359: - displaying an error when status is -1, date of interview unknown and date of death known;
360: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
361: Older changes concerning s=-2, dating from 2005 have been supersed.
362:
1.216 brouard 363: Revision 1.215 2015/12/16 08:52:24 brouard
364: Summary: 0.98r4 working
365:
1.215 brouard 366: Revision 1.214 2015/12/16 06:57:54 brouard
367: Summary: temporary not working
368:
1.214 brouard 369: Revision 1.213 2015/12/11 18:22:17 brouard
370: Summary: 0.98r4
371:
1.213 brouard 372: Revision 1.212 2015/11/21 12:47:24 brouard
373: Summary: minor typo
374:
1.212 brouard 375: Revision 1.211 2015/11/21 12:41:11 brouard
376: Summary: 0.98r3 with some graph of projected cross-sectional
377:
378: Author: Nicolas Brouard
379:
1.211 brouard 380: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 381: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 382: Summary: Adding ftolpl parameter
383: Author: N Brouard
384:
385: We had difficulties to get smoothed confidence intervals. It was due
386: to the period prevalence which wasn't computed accurately. The inner
387: parameter ftolpl is now an outer parameter of the .imach parameter
388: file after estepm. If ftolpl is small 1.e-4 and estepm too,
389: computation are long.
390:
1.209 brouard 391: Revision 1.208 2015/11/17 14:31:57 brouard
392: Summary: temporary
393:
1.208 brouard 394: Revision 1.207 2015/10/27 17:36:57 brouard
395: *** empty log message ***
396:
1.207 brouard 397: Revision 1.206 2015/10/24 07:14:11 brouard
398: *** empty log message ***
399:
1.206 brouard 400: Revision 1.205 2015/10/23 15:50:53 brouard
401: Summary: 0.98r3 some clarification for graphs on likelihood contributions
402:
1.205 brouard 403: Revision 1.204 2015/10/01 16:20:26 brouard
404: Summary: Some new graphs of contribution to likelihood
405:
1.204 brouard 406: Revision 1.203 2015/09/30 17:45:14 brouard
407: Summary: looking at better estimation of the hessian
408:
409: Also a better criteria for convergence to the period prevalence And
410: therefore adding the number of years needed to converge. (The
411: prevalence in any alive state shold sum to one
412:
1.203 brouard 413: Revision 1.202 2015/09/22 19:45:16 brouard
414: Summary: Adding some overall graph on contribution to likelihood. Might change
415:
1.202 brouard 416: Revision 1.201 2015/09/15 17:34:58 brouard
417: Summary: 0.98r0
418:
419: - Some new graphs like suvival functions
420: - Some bugs fixed like model=1+age+V2.
421:
1.201 brouard 422: Revision 1.200 2015/09/09 16:53:55 brouard
423: Summary: Big bug thanks to Flavia
424:
425: Even model=1+age+V2. did not work anymore
426:
1.200 brouard 427: Revision 1.199 2015/09/07 14:09:23 brouard
428: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
429:
1.199 brouard 430: Revision 1.198 2015/09/03 07:14:39 brouard
431: Summary: 0.98q5 Flavia
432:
1.198 brouard 433: Revision 1.197 2015/09/01 18:24:39 brouard
434: *** empty log message ***
435:
1.197 brouard 436: Revision 1.196 2015/08/18 23:17:52 brouard
437: Summary: 0.98q5
438:
1.196 brouard 439: Revision 1.195 2015/08/18 16:28:39 brouard
440: Summary: Adding a hack for testing purpose
441:
442: After reading the title, ftol and model lines, if the comment line has
443: a q, starting with #q, the answer at the end of the run is quit. It
444: permits to run test files in batch with ctest. The former workaround was
445: $ echo q | imach foo.imach
446:
1.195 brouard 447: Revision 1.194 2015/08/18 13:32:00 brouard
448: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
449:
1.194 brouard 450: Revision 1.193 2015/08/04 07:17:42 brouard
451: Summary: 0.98q4
452:
1.193 brouard 453: Revision 1.192 2015/07/16 16:49:02 brouard
454: Summary: Fixing some outputs
455:
1.192 brouard 456: Revision 1.191 2015/07/14 10:00:33 brouard
457: Summary: Some fixes
458:
1.191 brouard 459: Revision 1.190 2015/05/05 08:51:13 brouard
460: Summary: Adding digits in output parameters (7 digits instead of 6)
461:
462: Fix 1+age+.
463:
1.190 brouard 464: Revision 1.189 2015/04/30 14:45:16 brouard
465: Summary: 0.98q2
466:
1.189 brouard 467: Revision 1.188 2015/04/30 08:27:53 brouard
468: *** empty log message ***
469:
1.188 brouard 470: Revision 1.187 2015/04/29 09:11:15 brouard
471: *** empty log message ***
472:
1.187 brouard 473: Revision 1.186 2015/04/23 12:01:52 brouard
474: Summary: V1*age is working now, version 0.98q1
475:
476: Some codes had been disabled in order to simplify and Vn*age was
477: working in the optimization phase, ie, giving correct MLE parameters,
478: but, as usual, outputs were not correct and program core dumped.
479:
1.186 brouard 480: Revision 1.185 2015/03/11 13:26:42 brouard
481: Summary: Inclusion of compile and links command line for Intel Compiler
482:
1.185 brouard 483: Revision 1.184 2015/03/11 11:52:39 brouard
484: Summary: Back from Windows 8. Intel Compiler
485:
1.184 brouard 486: Revision 1.183 2015/03/10 20:34:32 brouard
487: Summary: 0.98q0, trying with directest, mnbrak fixed
488:
489: We use directest instead of original Powell test; probably no
490: incidence on the results, but better justifications;
491: We fixed Numerical Recipes mnbrak routine which was wrong and gave
492: wrong results.
493:
1.183 brouard 494: Revision 1.182 2015/02/12 08:19:57 brouard
495: Summary: Trying to keep directest which seems simpler and more general
496: Author: Nicolas Brouard
497:
1.182 brouard 498: Revision 1.181 2015/02/11 23:22:24 brouard
499: Summary: Comments on Powell added
500:
501: Author:
502:
1.181 brouard 503: Revision 1.180 2015/02/11 17:33:45 brouard
504: Summary: Finishing move from main to function (hpijx and prevalence_limit)
505:
1.180 brouard 506: Revision 1.179 2015/01/04 09:57:06 brouard
507: Summary: back to OS/X
508:
1.179 brouard 509: Revision 1.178 2015/01/04 09:35:48 brouard
510: *** empty log message ***
511:
1.178 brouard 512: Revision 1.177 2015/01/03 18:40:56 brouard
513: Summary: Still testing ilc32 on OSX
514:
1.177 brouard 515: Revision 1.176 2015/01/03 16:45:04 brouard
516: *** empty log message ***
517:
1.176 brouard 518: Revision 1.175 2015/01/03 16:33:42 brouard
519: *** empty log message ***
520:
1.175 brouard 521: Revision 1.174 2015/01/03 16:15:49 brouard
522: Summary: Still in cross-compilation
523:
1.174 brouard 524: Revision 1.173 2015/01/03 12:06:26 brouard
525: Summary: trying to detect cross-compilation
526:
1.173 brouard 527: Revision 1.172 2014/12/27 12:07:47 brouard
528: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
529:
1.172 brouard 530: Revision 1.171 2014/12/23 13:26:59 brouard
531: Summary: Back from Visual C
532:
533: Still problem with utsname.h on Windows
534:
1.171 brouard 535: Revision 1.170 2014/12/23 11:17:12 brouard
536: Summary: Cleaning some \%% back to %%
537:
538: The escape was mandatory for a specific compiler (which one?), but too many warnings.
539:
1.170 brouard 540: Revision 1.169 2014/12/22 23:08:31 brouard
541: Summary: 0.98p
542:
543: Outputs some informations on compiler used, OS etc. Testing on different platforms.
544:
1.169 brouard 545: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 546: Summary: update
1.169 brouard 547:
1.168 brouard 548: Revision 1.167 2014/12/22 13:50:56 brouard
549: Summary: Testing uname and compiler version and if compiled 32 or 64
550:
551: Testing on Linux 64
552:
1.167 brouard 553: Revision 1.166 2014/12/22 11:40:47 brouard
554: *** empty log message ***
555:
1.166 brouard 556: Revision 1.165 2014/12/16 11:20:36 brouard
557: Summary: After compiling on Visual C
558:
559: * imach.c (Module): Merging 1.61 to 1.162
560:
1.165 brouard 561: Revision 1.164 2014/12/16 10:52:11 brouard
562: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
563:
564: * imach.c (Module): Merging 1.61 to 1.162
565:
1.164 brouard 566: Revision 1.163 2014/12/16 10:30:11 brouard
567: * imach.c (Module): Merging 1.61 to 1.162
568:
1.163 brouard 569: Revision 1.162 2014/09/25 11:43:39 brouard
570: Summary: temporary backup 0.99!
571:
1.162 brouard 572: Revision 1.1 2014/09/16 11:06:58 brouard
573: Summary: With some code (wrong) for nlopt
574:
575: Author:
576:
577: Revision 1.161 2014/09/15 20:41:41 brouard
578: Summary: Problem with macro SQR on Intel compiler
579:
1.161 brouard 580: Revision 1.160 2014/09/02 09:24:05 brouard
581: *** empty log message ***
582:
1.160 brouard 583: Revision 1.159 2014/09/01 10:34:10 brouard
584: Summary: WIN32
585: Author: Brouard
586:
1.159 brouard 587: Revision 1.158 2014/08/27 17:11:51 brouard
588: *** empty log message ***
589:
1.158 brouard 590: Revision 1.157 2014/08/27 16:26:55 brouard
591: Summary: Preparing windows Visual studio version
592: Author: Brouard
593:
594: In order to compile on Visual studio, time.h is now correct and time_t
595: and tm struct should be used. difftime should be used but sometimes I
596: just make the differences in raw time format (time(&now).
597: Trying to suppress #ifdef LINUX
598: Add xdg-open for __linux in order to open default browser.
599:
1.157 brouard 600: Revision 1.156 2014/08/25 20:10:10 brouard
601: *** empty log message ***
602:
1.156 brouard 603: Revision 1.155 2014/08/25 18:32:34 brouard
604: Summary: New compile, minor changes
605: Author: Brouard
606:
1.155 brouard 607: Revision 1.154 2014/06/20 17:32:08 brouard
608: Summary: Outputs now all graphs of convergence to period prevalence
609:
1.154 brouard 610: Revision 1.153 2014/06/20 16:45:46 brouard
611: Summary: If 3 live state, convergence to period prevalence on same graph
612: Author: Brouard
613:
1.153 brouard 614: Revision 1.152 2014/06/18 17:54:09 brouard
615: Summary: open browser, use gnuplot on same dir than imach if not found in the path
616:
1.152 brouard 617: Revision 1.151 2014/06/18 16:43:30 brouard
618: *** empty log message ***
619:
1.151 brouard 620: Revision 1.150 2014/06/18 16:42:35 brouard
621: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
622: Author: brouard
623:
1.150 brouard 624: Revision 1.149 2014/06/18 15:51:14 brouard
625: Summary: Some fixes in parameter files errors
626: Author: Nicolas Brouard
627:
1.149 brouard 628: Revision 1.148 2014/06/17 17:38:48 brouard
629: Summary: Nothing new
630: Author: Brouard
631:
632: Just a new packaging for OS/X version 0.98nS
633:
1.148 brouard 634: Revision 1.147 2014/06/16 10:33:11 brouard
635: *** empty log message ***
636:
1.147 brouard 637: Revision 1.146 2014/06/16 10:20:28 brouard
638: Summary: Merge
639: Author: Brouard
640:
641: Merge, before building revised version.
642:
1.146 brouard 643: Revision 1.145 2014/06/10 21:23:15 brouard
644: Summary: Debugging with valgrind
645: Author: Nicolas Brouard
646:
647: Lot of changes in order to output the results with some covariates
648: After the Edimburgh REVES conference 2014, it seems mandatory to
649: improve the code.
650: No more memory valgrind error but a lot has to be done in order to
651: continue the work of splitting the code into subroutines.
652: Also, decodemodel has been improved. Tricode is still not
653: optimal. nbcode should be improved. Documentation has been added in
654: the source code.
655:
1.144 brouard 656: Revision 1.143 2014/01/26 09:45:38 brouard
657: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
658:
659: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
660: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
661:
1.143 brouard 662: Revision 1.142 2014/01/26 03:57:36 brouard
663: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
664:
665: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
666:
1.142 brouard 667: Revision 1.141 2014/01/26 02:42:01 brouard
668: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
669:
1.141 brouard 670: Revision 1.140 2011/09/02 10:37:54 brouard
671: Summary: times.h is ok with mingw32 now.
672:
1.140 brouard 673: Revision 1.139 2010/06/14 07:50:17 brouard
674: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
675: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
676:
1.139 brouard 677: Revision 1.138 2010/04/30 18:19:40 brouard
678: *** empty log message ***
679:
1.138 brouard 680: Revision 1.137 2010/04/29 18:11:38 brouard
681: (Module): Checking covariates for more complex models
682: than V1+V2. A lot of change to be done. Unstable.
683:
1.137 brouard 684: Revision 1.136 2010/04/26 20:30:53 brouard
685: (Module): merging some libgsl code. Fixing computation
686: of likelione (using inter/intrapolation if mle = 0) in order to
687: get same likelihood as if mle=1.
688: Some cleaning of code and comments added.
689:
1.136 brouard 690: Revision 1.135 2009/10/29 15:33:14 brouard
691: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
692:
1.135 brouard 693: Revision 1.134 2009/10/29 13:18:53 brouard
694: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
695:
1.134 brouard 696: Revision 1.133 2009/07/06 10:21:25 brouard
697: just nforces
698:
1.133 brouard 699: Revision 1.132 2009/07/06 08:22:05 brouard
700: Many tings
701:
1.132 brouard 702: Revision 1.131 2009/06/20 16:22:47 brouard
703: Some dimensions resccaled
704:
1.131 brouard 705: Revision 1.130 2009/05/26 06:44:34 brouard
706: (Module): Max Covariate is now set to 20 instead of 8. A
707: lot of cleaning with variables initialized to 0. Trying to make
708: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
709:
1.130 brouard 710: Revision 1.129 2007/08/31 13:49:27 lievre
711: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
712:
1.129 lievre 713: Revision 1.128 2006/06/30 13:02:05 brouard
714: (Module): Clarifications on computing e.j
715:
1.128 brouard 716: Revision 1.127 2006/04/28 18:11:50 brouard
717: (Module): Yes the sum of survivors was wrong since
718: imach-114 because nhstepm was no more computed in the age
719: loop. Now we define nhstepma in the age loop.
720: (Module): In order to speed up (in case of numerous covariates) we
721: compute health expectancies (without variances) in a first step
722: and then all the health expectancies with variances or standard
723: deviation (needs data from the Hessian matrices) which slows the
724: computation.
725: In the future we should be able to stop the program is only health
726: expectancies and graph are needed without standard deviations.
727:
1.127 brouard 728: Revision 1.126 2006/04/28 17:23:28 brouard
729: (Module): Yes the sum of survivors was wrong since
730: imach-114 because nhstepm was no more computed in the age
731: loop. Now we define nhstepma in the age loop.
732: Version 0.98h
733:
1.126 brouard 734: Revision 1.125 2006/04/04 15:20:31 lievre
735: Errors in calculation of health expectancies. Age was not initialized.
736: Forecasting file added.
737:
738: Revision 1.124 2006/03/22 17:13:53 lievre
739: Parameters are printed with %lf instead of %f (more numbers after the comma).
740: The log-likelihood is printed in the log file
741:
742: Revision 1.123 2006/03/20 10:52:43 brouard
743: * imach.c (Module): <title> changed, corresponds to .htm file
744: name. <head> headers where missing.
745:
746: * imach.c (Module): Weights can have a decimal point as for
747: English (a comma might work with a correct LC_NUMERIC environment,
748: otherwise the weight is truncated).
749: Modification of warning when the covariates values are not 0 or
750: 1.
751: Version 0.98g
752:
753: Revision 1.122 2006/03/20 09:45:41 brouard
754: (Module): Weights can have a decimal point as for
755: English (a comma might work with a correct LC_NUMERIC environment,
756: otherwise the weight is truncated).
757: Modification of warning when the covariates values are not 0 or
758: 1.
759: Version 0.98g
760:
761: Revision 1.121 2006/03/16 17:45:01 lievre
762: * imach.c (Module): Comments concerning covariates added
763:
764: * imach.c (Module): refinements in the computation of lli if
765: status=-2 in order to have more reliable computation if stepm is
766: not 1 month. Version 0.98f
767:
768: Revision 1.120 2006/03/16 15:10:38 lievre
769: (Module): refinements in the computation of lli if
770: status=-2 in order to have more reliable computation if stepm is
771: not 1 month. Version 0.98f
772:
773: Revision 1.119 2006/03/15 17:42:26 brouard
774: (Module): Bug if status = -2, the loglikelihood was
775: computed as likelihood omitting the logarithm. Version O.98e
776:
777: Revision 1.118 2006/03/14 18:20:07 brouard
778: (Module): varevsij Comments added explaining the second
779: table of variances if popbased=1 .
780: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
781: (Module): Function pstamp added
782: (Module): Version 0.98d
783:
784: Revision 1.117 2006/03/14 17:16:22 brouard
785: (Module): varevsij Comments added explaining the second
786: table of variances if popbased=1 .
787: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
788: (Module): Function pstamp added
789: (Module): Version 0.98d
790:
791: Revision 1.116 2006/03/06 10:29:27 brouard
792: (Module): Variance-covariance wrong links and
793: varian-covariance of ej. is needed (Saito).
794:
795: Revision 1.115 2006/02/27 12:17:45 brouard
796: (Module): One freematrix added in mlikeli! 0.98c
797:
798: Revision 1.114 2006/02/26 12:57:58 brouard
799: (Module): Some improvements in processing parameter
800: filename with strsep.
801:
802: Revision 1.113 2006/02/24 14:20:24 brouard
803: (Module): Memory leaks checks with valgrind and:
804: datafile was not closed, some imatrix were not freed and on matrix
805: allocation too.
806:
807: Revision 1.112 2006/01/30 09:55:26 brouard
808: (Module): Back to gnuplot.exe instead of wgnuplot.exe
809:
810: Revision 1.111 2006/01/25 20:38:18 brouard
811: (Module): Lots of cleaning and bugs added (Gompertz)
812: (Module): Comments can be added in data file. Missing date values
813: can be a simple dot '.'.
814:
815: Revision 1.110 2006/01/25 00:51:50 brouard
816: (Module): Lots of cleaning and bugs added (Gompertz)
817:
818: Revision 1.109 2006/01/24 19:37:15 brouard
819: (Module): Comments (lines starting with a #) are allowed in data.
820:
821: Revision 1.108 2006/01/19 18:05:42 lievre
822: Gnuplot problem appeared...
823: To be fixed
824:
825: Revision 1.107 2006/01/19 16:20:37 brouard
826: Test existence of gnuplot in imach path
827:
828: Revision 1.106 2006/01/19 13:24:36 brouard
829: Some cleaning and links added in html output
830:
831: Revision 1.105 2006/01/05 20:23:19 lievre
832: *** empty log message ***
833:
834: Revision 1.104 2005/09/30 16:11:43 lievre
835: (Module): sump fixed, loop imx fixed, and simplifications.
836: (Module): If the status is missing at the last wave but we know
837: that the person is alive, then we can code his/her status as -2
838: (instead of missing=-1 in earlier versions) and his/her
839: contributions to the likelihood is 1 - Prob of dying from last
840: health status (= 1-p13= p11+p12 in the easiest case of somebody in
841: the healthy state at last known wave). Version is 0.98
842:
843: Revision 1.103 2005/09/30 15:54:49 lievre
844: (Module): sump fixed, loop imx fixed, and simplifications.
845:
846: Revision 1.102 2004/09/15 17:31:30 brouard
847: Add the possibility to read data file including tab characters.
848:
849: Revision 1.101 2004/09/15 10:38:38 brouard
850: Fix on curr_time
851:
852: Revision 1.100 2004/07/12 18:29:06 brouard
853: Add version for Mac OS X. Just define UNIX in Makefile
854:
855: Revision 1.99 2004/06/05 08:57:40 brouard
856: *** empty log message ***
857:
858: Revision 1.98 2004/05/16 15:05:56 brouard
859: New version 0.97 . First attempt to estimate force of mortality
860: directly from the data i.e. without the need of knowing the health
861: state at each age, but using a Gompertz model: log u =a + b*age .
862: This is the basic analysis of mortality and should be done before any
863: other analysis, in order to test if the mortality estimated from the
864: cross-longitudinal survey is different from the mortality estimated
865: from other sources like vital statistic data.
866:
867: The same imach parameter file can be used but the option for mle should be -3.
868:
1.133 brouard 869: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 870: former routines in order to include the new code within the former code.
871:
872: The output is very simple: only an estimate of the intercept and of
873: the slope with 95% confident intervals.
874:
875: Current limitations:
876: A) Even if you enter covariates, i.e. with the
877: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
878: B) There is no computation of Life Expectancy nor Life Table.
879:
880: Revision 1.97 2004/02/20 13:25:42 lievre
881: Version 0.96d. Population forecasting command line is (temporarily)
882: suppressed.
883:
884: Revision 1.96 2003/07/15 15:38:55 brouard
885: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
886: rewritten within the same printf. Workaround: many printfs.
887:
888: Revision 1.95 2003/07/08 07:54:34 brouard
889: * imach.c (Repository):
890: (Repository): Using imachwizard code to output a more meaningful covariance
891: matrix (cov(a12,c31) instead of numbers.
892:
893: Revision 1.94 2003/06/27 13:00:02 brouard
894: Just cleaning
895:
896: Revision 1.93 2003/06/25 16:33:55 brouard
897: (Module): On windows (cygwin) function asctime_r doesn't
898: exist so I changed back to asctime which exists.
899: (Module): Version 0.96b
900:
901: Revision 1.92 2003/06/25 16:30:45 brouard
902: (Module): On windows (cygwin) function asctime_r doesn't
903: exist so I changed back to asctime which exists.
904:
905: Revision 1.91 2003/06/25 15:30:29 brouard
906: * imach.c (Repository): Duplicated warning errors corrected.
907: (Repository): Elapsed time after each iteration is now output. It
908: helps to forecast when convergence will be reached. Elapsed time
909: is stamped in powell. We created a new html file for the graphs
910: concerning matrix of covariance. It has extension -cov.htm.
911:
912: Revision 1.90 2003/06/24 12:34:15 brouard
913: (Module): Some bugs corrected for windows. Also, when
914: mle=-1 a template is output in file "or"mypar.txt with the design
915: of the covariance matrix to be input.
916:
917: Revision 1.89 2003/06/24 12:30:52 brouard
918: (Module): Some bugs corrected for windows. Also, when
919: mle=-1 a template is output in file "or"mypar.txt with the design
920: of the covariance matrix to be input.
921:
922: Revision 1.88 2003/06/23 17:54:56 brouard
923: * 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.
924:
925: Revision 1.87 2003/06/18 12:26:01 brouard
926: Version 0.96
927:
928: Revision 1.86 2003/06/17 20:04:08 brouard
929: (Module): Change position of html and gnuplot routines and added
930: routine fileappend.
931:
932: Revision 1.85 2003/06/17 13:12:43 brouard
933: * imach.c (Repository): Check when date of death was earlier that
934: current date of interview. It may happen when the death was just
935: prior to the death. In this case, dh was negative and likelihood
936: was wrong (infinity). We still send an "Error" but patch by
937: assuming that the date of death was just one stepm after the
938: interview.
939: (Repository): Because some people have very long ID (first column)
940: we changed int to long in num[] and we added a new lvector for
941: memory allocation. But we also truncated to 8 characters (left
942: truncation)
943: (Repository): No more line truncation errors.
944:
945: Revision 1.84 2003/06/13 21:44:43 brouard
946: * imach.c (Repository): Replace "freqsummary" at a correct
947: place. It differs from routine "prevalence" which may be called
948: many times. Probs is memory consuming and must be used with
949: parcimony.
950: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
951:
952: Revision 1.83 2003/06/10 13:39:11 lievre
953: *** empty log message ***
954:
955: Revision 1.82 2003/06/05 15:57:20 brouard
956: Add log in imach.c and fullversion number is now printed.
957:
958: */
959: /*
960: Interpolated Markov Chain
961:
962: Short summary of the programme:
963:
1.227 brouard 964: This program computes Healthy Life Expectancies or State-specific
965: (if states aren't health statuses) Expectancies from
966: cross-longitudinal data. Cross-longitudinal data consist in:
967:
968: -1- a first survey ("cross") where individuals from different ages
969: are interviewed on their health status or degree of disability (in
970: the case of a health survey which is our main interest)
971:
972: -2- at least a second wave of interviews ("longitudinal") which
973: measure each change (if any) in individual health status. Health
974: expectancies are computed from the time spent in each health state
975: according to a model. More health states you consider, more time is
976: necessary to reach the Maximum Likelihood of the parameters involved
977: in the model. The simplest model is the multinomial logistic model
978: where pij is the probability to be observed in state j at the second
979: wave conditional to be observed in state i at the first
980: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
981: etc , where 'age' is age and 'sex' is a covariate. If you want to
982: have a more complex model than "constant and age", you should modify
983: the program where the markup *Covariates have to be included here
984: again* invites you to do it. More covariates you add, slower the
1.126 brouard 985: convergence.
986:
987: The advantage of this computer programme, compared to a simple
988: multinomial logistic model, is clear when the delay between waves is not
989: identical for each individual. Also, if a individual missed an
990: intermediate interview, the information is lost, but taken into
991: account using an interpolation or extrapolation.
992:
993: hPijx is the probability to be observed in state i at age x+h
994: conditional to the observed state i at age x. The delay 'h' can be
995: split into an exact number (nh*stepm) of unobserved intermediate
996: states. This elementary transition (by month, quarter,
997: semester or year) is modelled as a multinomial logistic. The hPx
998: matrix is simply the matrix product of nh*stepm elementary matrices
999: and the contribution of each individual to the likelihood is simply
1000: hPijx.
1001:
1002: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1003: of the life expectancies. It also computes the period (stable) prevalence.
1004:
1005: Back prevalence and projections:
1.227 brouard 1006:
1007: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1008: double agemaxpar, double ftolpl, int *ncvyearp, double
1009: dateprev1,double dateprev2, int firstpass, int lastpass, int
1010: mobilavproj)
1011:
1012: Computes the back prevalence limit for any combination of
1013: covariate values k at any age between ageminpar and agemaxpar and
1014: returns it in **bprlim. In the loops,
1015:
1016: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1017: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1018:
1019: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1020: Computes for any combination of covariates k and any age between bage and fage
1021: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1022: oldm=oldms;savm=savms;
1.227 brouard 1023:
1.267 brouard 1024: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1025: Computes the transition matrix starting at age 'age' over
1026: 'nhstepm*hstepm*stepm' months (i.e. until
1027: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1028: nhstepm*hstepm matrices.
1029:
1030: Returns p3mat[i][j][h] after calling
1031: p3mat[i][j][h]=matprod2(newm,
1032: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1033: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1034: oldm);
1.226 brouard 1035:
1036: Important routines
1037:
1038: - func (or funcone), computes logit (pij) distinguishing
1039: o fixed variables (single or product dummies or quantitative);
1040: o varying variables by:
1041: (1) wave (single, product dummies, quantitative),
1042: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1043: % fixed dummy (treated) or quantitative (not done because time-consuming);
1044: % varying dummy (not done) or quantitative (not done);
1045: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1046: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1047: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1048: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1049: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1050:
1.226 brouard 1051:
1052:
1.133 brouard 1053: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1054: Institut national d'études démographiques, Paris.
1.126 brouard 1055: This software have been partly granted by Euro-REVES, a concerted action
1056: from the European Union.
1057: It is copyrighted identically to a GNU software product, ie programme and
1058: software can be distributed freely for non commercial use. Latest version
1059: can be accessed at http://euroreves.ined.fr/imach .
1060:
1061: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1062: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1063:
1064: **********************************************************************/
1065: /*
1066: main
1067: read parameterfile
1068: read datafile
1069: concatwav
1070: freqsummary
1071: if (mle >= 1)
1072: mlikeli
1073: print results files
1074: if mle==1
1075: computes hessian
1076: read end of parameter file: agemin, agemax, bage, fage, estepm
1077: begin-prev-date,...
1078: open gnuplot file
1079: open html file
1.145 brouard 1080: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1081: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1082: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1083: freexexit2 possible for memory heap.
1084:
1085: h Pij x | pij_nom ficrestpij
1086: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1087: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1088: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1089:
1090: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1091: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1092: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1093: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1094: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1095:
1.126 brouard 1096: forecasting if prevfcast==1 prevforecast call prevalence()
1097: health expectancies
1098: Variance-covariance of DFLE
1099: prevalence()
1100: movingaverage()
1101: varevsij()
1102: if popbased==1 varevsij(,popbased)
1103: total life expectancies
1104: Variance of period (stable) prevalence
1105: end
1106: */
1107:
1.187 brouard 1108: /* #define DEBUG */
1109: /* #define DEBUGBRENT */
1.203 brouard 1110: /* #define DEBUGLINMIN */
1111: /* #define DEBUGHESS */
1112: #define DEBUGHESSIJ
1.224 brouard 1113: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1114: #define POWELL /* Instead of NLOPT */
1.224 brouard 1115: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1116: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1117: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1118: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1119:
1120: #include <math.h>
1121: #include <stdio.h>
1122: #include <stdlib.h>
1123: #include <string.h>
1.226 brouard 1124: #include <ctype.h>
1.159 brouard 1125:
1126: #ifdef _WIN32
1127: #include <io.h>
1.172 brouard 1128: #include <windows.h>
1129: #include <tchar.h>
1.159 brouard 1130: #else
1.126 brouard 1131: #include <unistd.h>
1.159 brouard 1132: #endif
1.126 brouard 1133:
1134: #include <limits.h>
1135: #include <sys/types.h>
1.171 brouard 1136:
1137: #if defined(__GNUC__)
1138: #include <sys/utsname.h> /* Doesn't work on Windows */
1139: #endif
1140:
1.126 brouard 1141: #include <sys/stat.h>
1142: #include <errno.h>
1.159 brouard 1143: /* extern int errno; */
1.126 brouard 1144:
1.157 brouard 1145: /* #ifdef LINUX */
1146: /* #include <time.h> */
1147: /* #include "timeval.h" */
1148: /* #else */
1149: /* #include <sys/time.h> */
1150: /* #endif */
1151:
1.126 brouard 1152: #include <time.h>
1153:
1.136 brouard 1154: #ifdef GSL
1155: #include <gsl/gsl_errno.h>
1156: #include <gsl/gsl_multimin.h>
1157: #endif
1158:
1.167 brouard 1159:
1.162 brouard 1160: #ifdef NLOPT
1161: #include <nlopt.h>
1162: typedef struct {
1163: double (* function)(double [] );
1164: } myfunc_data ;
1165: #endif
1166:
1.126 brouard 1167: /* #include <libintl.h> */
1168: /* #define _(String) gettext (String) */
1169:
1.251 brouard 1170: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1171:
1172: #define GNUPLOTPROGRAM "gnuplot"
1173: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1174: #define FILENAMELENGTH 132
1175:
1176: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1177: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1178:
1.144 brouard 1179: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1180: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1181:
1182: #define NINTERVMAX 8
1.144 brouard 1183: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1184: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.318 brouard 1185: #define NCOVMAX 30 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1186: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1187: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1188: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1189: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1190: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1191: /* #define AGESUP 130 */
1.288 brouard 1192: /* #define AGESUP 150 */
1193: #define AGESUP 200
1.268 brouard 1194: #define AGEINF 0
1.218 brouard 1195: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1196: #define AGEBASE 40
1.194 brouard 1197: #define AGEOVERFLOW 1.e20
1.164 brouard 1198: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1199: #ifdef _WIN32
1200: #define DIRSEPARATOR '\\'
1201: #define CHARSEPARATOR "\\"
1202: #define ODIRSEPARATOR '/'
1203: #else
1.126 brouard 1204: #define DIRSEPARATOR '/'
1205: #define CHARSEPARATOR "/"
1206: #define ODIRSEPARATOR '\\'
1207: #endif
1208:
1.323 ! brouard 1209: /* $Id: imach.c,v 1.322 2022/07/22 12:27:48 brouard Exp $ */
1.126 brouard 1210: /* $State: Exp $ */
1.196 brouard 1211: #include "version.h"
1212: char version[]=__IMACH_VERSION__;
1.323 ! brouard 1213: char copyright[]="July 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";
! 1214: char fullversion[]="$Revision: 1.322 $ $Date: 2022/07/22 12:27:48 $";
1.126 brouard 1215: char strstart[80];
1216: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1217: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1218: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1219: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1220: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1221: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1222: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1223: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1224: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1225: int cptcovprodnoage=0; /**< Number of covariate products without age */
1226: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1227: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1228: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1229: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1230: int nsd=0; /**< Total number of single dummy variables (output) */
1231: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1232: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1233: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1234: int ntveff=0; /**< ntveff number of effective time varying variables */
1235: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1236: int cptcov=0; /* Working variable */
1.290 brouard 1237: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1238: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1239: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1240: int nlstate=2; /* Number of live states */
1241: int ndeath=1; /* Number of dead states */
1.130 brouard 1242: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1243: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1244: int popbased=0;
1245:
1246: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1247: int maxwav=0; /* Maxim number of waves */
1248: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1249: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1250: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1251: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1252: int mle=1, weightopt=0;
1.126 brouard 1253: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1254: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1255: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1256: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1257: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1258: int selected(int kvar); /* Is covariate kvar selected for printing results */
1259:
1.130 brouard 1260: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1261: double **matprod2(); /* test */
1.126 brouard 1262: double **oldm, **newm, **savm; /* Working pointers to matrices */
1263: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1264: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1265:
1.136 brouard 1266: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1267: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1268: FILE *ficlog, *ficrespow;
1.130 brouard 1269: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1270: double fretone; /* Only one call to likelihood */
1.130 brouard 1271: long ipmx=0; /* Number of contributions */
1.126 brouard 1272: double sw; /* Sum of weights */
1273: char filerespow[FILENAMELENGTH];
1274: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1275: FILE *ficresilk;
1276: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1277: FILE *ficresprobmorprev;
1278: FILE *fichtm, *fichtmcov; /* Html File */
1279: FILE *ficreseij;
1280: char filerese[FILENAMELENGTH];
1281: FILE *ficresstdeij;
1282: char fileresstde[FILENAMELENGTH];
1283: FILE *ficrescveij;
1284: char filerescve[FILENAMELENGTH];
1285: FILE *ficresvij;
1286: char fileresv[FILENAMELENGTH];
1.269 brouard 1287:
1.126 brouard 1288: char title[MAXLINE];
1.234 brouard 1289: char model[MAXLINE]; /**< The model line */
1.217 brouard 1290: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1291: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1292: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1293: char command[FILENAMELENGTH];
1294: int outcmd=0;
1295:
1.217 brouard 1296: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1297: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1298: char filelog[FILENAMELENGTH]; /* Log file */
1299: char filerest[FILENAMELENGTH];
1300: char fileregp[FILENAMELENGTH];
1301: char popfile[FILENAMELENGTH];
1302:
1303: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1304:
1.157 brouard 1305: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1306: /* struct timezone tzp; */
1307: /* extern int gettimeofday(); */
1308: struct tm tml, *gmtime(), *localtime();
1309:
1310: extern time_t time();
1311:
1312: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1313: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1314: struct tm tm;
1315:
1.126 brouard 1316: char strcurr[80], strfor[80];
1317:
1318: char *endptr;
1319: long lval;
1320: double dval;
1321:
1322: #define NR_END 1
1323: #define FREE_ARG char*
1324: #define FTOL 1.0e-10
1325:
1326: #define NRANSI
1.240 brouard 1327: #define ITMAX 200
1328: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1329:
1330: #define TOL 2.0e-4
1331:
1332: #define CGOLD 0.3819660
1333: #define ZEPS 1.0e-10
1334: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1335:
1336: #define GOLD 1.618034
1337: #define GLIMIT 100.0
1338: #define TINY 1.0e-20
1339:
1340: static double maxarg1,maxarg2;
1341: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1342: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1343:
1344: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1345: #define rint(a) floor(a+0.5)
1.166 brouard 1346: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1347: #define mytinydouble 1.0e-16
1.166 brouard 1348: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1349: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1350: /* static double dsqrarg; */
1351: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1352: static double sqrarg;
1353: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1354: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1355: int agegomp= AGEGOMP;
1356:
1357: int imx;
1358: int stepm=1;
1359: /* Stepm, step in month: minimum step interpolation*/
1360:
1361: int estepm;
1362: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1363:
1364: int m,nb;
1365: long *num;
1.197 brouard 1366: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1367: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1368: covariate for which somebody answered excluding
1369: undefined. Usually 2: 0 and 1. */
1370: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1371: covariate for which somebody answered including
1372: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1373: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1374: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1375: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1376: double *ageexmed,*agecens;
1377: double dateintmean=0;
1.296 brouard 1378: double anprojd, mprojd, jprojd; /* For eventual projections */
1379: double anprojf, mprojf, jprojf;
1.126 brouard 1380:
1.296 brouard 1381: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1382: double anbackf, mbackf, jbackf;
1383: double jintmean,mintmean,aintmean;
1.126 brouard 1384: double *weight;
1385: int **s; /* Status */
1.141 brouard 1386: double *agedc;
1.145 brouard 1387: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1388: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1389: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1390: double **coqvar; /* Fixed quantitative covariate nqv */
1391: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1392: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1393: double idx;
1394: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1395: /* Some documentation */
1396: /* Design original data
1397: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1398: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1399: * ntv=3 nqtv=1
1400: * cptcovn number of covariates (not including constant and age) = # of + plus 1 = 10+1=11
1401: * For time varying covariate, quanti or dummies
1402: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1403: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1404: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1405: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1406: * covar[k,i], value of kth fixed covariate dummy or quanti :
1407: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1408: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1409: * k= 1 2 3 4 5 6 7 8 9 10 11
1410: */
1411: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1412: /* 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
1413: # States 1=Coresidence, 2 Living alone, 3 Institution
1414: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1415: */
1.319 brouard 1416: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1417: /* k 1 2 3 4 5 6 7 8 9 */
1418: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1419: /* fixed or varying), 1 for age product, 2 for*/
1420: /* product */
1421: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1422: /*(single or product without age), 2 dummy*/
1423: /* with age product, 3 quant with age product*/
1424: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1425: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1426: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1427: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1428: /* nsq 1 2 */ /* Counting single quantit tv */
1429: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1430: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1431: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1432: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1433: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1434: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1435: /* 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 1436: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1437: /* Type */
1438: /* V 1 2 3 4 5 */
1439: /* F F V V V */
1440: /* D Q D D Q */
1441: /* */
1442: int *TvarsD;
1443: int *TvarsDind;
1444: int *TvarsQ;
1445: int *TvarsQind;
1446:
1.318 brouard 1447: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1448: int nresult=0;
1.258 brouard 1449: int parameterline=0; /* # of the parameter (type) line */
1.318 brouard 1450: int TKresult[MAXRESULTLINESPONE];
1451: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1452: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1453: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */
1454: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1455: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1456: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , variable # (output) */
1457:
1458: /* 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
1459: # States 1=Coresidence, 2 Living alone, 3 Institution
1460: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1461: */
1.234 brouard 1462: /* 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 1463: 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 */
1464: 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 */
1465: 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 */
1466: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1467: 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 */
1468: 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 1469: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1470: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1471: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1472: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1473: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1474: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1475: 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 */
1476: 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 */
1477:
1.230 brouard 1478: int *Tvarsel; /**< Selected covariates for output */
1479: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1480: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1481: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1482: 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 1483: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1484: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1485: int *Tage;
1.227 brouard 1486: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1487: 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 1488: 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*/
1489: 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 1490: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1491: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1492: int **Tvard;
1493: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1494: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1495: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1496: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1497: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1498: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1499: double *lsurv, *lpop, *tpop;
1500:
1.231 brouard 1501: #define FD 1; /* Fixed dummy covariate */
1502: #define FQ 2; /* Fixed quantitative covariate */
1503: #define FP 3; /* Fixed product covariate */
1504: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1505: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1506: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1507: #define VD 10; /* Varying dummy covariate */
1508: #define VQ 11; /* Varying quantitative covariate */
1509: #define VP 12; /* Varying product covariate */
1510: #define VPDD 13; /* Varying product dummy*dummy covariate */
1511: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1512: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1513: #define APFD 16; /* Age product * fixed dummy covariate */
1514: #define APFQ 17; /* Age product * fixed quantitative covariate */
1515: #define APVD 18; /* Age product * varying dummy covariate */
1516: #define APVQ 19; /* Age product * varying quantitative covariate */
1517:
1518: #define FTYPE 1; /* Fixed covariate */
1519: #define VTYPE 2; /* Varying covariate (loop in wave) */
1520: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1521:
1522: struct kmodel{
1523: int maintype; /* main type */
1524: int subtype; /* subtype */
1525: };
1526: struct kmodel modell[NCOVMAX];
1527:
1.143 brouard 1528: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1529: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1530:
1531: /**************** split *************************/
1532: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1533: {
1534: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1535: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1536: */
1537: char *ss; /* pointer */
1.186 brouard 1538: int l1=0, l2=0; /* length counters */
1.126 brouard 1539:
1540: l1 = strlen(path ); /* length of path */
1541: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1542: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1543: if ( ss == NULL ) { /* no directory, so determine current directory */
1544: strcpy( name, path ); /* we got the fullname name because no directory */
1545: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1546: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1547: /* get current working directory */
1548: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1549: #ifdef WIN32
1550: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1551: #else
1552: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1553: #endif
1.126 brouard 1554: return( GLOCK_ERROR_GETCWD );
1555: }
1556: /* got dirc from getcwd*/
1557: printf(" DIRC = %s \n",dirc);
1.205 brouard 1558: } else { /* strip directory from path */
1.126 brouard 1559: ss++; /* after this, the filename */
1560: l2 = strlen( ss ); /* length of filename */
1561: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1562: strcpy( name, ss ); /* save file name */
1563: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1564: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1565: printf(" DIRC2 = %s \n",dirc);
1566: }
1567: /* We add a separator at the end of dirc if not exists */
1568: l1 = strlen( dirc ); /* length of directory */
1569: if( dirc[l1-1] != DIRSEPARATOR ){
1570: dirc[l1] = DIRSEPARATOR;
1571: dirc[l1+1] = 0;
1572: printf(" DIRC3 = %s \n",dirc);
1573: }
1574: ss = strrchr( name, '.' ); /* find last / */
1575: if (ss >0){
1576: ss++;
1577: strcpy(ext,ss); /* save extension */
1578: l1= strlen( name);
1579: l2= strlen(ss)+1;
1580: strncpy( finame, name, l1-l2);
1581: finame[l1-l2]= 0;
1582: }
1583:
1584: return( 0 ); /* we're done */
1585: }
1586:
1587:
1588: /******************************************/
1589:
1590: void replace_back_to_slash(char *s, char*t)
1591: {
1592: int i;
1593: int lg=0;
1594: i=0;
1595: lg=strlen(t);
1596: for(i=0; i<= lg; i++) {
1597: (s[i] = t[i]);
1598: if (t[i]== '\\') s[i]='/';
1599: }
1600: }
1601:
1.132 brouard 1602: char *trimbb(char *out, char *in)
1.137 brouard 1603: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1604: char *s;
1605: s=out;
1606: while (*in != '\0'){
1.137 brouard 1607: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1608: in++;
1609: }
1610: *out++ = *in++;
1611: }
1612: *out='\0';
1613: return s;
1614: }
1615:
1.187 brouard 1616: /* char *substrchaine(char *out, char *in, char *chain) */
1617: /* { */
1618: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1619: /* char *s, *t; */
1620: /* t=in;s=out; */
1621: /* while ((*in != *chain) && (*in != '\0')){ */
1622: /* *out++ = *in++; */
1623: /* } */
1624:
1625: /* /\* *in matches *chain *\/ */
1626: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1627: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1628: /* } */
1629: /* in--; chain--; */
1630: /* while ( (*in != '\0')){ */
1631: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1632: /* *out++ = *in++; */
1633: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1634: /* } */
1635: /* *out='\0'; */
1636: /* out=s; */
1637: /* return out; */
1638: /* } */
1639: char *substrchaine(char *out, char *in, char *chain)
1640: {
1641: /* Substract chain 'chain' from 'in', return and output 'out' */
1642: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1643:
1644: char *strloc;
1645:
1646: strcpy (out, in);
1647: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1648: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1649: if(strloc != NULL){
1650: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1651: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1652: /* strcpy (strloc, strloc +strlen(chain));*/
1653: }
1654: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1655: return out;
1656: }
1657:
1658:
1.145 brouard 1659: char *cutl(char *blocc, char *alocc, char *in, char occ)
1660: {
1.187 brouard 1661: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1662: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1663: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1664: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1665: */
1.160 brouard 1666: char *s, *t;
1.145 brouard 1667: t=in;s=in;
1668: while ((*in != occ) && (*in != '\0')){
1669: *alocc++ = *in++;
1670: }
1671: if( *in == occ){
1672: *(alocc)='\0';
1673: s=++in;
1674: }
1675:
1676: if (s == t) {/* occ not found */
1677: *(alocc-(in-s))='\0';
1678: in=s;
1679: }
1680: while ( *in != '\0'){
1681: *blocc++ = *in++;
1682: }
1683:
1684: *blocc='\0';
1685: return t;
1686: }
1.137 brouard 1687: char *cutv(char *blocc, char *alocc, char *in, char occ)
1688: {
1.187 brouard 1689: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1690: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1691: gives blocc="abcdef2ghi" and alocc="j".
1692: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1693: */
1694: char *s, *t;
1695: t=in;s=in;
1696: while (*in != '\0'){
1697: while( *in == occ){
1698: *blocc++ = *in++;
1699: s=in;
1700: }
1701: *blocc++ = *in++;
1702: }
1703: if (s == t) /* occ not found */
1704: *(blocc-(in-s))='\0';
1705: else
1706: *(blocc-(in-s)-1)='\0';
1707: in=s;
1708: while ( *in != '\0'){
1709: *alocc++ = *in++;
1710: }
1711:
1712: *alocc='\0';
1713: return s;
1714: }
1715:
1.126 brouard 1716: int nbocc(char *s, char occ)
1717: {
1718: int i,j=0;
1719: int lg=20;
1720: i=0;
1721: lg=strlen(s);
1722: for(i=0; i<= lg; i++) {
1.234 brouard 1723: if (s[i] == occ ) j++;
1.126 brouard 1724: }
1725: return j;
1726: }
1727:
1.137 brouard 1728: /* void cutv(char *u,char *v, char*t, char occ) */
1729: /* { */
1730: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1731: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1732: /* gives u="abcdef2ghi" and v="j" *\/ */
1733: /* int i,lg,j,p=0; */
1734: /* i=0; */
1735: /* lg=strlen(t); */
1736: /* for(j=0; j<=lg-1; j++) { */
1737: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1738: /* } */
1.126 brouard 1739:
1.137 brouard 1740: /* for(j=0; j<p; j++) { */
1741: /* (u[j] = t[j]); */
1742: /* } */
1743: /* u[p]='\0'; */
1.126 brouard 1744:
1.137 brouard 1745: /* for(j=0; j<= lg; j++) { */
1746: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1747: /* } */
1748: /* } */
1.126 brouard 1749:
1.160 brouard 1750: #ifdef _WIN32
1751: char * strsep(char **pp, const char *delim)
1752: {
1753: char *p, *q;
1754:
1755: if ((p = *pp) == NULL)
1756: return 0;
1757: if ((q = strpbrk (p, delim)) != NULL)
1758: {
1759: *pp = q + 1;
1760: *q = '\0';
1761: }
1762: else
1763: *pp = 0;
1764: return p;
1765: }
1766: #endif
1767:
1.126 brouard 1768: /********************** nrerror ********************/
1769:
1770: void nrerror(char error_text[])
1771: {
1772: fprintf(stderr,"ERREUR ...\n");
1773: fprintf(stderr,"%s\n",error_text);
1774: exit(EXIT_FAILURE);
1775: }
1776: /*********************** vector *******************/
1777: double *vector(int nl, int nh)
1778: {
1779: double *v;
1780: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1781: if (!v) nrerror("allocation failure in vector");
1782: return v-nl+NR_END;
1783: }
1784:
1785: /************************ free vector ******************/
1786: void free_vector(double*v, int nl, int nh)
1787: {
1788: free((FREE_ARG)(v+nl-NR_END));
1789: }
1790:
1791: /************************ivector *******************************/
1792: int *ivector(long nl,long nh)
1793: {
1794: int *v;
1795: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1796: if (!v) nrerror("allocation failure in ivector");
1797: return v-nl+NR_END;
1798: }
1799:
1800: /******************free ivector **************************/
1801: void free_ivector(int *v, long nl, long nh)
1802: {
1803: free((FREE_ARG)(v+nl-NR_END));
1804: }
1805:
1806: /************************lvector *******************************/
1807: long *lvector(long nl,long nh)
1808: {
1809: long *v;
1810: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1811: if (!v) nrerror("allocation failure in ivector");
1812: return v-nl+NR_END;
1813: }
1814:
1815: /******************free lvector **************************/
1816: void free_lvector(long *v, long nl, long nh)
1817: {
1818: free((FREE_ARG)(v+nl-NR_END));
1819: }
1820:
1821: /******************* imatrix *******************************/
1822: int **imatrix(long nrl, long nrh, long ncl, long nch)
1823: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1824: {
1825: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1826: int **m;
1827:
1828: /* allocate pointers to rows */
1829: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1830: if (!m) nrerror("allocation failure 1 in matrix()");
1831: m += NR_END;
1832: m -= nrl;
1833:
1834:
1835: /* allocate rows and set pointers to them */
1836: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1837: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1838: m[nrl] += NR_END;
1839: m[nrl] -= ncl;
1840:
1841: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1842:
1843: /* return pointer to array of pointers to rows */
1844: return m;
1845: }
1846:
1847: /****************** free_imatrix *************************/
1848: void free_imatrix(m,nrl,nrh,ncl,nch)
1849: int **m;
1850: long nch,ncl,nrh,nrl;
1851: /* free an int matrix allocated by imatrix() */
1852: {
1853: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1854: free((FREE_ARG) (m+nrl-NR_END));
1855: }
1856:
1857: /******************* matrix *******************************/
1858: double **matrix(long nrl, long nrh, long ncl, long nch)
1859: {
1860: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1861: double **m;
1862:
1863: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1864: if (!m) nrerror("allocation failure 1 in matrix()");
1865: m += NR_END;
1866: m -= nrl;
1867:
1868: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1869: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1870: m[nrl] += NR_END;
1871: m[nrl] -= ncl;
1872:
1873: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1874: return m;
1.145 brouard 1875: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1876: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1877: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1878: */
1879: }
1880:
1881: /*************************free matrix ************************/
1882: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1883: {
1884: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1885: free((FREE_ARG)(m+nrl-NR_END));
1886: }
1887:
1888: /******************* ma3x *******************************/
1889: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1890: {
1891: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1892: double ***m;
1893:
1894: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1895: if (!m) nrerror("allocation failure 1 in matrix()");
1896: m += NR_END;
1897: m -= nrl;
1898:
1899: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1900: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1901: m[nrl] += NR_END;
1902: m[nrl] -= ncl;
1903:
1904: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1905:
1906: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1907: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1908: m[nrl][ncl] += NR_END;
1909: m[nrl][ncl] -= nll;
1910: for (j=ncl+1; j<=nch; j++)
1911: m[nrl][j]=m[nrl][j-1]+nlay;
1912:
1913: for (i=nrl+1; i<=nrh; i++) {
1914: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1915: for (j=ncl+1; j<=nch; j++)
1916: m[i][j]=m[i][j-1]+nlay;
1917: }
1918: return m;
1919: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1920: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1921: */
1922: }
1923:
1924: /*************************free ma3x ************************/
1925: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1926: {
1927: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1928: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1929: free((FREE_ARG)(m+nrl-NR_END));
1930: }
1931:
1932: /*************** function subdirf ***********/
1933: char *subdirf(char fileres[])
1934: {
1935: /* Caution optionfilefiname is hidden */
1936: strcpy(tmpout,optionfilefiname);
1937: strcat(tmpout,"/"); /* Add to the right */
1938: strcat(tmpout,fileres);
1939: return tmpout;
1940: }
1941:
1942: /*************** function subdirf2 ***********/
1943: char *subdirf2(char fileres[], char *preop)
1944: {
1.314 brouard 1945: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
1946: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 1947: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 1948: /* Caution optionfilefiname is hidden */
1949: strcpy(tmpout,optionfilefiname);
1950: strcat(tmpout,"/");
1951: strcat(tmpout,preop);
1952: strcat(tmpout,fileres);
1953: return tmpout;
1954: }
1955:
1956: /*************** function subdirf3 ***********/
1957: char *subdirf3(char fileres[], char *preop, char *preop2)
1958: {
1959:
1960: /* Caution optionfilefiname is hidden */
1961: strcpy(tmpout,optionfilefiname);
1962: strcat(tmpout,"/");
1963: strcat(tmpout,preop);
1964: strcat(tmpout,preop2);
1965: strcat(tmpout,fileres);
1966: return tmpout;
1967: }
1.213 brouard 1968:
1969: /*************** function subdirfext ***********/
1970: char *subdirfext(char fileres[], char *preop, char *postop)
1971: {
1972:
1973: strcpy(tmpout,preop);
1974: strcat(tmpout,fileres);
1975: strcat(tmpout,postop);
1976: return tmpout;
1977: }
1.126 brouard 1978:
1.213 brouard 1979: /*************** function subdirfext3 ***********/
1980: char *subdirfext3(char fileres[], char *preop, char *postop)
1981: {
1982:
1983: /* Caution optionfilefiname is hidden */
1984: strcpy(tmpout,optionfilefiname);
1985: strcat(tmpout,"/");
1986: strcat(tmpout,preop);
1987: strcat(tmpout,fileres);
1988: strcat(tmpout,postop);
1989: return tmpout;
1990: }
1991:
1.162 brouard 1992: char *asc_diff_time(long time_sec, char ascdiff[])
1993: {
1994: long sec_left, days, hours, minutes;
1995: days = (time_sec) / (60*60*24);
1996: sec_left = (time_sec) % (60*60*24);
1997: hours = (sec_left) / (60*60) ;
1998: sec_left = (sec_left) %(60*60);
1999: minutes = (sec_left) /60;
2000: sec_left = (sec_left) % (60);
2001: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2002: return ascdiff;
2003: }
2004:
1.126 brouard 2005: /***************** f1dim *************************/
2006: extern int ncom;
2007: extern double *pcom,*xicom;
2008: extern double (*nrfunc)(double []);
2009:
2010: double f1dim(double x)
2011: {
2012: int j;
2013: double f;
2014: double *xt;
2015:
2016: xt=vector(1,ncom);
2017: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2018: f=(*nrfunc)(xt);
2019: free_vector(xt,1,ncom);
2020: return f;
2021: }
2022:
2023: /*****************brent *************************/
2024: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2025: {
2026: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2027: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2028: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2029: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2030: * returned function value.
2031: */
1.126 brouard 2032: int iter;
2033: double a,b,d,etemp;
1.159 brouard 2034: double fu=0,fv,fw,fx;
1.164 brouard 2035: double ftemp=0.;
1.126 brouard 2036: double p,q,r,tol1,tol2,u,v,w,x,xm;
2037: double e=0.0;
2038:
2039: a=(ax < cx ? ax : cx);
2040: b=(ax > cx ? ax : cx);
2041: x=w=v=bx;
2042: fw=fv=fx=(*f)(x);
2043: for (iter=1;iter<=ITMAX;iter++) {
2044: xm=0.5*(a+b);
2045: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2046: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2047: printf(".");fflush(stdout);
2048: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2049: #ifdef DEBUGBRENT
1.126 brouard 2050: 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);
2051: 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);
2052: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2053: #endif
2054: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2055: *xmin=x;
2056: return fx;
2057: }
2058: ftemp=fu;
2059: if (fabs(e) > tol1) {
2060: r=(x-w)*(fx-fv);
2061: q=(x-v)*(fx-fw);
2062: p=(x-v)*q-(x-w)*r;
2063: q=2.0*(q-r);
2064: if (q > 0.0) p = -p;
2065: q=fabs(q);
2066: etemp=e;
2067: e=d;
2068: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2069: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2070: else {
1.224 brouard 2071: d=p/q;
2072: u=x+d;
2073: if (u-a < tol2 || b-u < tol2)
2074: d=SIGN(tol1,xm-x);
1.126 brouard 2075: }
2076: } else {
2077: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2078: }
2079: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2080: fu=(*f)(u);
2081: if (fu <= fx) {
2082: if (u >= x) a=x; else b=x;
2083: SHFT(v,w,x,u)
1.183 brouard 2084: SHFT(fv,fw,fx,fu)
2085: } else {
2086: if (u < x) a=u; else b=u;
2087: if (fu <= fw || w == x) {
1.224 brouard 2088: v=w;
2089: w=u;
2090: fv=fw;
2091: fw=fu;
1.183 brouard 2092: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2093: v=u;
2094: fv=fu;
1.183 brouard 2095: }
2096: }
1.126 brouard 2097: }
2098: nrerror("Too many iterations in brent");
2099: *xmin=x;
2100: return fx;
2101: }
2102:
2103: /****************** mnbrak ***********************/
2104:
2105: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2106: double (*func)(double))
1.183 brouard 2107: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2108: the downhill direction (defined by the function as evaluated at the initial points) and returns
2109: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2110: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2111: */
1.126 brouard 2112: double ulim,u,r,q, dum;
2113: double fu;
1.187 brouard 2114:
2115: double scale=10.;
2116: int iterscale=0;
2117:
2118: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2119: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2120:
2121:
2122: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2123: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2124: /* *bx = *ax - (*ax - *bx)/scale; */
2125: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2126: /* } */
2127:
1.126 brouard 2128: if (*fb > *fa) {
2129: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2130: SHFT(dum,*fb,*fa,dum)
2131: }
1.126 brouard 2132: *cx=(*bx)+GOLD*(*bx-*ax);
2133: *fc=(*func)(*cx);
1.183 brouard 2134: #ifdef DEBUG
1.224 brouard 2135: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2136: 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 2137: #endif
1.224 brouard 2138: 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 2139: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2140: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2141: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2142: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2143: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2144: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2145: fu=(*func)(u);
1.163 brouard 2146: #ifdef DEBUG
2147: /* f(x)=A(x-u)**2+f(u) */
2148: double A, fparabu;
2149: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2150: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2151: 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);
2152: 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 2153: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2154: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2155: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2156: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2157: #endif
1.184 brouard 2158: #ifdef MNBRAKORIGINAL
1.183 brouard 2159: #else
1.191 brouard 2160: /* if (fu > *fc) { */
2161: /* #ifdef DEBUG */
2162: /* printf("mnbrak4 fu > fc \n"); */
2163: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2164: /* #endif */
2165: /* /\* 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 *\\/ *\/ */
2166: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2167: /* dum=u; /\* Shifting c and u *\/ */
2168: /* u = *cx; */
2169: /* *cx = dum; */
2170: /* dum = fu; */
2171: /* fu = *fc; */
2172: /* *fc =dum; */
2173: /* } else { /\* end *\/ */
2174: /* #ifdef DEBUG */
2175: /* printf("mnbrak3 fu < fc \n"); */
2176: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2177: /* #endif */
2178: /* dum=u; /\* Shifting c and u *\/ */
2179: /* u = *cx; */
2180: /* *cx = dum; */
2181: /* dum = fu; */
2182: /* fu = *fc; */
2183: /* *fc =dum; */
2184: /* } */
1.224 brouard 2185: #ifdef DEBUGMNBRAK
2186: double A, fparabu;
2187: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2188: fparabu= *fa - A*(*ax-u)*(*ax-u);
2189: 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);
2190: 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 2191: #endif
1.191 brouard 2192: dum=u; /* Shifting c and u */
2193: u = *cx;
2194: *cx = dum;
2195: dum = fu;
2196: fu = *fc;
2197: *fc =dum;
1.183 brouard 2198: #endif
1.162 brouard 2199: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2200: #ifdef DEBUG
1.224 brouard 2201: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2202: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2203: #endif
1.126 brouard 2204: fu=(*func)(u);
2205: if (fu < *fc) {
1.183 brouard 2206: #ifdef DEBUG
1.224 brouard 2207: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2208: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2209: #endif
2210: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2211: SHFT(*fb,*fc,fu,(*func)(u))
2212: #ifdef DEBUG
2213: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2214: #endif
2215: }
1.162 brouard 2216: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2217: #ifdef DEBUG
1.224 brouard 2218: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2219: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2220: #endif
1.126 brouard 2221: u=ulim;
2222: fu=(*func)(u);
1.183 brouard 2223: } else { /* u could be left to b (if r > q parabola has a maximum) */
2224: #ifdef DEBUG
1.224 brouard 2225: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2226: 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 2227: #endif
1.126 brouard 2228: u=(*cx)+GOLD*(*cx-*bx);
2229: fu=(*func)(u);
1.224 brouard 2230: #ifdef DEBUG
2231: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2232: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2233: #endif
1.183 brouard 2234: } /* end tests */
1.126 brouard 2235: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2236: SHFT(*fa,*fb,*fc,fu)
2237: #ifdef DEBUG
1.224 brouard 2238: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2239: 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 2240: #endif
2241: } /* 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 2242: }
2243:
2244: /*************** linmin ************************/
1.162 brouard 2245: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2246: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2247: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2248: the value of func at the returned location p . This is actually all accomplished by calling the
2249: routines mnbrak and brent .*/
1.126 brouard 2250: int ncom;
2251: double *pcom,*xicom;
2252: double (*nrfunc)(double []);
2253:
1.224 brouard 2254: #ifdef LINMINORIGINAL
1.126 brouard 2255: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2256: #else
2257: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2258: #endif
1.126 brouard 2259: {
2260: double brent(double ax, double bx, double cx,
2261: double (*f)(double), double tol, double *xmin);
2262: double f1dim(double x);
2263: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2264: double *fc, double (*func)(double));
2265: int j;
2266: double xx,xmin,bx,ax;
2267: double fx,fb,fa;
1.187 brouard 2268:
1.203 brouard 2269: #ifdef LINMINORIGINAL
2270: #else
2271: double scale=10., axs, xxs; /* Scale added for infinity */
2272: #endif
2273:
1.126 brouard 2274: ncom=n;
2275: pcom=vector(1,n);
2276: xicom=vector(1,n);
2277: nrfunc=func;
2278: for (j=1;j<=n;j++) {
2279: pcom[j]=p[j];
1.202 brouard 2280: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2281: }
1.187 brouard 2282:
1.203 brouard 2283: #ifdef LINMINORIGINAL
2284: xx=1.;
2285: #else
2286: axs=0.0;
2287: xxs=1.;
2288: do{
2289: xx= xxs;
2290: #endif
1.187 brouard 2291: ax=0.;
2292: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2293: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2294: /* 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)) */
2295: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2296: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2297: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2298: /* 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 2299: #ifdef LINMINORIGINAL
2300: #else
2301: if (fx != fx){
1.224 brouard 2302: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2303: printf("|");
2304: fprintf(ficlog,"|");
1.203 brouard 2305: #ifdef DEBUGLINMIN
1.224 brouard 2306: 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 2307: #endif
2308: }
1.224 brouard 2309: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2310: #endif
2311:
1.191 brouard 2312: #ifdef DEBUGLINMIN
2313: 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 2314: 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 2315: #endif
1.224 brouard 2316: #ifdef LINMINORIGINAL
2317: #else
1.317 brouard 2318: if(fb == fx){ /* Flat function in the direction */
2319: xmin=xx;
1.224 brouard 2320: *flat=1;
1.317 brouard 2321: }else{
1.224 brouard 2322: *flat=0;
2323: #endif
2324: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2325: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2326: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2327: /* fmin = f(p[j] + xmin * xi[j]) */
2328: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2329: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2330: #ifdef DEBUG
1.224 brouard 2331: 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);
2332: 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);
2333: #endif
2334: #ifdef LINMINORIGINAL
2335: #else
2336: }
1.126 brouard 2337: #endif
1.191 brouard 2338: #ifdef DEBUGLINMIN
2339: printf("linmin end ");
1.202 brouard 2340: fprintf(ficlog,"linmin end ");
1.191 brouard 2341: #endif
1.126 brouard 2342: for (j=1;j<=n;j++) {
1.203 brouard 2343: #ifdef LINMINORIGINAL
2344: xi[j] *= xmin;
2345: #else
2346: #ifdef DEBUGLINMIN
2347: if(xxs <1.0)
2348: printf(" before xi[%d]=%12.8f", j,xi[j]);
2349: #endif
2350: 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) */
2351: #ifdef DEBUGLINMIN
2352: if(xxs <1.0)
2353: 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 );
2354: #endif
2355: #endif
1.187 brouard 2356: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2357: }
1.191 brouard 2358: #ifdef DEBUGLINMIN
1.203 brouard 2359: printf("\n");
1.191 brouard 2360: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2361: 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 2362: for (j=1;j<=n;j++) {
1.202 brouard 2363: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2364: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2365: if(j % ncovmodel == 0){
1.191 brouard 2366: printf("\n");
1.202 brouard 2367: fprintf(ficlog,"\n");
2368: }
1.191 brouard 2369: }
1.203 brouard 2370: #else
1.191 brouard 2371: #endif
1.126 brouard 2372: free_vector(xicom,1,n);
2373: free_vector(pcom,1,n);
2374: }
2375:
2376:
2377: /*************** powell ************************/
1.162 brouard 2378: /*
1.317 brouard 2379: Minimization of a function func of n variables. Input consists in an initial starting point
2380: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2381: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2382: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2383: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2384: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2385: */
1.224 brouard 2386: #ifdef LINMINORIGINAL
2387: #else
2388: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2389: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2390: #endif
1.126 brouard 2391: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2392: double (*func)(double []))
2393: {
1.224 brouard 2394: #ifdef LINMINORIGINAL
2395: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2396: double (*func)(double []));
1.224 brouard 2397: #else
1.241 brouard 2398: void linmin(double p[], double xi[], int n, double *fret,
2399: double (*func)(double []),int *flat);
1.224 brouard 2400: #endif
1.239 brouard 2401: int i,ibig,j,jk,k;
1.126 brouard 2402: double del,t,*pt,*ptt,*xit;
1.181 brouard 2403: double directest;
1.126 brouard 2404: double fp,fptt;
2405: double *xits;
2406: int niterf, itmp;
2407:
2408: pt=vector(1,n);
2409: ptt=vector(1,n);
2410: xit=vector(1,n);
2411: xits=vector(1,n);
2412: *fret=(*func)(p);
2413: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2414: rcurr_time = time(NULL);
1.126 brouard 2415: for (*iter=1;;++(*iter)) {
1.187 brouard 2416: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2417: ibig=0;
2418: del=0.0;
1.157 brouard 2419: rlast_time=rcurr_time;
2420: /* (void) gettimeofday(&curr_time,&tzp); */
2421: rcurr_time = time(NULL);
2422: curr_time = *localtime(&rcurr_time);
2423: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2424: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2425: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2426: for (i=1;i<=n;i++) {
1.126 brouard 2427: fprintf(ficrespow," %.12lf", p[i]);
2428: }
1.239 brouard 2429: fprintf(ficrespow,"\n");fflush(ficrespow);
2430: printf("\n#model= 1 + age ");
2431: fprintf(ficlog,"\n#model= 1 + age ");
2432: if(nagesqr==1){
1.241 brouard 2433: printf(" + age*age ");
2434: fprintf(ficlog," + age*age ");
1.239 brouard 2435: }
2436: for(j=1;j <=ncovmodel-2;j++){
2437: if(Typevar[j]==0) {
2438: printf(" + V%d ",Tvar[j]);
2439: fprintf(ficlog," + V%d ",Tvar[j]);
2440: }else if(Typevar[j]==1) {
2441: printf(" + V%d*age ",Tvar[j]);
2442: fprintf(ficlog," + V%d*age ",Tvar[j]);
2443: }else if(Typevar[j]==2) {
2444: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2445: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2446: }
2447: }
1.126 brouard 2448: printf("\n");
1.239 brouard 2449: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2450: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2451: fprintf(ficlog,"\n");
1.239 brouard 2452: for(i=1,jk=1; i <=nlstate; i++){
2453: for(k=1; k <=(nlstate+ndeath); k++){
2454: if (k != i) {
2455: printf("%d%d ",i,k);
2456: fprintf(ficlog,"%d%d ",i,k);
2457: for(j=1; j <=ncovmodel; j++){
2458: printf("%12.7f ",p[jk]);
2459: fprintf(ficlog,"%12.7f ",p[jk]);
2460: jk++;
2461: }
2462: printf("\n");
2463: fprintf(ficlog,"\n");
2464: }
2465: }
2466: }
1.241 brouard 2467: if(*iter <=3 && *iter >1){
1.157 brouard 2468: tml = *localtime(&rcurr_time);
2469: strcpy(strcurr,asctime(&tml));
2470: rforecast_time=rcurr_time;
1.126 brouard 2471: itmp = strlen(strcurr);
2472: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2473: strcurr[itmp-1]='\0';
1.162 brouard 2474: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2475: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2476: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2477: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2478: forecast_time = *localtime(&rforecast_time);
2479: strcpy(strfor,asctime(&forecast_time));
2480: itmp = strlen(strfor);
2481: if(strfor[itmp-1]=='\n')
2482: strfor[itmp-1]='\0';
2483: 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);
2484: 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 2485: }
2486: }
1.187 brouard 2487: for (i=1;i<=n;i++) { /* For each direction i */
2488: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2489: fptt=(*fret);
2490: #ifdef DEBUG
1.203 brouard 2491: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2492: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2493: #endif
1.203 brouard 2494: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2495: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2496: #ifdef LINMINORIGINAL
1.188 brouard 2497: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2498: #else
2499: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2500: flatdir[i]=flat; /* Function is vanishing in that direction i */
2501: #endif
2502: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2503: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2504: /* because that direction will be replaced unless the gain del is small */
2505: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2506: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2507: /* with the new direction. */
2508: del=fabs(fptt-(*fret));
2509: ibig=i;
1.126 brouard 2510: }
2511: #ifdef DEBUG
2512: printf("%d %.12e",i,(*fret));
2513: fprintf(ficlog,"%d %.12e",i,(*fret));
2514: for (j=1;j<=n;j++) {
1.224 brouard 2515: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2516: printf(" x(%d)=%.12e",j,xit[j]);
2517: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2518: }
2519: for(j=1;j<=n;j++) {
1.225 brouard 2520: printf(" p(%d)=%.12e",j,p[j]);
2521: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2522: }
2523: printf("\n");
2524: fprintf(ficlog,"\n");
2525: #endif
1.187 brouard 2526: } /* end loop on each direction i */
2527: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2528: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2529: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2530: for(j=1;j<=n;j++) {
2531: if(flatdir[j] >0){
2532: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2533: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2534: }
1.319 brouard 2535: /* printf("\n"); */
2536: /* fprintf(ficlog,"\n"); */
2537: }
1.243 brouard 2538: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2539: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2540: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2541: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2542: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2543: /* decreased of more than 3.84 */
2544: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2545: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2546: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2547:
1.188 brouard 2548: /* Starting the program with initial values given by a former maximization will simply change */
2549: /* the scales of the directions and the directions, because the are reset to canonical directions */
2550: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2551: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2552: #ifdef DEBUG
2553: int k[2],l;
2554: k[0]=1;
2555: k[1]=-1;
2556: printf("Max: %.12e",(*func)(p));
2557: fprintf(ficlog,"Max: %.12e",(*func)(p));
2558: for (j=1;j<=n;j++) {
2559: printf(" %.12e",p[j]);
2560: fprintf(ficlog," %.12e",p[j]);
2561: }
2562: printf("\n");
2563: fprintf(ficlog,"\n");
2564: for(l=0;l<=1;l++) {
2565: for (j=1;j<=n;j++) {
2566: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2567: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2568: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2569: }
2570: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2571: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2572: }
2573: #endif
2574:
2575: free_vector(xit,1,n);
2576: free_vector(xits,1,n);
2577: free_vector(ptt,1,n);
2578: free_vector(pt,1,n);
2579: return;
1.192 brouard 2580: } /* enough precision */
1.240 brouard 2581: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2582: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2583: ptt[j]=2.0*p[j]-pt[j];
2584: xit[j]=p[j]-pt[j];
2585: pt[j]=p[j];
2586: }
1.181 brouard 2587: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2588: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2589: if (*iter <=4) {
1.225 brouard 2590: #else
2591: #endif
1.224 brouard 2592: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2593: #else
1.161 brouard 2594: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2595: #endif
1.162 brouard 2596: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2597: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2598: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2599: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2600: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2601: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2602: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2603: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2604: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2605: /* Even if f3 <f1, directest can be negative and t >0 */
2606: /* mu² and del² are equal when f3=f1 */
2607: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2608: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2609: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2610: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2611: #ifdef NRCORIGINAL
2612: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2613: #else
2614: 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 2615: t= t- del*SQR(fp-fptt);
1.183 brouard 2616: #endif
1.202 brouard 2617: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2618: #ifdef DEBUG
1.181 brouard 2619: 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);
2620: 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 2621: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2622: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2623: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2624: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2625: 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);
2626: 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);
2627: #endif
1.183 brouard 2628: #ifdef POWELLORIGINAL
2629: if (t < 0.0) { /* Then we use it for new direction */
2630: #else
1.182 brouard 2631: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2632: 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 2633: 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 2634: 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 2635: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2636: }
1.181 brouard 2637: if (directest < 0.0) { /* Then we use it for new direction */
2638: #endif
1.191 brouard 2639: #ifdef DEBUGLINMIN
1.234 brouard 2640: printf("Before linmin in direction P%d-P0\n",n);
2641: for (j=1;j<=n;j++) {
2642: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2643: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2644: if(j % ncovmodel == 0){
2645: printf("\n");
2646: fprintf(ficlog,"\n");
2647: }
2648: }
1.224 brouard 2649: #endif
2650: #ifdef LINMINORIGINAL
1.234 brouard 2651: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2652: #else
1.234 brouard 2653: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2654: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2655: #endif
1.234 brouard 2656:
1.191 brouard 2657: #ifdef DEBUGLINMIN
1.234 brouard 2658: for (j=1;j<=n;j++) {
2659: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2660: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2661: if(j % ncovmodel == 0){
2662: printf("\n");
2663: fprintf(ficlog,"\n");
2664: }
2665: }
1.224 brouard 2666: #endif
1.234 brouard 2667: for (j=1;j<=n;j++) {
2668: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2669: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2670: }
1.224 brouard 2671: #ifdef LINMINORIGINAL
2672: #else
1.234 brouard 2673: for (j=1, flatd=0;j<=n;j++) {
2674: if(flatdir[j]>0)
2675: flatd++;
2676: }
2677: if(flatd >0){
1.255 brouard 2678: printf("%d flat directions: ",flatd);
2679: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2680: for (j=1;j<=n;j++) {
2681: if(flatdir[j]>0){
2682: printf("%d ",j);
2683: fprintf(ficlog,"%d ",j);
2684: }
2685: }
2686: printf("\n");
2687: fprintf(ficlog,"\n");
1.319 brouard 2688: #ifdef FLATSUP
2689: free_vector(xit,1,n);
2690: free_vector(xits,1,n);
2691: free_vector(ptt,1,n);
2692: free_vector(pt,1,n);
2693: return;
2694: #endif
1.234 brouard 2695: }
1.191 brouard 2696: #endif
1.234 brouard 2697: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2698: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2699:
1.126 brouard 2700: #ifdef DEBUG
1.234 brouard 2701: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2702: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2703: for(j=1;j<=n;j++){
2704: printf(" %lf",xit[j]);
2705: fprintf(ficlog," %lf",xit[j]);
2706: }
2707: printf("\n");
2708: fprintf(ficlog,"\n");
1.126 brouard 2709: #endif
1.192 brouard 2710: } /* end of t or directest negative */
1.224 brouard 2711: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2712: #else
1.234 brouard 2713: } /* end if (fptt < fp) */
1.192 brouard 2714: #endif
1.225 brouard 2715: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2716: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2717: #else
1.224 brouard 2718: #endif
1.234 brouard 2719: } /* loop iteration */
1.126 brouard 2720: }
1.234 brouard 2721:
1.126 brouard 2722: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2723:
1.235 brouard 2724: 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 2725: {
1.279 brouard 2726: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2727: * (and selected quantitative values in nres)
2728: * by left multiplying the unit
2729: * matrix by transitions matrix until convergence is reached with precision ftolpl
2730: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2731: * Wx is row vector: population in state 1, population in state 2, population dead
2732: * or prevalence in state 1, prevalence in state 2, 0
2733: * newm is the matrix after multiplications, its rows are identical at a factor.
2734: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2735: * Output is prlim.
2736: * Initial matrix pimij
2737: */
1.206 brouard 2738: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2739: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2740: /* 0, 0 , 1} */
2741: /*
2742: * and after some iteration: */
2743: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2744: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2745: /* 0, 0 , 1} */
2746: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2747: /* {0.51571254859325999, 0.4842874514067399, */
2748: /* 0.51326036147820708, 0.48673963852179264} */
2749: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2750:
1.126 brouard 2751: int i, ii,j,k;
1.209 brouard 2752: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2753: /* double **matprod2(); */ /* test */
1.218 brouard 2754: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2755: double **newm;
1.209 brouard 2756: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2757: int ncvloop=0;
1.288 brouard 2758: int first=0;
1.169 brouard 2759:
1.209 brouard 2760: min=vector(1,nlstate);
2761: max=vector(1,nlstate);
2762: meandiff=vector(1,nlstate);
2763:
1.218 brouard 2764: /* Starting with matrix unity */
1.126 brouard 2765: for (ii=1;ii<=nlstate+ndeath;ii++)
2766: for (j=1;j<=nlstate+ndeath;j++){
2767: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2768: }
1.169 brouard 2769:
2770: cov[1]=1.;
2771:
2772: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2773: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2774: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2775: ncvloop++;
1.126 brouard 2776: newm=savm;
2777: /* Covariates have to be included here again */
1.138 brouard 2778: cov[2]=agefin;
1.319 brouard 2779: if(nagesqr==1){
2780: cov[3]= agefin*agefin;
2781: }
1.234 brouard 2782: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2783: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2784: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.319 brouard 2785: /* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; */
1.235 brouard 2786: /* 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)); */
1.234 brouard 2787: }
2788: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2789: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 2790: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2791: /* cov[++k1]=Tqresult[nres][k]; */
1.235 brouard 2792: /* 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]); */
1.138 brouard 2793: }
1.237 brouard 2794: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2795: if(Dummy[Tage[k]]==2){ /* dummy with age */
1.234 brouard 2796: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2797: /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
2798: } else if(Dummy[Tage[k]]==3){ /* quantitative with age */
2799: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2800: /* cov[++k1]=Tqresult[nres][k]; */
1.234 brouard 2801: }
1.235 brouard 2802: /* 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]); */
1.234 brouard 2803: }
1.237 brouard 2804: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2805: /* 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]); */
1.237 brouard 2806: if(Dummy[Tvard[k][1]==0]){
2807: if(Dummy[Tvard[k][2]==0]){
2808: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
1.319 brouard 2809: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.237 brouard 2810: }else{
2811: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
1.319 brouard 2812: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */
1.237 brouard 2813: }
2814: }else{
2815: if(Dummy[Tvard[k][2]==0]){
2816: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
1.319 brouard 2817: /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */
1.237 brouard 2818: }else{
2819: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
1.319 brouard 2820: /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
1.237 brouard 2821: }
2822: }
1.234 brouard 2823: }
1.138 brouard 2824: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2825: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2826: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2827: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2828: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2829: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2830: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2831:
1.126 brouard 2832: savm=oldm;
2833: oldm=newm;
1.209 brouard 2834:
2835: for(j=1; j<=nlstate; j++){
2836: max[j]=0.;
2837: min[j]=1.;
2838: }
2839: for(i=1;i<=nlstate;i++){
2840: sumnew=0;
2841: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2842: for(j=1; j<=nlstate; j++){
2843: prlim[i][j]= newm[i][j]/(1-sumnew);
2844: max[j]=FMAX(max[j],prlim[i][j]);
2845: min[j]=FMIN(min[j],prlim[i][j]);
2846: }
2847: }
2848:
1.126 brouard 2849: maxmax=0.;
1.209 brouard 2850: for(j=1; j<=nlstate; j++){
2851: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2852: maxmax=FMAX(maxmax,meandiff[j]);
2853: /* 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 2854: } /* j loop */
1.203 brouard 2855: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2856: /* 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 2857: if(maxmax < ftolpl){
1.209 brouard 2858: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2859: free_vector(min,1,nlstate);
2860: free_vector(max,1,nlstate);
2861: free_vector(meandiff,1,nlstate);
1.126 brouard 2862: return prlim;
2863: }
1.288 brouard 2864: } /* agefin loop */
1.208 brouard 2865: /* After some age loop it doesn't converge */
1.288 brouard 2866: if(!first){
2867: first=1;
2868: 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 2869: 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);
2870: }else if (first >=1 && first <10){
2871: 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);
2872: first++;
2873: }else if (first ==10){
2874: 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);
2875: 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");
2876: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
2877: first++;
1.288 brouard 2878: }
2879:
1.209 brouard 2880: /* 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); */
2881: free_vector(min,1,nlstate);
2882: free_vector(max,1,nlstate);
2883: free_vector(meandiff,1,nlstate);
1.208 brouard 2884:
1.169 brouard 2885: return prlim; /* should not reach here */
1.126 brouard 2886: }
2887:
1.217 brouard 2888:
2889: /**** Back Prevalence limit (stable or period prevalence) ****************/
2890:
1.218 brouard 2891: /* 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) */
2892: /* 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 2893: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2894: {
1.264 brouard 2895: /* 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 2896: matrix by transitions matrix until convergence is reached with precision ftolpl */
2897: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2898: /* Wx is row vector: population in state 1, population in state 2, population dead */
2899: /* or prevalence in state 1, prevalence in state 2, 0 */
2900: /* newm is the matrix after multiplications, its rows are identical at a factor */
2901: /* Initial matrix pimij */
2902: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2903: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2904: /* 0, 0 , 1} */
2905: /*
2906: * and after some iteration: */
2907: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2908: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2909: /* 0, 0 , 1} */
2910: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2911: /* {0.51571254859325999, 0.4842874514067399, */
2912: /* 0.51326036147820708, 0.48673963852179264} */
2913: /* If we start from prlim again, prlim tends to a constant matrix */
2914:
2915: int i, ii,j,k;
1.247 brouard 2916: int first=0;
1.217 brouard 2917: double *min, *max, *meandiff, maxmax,sumnew=0.;
2918: /* double **matprod2(); */ /* test */
2919: double **out, cov[NCOVMAX+1], **bmij();
2920: double **newm;
1.218 brouard 2921: double **dnewm, **doldm, **dsavm; /* for use */
2922: double **oldm, **savm; /* for use */
2923:
1.217 brouard 2924: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2925: int ncvloop=0;
2926:
2927: min=vector(1,nlstate);
2928: max=vector(1,nlstate);
2929: meandiff=vector(1,nlstate);
2930:
1.266 brouard 2931: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2932: oldm=oldms; savm=savms;
2933:
2934: /* Starting with matrix unity */
2935: for (ii=1;ii<=nlstate+ndeath;ii++)
2936: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2937: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2938: }
2939:
2940: cov[1]=1.;
2941:
2942: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2943: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2944: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2945: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2946: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2947: ncvloop++;
1.218 brouard 2948: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2949: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2950: /* Covariates have to be included here again */
2951: cov[2]=agefin;
1.319 brouard 2952: if(nagesqr==1){
1.217 brouard 2953: cov[3]= agefin*agefin;;
1.319 brouard 2954: }
1.242 brouard 2955: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2956: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2957: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2958: /* 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)); */
1.242 brouard 2959: }
2960: /* for (k=1; k<=cptcovn;k++) { */
2961: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2962: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2963: /* /\* 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])]); *\/ */
2964: /* } */
2965: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2966: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2967: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2968: /* 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]); */
2969: }
2970: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2971: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2972: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2973: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2974: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2975: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ ERROR ???*/
2976: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.242 brouard 2977: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2978: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
2979: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.242 brouard 2980: }
2981: /* 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]); */
2982: }
2983: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2984: /* 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]); */
2985: if(Dummy[Tvard[k][1]==0]){
2986: if(Dummy[Tvard[k][2]==0]){
2987: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2988: }else{
2989: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2990: }
2991: }else{
2992: if(Dummy[Tvard[k][2]==0]){
2993: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2994: }else{
2995: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2996: }
2997: }
1.217 brouard 2998: }
2999:
3000: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3001: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3002: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3003: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3004: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3005: /* ij should be linked to the correct index of cov */
3006: /* age and covariate values ij are in 'cov', but we need to pass
3007: * ij for the observed prevalence at age and status and covariate
3008: * number: prevacurrent[(int)agefin][ii][ij]
3009: */
3010: /* 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 *\/ */
3011: /* 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 *\/ */
3012: 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 3013: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3014: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3015: /* for(i=1; i<=nlstate+ndeath; i++) { */
3016: /* printf("%d newm= ",i); */
3017: /* for(j=1;j<=nlstate+ndeath;j++) { */
3018: /* printf("%f ",newm[i][j]); */
3019: /* } */
3020: /* printf("oldm * "); */
3021: /* for(j=1;j<=nlstate+ndeath;j++) { */
3022: /* printf("%f ",oldm[i][j]); */
3023: /* } */
1.268 brouard 3024: /* printf(" bmmij "); */
1.266 brouard 3025: /* for(j=1;j<=nlstate+ndeath;j++) { */
3026: /* printf("%f ",pmmij[i][j]); */
3027: /* } */
3028: /* printf("\n"); */
3029: /* } */
3030: /* } */
1.217 brouard 3031: savm=oldm;
3032: oldm=newm;
1.266 brouard 3033:
1.217 brouard 3034: for(j=1; j<=nlstate; j++){
3035: max[j]=0.;
3036: min[j]=1.;
3037: }
3038: for(j=1; j<=nlstate; j++){
3039: for(i=1;i<=nlstate;i++){
1.234 brouard 3040: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3041: bprlim[i][j]= newm[i][j];
3042: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3043: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3044: }
3045: }
1.218 brouard 3046:
1.217 brouard 3047: maxmax=0.;
3048: for(i=1; i<=nlstate; i++){
1.318 brouard 3049: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3050: maxmax=FMAX(maxmax,meandiff[i]);
3051: /* 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 3052: } /* i loop */
1.217 brouard 3053: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3054: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3055: if(maxmax < ftolpl){
1.220 brouard 3056: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3057: free_vector(min,1,nlstate);
3058: free_vector(max,1,nlstate);
3059: free_vector(meandiff,1,nlstate);
3060: return bprlim;
3061: }
1.288 brouard 3062: } /* agefin loop */
1.217 brouard 3063: /* After some age loop it doesn't converge */
1.288 brouard 3064: if(!first){
1.247 brouard 3065: first=1;
3066: 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\
3067: 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);
3068: }
3069: 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 3070: 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);
3071: /* 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); */
3072: free_vector(min,1,nlstate);
3073: free_vector(max,1,nlstate);
3074: free_vector(meandiff,1,nlstate);
3075:
3076: return bprlim; /* should not reach here */
3077: }
3078:
1.126 brouard 3079: /*************** transition probabilities ***************/
3080:
3081: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3082: {
1.138 brouard 3083: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3084: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3085: model to the ncovmodel covariates (including constant and age).
3086: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3087: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3088: ncth covariate in the global vector x is given by the formula:
3089: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3090: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3091: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3092: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3093: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3094: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3095: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3096: */
3097: double s1, lnpijopii;
1.126 brouard 3098: /*double t34;*/
1.164 brouard 3099: int i,j, nc, ii, jj;
1.126 brouard 3100:
1.223 brouard 3101: for(i=1; i<= nlstate; i++){
3102: for(j=1; j<i;j++){
3103: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3104: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3105: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3106: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3107: }
3108: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3109: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3110: }
3111: for(j=i+1; j<=nlstate+ndeath;j++){
3112: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3113: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3114: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3115: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3116: }
3117: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3118: }
3119: }
1.218 brouard 3120:
1.223 brouard 3121: for(i=1; i<= nlstate; i++){
3122: s1=0;
3123: for(j=1; j<i; j++){
3124: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3125: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3126: }
3127: for(j=i+1; j<=nlstate+ndeath; j++){
3128: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3129: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3130: }
3131: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3132: ps[i][i]=1./(s1+1.);
3133: /* Computing other pijs */
3134: for(j=1; j<i; j++)
3135: ps[i][j]= exp(ps[i][j])*ps[i][i];
3136: for(j=i+1; j<=nlstate+ndeath; j++)
3137: ps[i][j]= exp(ps[i][j])*ps[i][i];
3138: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3139: } /* end i */
1.218 brouard 3140:
1.223 brouard 3141: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3142: for(jj=1; jj<= nlstate+ndeath; jj++){
3143: ps[ii][jj]=0;
3144: ps[ii][ii]=1;
3145: }
3146: }
1.294 brouard 3147:
3148:
1.223 brouard 3149: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3150: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3151: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3152: /* } */
3153: /* printf("\n "); */
3154: /* } */
3155: /* printf("\n ");printf("%lf ",cov[2]);*/
3156: /*
3157: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3158: goto end;*/
1.266 brouard 3159: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3160: }
3161:
1.218 brouard 3162: /*************** backward transition probabilities ***************/
3163:
3164: /* 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 ) */
3165: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3166: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3167: {
1.302 brouard 3168: /* 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 3169: * 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 3170: */
1.218 brouard 3171: int i, ii, j,k;
1.222 brouard 3172:
3173: double **out, **pmij();
3174: double sumnew=0.;
1.218 brouard 3175: double agefin;
1.292 brouard 3176: 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 3177: double **dnewm, **dsavm, **doldm;
3178: double **bbmij;
3179:
1.218 brouard 3180: doldm=ddoldms; /* global pointers */
1.222 brouard 3181: dnewm=ddnewms;
3182: dsavm=ddsavms;
1.318 brouard 3183:
3184: /* Debug */
3185: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3186: agefin=cov[2];
1.268 brouard 3187: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3188: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3189: the observed prevalence (with this covariate ij) at beginning of transition */
3190: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3191:
3192: /* P_x */
1.266 brouard 3193: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3194: /* outputs pmmij which is a stochastic matrix in row */
3195:
3196: /* Diag(w_x) */
1.292 brouard 3197: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3198: sumnew=0.;
1.269 brouard 3199: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3200: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3201: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3202: sumnew+=prevacurrent[(int)agefin][ii][ij];
3203: }
3204: if(sumnew >0.01){ /* At least some value in the prevalence */
3205: for (ii=1;ii<=nlstate+ndeath;ii++){
3206: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3207: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3208: }
3209: }else{
3210: for (ii=1;ii<=nlstate+ndeath;ii++){
3211: for (j=1;j<=nlstate+ndeath;j++)
3212: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3213: }
3214: /* if(sumnew <0.9){ */
3215: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3216: /* } */
3217: }
3218: k3=0.0; /* We put the last diagonal to 0 */
3219: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3220: doldm[ii][ii]= k3;
3221: }
3222: /* End doldm, At the end doldm is diag[(w_i)] */
3223:
1.292 brouard 3224: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3225: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3226:
1.292 brouard 3227: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3228: /* 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 3229: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3230: sumnew=0.;
1.222 brouard 3231: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3232: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3233: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3234: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3235: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3236: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3237: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3238: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3239: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3240: /* }else */
1.268 brouard 3241: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3242: } /*End ii */
3243: } /* 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 */
3244:
1.292 brouard 3245: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3246: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3247: /* end bmij */
1.266 brouard 3248: return ps; /*pointer is unchanged */
1.218 brouard 3249: }
1.217 brouard 3250: /*************** transition probabilities ***************/
3251:
1.218 brouard 3252: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3253: {
3254: /* According to parameters values stored in x and the covariate's values stored in cov,
3255: computes the probability to be observed in state j being in state i by appying the
3256: model to the ncovmodel covariates (including constant and age).
3257: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3258: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3259: ncth covariate in the global vector x is given by the formula:
3260: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3261: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3262: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3263: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3264: Outputs ps[i][j] the probability to be observed in j being in j according to
3265: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3266: */
3267: double s1, lnpijopii;
3268: /*double t34;*/
3269: int i,j, nc, ii, jj;
3270:
1.234 brouard 3271: for(i=1; i<= nlstate; i++){
3272: for(j=1; j<i;j++){
3273: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3274: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3275: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3276: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3277: }
3278: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3279: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3280: }
3281: for(j=i+1; j<=nlstate+ndeath;j++){
3282: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3283: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3284: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3285: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3286: }
3287: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3288: }
3289: }
3290:
3291: for(i=1; i<= nlstate; i++){
3292: s1=0;
3293: for(j=1; j<i; j++){
3294: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3295: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3296: }
3297: for(j=i+1; j<=nlstate+ndeath; j++){
3298: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3299: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3300: }
3301: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3302: ps[i][i]=1./(s1+1.);
3303: /* Computing other pijs */
3304: for(j=1; j<i; j++)
3305: ps[i][j]= exp(ps[i][j])*ps[i][i];
3306: for(j=i+1; j<=nlstate+ndeath; j++)
3307: ps[i][j]= exp(ps[i][j])*ps[i][i];
3308: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3309: } /* end i */
3310:
3311: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3312: for(jj=1; jj<= nlstate+ndeath; jj++){
3313: ps[ii][jj]=0;
3314: ps[ii][ii]=1;
3315: }
3316: }
1.296 brouard 3317: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3318: for(jj=1; jj<= nlstate+ndeath; jj++){
3319: s1=0.;
3320: for(ii=1; ii<= nlstate+ndeath; ii++){
3321: s1+=ps[ii][jj];
3322: }
3323: for(ii=1; ii<= nlstate; ii++){
3324: ps[ii][jj]=ps[ii][jj]/s1;
3325: }
3326: }
3327: /* Transposition */
3328: for(jj=1; jj<= nlstate+ndeath; jj++){
3329: for(ii=jj; ii<= nlstate+ndeath; ii++){
3330: s1=ps[ii][jj];
3331: ps[ii][jj]=ps[jj][ii];
3332: ps[jj][ii]=s1;
3333: }
3334: }
3335: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3336: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3337: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3338: /* } */
3339: /* printf("\n "); */
3340: /* } */
3341: /* printf("\n ");printf("%lf ",cov[2]);*/
3342: /*
3343: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3344: goto end;*/
3345: return ps;
1.217 brouard 3346: }
3347:
3348:
1.126 brouard 3349: /**************** Product of 2 matrices ******************/
3350:
1.145 brouard 3351: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3352: {
3353: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3354: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3355: /* in, b, out are matrice of pointers which should have been initialized
3356: before: only the contents of out is modified. The function returns
3357: a pointer to pointers identical to out */
1.145 brouard 3358: int i, j, k;
1.126 brouard 3359: for(i=nrl; i<= nrh; i++)
1.145 brouard 3360: for(k=ncolol; k<=ncoloh; k++){
3361: out[i][k]=0.;
3362: for(j=ncl; j<=nch; j++)
3363: out[i][k] +=in[i][j]*b[j][k];
3364: }
1.126 brouard 3365: return out;
3366: }
3367:
3368:
3369: /************* Higher Matrix Product ***************/
3370:
1.235 brouard 3371: 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 3372: {
1.218 brouard 3373: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3374: 'nhstepm*hstepm*stepm' months (i.e. until
3375: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3376: nhstepm*hstepm matrices.
3377: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3378: (typically every 2 years instead of every month which is too big
3379: for the memory).
3380: Model is determined by parameters x and covariates have to be
3381: included manually here.
3382:
3383: */
3384:
3385: int i, j, d, h, k;
1.131 brouard 3386: double **out, cov[NCOVMAX+1];
1.126 brouard 3387: double **newm;
1.187 brouard 3388: double agexact;
1.214 brouard 3389: double agebegin, ageend;
1.126 brouard 3390:
3391: /* Hstepm could be zero and should return the unit matrix */
3392: for (i=1;i<=nlstate+ndeath;i++)
3393: for (j=1;j<=nlstate+ndeath;j++){
3394: oldm[i][j]=(i==j ? 1.0 : 0.0);
3395: po[i][j][0]=(i==j ? 1.0 : 0.0);
3396: }
3397: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3398: for(h=1; h <=nhstepm; h++){
3399: for(d=1; d <=hstepm; d++){
3400: newm=savm;
3401: /* Covariates have to be included here again */
3402: cov[1]=1.;
1.214 brouard 3403: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3404: cov[2]=agexact;
1.319 brouard 3405: if(nagesqr==1){
1.227 brouard 3406: cov[3]= agexact*agexact;
1.319 brouard 3407: }
1.235 brouard 3408: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
1.319 brouard 3409: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3410: /* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 */
3411: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3412: /* k 1 2 3 4 5 6 7 8 9 */
3413: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
3414: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
3415: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
3416: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1.235 brouard 3417: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3418: /* printf("hpxij 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)); */
3419: }
3420: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3421: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 3422: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
1.235 brouard 3423: /* 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]); */
3424: }
1.319 brouard 3425: for (k=1; k<=cptcovage;k++){ /* For product with age V1+V1*age +V4 +age*V3 */
3426: /* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*/
3427: /* */
3428: if(Dummy[Tage[k]]== 2){ /* dummy with age */
3429: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ */
1.235 brouard 3430: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3431: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
3432: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.235 brouard 3433: }
3434: /* 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]); */
3435: }
1.319 brouard 3436: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 3437: /* printf("hPxij 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]); */
1.319 brouard 3438: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
3439: if(Dummy[Tvard[k][1]==0]){
3440: if(Dummy[Tvard[k][2]==0]){
3441: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3442: }else{
3443: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
3444: }
3445: }else{
3446: if(Dummy[Tvard[k][2]==0]){
3447: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
3448: }else{
3449: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3450: }
3451: }
1.235 brouard 3452: }
3453: /* for (k=1; k<=cptcovn;k++) */
3454: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3455: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3456: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3457: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3458: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3459:
3460:
1.126 brouard 3461: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3462: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3463: /* right multiplication of oldm by the current matrix */
1.126 brouard 3464: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3465: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3466: /* if((int)age == 70){ */
3467: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3468: /* for(i=1; i<=nlstate+ndeath; i++) { */
3469: /* printf("%d pmmij ",i); */
3470: /* for(j=1;j<=nlstate+ndeath;j++) { */
3471: /* printf("%f ",pmmij[i][j]); */
3472: /* } */
3473: /* printf(" oldm "); */
3474: /* for(j=1;j<=nlstate+ndeath;j++) { */
3475: /* printf("%f ",oldm[i][j]); */
3476: /* } */
3477: /* printf("\n"); */
3478: /* } */
3479: /* } */
1.126 brouard 3480: savm=oldm;
3481: oldm=newm;
3482: }
3483: for(i=1; i<=nlstate+ndeath; i++)
3484: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3485: po[i][j][h]=newm[i][j];
3486: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3487: }
1.128 brouard 3488: /*printf("h=%d ",h);*/
1.126 brouard 3489: } /* end h */
1.267 brouard 3490: /* printf("\n H=%d \n",h); */
1.126 brouard 3491: return po;
3492: }
3493:
1.217 brouard 3494: /************* Higher Back Matrix Product ***************/
1.218 brouard 3495: /* 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 3496: 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 3497: {
1.266 brouard 3498: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3499: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3500: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3501: nhstepm*hstepm matrices.
3502: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3503: (typically every 2 years instead of every month which is too big
1.217 brouard 3504: for the memory).
1.218 brouard 3505: Model is determined by parameters x and covariates have to be
1.266 brouard 3506: included manually here. Then we use a call to bmij(x and cov)
3507: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3508: */
1.217 brouard 3509:
3510: int i, j, d, h, k;
1.266 brouard 3511: double **out, cov[NCOVMAX+1], **bmij();
3512: double **newm, ***newmm;
1.217 brouard 3513: double agexact;
3514: double agebegin, ageend;
1.222 brouard 3515: double **oldm, **savm;
1.217 brouard 3516:
1.266 brouard 3517: newmm=po; /* To be saved */
3518: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3519: /* Hstepm could be zero and should return the unit matrix */
3520: for (i=1;i<=nlstate+ndeath;i++)
3521: for (j=1;j<=nlstate+ndeath;j++){
3522: oldm[i][j]=(i==j ? 1.0 : 0.0);
3523: po[i][j][0]=(i==j ? 1.0 : 0.0);
3524: }
3525: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3526: for(h=1; h <=nhstepm; h++){
3527: for(d=1; d <=hstepm; d++){
3528: newm=savm;
3529: /* Covariates have to be included here again */
3530: cov[1]=1.;
1.271 brouard 3531: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3532: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3533: /* Debug */
3534: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3535: cov[2]=agexact;
3536: if(nagesqr==1)
1.222 brouard 3537: cov[3]= agexact*agexact;
1.266 brouard 3538: for (k=1; k<=cptcovn;k++){
3539: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3540: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3541: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3542: /* 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)); */
3543: }
1.267 brouard 3544: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3545: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3546: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3547: /* 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]); */
3548: }
1.319 brouard 3549: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 *//* For product with age */
3550: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age error!!!*\/ */
3551: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.267 brouard 3552: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3553: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
1.267 brouard 3554: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3555: }
3556: /* 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]); */
3557: }
3558: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3559: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3560: }
1.217 brouard 3561: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3562: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3563:
1.218 brouard 3564: /* Careful transposed matrix */
1.266 brouard 3565: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3566: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3567: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3568: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3569: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3570: /* if((int)age == 70){ */
3571: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3572: /* for(i=1; i<=nlstate+ndeath; i++) { */
3573: /* printf("%d pmmij ",i); */
3574: /* for(j=1;j<=nlstate+ndeath;j++) { */
3575: /* printf("%f ",pmmij[i][j]); */
3576: /* } */
3577: /* printf(" oldm "); */
3578: /* for(j=1;j<=nlstate+ndeath;j++) { */
3579: /* printf("%f ",oldm[i][j]); */
3580: /* } */
3581: /* printf("\n"); */
3582: /* } */
3583: /* } */
3584: savm=oldm;
3585: oldm=newm;
3586: }
3587: for(i=1; i<=nlstate+ndeath; i++)
3588: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3589: po[i][j][h]=newm[i][j];
1.268 brouard 3590: /* if(h==nhstepm) */
3591: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3592: }
1.268 brouard 3593: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3594: } /* end h */
1.268 brouard 3595: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3596: return po;
3597: }
3598:
3599:
1.162 brouard 3600: #ifdef NLOPT
3601: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3602: double fret;
3603: double *xt;
3604: int j;
3605: myfunc_data *d2 = (myfunc_data *) pd;
3606: /* xt = (p1-1); */
3607: xt=vector(1,n);
3608: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3609:
3610: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3611: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3612: printf("Function = %.12lf ",fret);
3613: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3614: printf("\n");
3615: free_vector(xt,1,n);
3616: return fret;
3617: }
3618: #endif
1.126 brouard 3619:
3620: /*************** log-likelihood *************/
3621: double func( double *x)
3622: {
1.226 brouard 3623: int i, ii, j, k, mi, d, kk;
3624: int ioffset=0;
3625: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3626: double **out;
3627: double lli; /* Individual log likelihood */
3628: int s1, s2;
1.228 brouard 3629: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
1.226 brouard 3630: double bbh, survp;
3631: long ipmx;
3632: double agexact;
3633: /*extern weight */
3634: /* We are differentiating ll according to initial status */
3635: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3636: /*for(i=1;i<imx;i++)
3637: printf(" %d\n",s[4][i]);
3638: */
1.162 brouard 3639:
1.226 brouard 3640: ++countcallfunc;
1.162 brouard 3641:
1.226 brouard 3642: cov[1]=1.;
1.126 brouard 3643:
1.226 brouard 3644: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3645: ioffset=0;
1.226 brouard 3646: if(mle==1){
3647: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3648: /* Computes the values of the ncovmodel covariates of the model
3649: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3650: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3651: to be observed in j being in i according to the model.
3652: */
1.243 brouard 3653: ioffset=2+nagesqr ;
1.233 brouard 3654: /* Fixed */
1.319 brouard 3655: for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */
3656: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3657: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3658: /* 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 3659: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.319 brouard 3660: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/
3661: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3662: }
1.226 brouard 3663: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3664: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3665: has been calculated etc */
3666: /* For an individual i, wav[i] gives the number of effective waves */
3667: /* We compute the contribution to Likelihood of each effective transition
3668: mw[mi][i] is real wave of the mi th effectve wave */
3669: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3670: s2=s[mw[mi+1][i]][i];
3671: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3672: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3673: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3674: */
3675: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3676: 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*/
3677: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */
1.242 brouard 3678: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3679: }
3680: for (ii=1;ii<=nlstate+ndeath;ii++)
3681: for (j=1;j<=nlstate+ndeath;j++){
3682: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3683: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3684: }
3685: for(d=0; d<dh[mi][i]; d++){
3686: newm=savm;
3687: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3688: cov[2]=agexact;
3689: if(nagesqr==1)
3690: cov[3]= agexact*agexact; /* Should be changed here */
3691: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3692: if(!FixedV[Tvar[Tage[kk]]])
3693: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3694: else
3695: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3696: }
3697: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3698: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3699: savm=oldm;
3700: oldm=newm;
3701: } /* end mult */
3702:
3703: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3704: /* But now since version 0.9 we anticipate for bias at large stepm.
3705: * If stepm is larger than one month (smallest stepm) and if the exact delay
3706: * (in months) between two waves is not a multiple of stepm, we rounded to
3707: * the nearest (and in case of equal distance, to the lowest) interval but now
3708: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3709: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3710: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3711: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3712: * -stepm/2 to stepm/2 .
3713: * For stepm=1 the results are the same as for previous versions of Imach.
3714: * For stepm > 1 the results are less biased than in previous versions.
3715: */
1.234 brouard 3716: s1=s[mw[mi][i]][i];
3717: s2=s[mw[mi+1][i]][i];
3718: bbh=(double)bh[mi][i]/(double)stepm;
3719: /* bias bh is positive if real duration
3720: * is higher than the multiple of stepm and negative otherwise.
3721: */
3722: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3723: if( s2 > nlstate){
3724: /* i.e. if s2 is a death state and if the date of death is known
3725: then the contribution to the likelihood is the probability to
3726: die between last step unit time and current step unit time,
3727: which is also equal to probability to die before dh
3728: minus probability to die before dh-stepm .
3729: In version up to 0.92 likelihood was computed
3730: as if date of death was unknown. Death was treated as any other
3731: health state: the date of the interview describes the actual state
3732: and not the date of a change in health state. The former idea was
3733: to consider that at each interview the state was recorded
3734: (healthy, disable or death) and IMaCh was corrected; but when we
3735: introduced the exact date of death then we should have modified
3736: the contribution of an exact death to the likelihood. This new
3737: contribution is smaller and very dependent of the step unit
3738: stepm. It is no more the probability to die between last interview
3739: and month of death but the probability to survive from last
3740: interview up to one month before death multiplied by the
3741: probability to die within a month. Thanks to Chris
3742: Jackson for correcting this bug. Former versions increased
3743: mortality artificially. The bad side is that we add another loop
3744: which slows down the processing. The difference can be up to 10%
3745: lower mortality.
3746: */
3747: /* If, at the beginning of the maximization mostly, the
3748: cumulative probability or probability to be dead is
3749: constant (ie = 1) over time d, the difference is equal to
3750: 0. out[s1][3] = savm[s1][3]: probability, being at state
3751: s1 at precedent wave, to be dead a month before current
3752: wave is equal to probability, being at state s1 at
3753: precedent wave, to be dead at mont of the current
3754: wave. Then the observed probability (that this person died)
3755: is null according to current estimated parameter. In fact,
3756: it should be very low but not zero otherwise the log go to
3757: infinity.
3758: */
1.183 brouard 3759: /* #ifdef INFINITYORIGINAL */
3760: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3761: /* #else */
3762: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3763: /* lli=log(mytinydouble); */
3764: /* else */
3765: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3766: /* #endif */
1.226 brouard 3767: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3768:
1.226 brouard 3769: } else if ( s2==-1 ) { /* alive */
3770: for (j=1,survp=0. ; j<=nlstate; j++)
3771: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3772: /*survp += out[s1][j]; */
3773: lli= log(survp);
3774: }
3775: else if (s2==-4) {
3776: for (j=3,survp=0. ; j<=nlstate; j++)
3777: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3778: lli= log(survp);
3779: }
3780: else if (s2==-5) {
3781: for (j=1,survp=0. ; j<=2; j++)
3782: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3783: lli= log(survp);
3784: }
3785: else{
3786: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3787: /* 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 */
3788: }
3789: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3790: /*if(lli ==000.0)*/
3791: /*printf("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); */
3792: ipmx +=1;
3793: sw += weight[i];
3794: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3795: /* if (lli < log(mytinydouble)){ */
3796: /* 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); */
3797: /* 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]); */
3798: /* } */
3799: } /* end of wave */
3800: } /* end of individual */
3801: } else if(mle==2){
3802: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 3803: ioffset=2+nagesqr ;
3804: for (k=1; k<=ncovf;k++)
3805: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 3806: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3807: for(k=1; k <= ncovv ; k++){
3808: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3809: }
1.226 brouard 3810: for (ii=1;ii<=nlstate+ndeath;ii++)
3811: for (j=1;j<=nlstate+ndeath;j++){
3812: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3813: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3814: }
3815: for(d=0; d<=dh[mi][i]; d++){
3816: newm=savm;
3817: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3818: cov[2]=agexact;
3819: if(nagesqr==1)
3820: cov[3]= agexact*agexact;
3821: for (kk=1; kk<=cptcovage;kk++) {
3822: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3823: }
3824: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3825: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3826: savm=oldm;
3827: oldm=newm;
3828: } /* end mult */
3829:
3830: s1=s[mw[mi][i]][i];
3831: s2=s[mw[mi+1][i]][i];
3832: bbh=(double)bh[mi][i]/(double)stepm;
3833: 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 */
3834: ipmx +=1;
3835: sw += weight[i];
3836: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3837: } /* end of wave */
3838: } /* end of individual */
3839: } else if(mle==3){ /* exponential inter-extrapolation */
3840: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3841: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3842: for(mi=1; mi<= wav[i]-1; mi++){
3843: for (ii=1;ii<=nlstate+ndeath;ii++)
3844: for (j=1;j<=nlstate+ndeath;j++){
3845: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3846: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3847: }
3848: for(d=0; d<dh[mi][i]; d++){
3849: newm=savm;
3850: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3851: cov[2]=agexact;
3852: if(nagesqr==1)
3853: cov[3]= agexact*agexact;
3854: for (kk=1; kk<=cptcovage;kk++) {
3855: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3856: }
3857: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3858: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3859: savm=oldm;
3860: oldm=newm;
3861: } /* end mult */
3862:
3863: s1=s[mw[mi][i]][i];
3864: s2=s[mw[mi+1][i]][i];
3865: bbh=(double)bh[mi][i]/(double)stepm;
3866: 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 */
3867: ipmx +=1;
3868: sw += weight[i];
3869: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3870: } /* end of wave */
3871: } /* end of individual */
3872: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3873: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3874: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3875: for(mi=1; mi<= wav[i]-1; mi++){
3876: for (ii=1;ii<=nlstate+ndeath;ii++)
3877: for (j=1;j<=nlstate+ndeath;j++){
3878: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3879: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3880: }
3881: for(d=0; d<dh[mi][i]; d++){
3882: newm=savm;
3883: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3884: cov[2]=agexact;
3885: if(nagesqr==1)
3886: cov[3]= agexact*agexact;
3887: for (kk=1; kk<=cptcovage;kk++) {
3888: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3889: }
1.126 brouard 3890:
1.226 brouard 3891: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3892: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3893: savm=oldm;
3894: oldm=newm;
3895: } /* end mult */
3896:
3897: s1=s[mw[mi][i]][i];
3898: s2=s[mw[mi+1][i]][i];
3899: if( s2 > nlstate){
3900: lli=log(out[s1][s2] - savm[s1][s2]);
3901: } else if ( s2==-1 ) { /* alive */
3902: for (j=1,survp=0. ; j<=nlstate; j++)
3903: survp += out[s1][j];
3904: lli= log(survp);
3905: }else{
3906: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3907: }
3908: ipmx +=1;
3909: sw += weight[i];
3910: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3911: /* 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 3912: } /* end of wave */
3913: } /* end of individual */
3914: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3915: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3916: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3917: for(mi=1; mi<= wav[i]-1; mi++){
3918: for (ii=1;ii<=nlstate+ndeath;ii++)
3919: for (j=1;j<=nlstate+ndeath;j++){
3920: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3921: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3922: }
3923: for(d=0; d<dh[mi][i]; d++){
3924: newm=savm;
3925: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3926: cov[2]=agexact;
3927: if(nagesqr==1)
3928: cov[3]= agexact*agexact;
3929: for (kk=1; kk<=cptcovage;kk++) {
3930: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3931: }
1.126 brouard 3932:
1.226 brouard 3933: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3934: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3935: savm=oldm;
3936: oldm=newm;
3937: } /* end mult */
3938:
3939: s1=s[mw[mi][i]][i];
3940: s2=s[mw[mi+1][i]][i];
3941: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3942: ipmx +=1;
3943: sw += weight[i];
3944: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3945: /*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]);*/
3946: } /* end of wave */
3947: } /* end of individual */
3948: } /* End of if */
3949: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3950: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3951: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3952: return -l;
1.126 brouard 3953: }
3954:
3955: /*************** log-likelihood *************/
3956: double funcone( double *x)
3957: {
1.228 brouard 3958: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3959: int i, ii, j, k, mi, d, kk;
1.228 brouard 3960: int ioffset=0;
1.131 brouard 3961: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3962: double **out;
3963: double lli; /* Individual log likelihood */
3964: double llt;
3965: int s1, s2;
1.228 brouard 3966: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3967:
1.126 brouard 3968: double bbh, survp;
1.187 brouard 3969: double agexact;
1.214 brouard 3970: double agebegin, ageend;
1.126 brouard 3971: /*extern weight */
3972: /* We are differentiating ll according to initial status */
3973: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3974: /*for(i=1;i<imx;i++)
3975: printf(" %d\n",s[4][i]);
3976: */
3977: cov[1]=1.;
3978:
3979: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3980: ioffset=0;
3981: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3982: /* ioffset=2+nagesqr+cptcovage; */
3983: ioffset=2+nagesqr;
1.232 brouard 3984: /* Fixed */
1.224 brouard 3985: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3986: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 3987: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.232 brouard 3988: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
3989: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3990: /* cov[2+6]=covar[Tvar[6]][i]; */
3991: /* cov[2+6]=covar[2][i]; V2 */
3992: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3993: /* cov[2+7]=covar[Tvar[7]][i]; */
3994: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3995: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3996: /* cov[2+9]=covar[Tvar[9]][i]; */
3997: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3998: }
1.232 brouard 3999: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4000: /* 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?)*\/ */
4001: /* } */
1.231 brouard 4002: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4003: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4004: /* } */
1.225 brouard 4005:
1.233 brouard 4006:
4007: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 4008: /* Wave varying (but not age varying) */
4009: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 4010: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
4011: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4012: }
1.232 brouard 4013: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 4014: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4015: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4016: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4017: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4018: /* 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]); */
1.232 brouard 4019: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4020: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4021: /* /\* 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]); *\/ */
4022: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4023: /* } */
1.126 brouard 4024: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4025: for (j=1;j<=nlstate+ndeath;j++){
4026: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4027: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4028: }
1.214 brouard 4029:
4030: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4031: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4032: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4033: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4034: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4035: and mw[mi+1][i]. dh depends on stepm.*/
4036: newm=savm;
1.247 brouard 4037: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4038: cov[2]=agexact;
4039: if(nagesqr==1)
4040: cov[3]= agexact*agexact;
4041: for (kk=1; kk<=cptcovage;kk++) {
4042: if(!FixedV[Tvar[Tage[kk]]])
4043: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4044: else
4045: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
4046: }
4047: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4048: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4049: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4050: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4051: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4052: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4053: savm=oldm;
4054: oldm=newm;
1.126 brouard 4055: } /* end mult */
4056:
4057: s1=s[mw[mi][i]][i];
4058: s2=s[mw[mi+1][i]][i];
1.217 brouard 4059: /* if(s2==-1){ */
1.268 brouard 4060: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4061: /* /\* exit(1); *\/ */
4062: /* } */
1.126 brouard 4063: bbh=(double)bh[mi][i]/(double)stepm;
4064: /* bias is positive if real duration
4065: * is higher than the multiple of stepm and negative otherwise.
4066: */
4067: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4068: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4069: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4070: for (j=1,survp=0. ; j<=nlstate; j++)
4071: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4072: lli= log(survp);
1.126 brouard 4073: }else if (mle==1){
1.242 brouard 4074: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4075: } else if(mle==2){
1.242 brouard 4076: 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 4077: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4078: 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 4079: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4080: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4081: } else{ /* mle=0 back to 1 */
1.242 brouard 4082: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4083: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4084: } /* End of if */
4085: ipmx +=1;
4086: sw += weight[i];
4087: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 4088: /*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]); */
1.126 brouard 4089: if(globpr){
1.246 brouard 4090: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4091: %11.6f %11.6f %11.6f ", \
1.242 brouard 4092: 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 4093: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 4094: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4095: llt +=ll[k]*gipmx/gsw;
4096: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
4097: }
4098: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 4099: }
1.232 brouard 4100: } /* end of wave */
4101: } /* end of individual */
4102: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4103: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4104: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4105: if(globpr==0){ /* First time we count the contributions and weights */
4106: gipmx=ipmx;
4107: gsw=sw;
4108: }
4109: return -l;
1.126 brouard 4110: }
4111:
4112:
4113: /*************** function likelione ***********/
1.292 brouard 4114: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4115: {
4116: /* This routine should help understanding what is done with
4117: the selection of individuals/waves and
4118: to check the exact contribution to the likelihood.
4119: Plotting could be done.
4120: */
4121: int k;
4122:
4123: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4124: strcpy(fileresilk,"ILK_");
1.202 brouard 4125: strcat(fileresilk,fileresu);
1.126 brouard 4126: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4127: printf("Problem with resultfile: %s\n", fileresilk);
4128: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4129: }
1.214 brouard 4130: 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");
4131: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4132: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4133: for(k=1; k<=nlstate; k++)
4134: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4135: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4136: }
4137:
1.292 brouard 4138: *fretone=(*func)(p);
1.126 brouard 4139: if(*globpri !=0){
4140: fclose(ficresilk);
1.205 brouard 4141: if (mle ==0)
4142: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4143: else if(mle >=1)
4144: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4145: 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 4146: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4147:
4148: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4149: 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 4150: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4151: }
1.207 brouard 4152: 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 4153: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4154: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4155: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4156: fflush(fichtm);
1.205 brouard 4157: }
1.126 brouard 4158: return;
4159: }
4160:
4161:
4162: /*********** Maximum Likelihood Estimation ***************/
4163:
4164: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4165: {
1.319 brouard 4166: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4167: double **xi;
4168: double fret;
4169: double fretone; /* Only one call to likelihood */
4170: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4171:
4172: #ifdef NLOPT
4173: int creturn;
4174: nlopt_opt opt;
4175: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4176: double *lb;
4177: double minf; /* the minimum objective value, upon return */
4178: double * p1; /* Shifted parameters from 0 instead of 1 */
4179: myfunc_data dinst, *d = &dinst;
4180: #endif
4181:
4182:
1.126 brouard 4183: xi=matrix(1,npar,1,npar);
4184: for (i=1;i<=npar;i++)
4185: for (j=1;j<=npar;j++)
4186: xi[i][j]=(i==j ? 1.0 : 0.0);
4187: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4188: strcpy(filerespow,"POW_");
1.126 brouard 4189: strcat(filerespow,fileres);
4190: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4191: printf("Problem with resultfile: %s\n", filerespow);
4192: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4193: }
4194: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4195: for (i=1;i<=nlstate;i++)
4196: for(j=1;j<=nlstate+ndeath;j++)
4197: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4198: fprintf(ficrespow,"\n");
1.162 brouard 4199: #ifdef POWELL
1.319 brouard 4200: #ifdef LINMINORIGINAL
4201: #else /* LINMINORIGINAL */
4202:
4203: flatdir=ivector(1,npar);
4204: for (j=1;j<=npar;j++) flatdir[j]=0;
4205: #endif /*LINMINORIGINAL */
4206:
4207: #ifdef FLATSUP
4208: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4209: /* reorganizing p by suppressing flat directions */
4210: for(i=1, jk=1; i <=nlstate; i++){
4211: for(k=1; k <=(nlstate+ndeath); k++){
4212: if (k != i) {
4213: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4214: if(flatdir[jk]==1){
4215: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4216: }
4217: for(j=1; j <=ncovmodel; j++){
4218: printf("%12.7f ",p[jk]);
4219: jk++;
4220: }
4221: printf("\n");
4222: }
4223: }
4224: }
4225: /* skipping */
4226: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4227: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4228: for(k=1; k <=(nlstate+ndeath); k++){
4229: if (k != i) {
4230: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4231: if(flatdir[jk]==1){
4232: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4233: for(j=1; j <=ncovmodel; jk++,j++){
4234: printf(" p[%d]=%12.7f",jk, p[jk]);
4235: /*q[jjk]=p[jk];*/
4236: }
4237: }else{
4238: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4239: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4240: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4241: /*q[jjk]=p[jk];*/
4242: }
4243: }
4244: printf("\n");
4245: }
4246: fflush(stdout);
4247: }
4248: }
4249: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4250: #else /* FLATSUP */
1.126 brouard 4251: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4252: #endif /* FLATSUP */
4253:
4254: #ifdef LINMINORIGINAL
4255: #else
4256: free_ivector(flatdir,1,npar);
4257: #endif /* LINMINORIGINAL*/
4258: #endif /* POWELL */
1.126 brouard 4259:
1.162 brouard 4260: #ifdef NLOPT
4261: #ifdef NEWUOA
4262: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4263: #else
4264: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4265: #endif
4266: lb=vector(0,npar-1);
4267: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4268: nlopt_set_lower_bounds(opt, lb);
4269: nlopt_set_initial_step1(opt, 0.1);
4270:
4271: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4272: d->function = func;
4273: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4274: nlopt_set_min_objective(opt, myfunc, d);
4275: nlopt_set_xtol_rel(opt, ftol);
4276: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4277: printf("nlopt failed! %d\n",creturn);
4278: }
4279: else {
4280: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4281: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4282: iter=1; /* not equal */
4283: }
4284: nlopt_destroy(opt);
4285: #endif
1.319 brouard 4286: #ifdef FLATSUP
4287: /* npared = npar -flatd/ncovmodel; */
4288: /* xired= matrix(1,npared,1,npared); */
4289: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4290: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4291: /* free_matrix(xire,1,npared,1,npared); */
4292: #else /* FLATSUP */
4293: #endif /* FLATSUP */
1.126 brouard 4294: free_matrix(xi,1,npar,1,npar);
4295: fclose(ficrespow);
1.203 brouard 4296: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4297: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4298: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4299:
4300: }
4301:
4302: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4303: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4304: {
4305: double **a,**y,*x,pd;
1.203 brouard 4306: /* double **hess; */
1.164 brouard 4307: int i, j;
1.126 brouard 4308: int *indx;
4309:
4310: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4311: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4312: void lubksb(double **a, int npar, int *indx, double b[]) ;
4313: void ludcmp(double **a, int npar, int *indx, double *d) ;
4314: double gompertz(double p[]);
1.203 brouard 4315: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4316:
4317: printf("\nCalculation of the hessian matrix. Wait...\n");
4318: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4319: for (i=1;i<=npar;i++){
1.203 brouard 4320: printf("%d-",i);fflush(stdout);
4321: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4322:
4323: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4324:
4325: /* printf(" %f ",p[i]);
4326: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4327: }
4328:
4329: for (i=1;i<=npar;i++) {
4330: for (j=1;j<=npar;j++) {
4331: if (j>i) {
1.203 brouard 4332: printf(".%d-%d",i,j);fflush(stdout);
4333: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4334: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4335:
4336: hess[j][i]=hess[i][j];
4337: /*printf(" %lf ",hess[i][j]);*/
4338: }
4339: }
4340: }
4341: printf("\n");
4342: fprintf(ficlog,"\n");
4343:
4344: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4345: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4346:
4347: a=matrix(1,npar,1,npar);
4348: y=matrix(1,npar,1,npar);
4349: x=vector(1,npar);
4350: indx=ivector(1,npar);
4351: for (i=1;i<=npar;i++)
4352: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4353: ludcmp(a,npar,indx,&pd);
4354:
4355: for (j=1;j<=npar;j++) {
4356: for (i=1;i<=npar;i++) x[i]=0;
4357: x[j]=1;
4358: lubksb(a,npar,indx,x);
4359: for (i=1;i<=npar;i++){
4360: matcov[i][j]=x[i];
4361: }
4362: }
4363:
4364: printf("\n#Hessian matrix#\n");
4365: fprintf(ficlog,"\n#Hessian matrix#\n");
4366: for (i=1;i<=npar;i++) {
4367: for (j=1;j<=npar;j++) {
1.203 brouard 4368: printf("%.6e ",hess[i][j]);
4369: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4370: }
4371: printf("\n");
4372: fprintf(ficlog,"\n");
4373: }
4374:
1.203 brouard 4375: /* printf("\n#Covariance matrix#\n"); */
4376: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4377: /* for (i=1;i<=npar;i++) { */
4378: /* for (j=1;j<=npar;j++) { */
4379: /* printf("%.6e ",matcov[i][j]); */
4380: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4381: /* } */
4382: /* printf("\n"); */
4383: /* fprintf(ficlog,"\n"); */
4384: /* } */
4385:
1.126 brouard 4386: /* Recompute Inverse */
1.203 brouard 4387: /* for (i=1;i<=npar;i++) */
4388: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4389: /* ludcmp(a,npar,indx,&pd); */
4390:
4391: /* printf("\n#Hessian matrix recomputed#\n"); */
4392:
4393: /* for (j=1;j<=npar;j++) { */
4394: /* for (i=1;i<=npar;i++) x[i]=0; */
4395: /* x[j]=1; */
4396: /* lubksb(a,npar,indx,x); */
4397: /* for (i=1;i<=npar;i++){ */
4398: /* y[i][j]=x[i]; */
4399: /* printf("%.3e ",y[i][j]); */
4400: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4401: /* } */
4402: /* printf("\n"); */
4403: /* fprintf(ficlog,"\n"); */
4404: /* } */
4405:
4406: /* Verifying the inverse matrix */
4407: #ifdef DEBUGHESS
4408: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4409:
1.203 brouard 4410: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4411: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4412:
4413: for (j=1;j<=npar;j++) {
4414: for (i=1;i<=npar;i++){
1.203 brouard 4415: printf("%.2f ",y[i][j]);
4416: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4417: }
4418: printf("\n");
4419: fprintf(ficlog,"\n");
4420: }
1.203 brouard 4421: #endif
1.126 brouard 4422:
4423: free_matrix(a,1,npar,1,npar);
4424: free_matrix(y,1,npar,1,npar);
4425: free_vector(x,1,npar);
4426: free_ivector(indx,1,npar);
1.203 brouard 4427: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4428:
4429:
4430: }
4431:
4432: /*************** hessian matrix ****************/
4433: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4434: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4435: int i;
4436: int l=1, lmax=20;
1.203 brouard 4437: double k1,k2, res, fx;
1.132 brouard 4438: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4439: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4440: int k=0,kmax=10;
4441: double l1;
4442:
4443: fx=func(x);
4444: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4445: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4446: l1=pow(10,l);
4447: delts=delt;
4448: for(k=1 ; k <kmax; k=k+1){
4449: delt = delta*(l1*k);
4450: p2[theta]=x[theta] +delt;
1.145 brouard 4451: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4452: p2[theta]=x[theta]-delt;
4453: k2=func(p2)-fx;
4454: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4455: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4456:
1.203 brouard 4457: #ifdef DEBUGHESSII
1.126 brouard 4458: 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);
4459: 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);
4460: #endif
4461: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4462: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4463: k=kmax;
4464: }
4465: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4466: k=kmax; l=lmax*10;
1.126 brouard 4467: }
4468: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4469: delts=delt;
4470: }
1.203 brouard 4471: } /* End loop k */
1.126 brouard 4472: }
4473: delti[theta]=delts;
4474: return res;
4475:
4476: }
4477:
1.203 brouard 4478: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4479: {
4480: int i;
1.164 brouard 4481: int l=1, lmax=20;
1.126 brouard 4482: double k1,k2,k3,k4,res,fx;
1.132 brouard 4483: double p2[MAXPARM+1];
1.203 brouard 4484: int k, kmax=1;
4485: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4486:
4487: int firstime=0;
1.203 brouard 4488:
1.126 brouard 4489: fx=func(x);
1.203 brouard 4490: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4491: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4492: p2[thetai]=x[thetai]+delti[thetai]*k;
4493: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4494: k1=func(p2)-fx;
4495:
1.203 brouard 4496: p2[thetai]=x[thetai]+delti[thetai]*k;
4497: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4498: k2=func(p2)-fx;
4499:
1.203 brouard 4500: p2[thetai]=x[thetai]-delti[thetai]*k;
4501: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4502: k3=func(p2)-fx;
4503:
1.203 brouard 4504: p2[thetai]=x[thetai]-delti[thetai]*k;
4505: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4506: k4=func(p2)-fx;
1.203 brouard 4507: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4508: if(k1*k2*k3*k4 <0.){
1.208 brouard 4509: firstime=1;
1.203 brouard 4510: kmax=kmax+10;
1.208 brouard 4511: }
4512: if(kmax >=10 || firstime ==1){
1.246 brouard 4513: 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);
4514: 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 4515: 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);
4516: 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);
4517: }
4518: #ifdef DEBUGHESSIJ
4519: v1=hess[thetai][thetai];
4520: v2=hess[thetaj][thetaj];
4521: cv12=res;
4522: /* Computing eigen value of Hessian matrix */
4523: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4524: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4525: if ((lc2 <0) || (lc1 <0) ){
4526: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4527: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4528: 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);
4529: 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);
4530: }
1.126 brouard 4531: #endif
4532: }
4533: return res;
4534: }
4535:
1.203 brouard 4536: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4537: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4538: /* { */
4539: /* int i; */
4540: /* int l=1, lmax=20; */
4541: /* double k1,k2,k3,k4,res,fx; */
4542: /* double p2[MAXPARM+1]; */
4543: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4544: /* int k=0,kmax=10; */
4545: /* double l1; */
4546:
4547: /* fx=func(x); */
4548: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4549: /* l1=pow(10,l); */
4550: /* delts=delt; */
4551: /* for(k=1 ; k <kmax; k=k+1){ */
4552: /* delt = delti*(l1*k); */
4553: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4554: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4555: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4556: /* k1=func(p2)-fx; */
4557:
4558: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4559: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4560: /* k2=func(p2)-fx; */
4561:
4562: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4563: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4564: /* k3=func(p2)-fx; */
4565:
4566: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4567: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4568: /* k4=func(p2)-fx; */
4569: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4570: /* #ifdef DEBUGHESSIJ */
4571: /* 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); */
4572: /* 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); */
4573: /* #endif */
4574: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4575: /* k=kmax; */
4576: /* } */
4577: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4578: /* k=kmax; l=lmax*10; */
4579: /* } */
4580: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4581: /* delts=delt; */
4582: /* } */
4583: /* } /\* End loop k *\/ */
4584: /* } */
4585: /* delti[theta]=delts; */
4586: /* return res; */
4587: /* } */
4588:
4589:
1.126 brouard 4590: /************** Inverse of matrix **************/
4591: void ludcmp(double **a, int n, int *indx, double *d)
4592: {
4593: int i,imax,j,k;
4594: double big,dum,sum,temp;
4595: double *vv;
4596:
4597: vv=vector(1,n);
4598: *d=1.0;
4599: for (i=1;i<=n;i++) {
4600: big=0.0;
4601: for (j=1;j<=n;j++)
4602: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4603: if (big == 0.0){
4604: printf(" Singular Hessian matrix at row %d:\n",i);
4605: for (j=1;j<=n;j++) {
4606: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4607: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4608: }
4609: fflush(ficlog);
4610: fclose(ficlog);
4611: nrerror("Singular matrix in routine ludcmp");
4612: }
1.126 brouard 4613: vv[i]=1.0/big;
4614: }
4615: for (j=1;j<=n;j++) {
4616: for (i=1;i<j;i++) {
4617: sum=a[i][j];
4618: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4619: a[i][j]=sum;
4620: }
4621: big=0.0;
4622: for (i=j;i<=n;i++) {
4623: sum=a[i][j];
4624: for (k=1;k<j;k++)
4625: sum -= a[i][k]*a[k][j];
4626: a[i][j]=sum;
4627: if ( (dum=vv[i]*fabs(sum)) >= big) {
4628: big=dum;
4629: imax=i;
4630: }
4631: }
4632: if (j != imax) {
4633: for (k=1;k<=n;k++) {
4634: dum=a[imax][k];
4635: a[imax][k]=a[j][k];
4636: a[j][k]=dum;
4637: }
4638: *d = -(*d);
4639: vv[imax]=vv[j];
4640: }
4641: indx[j]=imax;
4642: if (a[j][j] == 0.0) a[j][j]=TINY;
4643: if (j != n) {
4644: dum=1.0/(a[j][j]);
4645: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4646: }
4647: }
4648: free_vector(vv,1,n); /* Doesn't work */
4649: ;
4650: }
4651:
4652: void lubksb(double **a, int n, int *indx, double b[])
4653: {
4654: int i,ii=0,ip,j;
4655: double sum;
4656:
4657: for (i=1;i<=n;i++) {
4658: ip=indx[i];
4659: sum=b[ip];
4660: b[ip]=b[i];
4661: if (ii)
4662: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4663: else if (sum) ii=i;
4664: b[i]=sum;
4665: }
4666: for (i=n;i>=1;i--) {
4667: sum=b[i];
4668: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4669: b[i]=sum/a[i][i];
4670: }
4671: }
4672:
4673: void pstamp(FILE *fichier)
4674: {
1.196 brouard 4675: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4676: }
4677:
1.297 brouard 4678: void date2dmy(double date,double *day, double *month, double *year){
4679: double yp=0., yp1=0., yp2=0.;
4680:
4681: yp1=modf(date,&yp);/* extracts integral of date in yp and
4682: fractional in yp1 */
4683: *year=yp;
4684: yp2=modf((yp1*12),&yp);
4685: *month=yp;
4686: yp1=modf((yp2*30.5),&yp);
4687: *day=yp;
4688: if(*day==0) *day=1;
4689: if(*month==0) *month=1;
4690: }
4691:
1.253 brouard 4692:
4693:
1.126 brouard 4694: /************ Frequencies ********************/
1.251 brouard 4695: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4696: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4697: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4698: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4699:
1.265 brouard 4700: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4701: int iind=0, iage=0;
4702: int mi; /* Effective wave */
4703: int first;
4704: double ***freq; /* Frequencies */
1.268 brouard 4705: 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 */
4706: 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 4707: double *meanq, *stdq, *idq;
1.226 brouard 4708: double **meanqt;
4709: double *pp, **prop, *posprop, *pospropt;
4710: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4711: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4712: double agebegin, ageend;
4713:
4714: pp=vector(1,nlstate);
1.251 brouard 4715: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4716: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4717: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4718: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4719: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4720: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4721: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4722: meanqt=matrix(1,lastpass,1,nqtveff);
4723: strcpy(fileresp,"P_");
4724: strcat(fileresp,fileresu);
4725: /*strcat(fileresphtm,fileresu);*/
4726: if((ficresp=fopen(fileresp,"w"))==NULL) {
4727: printf("Problem with prevalence resultfile: %s\n", fileresp);
4728: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4729: exit(0);
4730: }
1.240 brouard 4731:
1.226 brouard 4732: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4733: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4734: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4735: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4736: fflush(ficlog);
4737: exit(70);
4738: }
4739: else{
4740: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4741: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4742: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4743: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4744: }
1.319 brouard 4745: 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 4746:
1.226 brouard 4747: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4748: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4749: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4750: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4751: fflush(ficlog);
4752: exit(70);
1.240 brouard 4753: } else{
1.226 brouard 4754: 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 4755: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4756: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4757: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4758: }
1.319 brouard 4759: 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 4760:
1.253 brouard 4761: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4762: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4763: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4764: j1=0;
1.126 brouard 4765:
1.227 brouard 4766: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4767: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4768: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4769:
4770:
1.226 brouard 4771: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4772: reference=low_education V1=0,V2=0
4773: med_educ V1=1 V2=0,
4774: high_educ V1=0 V2=1
4775: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4776: */
1.249 brouard 4777: dateintsum=0;
4778: k2cpt=0;
4779:
1.253 brouard 4780: if(cptcoveff == 0 )
1.265 brouard 4781: nl=1; /* Constant and age model only */
1.253 brouard 4782: else
4783: nl=2;
1.265 brouard 4784:
4785: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4786: /* Loop on nj=1 or 2 if dummy covariates j!=0
4787: * Loop on j1(1 to 2**cptcoveff) covariate combination
4788: * freq[s1][s2][iage] =0.
4789: * Loop on iind
4790: * ++freq[s1][s2][iage] weighted
4791: * end iind
4792: * if covariate and j!0
4793: * headers Variable on one line
4794: * endif cov j!=0
4795: * header of frequency table by age
4796: * Loop on age
4797: * pp[s1]+=freq[s1][s2][iage] weighted
4798: * pos+=freq[s1][s2][iage] weighted
4799: * Loop on s1 initial state
4800: * fprintf(ficresp
4801: * end s1
4802: * end age
4803: * if j!=0 computes starting values
4804: * end compute starting values
4805: * end j1
4806: * end nl
4807: */
1.253 brouard 4808: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4809: if(nj==1)
4810: j=0; /* First pass for the constant */
1.265 brouard 4811: else{
1.253 brouard 4812: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4813: }
1.251 brouard 4814: first=1;
1.265 brouard 4815: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all covariates combination of the model, excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
1.251 brouard 4816: posproptt=0.;
4817: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4818: scanf("%d", i);*/
4819: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4820: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4821: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4822: freq[i][s2][m]=0;
1.251 brouard 4823:
4824: for (i=1; i<=nlstate; i++) {
1.240 brouard 4825: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4826: prop[i][m]=0;
4827: posprop[i]=0;
4828: pospropt[i]=0;
4829: }
1.283 brouard 4830: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4831: idq[z1]=0.;
4832: meanq[z1]=0.;
4833: stdq[z1]=0.;
1.283 brouard 4834: }
4835: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4836: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4837: /* meanqt[m][z1]=0.; */
4838: /* } */
4839: /* } */
1.251 brouard 4840: /* dateintsum=0; */
4841: /* k2cpt=0; */
4842:
1.265 brouard 4843: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4844: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4845: bool=1;
4846: if(j !=0){
4847: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4848: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4849: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4850: /* if(Tvaraff[z1] ==-20){ */
4851: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4852: /* }else if(Tvaraff[z1] ==-10){ */
4853: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4854: /* }else */
4855: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4856: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4857: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4858: /* 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",
4859: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4860: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4861: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4862: } /* Onlyf fixed */
4863: } /* end z1 */
4864: } /* cptcovn > 0 */
4865: } /* end any */
4866: }/* end j==0 */
1.265 brouard 4867: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4868: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4869: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4870: m=mw[mi][iind];
4871: if(j!=0){
4872: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4873: for (z1=1; z1<=cptcoveff; z1++) {
4874: if( Fixed[Tmodelind[z1]]==1){
4875: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4876: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4877: value is -1, we don't select. It differs from the
4878: constant and age model which counts them. */
4879: bool=0; /* not selected */
4880: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4881: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4882: bool=0;
4883: }
4884: }
4885: }
4886: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4887: } /* end j==0 */
4888: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4889: if(bool==1){ /*Selected */
1.251 brouard 4890: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4891: and mw[mi+1][iind]. dh depends on stepm. */
4892: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4893: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4894: if(m >=firstpass && m <=lastpass){
4895: k2=anint[m][iind]+(mint[m][iind]/12.);
4896: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4897: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4898: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4899: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4900: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4901: if (m<lastpass) {
4902: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4903: /* 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]); */
4904: if(s[m][iind]==-1)
4905: 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.));
4906: 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 4907: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
4908: if(!isnan(covar[ncovcol+z1][iind])){
4909: idq[z1]=idq[z1]+weight[iind];
4910: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4911: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
4912: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4913: }
1.284 brouard 4914: }
1.251 brouard 4915: /* if((int)agev[m][iind] == 55) */
4916: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4917: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4918: 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 4919: }
1.251 brouard 4920: } /* end if between passes */
4921: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4922: dateintsum=dateintsum+k2; /* on all covariates ?*/
4923: k2cpt++;
4924: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4925: }
1.251 brouard 4926: }else{
4927: bool=1;
4928: }/* end bool 2 */
4929: } /* end m */
1.284 brouard 4930: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4931: /* idq[z1]=idq[z1]+weight[iind]; */
4932: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4933: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4934: /* } */
1.251 brouard 4935: } /* end bool */
4936: } /* end iind = 1 to imx */
1.319 brouard 4937: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 4938: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4939:
4940:
4941: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4942: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4943: pstamp(ficresp);
1.251 brouard 4944: if (cptcoveff>0 && j!=0){
1.265 brouard 4945: pstamp(ficresp);
1.251 brouard 4946: printf( "\n#********** Variable ");
4947: fprintf(ficresp, "\n#********** Variable ");
4948: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4949: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4950: fprintf(ficlog, "\n#********** Variable ");
4951: for (z1=1; z1<=cptcoveff; z1++){
4952: if(!FixedV[Tvaraff[z1]]){
4953: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4954: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4955: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4956: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4957: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4958: }else{
1.251 brouard 4959: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4960: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4961: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4962: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4963: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4964: }
4965: }
4966: printf( "**********\n#");
4967: fprintf(ficresp, "**********\n#");
4968: fprintf(ficresphtm, "**********</h3>\n");
4969: fprintf(ficresphtmfr, "**********</h3>\n");
4970: fprintf(ficlog, "**********\n");
4971: }
1.284 brouard 4972: /*
4973: Printing means of quantitative variables if any
4974: */
4975: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 4976: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 4977: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 4978: if(weightopt==1){
4979: printf(" Weighted mean and standard deviation of");
4980: fprintf(ficlog," Weighted mean and standard deviation of");
4981: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4982: }
1.311 brouard 4983: /* mu = \frac{w x}{\sum w}
4984: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
4985: */
4986: 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]));
4987: 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]));
4988: 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 4989: }
4990: /* for (z1=1; z1<= nqtveff; z1++) { */
4991: /* for(m=1;m<=lastpass;m++){ */
4992: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4993: /* } */
4994: /* } */
1.283 brouard 4995:
1.251 brouard 4996: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4997: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4998: fprintf(ficresp, " Age");
4999: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.251 brouard 5000: for(i=1; i<=nlstate;i++) {
1.265 brouard 5001: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5002: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5003: }
1.265 brouard 5004: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5005: fprintf(ficresphtm, "\n");
5006:
5007: /* Header of frequency table by age */
5008: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5009: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5010: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5011: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5012: if(s2!=0 && m!=0)
5013: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5014: }
1.226 brouard 5015: }
1.251 brouard 5016: fprintf(ficresphtmfr, "\n");
5017:
5018: /* For each age */
5019: for(iage=iagemin; iage <= iagemax+3; iage++){
5020: fprintf(ficresphtm,"<tr>");
5021: if(iage==iagemax+1){
5022: fprintf(ficlog,"1");
5023: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5024: }else if(iage==iagemax+2){
5025: fprintf(ficlog,"0");
5026: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5027: }else if(iage==iagemax+3){
5028: fprintf(ficlog,"Total");
5029: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5030: }else{
1.240 brouard 5031: if(first==1){
1.251 brouard 5032: first=0;
5033: printf("See log file for details...\n");
5034: }
5035: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5036: fprintf(ficlog,"Age %d", iage);
5037: }
1.265 brouard 5038: for(s1=1; s1 <=nlstate ; s1++){
5039: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5040: pp[s1] += freq[s1][m][iage];
1.251 brouard 5041: }
1.265 brouard 5042: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5043: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5044: pos += freq[s1][m][iage];
5045: if(pp[s1]>=1.e-10){
1.251 brouard 5046: if(first==1){
1.265 brouard 5047: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5048: }
1.265 brouard 5049: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5050: }else{
5051: if(first==1)
1.265 brouard 5052: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5053: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5054: }
5055: }
5056:
1.265 brouard 5057: for(s1=1; s1 <=nlstate ; s1++){
5058: /* posprop[s1]=0; */
5059: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5060: pp[s1] += freq[s1][m][iage];
5061: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5062:
5063: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5064: pos += pp[s1]; /* pos is the total number of transitions until this age */
5065: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5066: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5067: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5068: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5069: }
5070:
5071: /* Writing ficresp */
5072: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5073: if( iage <= iagemax){
5074: fprintf(ficresp," %d",iage);
5075: }
5076: }else if( nj==2){
5077: if( iage <= iagemax){
5078: fprintf(ficresp," %d",iage);
5079: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
5080: }
1.240 brouard 5081: }
1.265 brouard 5082: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5083: if(pos>=1.e-5){
1.251 brouard 5084: if(first==1)
1.265 brouard 5085: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5086: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5087: }else{
5088: if(first==1)
1.265 brouard 5089: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5090: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5091: }
5092: if( iage <= iagemax){
5093: if(pos>=1.e-5){
1.265 brouard 5094: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5095: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5096: }else if( nj==2){
5097: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5098: }
5099: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5100: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5101: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5102: } else{
5103: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
5104: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5105: }
1.240 brouard 5106: }
1.265 brouard 5107: pospropt[s1] +=posprop[s1];
5108: } /* end loop s1 */
1.251 brouard 5109: /* pospropt=0.; */
1.265 brouard 5110: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5111: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5112: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5113: if(first==1){
1.265 brouard 5114: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5115: }
1.265 brouard 5116: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5117: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5118: }
1.265 brouard 5119: if(s1!=0 && m!=0)
5120: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5121: }
1.265 brouard 5122: } /* end loop s1 */
1.251 brouard 5123: posproptt=0.;
1.265 brouard 5124: for(s1=1; s1 <=nlstate; s1++){
5125: posproptt += pospropt[s1];
1.251 brouard 5126: }
5127: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5128: fprintf(ficresphtm,"</tr>\n");
5129: if((cptcoveff==0 && nj==1)|| nj==2 ) {
5130: if(iage <= iagemax)
5131: fprintf(ficresp,"\n");
1.240 brouard 5132: }
1.251 brouard 5133: if(first==1)
5134: printf("Others in log...\n");
5135: fprintf(ficlog,"\n");
5136: } /* end loop age iage */
1.265 brouard 5137:
1.251 brouard 5138: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5139: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5140: if(posproptt < 1.e-5){
1.265 brouard 5141: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5142: }else{
1.265 brouard 5143: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5144: }
1.226 brouard 5145: }
1.251 brouard 5146: fprintf(ficresphtm,"</tr>\n");
5147: fprintf(ficresphtm,"</table>\n");
5148: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5149: if(posproptt < 1.e-5){
1.251 brouard 5150: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5151: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5152: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5153: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5154: invalidvarcomb[j1]=1;
1.226 brouard 5155: }else{
1.251 brouard 5156: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
5157: invalidvarcomb[j1]=0;
1.226 brouard 5158: }
1.251 brouard 5159: fprintf(ficresphtmfr,"</table>\n");
5160: fprintf(ficlog,"\n");
5161: if(j!=0){
5162: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5163: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5164: for(k=1; k <=(nlstate+ndeath); k++){
5165: if (k != i) {
1.265 brouard 5166: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5167: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5168: if(j1==1){ /* All dummy covariates to zero */
5169: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5170: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5171: printf("%d%d ",i,k);
5172: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5173: 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]));
5174: 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]));
5175: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5176: }
1.253 brouard 5177: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5178: for(iage=iagemin; iage <= iagemax+3; iage++){
5179: x[iage]= (double)iage;
5180: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5181: /* 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 5182: }
1.268 brouard 5183: /* Some are not finite, but linreg will ignore these ages */
5184: no=0;
1.253 brouard 5185: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5186: pstart[s1]=b;
5187: pstart[s1-1]=a;
1.252 brouard 5188: }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 */
5189: 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]);
5190: 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 5191: 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 5192: printf("%d%d ",i,k);
5193: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5194: 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 5195: }else{ /* Other cases, like quantitative fixed or varying covariates */
5196: ;
5197: }
5198: /* printf("%12.7f )", param[i][jj][k]); */
5199: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5200: s1++;
1.251 brouard 5201: } /* end jj */
5202: } /* end k!= i */
5203: } /* end k */
1.265 brouard 5204: } /* end i, s1 */
1.251 brouard 5205: } /* end j !=0 */
5206: } /* end selected combination of covariate j1 */
5207: if(j==0){ /* We can estimate starting values from the occurences in each case */
5208: printf("#Freqsummary: Starting values for the constants:\n");
5209: fprintf(ficlog,"\n");
1.265 brouard 5210: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5211: for(k=1; k <=(nlstate+ndeath); k++){
5212: if (k != i) {
5213: printf("%d%d ",i,k);
5214: fprintf(ficlog,"%d%d ",i,k);
5215: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5216: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5217: if(jj==1){ /* Age has to be done */
1.265 brouard 5218: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5219: 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]));
5220: 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 5221: }
5222: /* printf("%12.7f )", param[i][jj][k]); */
5223: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5224: s1++;
1.250 brouard 5225: }
1.251 brouard 5226: printf("\n");
5227: fprintf(ficlog,"\n");
1.250 brouard 5228: }
5229: }
1.284 brouard 5230: } /* end of state i */
1.251 brouard 5231: printf("#Freqsummary\n");
5232: fprintf(ficlog,"\n");
1.265 brouard 5233: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5234: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5235: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5236: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5237: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5238: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5239: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5240: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5241: /* } */
5242: }
1.265 brouard 5243: } /* end loop s1 */
1.251 brouard 5244:
5245: printf("\n");
5246: fprintf(ficlog,"\n");
5247: } /* end j=0 */
1.249 brouard 5248: } /* end j */
1.252 brouard 5249:
1.253 brouard 5250: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5251: for(i=1, jk=1; i <=nlstate; i++){
5252: for(j=1; j <=nlstate+ndeath; j++){
5253: if(j!=i){
5254: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5255: printf("%1d%1d",i,j);
5256: fprintf(ficparo,"%1d%1d",i,j);
5257: for(k=1; k<=ncovmodel;k++){
5258: /* printf(" %lf",param[i][j][k]); */
5259: /* fprintf(ficparo," %lf",param[i][j][k]); */
5260: p[jk]=pstart[jk];
5261: printf(" %f ",pstart[jk]);
5262: fprintf(ficparo," %f ",pstart[jk]);
5263: jk++;
5264: }
5265: printf("\n");
5266: fprintf(ficparo,"\n");
5267: }
5268: }
5269: }
5270: } /* end mle=-2 */
1.226 brouard 5271: dateintmean=dateintsum/k2cpt;
1.296 brouard 5272: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5273:
1.226 brouard 5274: fclose(ficresp);
5275: fclose(ficresphtm);
5276: fclose(ficresphtmfr);
1.283 brouard 5277: free_vector(idq,1,nqfveff);
1.226 brouard 5278: free_vector(meanq,1,nqfveff);
1.284 brouard 5279: free_vector(stdq,1,nqfveff);
1.226 brouard 5280: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5281: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5282: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5283: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5284: free_vector(pospropt,1,nlstate);
5285: free_vector(posprop,1,nlstate);
1.251 brouard 5286: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5287: free_vector(pp,1,nlstate);
5288: /* End of freqsummary */
5289: }
1.126 brouard 5290:
1.268 brouard 5291: /* Simple linear regression */
5292: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5293:
5294: /* y=a+bx regression */
5295: double sumx = 0.0; /* sum of x */
5296: double sumx2 = 0.0; /* sum of x**2 */
5297: double sumxy = 0.0; /* sum of x * y */
5298: double sumy = 0.0; /* sum of y */
5299: double sumy2 = 0.0; /* sum of y**2 */
5300: double sume2 = 0.0; /* sum of square or residuals */
5301: double yhat;
5302:
5303: double denom=0;
5304: int i;
5305: int ne=*no;
5306:
5307: for ( i=ifi, ne=0;i<=ila;i++) {
5308: if(!isfinite(x[i]) || !isfinite(y[i])){
5309: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5310: continue;
5311: }
5312: ne=ne+1;
5313: sumx += x[i];
5314: sumx2 += x[i]*x[i];
5315: sumxy += x[i] * y[i];
5316: sumy += y[i];
5317: sumy2 += y[i]*y[i];
5318: denom = (ne * sumx2 - sumx*sumx);
5319: /* 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); */
5320: }
5321:
5322: denom = (ne * sumx2 - sumx*sumx);
5323: if (denom == 0) {
5324: // vertical, slope m is infinity
5325: *b = INFINITY;
5326: *a = 0;
5327: if (r) *r = 0;
5328: return 1;
5329: }
5330:
5331: *b = (ne * sumxy - sumx * sumy) / denom;
5332: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5333: if (r!=NULL) {
5334: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5335: sqrt((sumx2 - sumx*sumx/ne) *
5336: (sumy2 - sumy*sumy/ne));
5337: }
5338: *no=ne;
5339: for ( i=ifi, ne=0;i<=ila;i++) {
5340: if(!isfinite(x[i]) || !isfinite(y[i])){
5341: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5342: continue;
5343: }
5344: ne=ne+1;
5345: yhat = y[i] - *a -*b* x[i];
5346: sume2 += yhat * yhat ;
5347:
5348: denom = (ne * sumx2 - sumx*sumx);
5349: /* 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); */
5350: }
5351: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5352: *sa= *sb * sqrt(sumx2/ne);
5353:
5354: return 0;
5355: }
5356:
1.126 brouard 5357: /************ Prevalence ********************/
1.227 brouard 5358: 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)
5359: {
5360: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5361: in each health status at the date of interview (if between dateprev1 and dateprev2).
5362: We still use firstpass and lastpass as another selection.
5363: */
1.126 brouard 5364:
1.227 brouard 5365: int i, m, jk, j1, bool, z1,j, iv;
5366: int mi; /* Effective wave */
5367: int iage;
5368: double agebegin, ageend;
5369:
5370: double **prop;
5371: double posprop;
5372: double y2; /* in fractional years */
5373: int iagemin, iagemax;
5374: int first; /** to stop verbosity which is redirected to log file */
5375:
5376: iagemin= (int) agemin;
5377: iagemax= (int) agemax;
5378: /*pp=vector(1,nlstate);*/
1.251 brouard 5379: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5380: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5381: j1=0;
1.222 brouard 5382:
1.227 brouard 5383: /*j=cptcoveff;*/
5384: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5385:
1.288 brouard 5386: first=0;
1.227 brouard 5387: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5388: for (i=1; i<=nlstate; i++)
1.251 brouard 5389: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5390: prop[i][iage]=0.0;
5391: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5392: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5393: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5394:
5395: for (i=1; i<=imx; i++) { /* Each individual */
5396: bool=1;
5397: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5398: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5399: m=mw[mi][i];
5400: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5401: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5402: for (z1=1; z1<=cptcoveff; z1++){
5403: if( Fixed[Tmodelind[z1]]==1){
5404: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5405: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5406: bool=0;
5407: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5408: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5409: bool=0;
5410: }
5411: }
5412: if(bool==1){ /* Otherwise we skip that wave/person */
5413: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5414: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5415: if(m >=firstpass && m <=lastpass){
5416: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5417: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5418: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5419: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5420: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5421: 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);
5422: exit(1);
5423: }
5424: if (s[m][i]>0 && s[m][i]<=nlstate) {
5425: /*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]]);*/
5426: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5427: prop[s[m][i]][iagemax+3] += weight[i];
5428: } /* end valid statuses */
5429: } /* end selection of dates */
5430: } /* end selection of waves */
5431: } /* end bool */
5432: } /* end wave */
5433: } /* end individual */
5434: for(i=iagemin; i <= iagemax+3; i++){
5435: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5436: posprop += prop[jk][i];
5437: }
5438:
5439: for(jk=1; jk <=nlstate ; jk++){
5440: if( i <= iagemax){
5441: if(posprop>=1.e-5){
5442: probs[i][jk][j1]= prop[jk][i]/posprop;
5443: } else{
1.288 brouard 5444: if(!first){
5445: first=1;
1.266 brouard 5446: 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]);
5447: }else{
1.288 brouard 5448: 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 5449: }
5450: }
5451: }
5452: }/* end jk */
5453: }/* end i */
1.222 brouard 5454: /*} *//* end i1 */
1.227 brouard 5455: } /* end j1 */
1.222 brouard 5456:
1.227 brouard 5457: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5458: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5459: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5460: } /* End of prevalence */
1.126 brouard 5461:
5462: /************* Waves Concatenation ***************/
5463:
5464: 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)
5465: {
1.298 brouard 5466: /* 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 5467: Death is a valid wave (if date is known).
5468: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5469: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5470: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5471: */
1.126 brouard 5472:
1.224 brouard 5473: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5474: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5475: double sum=0., jmean=0.;*/
1.224 brouard 5476: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5477: int j, k=0,jk, ju, jl;
5478: double sum=0.;
5479: first=0;
1.214 brouard 5480: firstwo=0;
1.217 brouard 5481: firsthree=0;
1.218 brouard 5482: firstfour=0;
1.164 brouard 5483: jmin=100000;
1.126 brouard 5484: jmax=-1;
5485: jmean=0.;
1.224 brouard 5486:
5487: /* Treating live states */
1.214 brouard 5488: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5489: mi=0; /* First valid wave */
1.227 brouard 5490: mli=0; /* Last valid wave */
1.309 brouard 5491: m=firstpass; /* Loop on waves */
5492: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5493: 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 */
5494: mli=m-1;/* mw[++mi][i]=m-1; */
5495: }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 5496: 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 5497: mli=m;
1.224 brouard 5498: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5499: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5500: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5501: }
1.309 brouard 5502: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5503: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5504: break;
1.224 brouard 5505: #else
1.317 brouard 5506: 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 5507: if(firsthree == 0){
1.302 brouard 5508: 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 5509: firsthree=1;
1.317 brouard 5510: }else if(firsthree >=1 && firsthree < 10){
5511: 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);
5512: firsthree++;
5513: }else if(firsthree == 10){
5514: printf("Information, too many Information flags: no more reported to log either\n");
5515: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5516: firsthree++;
5517: }else{
5518: firsthree++;
1.227 brouard 5519: }
1.309 brouard 5520: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5521: mli=m;
5522: }
5523: if(s[m][i]==-2){ /* Vital status is really unknown */
5524: nbwarn++;
1.309 brouard 5525: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5526: 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);
5527: 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);
5528: }
5529: break;
5530: }
5531: break;
1.224 brouard 5532: #endif
1.227 brouard 5533: }/* End m >= lastpass */
1.126 brouard 5534: }/* end while */
1.224 brouard 5535:
1.227 brouard 5536: /* 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 5537: /* After last pass */
1.224 brouard 5538: /* Treating death states */
1.214 brouard 5539: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5540: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5541: /* } */
1.126 brouard 5542: mi++; /* Death is another wave */
5543: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5544: /* Only death is a correct wave */
1.126 brouard 5545: mw[mi][i]=m;
1.257 brouard 5546: } /* else not in a death state */
1.224 brouard 5547: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5548: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5549: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5550: 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 5551: nbwarn++;
5552: if(firstfiv==0){
1.309 brouard 5553: 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 5554: firstfiv=1;
5555: }else{
1.309 brouard 5556: 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 5557: }
1.309 brouard 5558: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5559: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5560: nberr++;
5561: if(firstwo==0){
1.309 brouard 5562: 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 5563: firstwo=1;
5564: }
1.309 brouard 5565: 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 5566: }
1.257 brouard 5567: }else{ /* if date of interview is unknown */
1.227 brouard 5568: /* death is known but not confirmed by death status at any wave */
5569: if(firstfour==0){
1.309 brouard 5570: 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 5571: firstfour=1;
5572: }
1.309 brouard 5573: 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 5574: }
1.224 brouard 5575: } /* end if date of death is known */
5576: #endif
1.309 brouard 5577: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5578: /* wav[i]=mw[mi][i]; */
1.126 brouard 5579: if(mi==0){
5580: nbwarn++;
5581: if(first==0){
1.227 brouard 5582: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5583: first=1;
1.126 brouard 5584: }
5585: if(first==1){
1.227 brouard 5586: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5587: }
5588: } /* end mi==0 */
5589: } /* End individuals */
1.214 brouard 5590: /* wav and mw are no more changed */
1.223 brouard 5591:
1.317 brouard 5592: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5593: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5594:
5595:
1.126 brouard 5596: for(i=1; i<=imx; i++){
5597: for(mi=1; mi<wav[i];mi++){
5598: if (stepm <=0)
1.227 brouard 5599: dh[mi][i]=1;
1.126 brouard 5600: else{
1.260 brouard 5601: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5602: if (agedc[i] < 2*AGESUP) {
5603: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5604: if(j==0) j=1; /* Survives at least one month after exam */
5605: else if(j<0){
5606: nberr++;
5607: 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]);
5608: j=1; /* Temporary Dangerous patch */
5609: 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);
5610: 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]);
5611: 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);
5612: }
5613: k=k+1;
5614: if (j >= jmax){
5615: jmax=j;
5616: ijmax=i;
5617: }
5618: if (j <= jmin){
5619: jmin=j;
5620: ijmin=i;
5621: }
5622: sum=sum+j;
5623: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5624: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5625: }
5626: }
5627: else{
5628: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5629: /* 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 5630:
1.227 brouard 5631: k=k+1;
5632: if (j >= jmax) {
5633: jmax=j;
5634: ijmax=i;
5635: }
5636: else if (j <= jmin){
5637: jmin=j;
5638: ijmin=i;
5639: }
5640: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5641: /*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]);*/
5642: if(j<0){
5643: nberr++;
5644: 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]);
5645: 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]);
5646: }
5647: sum=sum+j;
5648: }
5649: jk= j/stepm;
5650: jl= j -jk*stepm;
5651: ju= j -(jk+1)*stepm;
5652: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5653: if(jl==0){
5654: dh[mi][i]=jk;
5655: bh[mi][i]=0;
5656: }else{ /* We want a negative bias in order to only have interpolation ie
5657: * to avoid the price of an extra matrix product in likelihood */
5658: dh[mi][i]=jk+1;
5659: bh[mi][i]=ju;
5660: }
5661: }else{
5662: if(jl <= -ju){
5663: dh[mi][i]=jk;
5664: bh[mi][i]=jl; /* bias is positive if real duration
5665: * is higher than the multiple of stepm and negative otherwise.
5666: */
5667: }
5668: else{
5669: dh[mi][i]=jk+1;
5670: bh[mi][i]=ju;
5671: }
5672: if(dh[mi][i]==0){
5673: dh[mi][i]=1; /* At least one step */
5674: bh[mi][i]=ju; /* At least one step */
5675: /* 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);*/
5676: }
5677: } /* end if mle */
1.126 brouard 5678: }
5679: } /* end wave */
5680: }
5681: jmean=sum/k;
5682: 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 5683: 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 5684: }
1.126 brouard 5685:
5686: /*********** Tricode ****************************/
1.220 brouard 5687: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5688: {
5689: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5690: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5691: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5692: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5693: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5694: */
1.130 brouard 5695:
1.242 brouard 5696: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5697: int modmaxcovj=0; /* Modality max of covariates j */
5698: int cptcode=0; /* Modality max of covariates j */
5699: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5700:
5701:
1.242 brouard 5702: /* cptcoveff=0; */
5703: /* *cptcov=0; */
1.126 brouard 5704:
1.242 brouard 5705: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5706: for (k=1; k <= maxncov; k++)
5707: for(j=1; j<=2; j++)
5708: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5709:
1.242 brouard 5710: /* Loop on covariates without age and products and no quantitative variable */
5711: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5712: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5713: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5714: switch(Fixed[k]) {
5715: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5716: modmaxcovj=0;
5717: modmincovj=0;
1.242 brouard 5718: 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*/
5719: ij=(int)(covar[Tvar[k]][i]);
5720: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5721: * If product of Vn*Vm, still boolean *:
5722: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5723: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5724: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5725: modality of the nth covariate of individual i. */
5726: if (ij > modmaxcovj)
5727: modmaxcovj=ij;
5728: else if (ij < modmincovj)
5729: modmincovj=ij;
1.287 brouard 5730: if (ij <0 || ij >1 ){
1.311 brouard 5731: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5732: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5733: fflush(ficlog);
5734: exit(1);
1.287 brouard 5735: }
5736: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5737: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5738: exit(1);
5739: }else
5740: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5741: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5742: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5743: /* getting the maximum value of the modality of the covariate
5744: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5745: female ies 1, then modmaxcovj=1.
5746: */
5747: } /* end for loop on individuals i */
5748: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5749: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5750: cptcode=modmaxcovj;
5751: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5752: /*for (i=0; i<=cptcode; i++) {*/
5753: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5754: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5755: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5756: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5757: if( j != -1){
5758: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5759: covariate for which somebody answered excluding
5760: undefined. Usually 2: 0 and 1. */
5761: }
5762: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5763: covariate for which somebody answered including
5764: undefined. Usually 3: -1, 0 and 1. */
5765: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5766: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5767: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5768:
1.242 brouard 5769: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5770: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5771: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5772: /* modmincovj=3; modmaxcovj = 7; */
5773: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5774: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5775: /* defining two dummy variables: variables V1_1 and V1_2.*/
5776: /* nbcode[Tvar[j]][ij]=k; */
5777: /* nbcode[Tvar[j]][1]=0; */
5778: /* nbcode[Tvar[j]][2]=1; */
5779: /* nbcode[Tvar[j]][3]=2; */
5780: /* To be continued (not working yet). */
5781: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5782:
5783: /* 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*/
5784: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5785: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5786: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5787: /*, could be restored in the future */
5788: 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 5789: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5790: break;
5791: }
5792: ij++;
1.287 brouard 5793: 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 5794: cptcode = ij; /* New max modality for covar j */
5795: } /* end of loop on modality i=-1 to 1 or more */
5796: break;
5797: case 1: /* Testing on varying covariate, could be simple and
5798: * should look at waves or product of fixed *
5799: * varying. No time to test -1, assuming 0 and 1 only */
5800: ij=0;
5801: for(i=0; i<=1;i++){
5802: nbcode[Tvar[k]][++ij]=i;
5803: }
5804: break;
5805: default:
5806: break;
5807: } /* end switch */
5808: } /* end dummy test */
1.311 brouard 5809: if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5810: 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*/
5811: if(isnan(covar[Tvar[k]][i])){
5812: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5813: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5814: fflush(ficlog);
5815: exit(1);
5816: }
5817: }
5818: }
1.287 brouard 5819: } /* 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 5820:
5821: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5822: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5823: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5824: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5825: 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 */
5826: 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 */
5827: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5828: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5829:
5830: ij=0;
5831: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5832: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5833: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5834: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5835: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5836: /* If product not in single variable we don't print results */
5837: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5838: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5839: 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*/
5840: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5841: 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 */
5842: if(Fixed[k]!=0)
5843: anyvaryingduminmodel=1;
5844: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5845: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5846: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5847: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5848: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5849: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5850: }
5851: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5852: /* ij--; */
5853: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5854: *cptcov=ij; /*Number of total real effective covariates: effective
5855: * because they can be excluded from the model and real
5856: * if in the model but excluded because missing values, but how to get k from ij?*/
5857: for(j=ij+1; j<= cptcovt; j++){
5858: Tvaraff[j]=0;
5859: Tmodelind[j]=0;
5860: }
5861: for(j=ntveff+1; j<= cptcovt; j++){
5862: TmodelInvind[j]=0;
5863: }
5864: /* To be sorted */
5865: ;
5866: }
1.126 brouard 5867:
1.145 brouard 5868:
1.126 brouard 5869: /*********** Health Expectancies ****************/
5870:
1.235 brouard 5871: 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 5872:
5873: {
5874: /* Health expectancies, no variances */
1.164 brouard 5875: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5876: int nhstepma, nstepma; /* Decreasing with age */
5877: double age, agelim, hf;
5878: double ***p3mat;
5879: double eip;
5880:
1.238 brouard 5881: /* pstamp(ficreseij); */
1.126 brouard 5882: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5883: fprintf(ficreseij,"# Age");
5884: for(i=1; i<=nlstate;i++){
5885: for(j=1; j<=nlstate;j++){
5886: fprintf(ficreseij," e%1d%1d ",i,j);
5887: }
5888: fprintf(ficreseij," e%1d. ",i);
5889: }
5890: fprintf(ficreseij,"\n");
5891:
5892:
5893: if(estepm < stepm){
5894: printf ("Problem %d lower than %d\n",estepm, stepm);
5895: }
5896: else hstepm=estepm;
5897: /* We compute the life expectancy from trapezoids spaced every estepm months
5898: * This is mainly to measure the difference between two models: for example
5899: * if stepm=24 months pijx are given only every 2 years and by summing them
5900: * we are calculating an estimate of the Life Expectancy assuming a linear
5901: * progression in between and thus overestimating or underestimating according
5902: * to the curvature of the survival function. If, for the same date, we
5903: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5904: * to compare the new estimate of Life expectancy with the same linear
5905: * hypothesis. A more precise result, taking into account a more precise
5906: * curvature will be obtained if estepm is as small as stepm. */
5907:
5908: /* For example we decided to compute the life expectancy with the smallest unit */
5909: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5910: nhstepm is the number of hstepm from age to agelim
5911: nstepm is the number of stepm from age to agelin.
1.270 brouard 5912: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5913: and note for a fixed period like estepm months */
5914: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5915: survival function given by stepm (the optimization length). Unfortunately it
5916: means that if the survival funtion is printed only each two years of age and if
5917: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5918: results. So we changed our mind and took the option of the best precision.
5919: */
5920: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5921:
5922: agelim=AGESUP;
5923: /* If stepm=6 months */
5924: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5925: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5926:
5927: /* nhstepm age range expressed in number of stepm */
5928: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5929: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5930: /* if (stepm >= YEARM) hstepm=1;*/
5931: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5932: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5933:
5934: for (age=bage; age<=fage; age ++){
5935: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5936: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5937: /* if (stepm >= YEARM) hstepm=1;*/
5938: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5939:
5940: /* If stepm=6 months */
5941: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5942: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5943:
1.235 brouard 5944: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5945:
5946: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5947:
5948: printf("%d|",(int)age);fflush(stdout);
5949: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5950:
5951: /* Computing expectancies */
5952: for(i=1; i<=nlstate;i++)
5953: for(j=1; j<=nlstate;j++)
5954: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5955: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5956:
5957: /* 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]);*/
5958:
5959: }
5960:
5961: fprintf(ficreseij,"%3.0f",age );
5962: for(i=1; i<=nlstate;i++){
5963: eip=0;
5964: for(j=1; j<=nlstate;j++){
5965: eip +=eij[i][j][(int)age];
5966: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5967: }
5968: fprintf(ficreseij,"%9.4f", eip );
5969: }
5970: fprintf(ficreseij,"\n");
5971:
5972: }
5973: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5974: printf("\n");
5975: fprintf(ficlog,"\n");
5976:
5977: }
5978:
1.235 brouard 5979: 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 5980:
5981: {
5982: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5983: to initial status i, ei. .
1.126 brouard 5984: */
5985: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5986: int nhstepma, nstepma; /* Decreasing with age */
5987: double age, agelim, hf;
5988: double ***p3matp, ***p3matm, ***varhe;
5989: double **dnewm,**doldm;
5990: double *xp, *xm;
5991: double **gp, **gm;
5992: double ***gradg, ***trgradg;
5993: int theta;
5994:
5995: double eip, vip;
5996:
5997: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5998: xp=vector(1,npar);
5999: xm=vector(1,npar);
6000: dnewm=matrix(1,nlstate*nlstate,1,npar);
6001: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6002:
6003: pstamp(ficresstdeij);
6004: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6005: fprintf(ficresstdeij,"# Age");
6006: for(i=1; i<=nlstate;i++){
6007: for(j=1; j<=nlstate;j++)
6008: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6009: fprintf(ficresstdeij," e%1d. ",i);
6010: }
6011: fprintf(ficresstdeij,"\n");
6012:
6013: pstamp(ficrescveij);
6014: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6015: fprintf(ficrescveij,"# Age");
6016: for(i=1; i<=nlstate;i++)
6017: for(j=1; j<=nlstate;j++){
6018: cptj= (j-1)*nlstate+i;
6019: for(i2=1; i2<=nlstate;i2++)
6020: for(j2=1; j2<=nlstate;j2++){
6021: cptj2= (j2-1)*nlstate+i2;
6022: if(cptj2 <= cptj)
6023: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6024: }
6025: }
6026: fprintf(ficrescveij,"\n");
6027:
6028: if(estepm < stepm){
6029: printf ("Problem %d lower than %d\n",estepm, stepm);
6030: }
6031: else hstepm=estepm;
6032: /* We compute the life expectancy from trapezoids spaced every estepm months
6033: * This is mainly to measure the difference between two models: for example
6034: * if stepm=24 months pijx are given only every 2 years and by summing them
6035: * we are calculating an estimate of the Life Expectancy assuming a linear
6036: * progression in between and thus overestimating or underestimating according
6037: * to the curvature of the survival function. If, for the same date, we
6038: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6039: * to compare the new estimate of Life expectancy with the same linear
6040: * hypothesis. A more precise result, taking into account a more precise
6041: * curvature will be obtained if estepm is as small as stepm. */
6042:
6043: /* For example we decided to compute the life expectancy with the smallest unit */
6044: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6045: nhstepm is the number of hstepm from age to agelim
6046: nstepm is the number of stepm from age to agelin.
6047: Look at hpijx to understand the reason of that which relies in memory size
6048: and note for a fixed period like estepm months */
6049: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6050: survival function given by stepm (the optimization length). Unfortunately it
6051: means that if the survival funtion is printed only each two years of age and if
6052: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6053: results. So we changed our mind and took the option of the best precision.
6054: */
6055: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6056:
6057: /* If stepm=6 months */
6058: /* nhstepm age range expressed in number of stepm */
6059: agelim=AGESUP;
6060: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6061: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6062: /* if (stepm >= YEARM) hstepm=1;*/
6063: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6064:
6065: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6066: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6067: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6068: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6069: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6070: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6071:
6072: for (age=bage; age<=fage; age ++){
6073: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6074: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6075: /* if (stepm >= YEARM) hstepm=1;*/
6076: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6077:
1.126 brouard 6078: /* If stepm=6 months */
6079: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6080: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6081:
6082: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6083:
1.126 brouard 6084: /* Computing Variances of health expectancies */
6085: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6086: decrease memory allocation */
6087: for(theta=1; theta <=npar; theta++){
6088: for(i=1; i<=npar; i++){
1.222 brouard 6089: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6090: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6091: }
1.235 brouard 6092: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6093: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6094:
1.126 brouard 6095: for(j=1; j<= nlstate; j++){
1.222 brouard 6096: for(i=1; i<=nlstate; i++){
6097: for(h=0; h<=nhstepm-1; h++){
6098: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6099: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6100: }
6101: }
1.126 brouard 6102: }
1.218 brouard 6103:
1.126 brouard 6104: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6105: for(h=0; h<=nhstepm-1; h++){
6106: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6107: }
1.126 brouard 6108: }/* End theta */
6109:
6110:
6111: for(h=0; h<=nhstepm-1; h++)
6112: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6113: for(theta=1; theta <=npar; theta++)
6114: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6115:
1.218 brouard 6116:
1.222 brouard 6117: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6118: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6119: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6120:
1.222 brouard 6121: printf("%d|",(int)age);fflush(stdout);
6122: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6123: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6124: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6125: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6126: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6127: for(ij=1;ij<=nlstate*nlstate;ij++)
6128: for(ji=1;ji<=nlstate*nlstate;ji++)
6129: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6130: }
6131: }
1.320 brouard 6132: /* if((int)age ==50){ */
6133: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6134: /* } */
1.126 brouard 6135: /* Computing expectancies */
1.235 brouard 6136: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6137: for(i=1; i<=nlstate;i++)
6138: for(j=1; j<=nlstate;j++)
1.222 brouard 6139: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6140: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6141:
1.222 brouard 6142: /* 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 6143:
1.222 brouard 6144: }
1.269 brouard 6145:
6146: /* Standard deviation of expectancies ij */
1.126 brouard 6147: fprintf(ficresstdeij,"%3.0f",age );
6148: for(i=1; i<=nlstate;i++){
6149: eip=0.;
6150: vip=0.;
6151: for(j=1; j<=nlstate;j++){
1.222 brouard 6152: eip += eij[i][j][(int)age];
6153: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6154: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6155: 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 6156: }
6157: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6158: }
6159: fprintf(ficresstdeij,"\n");
1.218 brouard 6160:
1.269 brouard 6161: /* Variance of expectancies ij */
1.126 brouard 6162: fprintf(ficrescveij,"%3.0f",age );
6163: for(i=1; i<=nlstate;i++)
6164: for(j=1; j<=nlstate;j++){
1.222 brouard 6165: cptj= (j-1)*nlstate+i;
6166: for(i2=1; i2<=nlstate;i2++)
6167: for(j2=1; j2<=nlstate;j2++){
6168: cptj2= (j2-1)*nlstate+i2;
6169: if(cptj2 <= cptj)
6170: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6171: }
1.126 brouard 6172: }
6173: fprintf(ficrescveij,"\n");
1.218 brouard 6174:
1.126 brouard 6175: }
6176: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6177: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6178: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6179: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6180: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6181: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6182: printf("\n");
6183: fprintf(ficlog,"\n");
1.218 brouard 6184:
1.126 brouard 6185: free_vector(xm,1,npar);
6186: free_vector(xp,1,npar);
6187: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6188: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6189: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6190: }
1.218 brouard 6191:
1.126 brouard 6192: /************ Variance ******************/
1.235 brouard 6193: 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 6194: {
1.279 brouard 6195: /** Variance of health expectancies
6196: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6197: * double **newm;
6198: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6199: */
1.218 brouard 6200:
6201: /* int movingaverage(); */
6202: double **dnewm,**doldm;
6203: double **dnewmp,**doldmp;
6204: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6205: int first=0;
1.218 brouard 6206: int k;
6207: double *xp;
1.279 brouard 6208: double **gp, **gm; /**< for var eij */
6209: double ***gradg, ***trgradg; /**< for var eij */
6210: double **gradgp, **trgradgp; /**< for var p point j */
6211: double *gpp, *gmp; /**< for var p point j */
6212: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6213: double ***p3mat;
6214: double age,agelim, hf;
6215: /* double ***mobaverage; */
6216: int theta;
6217: char digit[4];
6218: char digitp[25];
6219:
6220: char fileresprobmorprev[FILENAMELENGTH];
6221:
6222: if(popbased==1){
6223: if(mobilav!=0)
6224: strcpy(digitp,"-POPULBASED-MOBILAV_");
6225: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6226: }
6227: else
6228: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6229:
1.218 brouard 6230: /* if (mobilav!=0) { */
6231: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6232: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6233: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6234: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6235: /* } */
6236: /* } */
6237:
6238: strcpy(fileresprobmorprev,"PRMORPREV-");
6239: sprintf(digit,"%-d",ij);
6240: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6241: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6242: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6243: strcat(fileresprobmorprev,fileresu);
6244: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6245: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6246: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6247: }
6248: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6249: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6250: pstamp(ficresprobmorprev);
6251: 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 6252: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
6253: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
6254: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
6255: }
6256: for(j=1;j<=cptcoveff;j++)
6257: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
6258: fprintf(ficresprobmorprev,"\n");
6259:
1.218 brouard 6260: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6261: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6262: fprintf(ficresprobmorprev," p.%-d SE",j);
6263: for(i=1; i<=nlstate;i++)
6264: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6265: }
6266: fprintf(ficresprobmorprev,"\n");
6267:
6268: fprintf(ficgp,"\n# Routine varevsij");
6269: fprintf(ficgp,"\nunset title \n");
6270: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6271: 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");
6272: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6273:
1.218 brouard 6274: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6275: pstamp(ficresvij);
6276: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6277: if(popbased==1)
6278: 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);
6279: else
6280: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6281: fprintf(ficresvij,"# Age");
6282: for(i=1; i<=nlstate;i++)
6283: for(j=1; j<=nlstate;j++)
6284: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6285: fprintf(ficresvij,"\n");
6286:
6287: xp=vector(1,npar);
6288: dnewm=matrix(1,nlstate,1,npar);
6289: doldm=matrix(1,nlstate,1,nlstate);
6290: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6291: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6292:
6293: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6294: gpp=vector(nlstate+1,nlstate+ndeath);
6295: gmp=vector(nlstate+1,nlstate+ndeath);
6296: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6297:
1.218 brouard 6298: if(estepm < stepm){
6299: printf ("Problem %d lower than %d\n",estepm, stepm);
6300: }
6301: else hstepm=estepm;
6302: /* For example we decided to compute the life expectancy with the smallest unit */
6303: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6304: nhstepm is the number of hstepm from age to agelim
6305: nstepm is the number of stepm from age to agelim.
6306: Look at function hpijx to understand why because of memory size limitations,
6307: we decided (b) to get a life expectancy respecting the most precise curvature of the
6308: survival function given by stepm (the optimization length). Unfortunately it
6309: means that if the survival funtion is printed every two years of age and if
6310: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6311: results. So we changed our mind and took the option of the best precision.
6312: */
6313: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6314: agelim = AGESUP;
6315: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6316: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6317: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6318: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6319: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6320: gp=matrix(0,nhstepm,1,nlstate);
6321: gm=matrix(0,nhstepm,1,nlstate);
6322:
6323:
6324: for(theta=1; theta <=npar; theta++){
6325: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6326: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6327: }
1.279 brouard 6328: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6329: * returns into prlim .
1.288 brouard 6330: */
1.242 brouard 6331: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6332:
6333: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6334: if (popbased==1) {
6335: if(mobilav ==0){
6336: for(i=1; i<=nlstate;i++)
6337: prlim[i][i]=probs[(int)age][i][ij];
6338: }else{ /* mobilav */
6339: for(i=1; i<=nlstate;i++)
6340: prlim[i][i]=mobaverage[(int)age][i][ij];
6341: }
6342: }
1.295 brouard 6343: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6344: */
6345: 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 6346: /**< 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 6347: * at horizon h in state j including mortality.
6348: */
1.218 brouard 6349: for(j=1; j<= nlstate; j++){
6350: for(h=0; h<=nhstepm; h++){
6351: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6352: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6353: }
6354: }
1.279 brouard 6355: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6356: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6357: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6358: */
6359: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6360: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6361: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6362: }
6363:
6364: /* Again with minus shift */
1.218 brouard 6365:
6366: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6367: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6368:
1.242 brouard 6369: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6370:
6371: if (popbased==1) {
6372: if(mobilav ==0){
6373: for(i=1; i<=nlstate;i++)
6374: prlim[i][i]=probs[(int)age][i][ij];
6375: }else{ /* mobilav */
6376: for(i=1; i<=nlstate;i++)
6377: prlim[i][i]=mobaverage[(int)age][i][ij];
6378: }
6379: }
6380:
1.235 brouard 6381: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6382:
6383: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6384: for(h=0; h<=nhstepm; h++){
6385: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6386: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6387: }
6388: }
6389: /* This for computing probability of death (h=1 means
6390: computed over hstepm matrices product = hstepm*stepm months)
6391: as a weighted average of prlim.
6392: */
6393: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6394: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6395: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6396: }
1.279 brouard 6397: /* end shifting computations */
6398:
6399: /**< Computing gradient matrix at horizon h
6400: */
1.218 brouard 6401: for(j=1; j<= nlstate; j++) /* vareij */
6402: for(h=0; h<=nhstepm; h++){
6403: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6404: }
1.279 brouard 6405: /**< Gradient of overall mortality p.3 (or p.j)
6406: */
6407: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6408: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6409: }
6410:
6411: } /* End theta */
1.279 brouard 6412:
6413: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6414: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6415:
6416: for(h=0; h<=nhstepm; h++) /* veij */
6417: for(j=1; j<=nlstate;j++)
6418: for(theta=1; theta <=npar; theta++)
6419: trgradg[h][j][theta]=gradg[h][theta][j];
6420:
6421: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6422: for(theta=1; theta <=npar; theta++)
6423: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6424: /**< as well as its transposed matrix
6425: */
1.218 brouard 6426:
6427: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6428: for(i=1;i<=nlstate;i++)
6429: for(j=1;j<=nlstate;j++)
6430: vareij[i][j][(int)age] =0.;
1.279 brouard 6431:
6432: /* Computing trgradg by matcov by gradg at age and summing over h
6433: * and k (nhstepm) formula 15 of article
6434: * Lievre-Brouard-Heathcote
6435: */
6436:
1.218 brouard 6437: for(h=0;h<=nhstepm;h++){
6438: for(k=0;k<=nhstepm;k++){
6439: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6440: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6441: for(i=1;i<=nlstate;i++)
6442: for(j=1;j<=nlstate;j++)
6443: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6444: }
6445: }
6446:
1.279 brouard 6447: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6448: * p.j overall mortality formula 49 but computed directly because
6449: * we compute the grad (wix pijx) instead of grad (pijx),even if
6450: * wix is independent of theta.
6451: */
1.218 brouard 6452: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6453: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6454: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6455: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6456: varppt[j][i]=doldmp[j][i];
6457: /* end ppptj */
6458: /* x centered again */
6459:
1.242 brouard 6460: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6461:
6462: if (popbased==1) {
6463: if(mobilav ==0){
6464: for(i=1; i<=nlstate;i++)
6465: prlim[i][i]=probs[(int)age][i][ij];
6466: }else{ /* mobilav */
6467: for(i=1; i<=nlstate;i++)
6468: prlim[i][i]=mobaverage[(int)age][i][ij];
6469: }
6470: }
6471:
6472: /* This for computing probability of death (h=1 means
6473: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6474: as a weighted average of prlim.
6475: */
1.235 brouard 6476: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6477: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6478: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6479: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6480: }
6481: /* end probability of death */
6482:
6483: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6484: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6485: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6486: for(i=1; i<=nlstate;i++){
6487: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6488: }
6489: }
6490: fprintf(ficresprobmorprev,"\n");
6491:
6492: fprintf(ficresvij,"%.0f ",age );
6493: for(i=1; i<=nlstate;i++)
6494: for(j=1; j<=nlstate;j++){
6495: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6496: }
6497: fprintf(ficresvij,"\n");
6498: free_matrix(gp,0,nhstepm,1,nlstate);
6499: free_matrix(gm,0,nhstepm,1,nlstate);
6500: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6501: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6502: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6503: } /* End age */
6504: free_vector(gpp,nlstate+1,nlstate+ndeath);
6505: free_vector(gmp,nlstate+1,nlstate+ndeath);
6506: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6507: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6508: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6509: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6510: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6511: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6512: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6513: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6514: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6515: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6516: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6517: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6518: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6519: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6520: 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);
6521: /* 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 6522: */
1.218 brouard 6523: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6524: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6525:
1.218 brouard 6526: free_vector(xp,1,npar);
6527: free_matrix(doldm,1,nlstate,1,nlstate);
6528: free_matrix(dnewm,1,nlstate,1,npar);
6529: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6530: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6531: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6532: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6533: fclose(ficresprobmorprev);
6534: fflush(ficgp);
6535: fflush(fichtm);
6536: } /* end varevsij */
1.126 brouard 6537:
6538: /************ Variance of prevlim ******************/
1.269 brouard 6539: 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 6540: {
1.205 brouard 6541: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6542: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6543:
1.268 brouard 6544: double **dnewmpar,**doldm;
1.126 brouard 6545: int i, j, nhstepm, hstepm;
6546: double *xp;
6547: double *gp, *gm;
6548: double **gradg, **trgradg;
1.208 brouard 6549: double **mgm, **mgp;
1.126 brouard 6550: double age,agelim;
6551: int theta;
6552:
6553: pstamp(ficresvpl);
1.288 brouard 6554: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6555: fprintf(ficresvpl,"# Age ");
6556: if(nresult >=1)
6557: fprintf(ficresvpl," Result# ");
1.126 brouard 6558: for(i=1; i<=nlstate;i++)
6559: fprintf(ficresvpl," %1d-%1d",i,i);
6560: fprintf(ficresvpl,"\n");
6561:
6562: xp=vector(1,npar);
1.268 brouard 6563: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6564: doldm=matrix(1,nlstate,1,nlstate);
6565:
6566: hstepm=1*YEARM; /* Every year of age */
6567: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6568: agelim = AGESUP;
6569: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6570: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6571: if (stepm >= YEARM) hstepm=1;
6572: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6573: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6574: mgp=matrix(1,npar,1,nlstate);
6575: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6576: gp=vector(1,nlstate);
6577: gm=vector(1,nlstate);
6578:
6579: for(theta=1; theta <=npar; theta++){
6580: for(i=1; i<=npar; i++){ /* Computes gradient */
6581: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6582: }
1.288 brouard 6583: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6584: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6585: /* else */
6586: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6587: for(i=1;i<=nlstate;i++){
1.126 brouard 6588: gp[i] = prlim[i][i];
1.208 brouard 6589: mgp[theta][i] = prlim[i][i];
6590: }
1.126 brouard 6591: for(i=1; i<=npar; i++) /* Computes gradient */
6592: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6593: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6594: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6595: /* else */
6596: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6597: for(i=1;i<=nlstate;i++){
1.126 brouard 6598: gm[i] = prlim[i][i];
1.208 brouard 6599: mgm[theta][i] = prlim[i][i];
6600: }
1.126 brouard 6601: for(i=1;i<=nlstate;i++)
6602: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6603: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6604: } /* End theta */
6605:
6606: trgradg =matrix(1,nlstate,1,npar);
6607:
6608: for(j=1; j<=nlstate;j++)
6609: for(theta=1; theta <=npar; theta++)
6610: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6611: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6612: /* printf("\nmgm mgp %d ",(int)age); */
6613: /* for(j=1; j<=nlstate;j++){ */
6614: /* printf(" %d ",j); */
6615: /* for(theta=1; theta <=npar; theta++) */
6616: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6617: /* printf("\n "); */
6618: /* } */
6619: /* } */
6620: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6621: /* printf("\n gradg %d ",(int)age); */
6622: /* for(j=1; j<=nlstate;j++){ */
6623: /* printf("%d ",j); */
6624: /* for(theta=1; theta <=npar; theta++) */
6625: /* printf("%d %lf ",theta,gradg[theta][j]); */
6626: /* printf("\n "); */
6627: /* } */
6628: /* } */
1.126 brouard 6629:
6630: for(i=1;i<=nlstate;i++)
6631: varpl[i][(int)age] =0.;
1.209 brouard 6632: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6633: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6634: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6635: }else{
1.268 brouard 6636: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6637: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6638: }
1.126 brouard 6639: for(i=1;i<=nlstate;i++)
6640: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6641:
6642: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6643: if(nresult >=1)
6644: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6645: for(i=1; i<=nlstate;i++){
1.126 brouard 6646: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6647: /* for(j=1;j<=nlstate;j++) */
6648: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6649: }
1.126 brouard 6650: fprintf(ficresvpl,"\n");
6651: free_vector(gp,1,nlstate);
6652: free_vector(gm,1,nlstate);
1.208 brouard 6653: free_matrix(mgm,1,npar,1,nlstate);
6654: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6655: free_matrix(gradg,1,npar,1,nlstate);
6656: free_matrix(trgradg,1,nlstate,1,npar);
6657: } /* End age */
6658:
6659: free_vector(xp,1,npar);
6660: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6661: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6662:
6663: }
6664:
6665:
6666: /************ Variance of backprevalence limit ******************/
1.269 brouard 6667: 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 6668: {
6669: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6670: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6671:
6672: double **dnewmpar,**doldm;
6673: int i, j, nhstepm, hstepm;
6674: double *xp;
6675: double *gp, *gm;
6676: double **gradg, **trgradg;
6677: double **mgm, **mgp;
6678: double age,agelim;
6679: int theta;
6680:
6681: pstamp(ficresvbl);
6682: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6683: fprintf(ficresvbl,"# Age ");
6684: if(nresult >=1)
6685: fprintf(ficresvbl," Result# ");
6686: for(i=1; i<=nlstate;i++)
6687: fprintf(ficresvbl," %1d-%1d",i,i);
6688: fprintf(ficresvbl,"\n");
6689:
6690: xp=vector(1,npar);
6691: dnewmpar=matrix(1,nlstate,1,npar);
6692: doldm=matrix(1,nlstate,1,nlstate);
6693:
6694: hstepm=1*YEARM; /* Every year of age */
6695: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6696: agelim = AGEINF;
6697: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6698: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6699: if (stepm >= YEARM) hstepm=1;
6700: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6701: gradg=matrix(1,npar,1,nlstate);
6702: mgp=matrix(1,npar,1,nlstate);
6703: mgm=matrix(1,npar,1,nlstate);
6704: gp=vector(1,nlstate);
6705: gm=vector(1,nlstate);
6706:
6707: for(theta=1; theta <=npar; theta++){
6708: for(i=1; i<=npar; i++){ /* Computes gradient */
6709: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6710: }
6711: if(mobilavproj > 0 )
6712: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6713: else
6714: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6715: for(i=1;i<=nlstate;i++){
6716: gp[i] = bprlim[i][i];
6717: mgp[theta][i] = bprlim[i][i];
6718: }
6719: for(i=1; i<=npar; i++) /* Computes gradient */
6720: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6721: if(mobilavproj > 0 )
6722: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6723: else
6724: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6725: for(i=1;i<=nlstate;i++){
6726: gm[i] = bprlim[i][i];
6727: mgm[theta][i] = bprlim[i][i];
6728: }
6729: for(i=1;i<=nlstate;i++)
6730: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6731: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6732: } /* End theta */
6733:
6734: trgradg =matrix(1,nlstate,1,npar);
6735:
6736: for(j=1; j<=nlstate;j++)
6737: for(theta=1; theta <=npar; theta++)
6738: trgradg[j][theta]=gradg[theta][j];
6739: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6740: /* printf("\nmgm mgp %d ",(int)age); */
6741: /* for(j=1; j<=nlstate;j++){ */
6742: /* printf(" %d ",j); */
6743: /* for(theta=1; theta <=npar; theta++) */
6744: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6745: /* printf("\n "); */
6746: /* } */
6747: /* } */
6748: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6749: /* printf("\n gradg %d ",(int)age); */
6750: /* for(j=1; j<=nlstate;j++){ */
6751: /* printf("%d ",j); */
6752: /* for(theta=1; theta <=npar; theta++) */
6753: /* printf("%d %lf ",theta,gradg[theta][j]); */
6754: /* printf("\n "); */
6755: /* } */
6756: /* } */
6757:
6758: for(i=1;i<=nlstate;i++)
6759: varbpl[i][(int)age] =0.;
6760: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6761: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6762: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6763: }else{
6764: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6765: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6766: }
6767: for(i=1;i<=nlstate;i++)
6768: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6769:
6770: fprintf(ficresvbl,"%.0f ",age );
6771: if(nresult >=1)
6772: fprintf(ficresvbl,"%d ",nres );
6773: for(i=1; i<=nlstate;i++)
6774: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6775: fprintf(ficresvbl,"\n");
6776: free_vector(gp,1,nlstate);
6777: free_vector(gm,1,nlstate);
6778: free_matrix(mgm,1,npar,1,nlstate);
6779: free_matrix(mgp,1,npar,1,nlstate);
6780: free_matrix(gradg,1,npar,1,nlstate);
6781: free_matrix(trgradg,1,nlstate,1,npar);
6782: } /* End age */
6783:
6784: free_vector(xp,1,npar);
6785: free_matrix(doldm,1,nlstate,1,npar);
6786: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6787:
6788: }
6789:
6790: /************ Variance of one-step probabilities ******************/
6791: 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 6792: {
6793: int i, j=0, k1, l1, tj;
6794: int k2, l2, j1, z1;
6795: int k=0, l;
6796: int first=1, first1, first2;
6797: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6798: double **dnewm,**doldm;
6799: double *xp;
6800: double *gp, *gm;
6801: double **gradg, **trgradg;
6802: double **mu;
6803: double age, cov[NCOVMAX+1];
6804: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6805: int theta;
6806: char fileresprob[FILENAMELENGTH];
6807: char fileresprobcov[FILENAMELENGTH];
6808: char fileresprobcor[FILENAMELENGTH];
6809: double ***varpij;
6810:
6811: strcpy(fileresprob,"PROB_");
6812: strcat(fileresprob,fileres);
6813: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6814: printf("Problem with resultfile: %s\n", fileresprob);
6815: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6816: }
6817: strcpy(fileresprobcov,"PROBCOV_");
6818: strcat(fileresprobcov,fileresu);
6819: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6820: printf("Problem with resultfile: %s\n", fileresprobcov);
6821: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6822: }
6823: strcpy(fileresprobcor,"PROBCOR_");
6824: strcat(fileresprobcor,fileresu);
6825: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6826: printf("Problem with resultfile: %s\n", fileresprobcor);
6827: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6828: }
6829: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6830: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6831: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6832: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6833: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6834: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6835: pstamp(ficresprob);
6836: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6837: fprintf(ficresprob,"# Age");
6838: pstamp(ficresprobcov);
6839: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6840: fprintf(ficresprobcov,"# Age");
6841: pstamp(ficresprobcor);
6842: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6843: fprintf(ficresprobcor,"# Age");
1.126 brouard 6844:
6845:
1.222 brouard 6846: for(i=1; i<=nlstate;i++)
6847: for(j=1; j<=(nlstate+ndeath);j++){
6848: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6849: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6850: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6851: }
6852: /* fprintf(ficresprob,"\n");
6853: fprintf(ficresprobcov,"\n");
6854: fprintf(ficresprobcor,"\n");
6855: */
6856: xp=vector(1,npar);
6857: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6858: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6859: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6860: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6861: first=1;
6862: fprintf(ficgp,"\n# Routine varprob");
6863: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6864: fprintf(fichtm,"\n");
6865:
1.288 brouard 6866: 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 6867: 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);
6868: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6869: and drawn. It helps understanding how is the covariance between two incidences.\
6870: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6871: 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 6872: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6873: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6874: standard deviations wide on each axis. <br>\
6875: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6876: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6877: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6878:
1.222 brouard 6879: cov[1]=1;
6880: /* tj=cptcoveff; */
1.225 brouard 6881: tj = (int) pow(2,cptcoveff);
1.222 brouard 6882: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6883: j1=0;
1.224 brouard 6884: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6885: if (cptcovn>0) {
6886: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6887: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6888: fprintf(ficresprob, "**********\n#\n");
6889: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6890: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6891: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6892:
1.222 brouard 6893: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6894: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6895: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6896:
6897:
1.222 brouard 6898: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.319 brouard 6899: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); */
6900: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtmcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6901: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6902:
1.222 brouard 6903: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6904: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6905: fprintf(ficresprobcor, "**********\n#");
6906: if(invalidvarcomb[j1]){
6907: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6908: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6909: continue;
6910: }
6911: }
6912: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6913: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6914: gp=vector(1,(nlstate)*(nlstate+ndeath));
6915: gm=vector(1,(nlstate)*(nlstate+ndeath));
6916: for (age=bage; age<=fage; age ++){
6917: cov[2]=age;
6918: if(nagesqr==1)
6919: cov[3]= age*age;
6920: for (k=1; k<=cptcovn;k++) {
6921: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6922: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6923: * 1 1 1 1 1
6924: * 2 2 1 1 1
6925: * 3 1 2 1 1
6926: */
6927: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6928: }
1.319 brouard 6929: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
6930: /* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] */
6931: /*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6932: for (k=1; k<=cptcovage;k++)
6933: cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.222 brouard 6934: for (k=1; k<=cptcovprod;k++)
6935: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6936:
6937:
1.222 brouard 6938: for(theta=1; theta <=npar; theta++){
6939: for(i=1; i<=npar; i++)
6940: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6941:
1.222 brouard 6942: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6943:
1.222 brouard 6944: k=0;
6945: for(i=1; i<= (nlstate); i++){
6946: for(j=1; j<=(nlstate+ndeath);j++){
6947: k=k+1;
6948: gp[k]=pmmij[i][j];
6949: }
6950: }
1.220 brouard 6951:
1.222 brouard 6952: for(i=1; i<=npar; i++)
6953: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6954:
1.222 brouard 6955: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6956: k=0;
6957: for(i=1; i<=(nlstate); i++){
6958: for(j=1; j<=(nlstate+ndeath);j++){
6959: k=k+1;
6960: gm[k]=pmmij[i][j];
6961: }
6962: }
1.220 brouard 6963:
1.222 brouard 6964: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6965: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6966: }
1.126 brouard 6967:
1.222 brouard 6968: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6969: for(theta=1; theta <=npar; theta++)
6970: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6971:
1.222 brouard 6972: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6973: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6974:
1.222 brouard 6975: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6976:
1.222 brouard 6977: k=0;
6978: for(i=1; i<=(nlstate); i++){
6979: for(j=1; j<=(nlstate+ndeath);j++){
6980: k=k+1;
6981: mu[k][(int) age]=pmmij[i][j];
6982: }
6983: }
6984: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6985: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6986: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6987:
1.222 brouard 6988: /*printf("\n%d ",(int)age);
6989: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6990: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6991: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6992: }*/
1.220 brouard 6993:
1.222 brouard 6994: fprintf(ficresprob,"\n%d ",(int)age);
6995: fprintf(ficresprobcov,"\n%d ",(int)age);
6996: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6997:
1.222 brouard 6998: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6999: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7000: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7001: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7002: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7003: }
7004: i=0;
7005: for (k=1; k<=(nlstate);k++){
7006: for (l=1; l<=(nlstate+ndeath);l++){
7007: i++;
7008: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7009: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7010: for (j=1; j<=i;j++){
7011: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7012: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7013: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7014: }
7015: }
7016: }/* end of loop for state */
7017: } /* end of loop for age */
7018: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7019: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7020: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7021: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7022:
7023: /* Confidence intervalle of pij */
7024: /*
7025: fprintf(ficgp,"\nunset parametric;unset label");
7026: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7027: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7028: 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);
7029: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7030: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7031: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7032: */
7033:
7034: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7035: first1=1;first2=2;
7036: for (k2=1; k2<=(nlstate);k2++){
7037: for (l2=1; l2<=(nlstate+ndeath);l2++){
7038: if(l2==k2) continue;
7039: j=(k2-1)*(nlstate+ndeath)+l2;
7040: for (k1=1; k1<=(nlstate);k1++){
7041: for (l1=1; l1<=(nlstate+ndeath);l1++){
7042: if(l1==k1) continue;
7043: i=(k1-1)*(nlstate+ndeath)+l1;
7044: if(i<=j) continue;
7045: for (age=bage; age<=fage; age ++){
7046: if ((int)age %5==0){
7047: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7048: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7049: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7050: mu1=mu[i][(int) age]/stepm*YEARM ;
7051: mu2=mu[j][(int) age]/stepm*YEARM;
7052: c12=cv12/sqrt(v1*v2);
7053: /* Computing eigen value of matrix of covariance */
7054: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7055: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7056: if ((lc2 <0) || (lc1 <0) ){
7057: if(first2==1){
7058: first1=0;
7059: 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);
7060: }
7061: 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);
7062: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7063: /* lc2=fabs(lc2); */
7064: }
1.220 brouard 7065:
1.222 brouard 7066: /* Eigen vectors */
1.280 brouard 7067: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7068: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7069: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7070: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7071: }else
7072: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7073: /*v21=sqrt(1.-v11*v11); *//* error */
7074: v21=(lc1-v1)/cv12*v11;
7075: v12=-v21;
7076: v22=v11;
7077: tnalp=v21/v11;
7078: if(first1==1){
7079: first1=0;
7080: 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);
7081: }
7082: 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);
7083: /*printf(fignu*/
7084: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7085: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7086: if(first==1){
7087: first=0;
7088: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7089: fprintf(ficgp,"\nset parametric;unset label");
7090: 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);
7091: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7092: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7093: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7094: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7095: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7096: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7097: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7098: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7099: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7100: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7101: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7102: 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 7103: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7104: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7105: }else{
7106: first=0;
7107: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7108: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7109: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7110: 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 7111: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7112: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7113: }/* if first */
7114: } /* age mod 5 */
7115: } /* end loop age */
7116: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7117: first=1;
7118: } /*l12 */
7119: } /* k12 */
7120: } /*l1 */
7121: }/* k1 */
7122: } /* loop on combination of covariates j1 */
7123: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7124: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7125: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7126: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7127: free_vector(xp,1,npar);
7128: fclose(ficresprob);
7129: fclose(ficresprobcov);
7130: fclose(ficresprobcor);
7131: fflush(ficgp);
7132: fflush(fichtmcov);
7133: }
1.126 brouard 7134:
7135:
7136: /******************* Printing html file ***********/
1.201 brouard 7137: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7138: int lastpass, int stepm, int weightopt, char model[],\
7139: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7140: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7141: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7142: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7143: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7144: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7145: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7146: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7147: </ul>");
1.319 brouard 7148: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7149: /* </ul>", model); */
1.214 brouard 7150: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7151: 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",
7152: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
7153: fprintf(fichtm,"<li> - Observed 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 7154: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7155: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7156: fprintf(fichtm,"\
7157: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7158: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7159: fprintf(fichtm,"\
1.217 brouard 7160: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7161: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7162: fprintf(fichtm,"\
1.288 brouard 7163: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7164: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7165: fprintf(fichtm,"\
1.288 brouard 7166: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7167: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7168: fprintf(fichtm,"\
1.211 brouard 7169: - (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 7170: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7171: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7172: if(prevfcast==1){
7173: fprintf(fichtm,"\
7174: - Prevalence projections by age and states: \
1.201 brouard 7175: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7176: }
1.126 brouard 7177:
7178:
1.225 brouard 7179: m=pow(2,cptcoveff);
1.222 brouard 7180: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7181:
1.317 brouard 7182: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7183:
7184: jj1=0;
7185:
7186: fprintf(fichtm," \n<ul>");
7187: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7188: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7189: if(m != 1 && TKresult[nres]!= k1)
7190: continue;
7191: jj1++;
7192: if (cptcovn > 0) {
7193: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
7194: for (cpt=1; cpt<=cptcoveff;cpt++){
7195: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7196: }
7197: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7198: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7199: }
7200: fprintf(fichtm,"\">");
7201:
7202: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7203: fprintf(fichtm,"************ Results for covariates");
7204: for (cpt=1; cpt<=cptcoveff;cpt++){
7205: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7206: }
7207: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7208: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7209: }
7210: if(invalidvarcomb[k1]){
7211: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7212: continue;
7213: }
7214: fprintf(fichtm,"</a></li>");
7215: } /* cptcovn >0 */
7216: }
1.317 brouard 7217: fprintf(fichtm," \n</ul>");
1.264 brouard 7218:
1.222 brouard 7219: jj1=0;
1.237 brouard 7220:
7221: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7222: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7223: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7224: continue;
1.220 brouard 7225:
1.222 brouard 7226: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7227: jj1++;
7228: if (cptcovn > 0) {
1.264 brouard 7229: fprintf(fichtm,"\n<p><a name=\"rescov");
7230: for (cpt=1; cpt<=cptcoveff;cpt++){
7231: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7232: }
7233: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7234: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7235: }
7236: fprintf(fichtm,"\"</a>");
7237:
1.222 brouard 7238: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7239: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7240: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7241: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7242: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7243: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7244: }
1.237 brouard 7245: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7246: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7247: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7248: }
7249:
1.230 brouard 7250: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.321 brouard 7251: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7252: if(invalidvarcomb[k1]){
7253: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7254: printf("\nCombination (%d) ignored because no cases \n",k1);
7255: continue;
7256: }
7257: }
7258: /* aij, bij */
1.259 brouard 7259: 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 7260: <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 7261: /* Pij */
1.241 brouard 7262: 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> \
7263: <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 7264: /* Quasi-incidences */
7265: 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 7266: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7267: 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 7268: 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> \
7269: <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 7270: /* Survival functions (period) in state j */
7271: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7272: 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> \
1.241 brouard 7273: <img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7274: }
7275: /* State specific survival functions (period) */
7276: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7277: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7278: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 7279: <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> <img src=\"%s_%d-%d-%d.svg\">", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7280: }
1.288 brouard 7281: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7282: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7283: 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> \
7284: <img src=\"%s_%d-%d-%d.svg\">", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7285: }
1.296 brouard 7286: if(prevbcast==1){
1.288 brouard 7287: /* Backward prevalence in each health state */
1.222 brouard 7288: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7289: 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> \
1.241 brouard 7290: <img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 7291: }
1.217 brouard 7292: }
1.222 brouard 7293: if(prevfcast==1){
1.288 brouard 7294: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7295: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7296: 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);
7297: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7298: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7299: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7300: }
7301: }
1.296 brouard 7302: if(prevbcast==1){
1.268 brouard 7303: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7304: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7305: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7306: 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 \
7307: 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 7308: 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);
7309: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7310: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7311: }
7312: }
1.220 brouard 7313:
1.222 brouard 7314: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7315: 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);
7316: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7317: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7318: }
7319: /* } /\* end i1 *\/ */
7320: }/* End k1 */
7321: fprintf(fichtm,"</ul>");
1.126 brouard 7322:
1.222 brouard 7323: fprintf(fichtm,"\
1.126 brouard 7324: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7325: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7326: - 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 7327: But because parameters are usually highly correlated (a higher incidence of disability \
7328: and a higher incidence of recovery can give very close observed transition) it might \
7329: be very useful to look not only at linear confidence intervals estimated from the \
7330: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7331: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7332: covariance matrix of the one-step probabilities. \
7333: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7334:
1.222 brouard 7335: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7336: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7337: fprintf(fichtm,"\
1.126 brouard 7338: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7339: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7340:
1.222 brouard 7341: fprintf(fichtm,"\
1.126 brouard 7342: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7343: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7344: fprintf(fichtm,"\
1.126 brouard 7345: - 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): \
7346: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7347: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7348: fprintf(fichtm,"\
1.126 brouard 7349: - (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): \
7350: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7351: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7352: fprintf(fichtm,"\
1.288 brouard 7353: - 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 7354: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7355: fprintf(fichtm,"\
1.128 brouard 7356: - 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 7357: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7358: fprintf(fichtm,"\
1.288 brouard 7359: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7360: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7361:
7362: /* if(popforecast==1) fprintf(fichtm,"\n */
7363: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7364: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7365: /* <br>",fileres,fileres,fileres,fileres); */
7366: /* else */
7367: /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
1.222 brouard 7368: fflush(fichtm);
1.126 brouard 7369:
1.225 brouard 7370: m=pow(2,cptcoveff);
1.222 brouard 7371: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7372:
1.317 brouard 7373: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7374:
7375: jj1=0;
7376:
7377: fprintf(fichtm," \n<ul>");
7378: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7379: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7380: if(m != 1 && TKresult[nres]!= k1)
7381: continue;
7382: jj1++;
7383: if (cptcovn > 0) {
7384: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
7385: for (cpt=1; cpt<=cptcoveff;cpt++){
7386: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7387: }
7388: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7389: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7390: }
7391: fprintf(fichtm,"\">");
7392:
7393: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7394: fprintf(fichtm,"************ Results for covariates");
7395: for (cpt=1; cpt<=cptcoveff;cpt++){
7396: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7397: }
7398: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7399: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7400: }
7401: if(invalidvarcomb[k1]){
7402: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7403: continue;
7404: }
7405: fprintf(fichtm,"</a></li>");
7406: } /* cptcovn >0 */
7407: }
7408: fprintf(fichtm," \n</ul>");
7409:
1.222 brouard 7410: jj1=0;
1.237 brouard 7411:
1.241 brouard 7412: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7413: for(k1=1; k1<=m;k1++){
1.253 brouard 7414: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7415: continue;
1.222 brouard 7416: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7417: jj1++;
1.126 brouard 7418: if (cptcovn > 0) {
1.317 brouard 7419: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
7420: for (cpt=1; cpt<=cptcoveff;cpt++){
7421: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7422: }
7423: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7424: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7425: }
7426: fprintf(fichtm,"\"</a>");
7427:
1.126 brouard 7428: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.317 brouard 7429: for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */
1.237 brouard 7430: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
1.317 brouard 7431: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
1.237 brouard 7432: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7433: }
1.237 brouard 7434: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7435: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7436: }
7437:
1.321 brouard 7438: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7439:
1.222 brouard 7440: if(invalidvarcomb[k1]){
7441: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7442: continue;
7443: }
1.126 brouard 7444: }
7445: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7446: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7447: 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);
7448: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7449: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7450: }
7451: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7452: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7453: true period expectancies (those weighted with period prevalences are also\
7454: drawn in addition to the population based expectancies computed using\
1.314 brouard 7455: 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);
7456: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7457: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7458: /* } /\* end i1 *\/ */
7459: }/* End k1 */
1.241 brouard 7460: }/* End nres */
1.222 brouard 7461: fprintf(fichtm,"</ul>");
7462: fflush(fichtm);
1.126 brouard 7463: }
7464:
7465: /******************* Gnuplot file **************/
1.296 brouard 7466: 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 7467:
7468: char dirfileres[132],optfileres[132];
1.264 brouard 7469: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7470: 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 7471: int lv=0, vlv=0, kl=0;
1.130 brouard 7472: int ng=0;
1.201 brouard 7473: int vpopbased;
1.223 brouard 7474: int ioffset; /* variable offset for columns */
1.270 brouard 7475: int iyearc=1; /* variable column for year of projection */
7476: int iagec=1; /* variable column for age of projection */
1.235 brouard 7477: int nres=0; /* Index of resultline */
1.266 brouard 7478: int istart=1; /* For starting graphs in projections */
1.219 brouard 7479:
1.126 brouard 7480: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7481: /* printf("Problem with file %s",optionfilegnuplot); */
7482: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7483: /* } */
7484:
7485: /*#ifdef windows */
7486: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7487: /*#endif */
1.225 brouard 7488: m=pow(2,cptcoveff);
1.126 brouard 7489:
1.274 brouard 7490: /* diagram of the model */
7491: fprintf(ficgp,"\n#Diagram of the model \n");
7492: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7493: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7494: 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);
7495:
7496: 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);
7497: fprintf(ficgp,"\n#show arrow\nunset label\n");
7498: 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);
7499: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7500: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7501: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7502: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7503:
1.202 brouard 7504: /* Contribution to likelihood */
7505: /* Plot the probability implied in the likelihood */
1.223 brouard 7506: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7507: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7508: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7509: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7510: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7511: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7512: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7513: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7514: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7515: 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));
7516: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7517: 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));
7518: for (i=1; i<= nlstate ; i ++) {
7519: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7520: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7521: 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);
7522: for (j=2; j<= nlstate+ndeath ; j ++) {
7523: 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);
7524: }
7525: fprintf(ficgp,";\nset out; unset ylabel;\n");
7526: }
7527: /* 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 */
7528: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7529: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7530: fprintf(ficgp,"\nset out;unset log\n");
7531: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7532:
1.126 brouard 7533: strcpy(dirfileres,optionfilefiname);
7534: strcpy(optfileres,"vpl");
1.223 brouard 7535: /* 1eme*/
1.238 brouard 7536: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7537: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7538: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7539: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7540: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7541: continue;
7542: /* We are interested in selected combination by the resultline */
1.246 brouard 7543: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7544: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7545: strcpy(gplotlabel,"(");
1.238 brouard 7546: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7547: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7548: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7549: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7550: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7551: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7552: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7553: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7554: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7555: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7556: }
7557: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7558: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7559: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7560: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7561: }
7562: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7563: /* printf("\n#\n"); */
1.238 brouard 7564: fprintf(ficgp,"\n#\n");
7565: if(invalidvarcomb[k1]){
1.260 brouard 7566: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7567: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7568: continue;
7569: }
1.235 brouard 7570:
1.241 brouard 7571: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7572: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7573: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
1.321 brouard 7574: fprintf(ficgp,"set title \"Alive state %d %s model=%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 7575: 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);
7576: /* 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); */
7577: /* k1-1 error should be nres-1*/
1.238 brouard 7578: for (i=1; i<= nlstate ; i ++) {
7579: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7580: else fprintf(ficgp," %%*lf (%%*lf)");
7581: }
1.288 brouard 7582: 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 7583: for (i=1; i<= nlstate ; i ++) {
7584: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7585: else fprintf(ficgp," %%*lf (%%*lf)");
7586: }
1.260 brouard 7587: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7588: for (i=1; i<= nlstate ; i ++) {
7589: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7590: else fprintf(ficgp," %%*lf (%%*lf)");
7591: }
1.265 brouard 7592: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7593:
7594: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7595: if(cptcoveff ==0){
1.271 brouard 7596: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7597: }else{
7598: kl=0;
7599: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7600: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7601: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7602: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7603: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7604: vlv= nbcode[Tvaraff[k]][lv];
7605: kl++;
7606: /* 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 *\/ */
7607: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7608: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7609: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7610: if(k==cptcoveff){
7611: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7612: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7613: }else{
7614: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7615: kl++;
7616: }
7617: } /* end covariate */
7618: } /* end if no covariate */
7619:
1.296 brouard 7620: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7621: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7622: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7623: if(cptcoveff ==0){
1.245 brouard 7624: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7625: }else{
7626: kl=0;
7627: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7628: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7629: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7630: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7631: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7632: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7633: kl++;
1.238 brouard 7634: /* 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 *\/ */
7635: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7636: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7637: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7638: if(k==cptcoveff){
1.245 brouard 7639: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7640: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7641: }else{
7642: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7643: kl++;
7644: }
7645: } /* end covariate */
7646: } /* end if no covariate */
1.296 brouard 7647: if(prevbcast == 1){
1.268 brouard 7648: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7649: /* k1-1 error should be nres-1*/
7650: for (i=1; i<= nlstate ; i ++) {
7651: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7652: else fprintf(ficgp," %%*lf (%%*lf)");
7653: }
1.271 brouard 7654: 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 7655: for (i=1; i<= nlstate ; i ++) {
7656: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7657: else fprintf(ficgp," %%*lf (%%*lf)");
7658: }
1.276 brouard 7659: 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 7660: for (i=1; i<= nlstate ; i ++) {
7661: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7662: else fprintf(ficgp," %%*lf (%%*lf)");
7663: }
1.274 brouard 7664: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7665: } /* end if backprojcast */
1.296 brouard 7666: } /* end if prevbcast */
1.276 brouard 7667: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7668: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7669: } /* nres */
1.201 brouard 7670: } /* k1 */
7671: } /* cpt */
1.235 brouard 7672:
7673:
1.126 brouard 7674: /*2 eme*/
1.238 brouard 7675: for (k1=1; k1<= m ; k1 ++){
7676: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7677: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7678: continue;
7679: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7680: strcpy(gplotlabel,"(");
1.238 brouard 7681: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7682: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7683: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7684: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7685: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7686: vlv= nbcode[Tvaraff[k]][lv];
7687: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7688: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7689: }
1.237 brouard 7690: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7691: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7692: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7693: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7694: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7695: }
1.264 brouard 7696: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7697: fprintf(ficgp,"\n#\n");
1.223 brouard 7698: if(invalidvarcomb[k1]){
7699: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7700: continue;
7701: }
1.219 brouard 7702:
1.241 brouard 7703: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7704: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7705: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7706: if(vpopbased==0){
1.238 brouard 7707: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7708: }else
1.238 brouard 7709: fprintf(ficgp,"\nreplot ");
7710: for (i=1; i<= nlstate+1 ; i ++) {
7711: k=2*i;
1.261 brouard 7712: 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 7713: for (j=1; j<= nlstate+1 ; j ++) {
7714: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7715: else fprintf(ficgp," %%*lf (%%*lf)");
7716: }
7717: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7718: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7719: 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 7720: for (j=1; j<= nlstate+1 ; j ++) {
7721: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7722: else fprintf(ficgp," %%*lf (%%*lf)");
7723: }
7724: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7725: 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 7726: for (j=1; j<= nlstate+1 ; j ++) {
7727: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7728: else fprintf(ficgp," %%*lf (%%*lf)");
7729: }
7730: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7731: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7732: } /* state */
7733: } /* vpopbased */
1.264 brouard 7734: 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 7735: } /* end nres */
7736: } /* k1 end 2 eme*/
7737:
7738:
7739: /*3eme*/
7740: for (k1=1; k1<= m ; k1 ++){
7741: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7742: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7743: continue;
7744:
7745: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7746: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7747: strcpy(gplotlabel,"(");
1.238 brouard 7748: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7749: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7750: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7751: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7752: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7753: vlv= nbcode[Tvaraff[k]][lv];
7754: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7755: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7756: }
7757: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7758: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7759: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7760: }
1.264 brouard 7761: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7762: fprintf(ficgp,"\n#\n");
7763: if(invalidvarcomb[k1]){
7764: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7765: continue;
7766: }
7767:
7768: /* k=2+nlstate*(2*cpt-2); */
7769: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7770: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7771: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7772: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7773: 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 7774: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7775: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7776: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7777: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7778: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7779: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7780:
1.238 brouard 7781: */
7782: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7783: 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 7784: /* 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 7785:
1.238 brouard 7786: }
1.261 brouard 7787: 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 7788: }
1.264 brouard 7789: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7790: } /* end nres */
7791: } /* end kl 3eme */
1.126 brouard 7792:
1.223 brouard 7793: /* 4eme */
1.201 brouard 7794: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7795: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7796: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7797: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7798: continue;
1.238 brouard 7799: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7800: strcpy(gplotlabel,"(");
1.238 brouard 7801: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7802: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7803: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7804: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7805: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7806: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7807: vlv= nbcode[Tvaraff[k]][lv];
7808: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7809: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7810: }
7811: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7812: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7813: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7814: }
1.264 brouard 7815: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7816: fprintf(ficgp,"\n#\n");
7817: if(invalidvarcomb[k1]){
7818: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7819: continue;
1.223 brouard 7820: }
1.238 brouard 7821:
1.241 brouard 7822: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7823: 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 7824: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7825: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7826: k=3;
7827: for (i=1; i<= nlstate ; i ++){
7828: if(i==1){
7829: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7830: }else{
7831: fprintf(ficgp,", '' ");
7832: }
7833: l=(nlstate+ndeath)*(i-1)+1;
7834: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7835: for (j=2; j<= nlstate+ndeath ; j ++)
7836: fprintf(ficgp,"+$%d",k+l+j-1);
7837: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7838: } /* nlstate */
1.264 brouard 7839: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7840: } /* end cpt state*/
7841: } /* end nres */
7842: } /* end covariate k1 */
7843:
1.220 brouard 7844: /* 5eme */
1.201 brouard 7845: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7846: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7847: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7848: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7849: continue;
1.238 brouard 7850: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7851: strcpy(gplotlabel,"(");
1.238 brouard 7852: 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);
7853: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7854: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7855: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7856: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7857: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7858: vlv= nbcode[Tvaraff[k]][lv];
7859: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7860: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7861: }
7862: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7863: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7864: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7865: }
1.264 brouard 7866: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7867: fprintf(ficgp,"\n#\n");
7868: if(invalidvarcomb[k1]){
7869: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7870: continue;
7871: }
1.227 brouard 7872:
1.241 brouard 7873: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7874: 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 7875: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7876: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7877: k=3;
7878: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7879: if(j==1)
7880: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7881: else
7882: fprintf(ficgp,", '' ");
7883: l=(nlstate+ndeath)*(cpt-1) +j;
7884: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7885: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7886: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7887: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7888: } /* nlstate */
7889: fprintf(ficgp,", '' ");
7890: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7891: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7892: l=(nlstate+ndeath)*(cpt-1) +j;
7893: if(j < nlstate)
7894: fprintf(ficgp,"$%d +",k+l);
7895: else
7896: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7897: }
1.264 brouard 7898: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7899: } /* end cpt state*/
7900: } /* end covariate */
7901: } /* end nres */
1.227 brouard 7902:
1.220 brouard 7903: /* 6eme */
1.202 brouard 7904: /* CV preval stable (period) for each covariate */
1.237 brouard 7905: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7906: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7907: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7908: continue;
1.255 brouard 7909: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7910: strcpy(gplotlabel,"(");
1.288 brouard 7911: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7912: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7913: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7914: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7915: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7916: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7917: vlv= nbcode[Tvaraff[k]][lv];
7918: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7919: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7920: }
1.237 brouard 7921: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7922: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7923: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7924: }
1.264 brouard 7925: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7926: fprintf(ficgp,"\n#\n");
1.223 brouard 7927: if(invalidvarcomb[k1]){
1.227 brouard 7928: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7929: continue;
1.223 brouard 7930: }
1.227 brouard 7931:
1.241 brouard 7932: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7933: 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 7934: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7935: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7936: k=3; /* Offset */
1.255 brouard 7937: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7938: if(i==1)
7939: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7940: else
7941: fprintf(ficgp,", '' ");
1.255 brouard 7942: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7943: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7944: for (j=2; j<= nlstate ; j ++)
7945: fprintf(ficgp,"+$%d",k+l+j-1);
7946: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7947: } /* nlstate */
1.264 brouard 7948: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7949: } /* end cpt state*/
7950: } /* end covariate */
1.227 brouard 7951:
7952:
1.220 brouard 7953: /* 7eme */
1.296 brouard 7954: if(prevbcast == 1){
1.288 brouard 7955: /* CV backward prevalence for each covariate */
1.237 brouard 7956: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7957: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7958: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7959: continue;
1.268 brouard 7960: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7961: strcpy(gplotlabel,"(");
1.288 brouard 7962: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7963: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7964: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7965: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7966: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7967: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7968: vlv= nbcode[Tvaraff[k]][lv];
7969: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7970: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7971: }
1.237 brouard 7972: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7973: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7974: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7975: }
1.264 brouard 7976: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7977: fprintf(ficgp,"\n#\n");
7978: if(invalidvarcomb[k1]){
7979: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7980: continue;
7981: }
7982:
1.241 brouard 7983: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7984: 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 7985: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7986: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7987: k=3; /* Offset */
1.268 brouard 7988: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7989: if(i==1)
7990: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7991: else
7992: fprintf(ficgp,", '' ");
7993: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7994: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7995: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7996: /* 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 7997: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7998: /* for (j=2; j<= nlstate ; j ++) */
7999: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8000: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8001: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8002: } /* nlstate */
1.264 brouard 8003: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8004: } /* end cpt state*/
8005: } /* end covariate */
1.296 brouard 8006: } /* End if prevbcast */
1.218 brouard 8007:
1.223 brouard 8008: /* 8eme */
1.218 brouard 8009: if(prevfcast==1){
1.288 brouard 8010: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8011:
1.237 brouard 8012: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8013: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8014: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8015: continue;
1.211 brouard 8016: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8017: strcpy(gplotlabel,"(");
1.288 brouard 8018: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8019: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8020: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8021: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8022: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8023: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8024: vlv= nbcode[Tvaraff[k]][lv];
8025: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8026: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8027: }
1.237 brouard 8028: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8029: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8030: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8031: }
1.264 brouard 8032: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8033: fprintf(ficgp,"\n#\n");
8034: if(invalidvarcomb[k1]){
8035: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8036: continue;
8037: }
8038:
8039: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8040: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8041: 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 8042: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8043: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8044:
8045: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8046: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8047: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8048: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8049: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8050: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8051: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8052: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8053: if(i==istart){
1.227 brouard 8054: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8055: }else{
8056: fprintf(ficgp,",\\\n '' ");
8057: }
8058: if(cptcoveff ==0){ /* No covariate */
8059: ioffset=2; /* Age is in 2 */
8060: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8061: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8062: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8063: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8064: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8065: if(i==nlstate+1){
1.270 brouard 8066: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8067: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8068: fprintf(ficgp,",\\\n '' ");
8069: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8070: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8071: offyear, \
1.268 brouard 8072: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8073: }else
1.227 brouard 8074: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8075: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8076: }else{ /* more than 2 covariates */
1.270 brouard 8077: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8078: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8079: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8080: iyearc=ioffset-1;
8081: iagec=ioffset;
1.227 brouard 8082: fprintf(ficgp," u %d:(",ioffset);
8083: kl=0;
8084: strcpy(gplotcondition,"(");
8085: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8086: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8087: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8088: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8089: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8090: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8091: kl++;
8092: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8093: kl++;
8094: if(k <cptcoveff && cptcoveff>1)
8095: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8096: }
8097: strcpy(gplotcondition+strlen(gplotcondition),")");
8098: /* 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 *\/ */
8099: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8100: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8101: /* '' 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*/
8102: if(i==nlstate+1){
1.270 brouard 8103: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8104: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8105: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8106: fprintf(ficgp," u %d:(",iagec);
8107: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8108: iyearc, iagec, offyear, \
8109: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8110: /* '' 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 8111: }else{
8112: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8113: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8114: }
8115: } /* end if covariate */
8116: } /* nlstate */
1.264 brouard 8117: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8118: } /* end cpt state*/
8119: } /* end covariate */
8120: } /* End if prevfcast */
1.227 brouard 8121:
1.296 brouard 8122: if(prevbcast==1){
1.268 brouard 8123: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8124:
8125: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8126: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8127: if(m != 1 && TKresult[nres]!= k1)
8128: continue;
8129: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8130: strcpy(gplotlabel,"(");
8131: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
8132: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8133: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8134: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8135: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8136: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8137: vlv= nbcode[Tvaraff[k]][lv];
8138: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8139: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8140: }
8141: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8142: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8143: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8144: }
8145: strcpy(gplotlabel+strlen(gplotlabel),")");
8146: fprintf(ficgp,"\n#\n");
8147: if(invalidvarcomb[k1]){
8148: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8149: continue;
8150: }
8151:
8152: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8153: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8154: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8155: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8156: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8157:
8158: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8159: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8160: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8161: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8162: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8163: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8164: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8165: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8166: if(i==istart){
8167: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8168: }else{
8169: fprintf(ficgp,",\\\n '' ");
8170: }
8171: if(cptcoveff ==0){ /* No covariate */
8172: ioffset=2; /* Age is in 2 */
8173: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8174: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8175: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8176: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8177: fprintf(ficgp," u %d:(", ioffset);
8178: if(i==nlstate+1){
1.270 brouard 8179: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8180: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8181: fprintf(ficgp,",\\\n '' ");
8182: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8183: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8184: offbyear, \
8185: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8186: }else
8187: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8188: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8189: }else{ /* more than 2 covariates */
1.270 brouard 8190: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8191: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8192: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8193: iyearc=ioffset-1;
8194: iagec=ioffset;
1.268 brouard 8195: fprintf(ficgp," u %d:(",ioffset);
8196: kl=0;
8197: strcpy(gplotcondition,"(");
8198: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8199: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8200: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8201: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8202: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8203: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8204: kl++;
8205: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8206: kl++;
8207: if(k <cptcoveff && cptcoveff>1)
8208: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8209: }
8210: strcpy(gplotcondition+strlen(gplotcondition),")");
8211: /* 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 *\/ */
8212: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8213: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8214: /* '' 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*/
8215: if(i==nlstate+1){
1.270 brouard 8216: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8217: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8218: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8219: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8220: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8221: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8222: iyearc,iagec,offbyear, \
8223: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8224: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8225: }else{
8226: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8227: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8228: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8229: }
8230: } /* end if covariate */
8231: } /* nlstate */
8232: fprintf(ficgp,"\nset out; unset label;\n");
8233: } /* end cpt state*/
8234: } /* end covariate */
1.296 brouard 8235: } /* End if prevbcast */
1.268 brouard 8236:
1.227 brouard 8237:
1.238 brouard 8238: /* 9eme writing MLE parameters */
8239: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8240: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8241: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8242: for(k=1; k <=(nlstate+ndeath); k++){
8243: if (k != i) {
1.227 brouard 8244: fprintf(ficgp,"# current state %d\n",k);
8245: for(j=1; j <=ncovmodel; j++){
8246: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8247: jk++;
8248: }
8249: fprintf(ficgp,"\n");
1.126 brouard 8250: }
8251: }
1.223 brouard 8252: }
1.187 brouard 8253: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8254:
1.145 brouard 8255: /*goto avoid;*/
1.238 brouard 8256: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8257: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8258: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8259: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8260: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8261: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8262: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8263: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8264: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8265: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8266: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8267: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8268: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8269: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8270: fprintf(ficgp,"#\n");
1.223 brouard 8271: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8272: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8273: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8274: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8275: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8276: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8277: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8278: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8279: continue;
1.264 brouard 8280: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8281: strcpy(gplotlabel,"(");
1.276 brouard 8282: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8283: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8284: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8285: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8286: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8287: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8288: vlv= nbcode[Tvaraff[k]][lv];
8289: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8290: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8291: }
1.237 brouard 8292: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8293: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8294: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8295: }
1.264 brouard 8296: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8297: fprintf(ficgp,"\n#\n");
1.264 brouard 8298: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8299: fprintf(ficgp,"\nset key outside ");
8300: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8301: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8302: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8303: if (ng==1){
8304: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8305: fprintf(ficgp,"\nunset log y");
8306: }else if (ng==2){
8307: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8308: fprintf(ficgp,"\nset log y");
8309: }else if (ng==3){
8310: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8311: fprintf(ficgp,"\nset log y");
8312: }else
8313: fprintf(ficgp,"\nunset title ");
8314: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8315: i=1;
8316: for(k2=1; k2<=nlstate; k2++) {
8317: k3=i;
8318: for(k=1; k<=(nlstate+ndeath); k++) {
8319: if (k != k2){
8320: switch( ng) {
8321: case 1:
8322: if(nagesqr==0)
8323: fprintf(ficgp," p%d+p%d*x",i,i+1);
8324: else /* nagesqr =1 */
8325: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8326: break;
8327: case 2: /* ng=2 */
8328: if(nagesqr==0)
8329: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8330: else /* nagesqr =1 */
8331: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8332: break;
8333: case 3:
8334: if(nagesqr==0)
8335: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8336: else /* nagesqr =1 */
8337: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8338: break;
8339: }
8340: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8341: ijp=1; /* product no age */
8342: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8343: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8344: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 8345: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8346: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
8347: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8348: if(DummyV[j]==0){
8349: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8350: }else{ /* quantitative */
8351: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8352: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8353: }
8354: ij++;
1.237 brouard 8355: }
1.268 brouard 8356: }
8357: }else if(cptcovprod >0){
8358: if(j==Tprod[ijp]) { /* */
8359: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8360: if(ijp <=cptcovprod) { /* Product */
8361: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8362: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8363: /* 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)]); */
8364: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8365: }else{ /* Vn is dummy and Vm is quanti */
8366: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8367: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8368: }
8369: }else{ /* Vn*Vm Vn is quanti */
8370: if(DummyV[Tvard[ijp][2]]==0){
8371: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8372: }else{ /* Both quanti */
8373: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8374: }
1.237 brouard 8375: }
1.268 brouard 8376: ijp++;
1.237 brouard 8377: }
1.268 brouard 8378: } /* end Tprod */
1.237 brouard 8379: } else{ /* simple covariate */
1.264 brouard 8380: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8381: if(Dummy[j]==0){
8382: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8383: }else{ /* quantitative */
8384: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8385: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8386: }
1.237 brouard 8387: } /* end simple */
8388: } /* end j */
1.223 brouard 8389: }else{
8390: i=i-ncovmodel;
8391: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8392: fprintf(ficgp," (1.");
8393: }
1.227 brouard 8394:
1.223 brouard 8395: if(ng != 1){
8396: fprintf(ficgp,")/(1");
1.227 brouard 8397:
1.264 brouard 8398: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8399: if(nagesqr==0)
1.264 brouard 8400: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8401: else /* nagesqr =1 */
1.264 brouard 8402: 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 8403:
1.223 brouard 8404: ij=1;
8405: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8406: if(cptcovage >0){
8407: if((j-2)==Tage[ij]) { /* Bug valgrind */
8408: if(ij <=cptcovage) { /* Bug valgrind */
8409: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8410: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8411: ij++;
8412: }
8413: }
8414: }else
8415: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/* Valgrind bug nbcode */
1.223 brouard 8416: }
8417: fprintf(ficgp,")");
8418: }
8419: fprintf(ficgp,")");
8420: if(ng ==2)
1.276 brouard 8421: 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 8422: else /* ng= 3 */
1.276 brouard 8423: 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);
1.223 brouard 8424: }else{ /* end ng <> 1 */
8425: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8426: 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 8427: }
8428: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8429: fprintf(ficgp,",");
8430: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8431: fprintf(ficgp,",");
8432: i=i+ncovmodel;
8433: } /* end k */
8434: } /* end k2 */
1.276 brouard 8435: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8436: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8437: } /* end k1 */
1.223 brouard 8438: } /* end ng */
8439: /* avoid: */
8440: fflush(ficgp);
1.126 brouard 8441: } /* end gnuplot */
8442:
8443:
8444: /*************** Moving average **************/
1.219 brouard 8445: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8446: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8447:
1.222 brouard 8448: int i, cpt, cptcod;
8449: int modcovmax =1;
8450: int mobilavrange, mob;
8451: int iage=0;
1.288 brouard 8452: int firstA1=0, firstA2=0;
1.222 brouard 8453:
1.266 brouard 8454: double sum=0., sumr=0.;
1.222 brouard 8455: double age;
1.266 brouard 8456: double *sumnewp, *sumnewm, *sumnewmr;
8457: double *agemingood, *agemaxgood;
8458: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8459:
8460:
1.278 brouard 8461: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8462: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8463:
8464: sumnewp = vector(1,ncovcombmax);
8465: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8466: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8467: agemingood = vector(1,ncovcombmax);
1.266 brouard 8468: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8469: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8470: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8471:
8472: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8473: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8474: sumnewp[cptcod]=0.;
1.266 brouard 8475: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8476: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8477: }
8478: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8479:
1.266 brouard 8480: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8481: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8482: else mobilavrange=mobilav;
8483: for (age=bage; age<=fage; age++)
8484: for (i=1; i<=nlstate;i++)
8485: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8486: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8487: /* We keep the original values on the extreme ages bage, fage and for
8488: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8489: we use a 5 terms etc. until the borders are no more concerned.
8490: */
8491: for (mob=3;mob <=mobilavrange;mob=mob+2){
8492: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8493: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8494: sumnewm[cptcod]=0.;
8495: for (i=1; i<=nlstate;i++){
1.222 brouard 8496: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8497: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8498: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8499: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8500: }
8501: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8502: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8503: } /* end i */
8504: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8505: } /* end cptcod */
1.222 brouard 8506: }/* end age */
8507: }/* end mob */
1.266 brouard 8508: }else{
8509: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8510: return -1;
1.266 brouard 8511: }
8512:
8513: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8514: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8515: if(invalidvarcomb[cptcod]){
8516: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8517: continue;
8518: }
1.219 brouard 8519:
1.266 brouard 8520: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8521: sumnewm[cptcod]=0.;
8522: sumnewmr[cptcod]=0.;
8523: for (i=1; i<=nlstate;i++){
8524: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8525: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8526: }
8527: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8528: agemingoodr[cptcod]=age;
8529: }
8530: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8531: agemingood[cptcod]=age;
8532: }
8533: } /* age */
8534: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8535: sumnewm[cptcod]=0.;
1.266 brouard 8536: sumnewmr[cptcod]=0.;
1.222 brouard 8537: for (i=1; i<=nlstate;i++){
8538: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8539: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8540: }
8541: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8542: agemaxgoodr[cptcod]=age;
1.222 brouard 8543: }
8544: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8545: agemaxgood[cptcod]=age;
8546: }
8547: } /* age */
8548: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8549: /* but they will change */
1.288 brouard 8550: firstA1=0;firstA2=0;
1.266 brouard 8551: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8552: sumnewm[cptcod]=0.;
8553: sumnewmr[cptcod]=0.;
8554: for (i=1; i<=nlstate;i++){
8555: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8556: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8557: }
8558: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8559: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8560: agemaxgoodr[cptcod]=age; /* age min */
8561: for (i=1; i<=nlstate;i++)
8562: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8563: }else{ /* bad we change the value with the values of good ages */
8564: for (i=1; i<=nlstate;i++){
8565: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8566: } /* i */
8567: } /* end bad */
8568: }else{
8569: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8570: agemaxgood[cptcod]=age;
8571: }else{ /* bad we change the value with the values of good ages */
8572: for (i=1; i<=nlstate;i++){
8573: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8574: } /* i */
8575: } /* end bad */
8576: }/* end else */
8577: sum=0.;sumr=0.;
8578: for (i=1; i<=nlstate;i++){
8579: sum+=mobaverage[(int)age][i][cptcod];
8580: sumr+=probs[(int)age][i][cptcod];
8581: }
8582: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8583: if(!firstA1){
8584: firstA1=1;
8585: 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);
8586: }
8587: 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 8588: } /* end bad */
8589: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8590: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8591: if(!firstA2){
8592: firstA2=1;
8593: 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);
8594: }
8595: 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 8596: } /* end bad */
8597: }/* age */
1.266 brouard 8598:
8599: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8600: sumnewm[cptcod]=0.;
1.266 brouard 8601: sumnewmr[cptcod]=0.;
1.222 brouard 8602: for (i=1; i<=nlstate;i++){
8603: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8604: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8605: }
8606: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8607: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8608: agemingoodr[cptcod]=age;
8609: for (i=1; i<=nlstate;i++)
8610: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8611: }else{ /* bad we change the value with the values of good ages */
8612: for (i=1; i<=nlstate;i++){
8613: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8614: } /* i */
8615: } /* end bad */
8616: }else{
8617: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8618: agemingood[cptcod]=age;
8619: }else{ /* bad */
8620: for (i=1; i<=nlstate;i++){
8621: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8622: } /* i */
8623: } /* end bad */
8624: }/* end else */
8625: sum=0.;sumr=0.;
8626: for (i=1; i<=nlstate;i++){
8627: sum+=mobaverage[(int)age][i][cptcod];
8628: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8629: }
1.266 brouard 8630: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8631: 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 8632: } /* end bad */
8633: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8634: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8635: 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 8636: } /* end bad */
8637: }/* age */
1.266 brouard 8638:
1.222 brouard 8639:
8640: for (age=bage; age<=fage; age++){
1.235 brouard 8641: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8642: sumnewp[cptcod]=0.;
8643: sumnewm[cptcod]=0.;
8644: for (i=1; i<=nlstate;i++){
8645: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8646: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8647: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8648: }
8649: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8650: }
8651: /* printf("\n"); */
8652: /* } */
1.266 brouard 8653:
1.222 brouard 8654: /* brutal averaging */
1.266 brouard 8655: /* for (i=1; i<=nlstate;i++){ */
8656: /* for (age=1; age<=bage; age++){ */
8657: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8658: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8659: /* } */
8660: /* for (age=fage; age<=AGESUP; age++){ */
8661: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8662: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8663: /* } */
8664: /* } /\* end i status *\/ */
8665: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8666: /* for (age=1; age<=AGESUP; age++){ */
8667: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8668: /* mobaverage[(int)age][i][cptcod]=0.; */
8669: /* } */
8670: /* } */
1.222 brouard 8671: }/* end cptcod */
1.266 brouard 8672: free_vector(agemaxgoodr,1, ncovcombmax);
8673: free_vector(agemaxgood,1, ncovcombmax);
8674: free_vector(agemingood,1, ncovcombmax);
8675: free_vector(agemingoodr,1, ncovcombmax);
8676: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8677: free_vector(sumnewm,1, ncovcombmax);
8678: free_vector(sumnewp,1, ncovcombmax);
8679: return 0;
8680: }/* End movingaverage */
1.218 brouard 8681:
1.126 brouard 8682:
1.296 brouard 8683:
1.126 brouard 8684: /************** Forecasting ******************/
1.296 brouard 8685: /* 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)*/
8686: 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){
8687: /* dateintemean, mean date of interviews
8688: dateprojd, year, month, day of starting projection
8689: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8690: agemin, agemax range of age
8691: dateprev1 dateprev2 range of dates during which prevalence is computed
8692: */
1.296 brouard 8693: /* double anprojd, mprojd, jprojd; */
8694: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8695: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8696: double agec; /* generic age */
1.296 brouard 8697: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8698: double *popeffectif,*popcount;
8699: double ***p3mat;
1.218 brouard 8700: /* double ***mobaverage; */
1.126 brouard 8701: char fileresf[FILENAMELENGTH];
8702:
8703: agelim=AGESUP;
1.211 brouard 8704: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8705: in each health status at the date of interview (if between dateprev1 and dateprev2).
8706: We still use firstpass and lastpass as another selection.
8707: */
1.214 brouard 8708: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8709: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8710:
1.201 brouard 8711: strcpy(fileresf,"F_");
8712: strcat(fileresf,fileresu);
1.126 brouard 8713: if((ficresf=fopen(fileresf,"w"))==NULL) {
8714: printf("Problem with forecast resultfile: %s\n", fileresf);
8715: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8716: }
1.235 brouard 8717: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8718: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8719:
1.225 brouard 8720: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8721:
8722:
8723: stepsize=(int) (stepm+YEARM-1)/YEARM;
8724: if (stepm<=12) stepsize=1;
8725: if(estepm < stepm){
8726: printf ("Problem %d lower than %d\n",estepm, stepm);
8727: }
1.270 brouard 8728: else{
8729: hstepm=estepm;
8730: }
8731: if(estepm > stepm){ /* Yes every two year */
8732: stepsize=2;
8733: }
1.296 brouard 8734: hstepm=hstepm/stepm;
1.126 brouard 8735:
1.296 brouard 8736:
8737: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8738: /* fractional in yp1 *\/ */
8739: /* aintmean=yp; */
8740: /* yp2=modf((yp1*12),&yp); */
8741: /* mintmean=yp; */
8742: /* yp1=modf((yp2*30.5),&yp); */
8743: /* jintmean=yp; */
8744: /* if(jintmean==0) jintmean=1; */
8745: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8746:
1.296 brouard 8747:
8748: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8749: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8750: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8751: i1=pow(2,cptcoveff);
1.126 brouard 8752: if (cptcovn < 1){i1=1;}
8753:
1.296 brouard 8754: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8755:
8756: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8757:
1.126 brouard 8758: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8759: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8760: for(k=1; k<=i1;k++){
1.253 brouard 8761: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8762: continue;
1.227 brouard 8763: if(invalidvarcomb[k]){
8764: printf("\nCombination (%d) projection ignored because no cases \n",k);
8765: continue;
8766: }
8767: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8768: for(j=1;j<=cptcoveff;j++) {
8769: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8770: }
1.235 brouard 8771: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8772: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8773: }
1.227 brouard 8774: fprintf(ficresf," yearproj age");
8775: for(j=1; j<=nlstate+ndeath;j++){
8776: for(i=1; i<=nlstate;i++)
8777: fprintf(ficresf," p%d%d",i,j);
8778: fprintf(ficresf," wp.%d",j);
8779: }
1.296 brouard 8780: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8781: fprintf(ficresf,"\n");
1.296 brouard 8782: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8783: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8784: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8785: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8786: nhstepm = nhstepm/hstepm;
8787: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8788: oldm=oldms;savm=savms;
1.268 brouard 8789: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8790: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8791: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8792: for (h=0; h<=nhstepm; h++){
8793: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8794: break;
8795: }
8796: }
8797: fprintf(ficresf,"\n");
8798: for(j=1;j<=cptcoveff;j++)
8799: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8800: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8801:
8802: for(j=1; j<=nlstate+ndeath;j++) {
8803: ppij=0.;
8804: for(i=1; i<=nlstate;i++) {
1.278 brouard 8805: if (mobilav>=1)
8806: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8807: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8808: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8809: }
1.268 brouard 8810: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8811: } /* end i */
8812: fprintf(ficresf," %.3f", ppij);
8813: }/* end j */
1.227 brouard 8814: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8815: } /* end agec */
1.266 brouard 8816: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8817: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8818: } /* end yearp */
8819: } /* end k */
1.219 brouard 8820:
1.126 brouard 8821: fclose(ficresf);
1.215 brouard 8822: printf("End of Computing forecasting \n");
8823: fprintf(ficlog,"End of Computing forecasting\n");
8824:
1.126 brouard 8825: }
8826:
1.269 brouard 8827: /************** Back Forecasting ******************/
1.296 brouard 8828: /* 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){ */
8829: 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){
8830: /* back1, year, month, day of starting backprojection
1.267 brouard 8831: agemin, agemax range of age
8832: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8833: anback2 year of end of backprojection (same day and month as back1).
8834: prevacurrent and prev are prevalences.
1.267 brouard 8835: */
8836: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8837: double agec; /* generic age */
1.302 brouard 8838: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 8839: double *popeffectif,*popcount;
8840: double ***p3mat;
8841: /* double ***mobaverage; */
8842: char fileresfb[FILENAMELENGTH];
8843:
1.268 brouard 8844: agelim=AGEINF;
1.267 brouard 8845: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8846: in each health status at the date of interview (if between dateprev1 and dateprev2).
8847: We still use firstpass and lastpass as another selection.
8848: */
8849: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8850: /* firstpass, lastpass, stepm, weightopt, model); */
8851:
8852: /*Do we need to compute prevalence again?*/
8853:
8854: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8855:
8856: strcpy(fileresfb,"FB_");
8857: strcat(fileresfb,fileresu);
8858: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8859: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8860: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8861: }
8862: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8863: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8864:
8865: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8866:
8867:
8868: stepsize=(int) (stepm+YEARM-1)/YEARM;
8869: if (stepm<=12) stepsize=1;
8870: if(estepm < stepm){
8871: printf ("Problem %d lower than %d\n",estepm, stepm);
8872: }
1.270 brouard 8873: else{
8874: hstepm=estepm;
8875: }
8876: if(estepm >= stepm){ /* Yes every two year */
8877: stepsize=2;
8878: }
1.267 brouard 8879:
8880: hstepm=hstepm/stepm;
1.296 brouard 8881: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8882: /* fractional in yp1 *\/ */
8883: /* aintmean=yp; */
8884: /* yp2=modf((yp1*12),&yp); */
8885: /* mintmean=yp; */
8886: /* yp1=modf((yp2*30.5),&yp); */
8887: /* jintmean=yp; */
8888: /* if(jintmean==0) jintmean=1; */
8889: /* if(mintmean==0) jintmean=1; */
1.267 brouard 8890:
8891: i1=pow(2,cptcoveff);
8892: if (cptcovn < 1){i1=1;}
8893:
1.296 brouard 8894: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
8895: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8896:
8897: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8898:
8899: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8900: for(k=1; k<=i1;k++){
8901: if(i1 != 1 && TKresult[nres]!= k)
8902: continue;
8903: if(invalidvarcomb[k]){
8904: printf("\nCombination (%d) projection ignored because no cases \n",k);
8905: continue;
8906: }
1.268 brouard 8907: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8908: for(j=1;j<=cptcoveff;j++) {
8909: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8910: }
8911: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8912: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8913: }
8914: fprintf(ficresfb," yearbproj age");
8915: for(j=1; j<=nlstate+ndeath;j++){
8916: for(i=1; i<=nlstate;i++)
1.268 brouard 8917: fprintf(ficresfb," b%d%d",i,j);
8918: fprintf(ficresfb," b.%d",j);
1.267 brouard 8919: }
1.296 brouard 8920: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 8921: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8922: fprintf(ficresfb,"\n");
1.296 brouard 8923: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 8924: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8925: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8926: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8927: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8928: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8929: nhstepm = nhstepm/hstepm;
8930: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8931: oldm=oldms;savm=savms;
1.268 brouard 8932: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8933: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8934: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8935: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8936: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8937: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8938: for (h=0; h<=nhstepm; h++){
1.268 brouard 8939: if (h*hstepm/YEARM*stepm ==-yearp) {
8940: break;
8941: }
8942: }
8943: fprintf(ficresfb,"\n");
8944: for(j=1;j<=cptcoveff;j++)
8945: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8946: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 8947: for(i=1; i<=nlstate+ndeath;i++) {
8948: ppij=0.;ppi=0.;
8949: for(j=1; j<=nlstate;j++) {
8950: /* if (mobilav==1) */
1.269 brouard 8951: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8952: ppi=ppi+prevacurrent[(int)agec][j][k];
8953: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8954: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8955: /* else { */
8956: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8957: /* } */
1.268 brouard 8958: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8959: } /* end j */
8960: if(ppi <0.99){
8961: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8962: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8963: }
8964: fprintf(ficresfb," %.3f", ppij);
8965: }/* end j */
1.267 brouard 8966: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8967: } /* end agec */
8968: } /* end yearp */
8969: } /* end k */
1.217 brouard 8970:
1.267 brouard 8971: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8972:
1.267 brouard 8973: fclose(ficresfb);
8974: printf("End of Computing Back forecasting \n");
8975: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8976:
1.267 brouard 8977: }
1.217 brouard 8978:
1.269 brouard 8979: /* Variance of prevalence limit: varprlim */
8980: 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 8981: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8982:
8983: char fileresvpl[FILENAMELENGTH];
8984: FILE *ficresvpl;
8985: double **oldm, **savm;
8986: double **varpl; /* Variances of prevalence limits by age */
8987: int i1, k, nres, j ;
8988:
8989: strcpy(fileresvpl,"VPL_");
8990: strcat(fileresvpl,fileresu);
8991: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8992: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8993: exit(0);
8994: }
1.288 brouard 8995: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8996: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8997:
8998: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8999: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9000:
9001: i1=pow(2,cptcoveff);
9002: if (cptcovn < 1){i1=1;}
9003:
9004: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9005: for(k=1; k<=i1;k++){
9006: if(i1 != 1 && TKresult[nres]!= k)
9007: continue;
9008: fprintf(ficresvpl,"\n#****** ");
9009: printf("\n#****** ");
9010: fprintf(ficlog,"\n#****** ");
9011: for(j=1;j<=cptcoveff;j++) {
9012: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9013: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9014: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9015: }
9016: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9017: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9018: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9019: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9020: }
9021: fprintf(ficresvpl,"******\n");
9022: printf("******\n");
9023: fprintf(ficlog,"******\n");
9024:
9025: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9026: oldm=oldms;savm=savms;
9027: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9028: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9029: /*}*/
9030: }
9031:
9032: fclose(ficresvpl);
1.288 brouard 9033: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9034: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9035:
9036: }
9037: /* Variance of back prevalence: varbprlim */
9038: 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){
9039: /*------- Variance of back (stable) prevalence------*/
9040:
9041: char fileresvbl[FILENAMELENGTH];
9042: FILE *ficresvbl;
9043:
9044: double **oldm, **savm;
9045: double **varbpl; /* Variances of back prevalence limits by age */
9046: int i1, k, nres, j ;
9047:
9048: strcpy(fileresvbl,"VBL_");
9049: strcat(fileresvbl,fileresu);
9050: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9051: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9052: exit(0);
9053: }
9054: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9055: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9056:
9057:
9058: i1=pow(2,cptcoveff);
9059: if (cptcovn < 1){i1=1;}
9060:
9061: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9062: for(k=1; k<=i1;k++){
9063: if(i1 != 1 && TKresult[nres]!= k)
9064: continue;
9065: fprintf(ficresvbl,"\n#****** ");
9066: printf("\n#****** ");
9067: fprintf(ficlog,"\n#****** ");
9068: for(j=1;j<=cptcoveff;j++) {
9069: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9070: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9071: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9072: }
9073: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9074: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9075: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9076: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9077: }
9078: fprintf(ficresvbl,"******\n");
9079: printf("******\n");
9080: fprintf(ficlog,"******\n");
9081:
9082: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9083: oldm=oldms;savm=savms;
9084:
9085: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9086: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9087: /*}*/
9088: }
9089:
9090: fclose(ficresvbl);
9091: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9092: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9093:
9094: } /* End of varbprlim */
9095:
1.126 brouard 9096: /************** Forecasting *****not tested NB*************/
1.227 brouard 9097: /* 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 9098:
1.227 brouard 9099: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9100: /* int *popage; */
9101: /* double calagedatem, agelim, kk1, kk2; */
9102: /* double *popeffectif,*popcount; */
9103: /* double ***p3mat,***tabpop,***tabpopprev; */
9104: /* /\* double ***mobaverage; *\/ */
9105: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9106:
1.227 brouard 9107: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9108: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9109: /* agelim=AGESUP; */
9110: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9111:
1.227 brouard 9112: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9113:
9114:
1.227 brouard 9115: /* strcpy(filerespop,"POP_"); */
9116: /* strcat(filerespop,fileresu); */
9117: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9118: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9119: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9120: /* } */
9121: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9122: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9123:
1.227 brouard 9124: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9125:
1.227 brouard 9126: /* /\* if (mobilav!=0) { *\/ */
9127: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9128: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9129: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9130: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9131: /* /\* } *\/ */
9132: /* /\* } *\/ */
1.126 brouard 9133:
1.227 brouard 9134: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9135: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9136:
1.227 brouard 9137: /* agelim=AGESUP; */
1.126 brouard 9138:
1.227 brouard 9139: /* hstepm=1; */
9140: /* hstepm=hstepm/stepm; */
1.218 brouard 9141:
1.227 brouard 9142: /* if (popforecast==1) { */
9143: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9144: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9145: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9146: /* } */
9147: /* popage=ivector(0,AGESUP); */
9148: /* popeffectif=vector(0,AGESUP); */
9149: /* popcount=vector(0,AGESUP); */
1.126 brouard 9150:
1.227 brouard 9151: /* i=1; */
9152: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9153:
1.227 brouard 9154: /* imx=i; */
9155: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9156: /* } */
1.218 brouard 9157:
1.227 brouard 9158: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9159: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9160: /* k=k+1; */
9161: /* fprintf(ficrespop,"\n#******"); */
9162: /* for(j=1;j<=cptcoveff;j++) { */
9163: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9164: /* } */
9165: /* fprintf(ficrespop,"******\n"); */
9166: /* fprintf(ficrespop,"# Age"); */
9167: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9168: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9169:
1.227 brouard 9170: /* for (cpt=0; cpt<=0;cpt++) { */
9171: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9172:
1.227 brouard 9173: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9174: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9175: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9176:
1.227 brouard 9177: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9178: /* oldm=oldms;savm=savms; */
9179: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9180:
1.227 brouard 9181: /* for (h=0; h<=nhstepm; h++){ */
9182: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9183: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9184: /* } */
9185: /* for(j=1; j<=nlstate+ndeath;j++) { */
9186: /* kk1=0.;kk2=0; */
9187: /* for(i=1; i<=nlstate;i++) { */
9188: /* if (mobilav==1) */
9189: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9190: /* else { */
9191: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9192: /* } */
9193: /* } */
9194: /* if (h==(int)(calagedatem+12*cpt)){ */
9195: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9196: /* /\*fprintf(ficrespop," %.3f", kk1); */
9197: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9198: /* } */
9199: /* } */
9200: /* for(i=1; i<=nlstate;i++){ */
9201: /* kk1=0.; */
9202: /* for(j=1; j<=nlstate;j++){ */
9203: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9204: /* } */
9205: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9206: /* } */
1.218 brouard 9207:
1.227 brouard 9208: /* if (h==(int)(calagedatem+12*cpt)) */
9209: /* for(j=1; j<=nlstate;j++) */
9210: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9211: /* } */
9212: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9213: /* } */
9214: /* } */
1.218 brouard 9215:
1.227 brouard 9216: /* /\******\/ */
1.218 brouard 9217:
1.227 brouard 9218: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9219: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9220: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9221: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9222: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9223:
1.227 brouard 9224: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9225: /* oldm=oldms;savm=savms; */
9226: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9227: /* for (h=0; h<=nhstepm; h++){ */
9228: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9229: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9230: /* } */
9231: /* for(j=1; j<=nlstate+ndeath;j++) { */
9232: /* kk1=0.;kk2=0; */
9233: /* for(i=1; i<=nlstate;i++) { */
9234: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9235: /* } */
9236: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9237: /* } */
9238: /* } */
9239: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9240: /* } */
9241: /* } */
9242: /* } */
9243: /* } */
1.218 brouard 9244:
1.227 brouard 9245: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9246:
1.227 brouard 9247: /* if (popforecast==1) { */
9248: /* free_ivector(popage,0,AGESUP); */
9249: /* free_vector(popeffectif,0,AGESUP); */
9250: /* free_vector(popcount,0,AGESUP); */
9251: /* } */
9252: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9253: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9254: /* fclose(ficrespop); */
9255: /* } /\* End of popforecast *\/ */
1.218 brouard 9256:
1.126 brouard 9257: int fileappend(FILE *fichier, char *optionfich)
9258: {
9259: if((fichier=fopen(optionfich,"a"))==NULL) {
9260: printf("Problem with file: %s\n", optionfich);
9261: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9262: return (0);
9263: }
9264: fflush(fichier);
9265: return (1);
9266: }
9267:
9268:
9269: /**************** function prwizard **********************/
9270: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9271: {
9272:
9273: /* Wizard to print covariance matrix template */
9274:
1.164 brouard 9275: char ca[32], cb[32];
9276: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9277: int numlinepar;
9278:
9279: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9280: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9281: for(i=1; i <=nlstate; i++){
9282: jj=0;
9283: for(j=1; j <=nlstate+ndeath; j++){
9284: if(j==i) continue;
9285: jj++;
9286: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9287: printf("%1d%1d",i,j);
9288: fprintf(ficparo,"%1d%1d",i,j);
9289: for(k=1; k<=ncovmodel;k++){
9290: /* printf(" %lf",param[i][j][k]); */
9291: /* fprintf(ficparo," %lf",param[i][j][k]); */
9292: printf(" 0.");
9293: fprintf(ficparo," 0.");
9294: }
9295: printf("\n");
9296: fprintf(ficparo,"\n");
9297: }
9298: }
9299: printf("# Scales (for hessian or gradient estimation)\n");
9300: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9301: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9302: for(i=1; i <=nlstate; i++){
9303: jj=0;
9304: for(j=1; j <=nlstate+ndeath; j++){
9305: if(j==i) continue;
9306: jj++;
9307: fprintf(ficparo,"%1d%1d",i,j);
9308: printf("%1d%1d",i,j);
9309: fflush(stdout);
9310: for(k=1; k<=ncovmodel;k++){
9311: /* printf(" %le",delti3[i][j][k]); */
9312: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9313: printf(" 0.");
9314: fprintf(ficparo," 0.");
9315: }
9316: numlinepar++;
9317: printf("\n");
9318: fprintf(ficparo,"\n");
9319: }
9320: }
9321: printf("# Covariance matrix\n");
9322: /* # 121 Var(a12)\n\ */
9323: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9324: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9325: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9326: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9327: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9328: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9329: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9330: fflush(stdout);
9331: fprintf(ficparo,"# Covariance matrix\n");
9332: /* # 121 Var(a12)\n\ */
9333: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9334: /* # ...\n\ */
9335: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9336:
9337: for(itimes=1;itimes<=2;itimes++){
9338: jj=0;
9339: for(i=1; i <=nlstate; i++){
9340: for(j=1; j <=nlstate+ndeath; j++){
9341: if(j==i) continue;
9342: for(k=1; k<=ncovmodel;k++){
9343: jj++;
9344: ca[0]= k+'a'-1;ca[1]='\0';
9345: if(itimes==1){
9346: printf("#%1d%1d%d",i,j,k);
9347: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9348: }else{
9349: printf("%1d%1d%d",i,j,k);
9350: fprintf(ficparo,"%1d%1d%d",i,j,k);
9351: /* printf(" %.5le",matcov[i][j]); */
9352: }
9353: ll=0;
9354: for(li=1;li <=nlstate; li++){
9355: for(lj=1;lj <=nlstate+ndeath; lj++){
9356: if(lj==li) continue;
9357: for(lk=1;lk<=ncovmodel;lk++){
9358: ll++;
9359: if(ll<=jj){
9360: cb[0]= lk +'a'-1;cb[1]='\0';
9361: if(ll<jj){
9362: if(itimes==1){
9363: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9364: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9365: }else{
9366: printf(" 0.");
9367: fprintf(ficparo," 0.");
9368: }
9369: }else{
9370: if(itimes==1){
9371: printf(" Var(%s%1d%1d)",ca,i,j);
9372: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9373: }else{
9374: printf(" 0.");
9375: fprintf(ficparo," 0.");
9376: }
9377: }
9378: }
9379: } /* end lk */
9380: } /* end lj */
9381: } /* end li */
9382: printf("\n");
9383: fprintf(ficparo,"\n");
9384: numlinepar++;
9385: } /* end k*/
9386: } /*end j */
9387: } /* end i */
9388: } /* end itimes */
9389:
9390: } /* end of prwizard */
9391: /******************* Gompertz Likelihood ******************************/
9392: double gompertz(double x[])
9393: {
1.302 brouard 9394: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9395: int i,n=0; /* n is the size of the sample */
9396:
1.220 brouard 9397: for (i=1;i<=imx ; i++) {
1.126 brouard 9398: sump=sump+weight[i];
9399: /* sump=sump+1;*/
9400: num=num+1;
9401: }
1.302 brouard 9402: L=0.0;
9403: /* agegomp=AGEGOMP; */
1.126 brouard 9404: /* for (i=0; i<=imx; i++)
9405: 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]);*/
9406:
1.302 brouard 9407: for (i=1;i<=imx ; i++) {
9408: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9409: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9410: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9411: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9412: * +
9413: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9414: */
9415: if (wav[i] > 1 || agedc[i] < AGESUP) {
9416: if (cens[i] == 1){
9417: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9418: } else if (cens[i] == 0){
1.126 brouard 9419: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9420: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9421: } else
9422: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9423: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9424: L=L+A*weight[i];
1.126 brouard 9425: /* 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 9426: }
9427: }
1.126 brouard 9428:
1.302 brouard 9429: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9430:
9431: return -2*L*num/sump;
9432: }
9433:
1.136 brouard 9434: #ifdef GSL
9435: /******************* Gompertz_f Likelihood ******************************/
9436: double gompertz_f(const gsl_vector *v, void *params)
9437: {
1.302 brouard 9438: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9439: double *x= (double *) v->data;
9440: int i,n=0; /* n is the size of the sample */
9441:
9442: for (i=0;i<=imx-1 ; i++) {
9443: sump=sump+weight[i];
9444: /* sump=sump+1;*/
9445: num=num+1;
9446: }
9447:
9448:
9449: /* for (i=0; i<=imx; i++)
9450: 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]);*/
9451: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9452: for (i=1;i<=imx ; i++)
9453: {
9454: if (cens[i] == 1 && wav[i]>1)
9455: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9456:
9457: if (cens[i] == 0 && wav[i]>1)
9458: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9459: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9460:
9461: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9462: if (wav[i] > 1 ) { /* ??? */
9463: LL=LL+A*weight[i];
9464: /* 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]);*/
9465: }
9466: }
9467:
9468: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9469: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9470:
9471: return -2*LL*num/sump;
9472: }
9473: #endif
9474:
1.126 brouard 9475: /******************* Printing html file ***********/
1.201 brouard 9476: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9477: int lastpass, int stepm, int weightopt, char model[],\
9478: int imx, double p[],double **matcov,double agemortsup){
9479: int i,k;
9480:
9481: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9482: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9483: for (i=1;i<=2;i++)
9484: 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 9485: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9486: fprintf(fichtm,"</ul>");
9487:
9488: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9489:
9490: 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>");
9491:
9492: for (k=agegomp;k<(agemortsup-2);k++)
9493: 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]);
9494:
9495:
9496: fflush(fichtm);
9497: }
9498:
9499: /******************* Gnuplot file **************/
1.201 brouard 9500: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9501:
9502: char dirfileres[132],optfileres[132];
1.164 brouard 9503:
1.126 brouard 9504: int ng;
9505:
9506:
9507: /*#ifdef windows */
9508: fprintf(ficgp,"cd \"%s\" \n",pathc);
9509: /*#endif */
9510:
9511:
9512: strcpy(dirfileres,optionfilefiname);
9513: strcpy(optfileres,"vpl");
1.199 brouard 9514: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9515: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9516: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9517: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9518: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9519:
9520: }
9521:
1.136 brouard 9522: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9523: {
1.126 brouard 9524:
1.136 brouard 9525: /*-------- data file ----------*/
9526: FILE *fic;
9527: char dummy[]=" ";
1.240 brouard 9528: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9529: int lstra;
1.136 brouard 9530: int linei, month, year,iout;
1.302 brouard 9531: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9532: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9533: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9534: char *stratrunc;
1.223 brouard 9535:
1.240 brouard 9536: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9537: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9538:
1.240 brouard 9539: for(v=1; v <=ncovcol;v++){
9540: DummyV[v]=0;
9541: FixedV[v]=0;
9542: }
9543: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9544: DummyV[v]=1;
9545: FixedV[v]=0;
9546: }
9547: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9548: DummyV[v]=0;
9549: FixedV[v]=1;
9550: }
9551: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9552: DummyV[v]=1;
9553: FixedV[v]=1;
9554: }
9555: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9556: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9557: 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]);
9558: }
1.126 brouard 9559:
1.136 brouard 9560: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9561: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9562: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9563: }
1.126 brouard 9564:
1.302 brouard 9565: /* Is it a BOM UTF-8 Windows file? */
9566: /* First data line */
9567: linei=0;
9568: while(fgets(line, MAXLINE, fic)) {
9569: noffset=0;
9570: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9571: {
9572: noffset=noffset+3;
9573: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9574: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9575: fflush(ficlog); return 1;
9576: }
9577: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9578: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9579: {
9580: noffset=noffset+2;
1.304 brouard 9581: 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);
9582: 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 9583: fflush(ficlog); return 1;
9584: }
9585: else if( line[0] == 0 && line[1] == 0)
9586: {
9587: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9588: noffset=noffset+4;
1.304 brouard 9589: 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);
9590: 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 9591: fflush(ficlog); return 1;
9592: }
9593: } else{
9594: ;/*printf(" Not a BOM file\n");*/
9595: }
9596: /* If line starts with a # it is a comment */
9597: if (line[noffset] == '#') {
9598: linei=linei+1;
9599: break;
9600: }else{
9601: break;
9602: }
9603: }
9604: fclose(fic);
9605: if((fic=fopen(datafile,"r"))==NULL) {
9606: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9607: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9608: }
9609: /* Not a Bom file */
9610:
1.136 brouard 9611: i=1;
9612: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9613: linei=linei+1;
9614: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9615: if(line[j] == '\t')
9616: line[j] = ' ';
9617: }
9618: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9619: ;
9620: };
9621: line[j+1]=0; /* Trims blanks at end of line */
9622: if(line[0]=='#'){
9623: fprintf(ficlog,"Comment line\n%s\n",line);
9624: printf("Comment line\n%s\n",line);
9625: continue;
9626: }
9627: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9628: strcpy(line, linetmp);
1.223 brouard 9629:
9630: /* Loops on waves */
9631: for (j=maxwav;j>=1;j--){
9632: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9633: cutv(stra, strb, line, ' ');
9634: if(strb[0]=='.') { /* Missing value */
9635: lval=-1;
9636: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9637: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9638: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9639: 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);
9640: 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);
9641: return 1;
9642: }
9643: }else{
9644: errno=0;
9645: /* what_kind_of_number(strb); */
9646: dval=strtod(strb,&endptr);
9647: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9648: /* if(strb != endptr && *endptr == '\0') */
9649: /* dval=dlval; */
9650: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9651: if( strb[0]=='\0' || (*endptr != '\0')){
9652: 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);
9653: 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);
9654: return 1;
9655: }
9656: cotqvar[j][iv][i]=dval;
9657: cotvar[j][ntv+iv][i]=dval;
9658: }
9659: strcpy(line,stra);
1.223 brouard 9660: }/* end loop ntqv */
1.225 brouard 9661:
1.223 brouard 9662: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9663: cutv(stra, strb, line, ' ');
9664: if(strb[0]=='.') { /* Missing value */
9665: lval=-1;
9666: }else{
9667: errno=0;
9668: lval=strtol(strb,&endptr,10);
9669: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9670: if( strb[0]=='\0' || (*endptr != '\0')){
9671: 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);
9672: 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);
9673: return 1;
9674: }
9675: }
9676: if(lval <-1 || lval >1){
9677: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9678: 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 9679: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9680: For example, for multinomial values like 1, 2 and 3,\n \
9681: build V1=0 V2=0 for the reference value (1),\n \
9682: V1=1 V2=0 for (2) \n \
1.223 brouard 9683: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9684: output of IMaCh is often meaningless.\n \
1.319 brouard 9685: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 9686: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9687: 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 9688: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9689: For example, for multinomial values like 1, 2 and 3,\n \
9690: build V1=0 V2=0 for the reference value (1),\n \
9691: V1=1 V2=0 for (2) \n \
1.223 brouard 9692: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9693: output of IMaCh is often meaningless.\n \
1.319 brouard 9694: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 9695: return 1;
9696: }
9697: cotvar[j][iv][i]=(double)(lval);
9698: strcpy(line,stra);
1.223 brouard 9699: }/* end loop ntv */
1.225 brouard 9700:
1.223 brouard 9701: /* Statuses at wave */
1.137 brouard 9702: cutv(stra, strb, line, ' ');
1.223 brouard 9703: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9704: lval=-1;
1.136 brouard 9705: }else{
1.238 brouard 9706: errno=0;
9707: lval=strtol(strb,&endptr,10);
9708: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9709: if( strb[0]=='\0' || (*endptr != '\0')){
9710: 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);
9711: 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);
9712: return 1;
9713: }
1.136 brouard 9714: }
1.225 brouard 9715:
1.136 brouard 9716: s[j][i]=lval;
1.225 brouard 9717:
1.223 brouard 9718: /* Date of Interview */
1.136 brouard 9719: strcpy(line,stra);
9720: cutv(stra, strb,line,' ');
1.169 brouard 9721: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9722: }
1.169 brouard 9723: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9724: month=99;
9725: year=9999;
1.136 brouard 9726: }else{
1.225 brouard 9727: 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);
9728: 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);
9729: return 1;
1.136 brouard 9730: }
9731: anint[j][i]= (double) year;
1.302 brouard 9732: mint[j][i]= (double)month;
9733: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
9734: /* 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]); */
9735: /* 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]); */
9736: /* } */
1.136 brouard 9737: strcpy(line,stra);
1.223 brouard 9738: } /* End loop on waves */
1.225 brouard 9739:
1.223 brouard 9740: /* Date of death */
1.136 brouard 9741: cutv(stra, strb,line,' ');
1.169 brouard 9742: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9743: }
1.169 brouard 9744: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9745: month=99;
9746: year=9999;
9747: }else{
1.141 brouard 9748: 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 9749: 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);
9750: return 1;
1.136 brouard 9751: }
9752: andc[i]=(double) year;
9753: moisdc[i]=(double) month;
9754: strcpy(line,stra);
9755:
1.223 brouard 9756: /* Date of birth */
1.136 brouard 9757: cutv(stra, strb,line,' ');
1.169 brouard 9758: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9759: }
1.169 brouard 9760: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9761: month=99;
9762: year=9999;
9763: }else{
1.141 brouard 9764: 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);
9765: 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 9766: return 1;
1.136 brouard 9767: }
9768: if (year==9999) {
1.141 brouard 9769: 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);
9770: 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 9771: return 1;
9772:
1.136 brouard 9773: }
9774: annais[i]=(double)(year);
1.302 brouard 9775: moisnais[i]=(double)(month);
9776: for (j=1;j<=maxwav;j++){
9777: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
9778: 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]);
9779: 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]);
9780: }
9781: }
9782:
1.136 brouard 9783: strcpy(line,stra);
1.225 brouard 9784:
1.223 brouard 9785: /* Sample weight */
1.136 brouard 9786: cutv(stra, strb,line,' ');
9787: errno=0;
9788: dval=strtod(strb,&endptr);
9789: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9790: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9791: 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 9792: fflush(ficlog);
9793: return 1;
9794: }
9795: weight[i]=dval;
9796: strcpy(line,stra);
1.225 brouard 9797:
1.223 brouard 9798: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9799: cutv(stra, strb, line, ' ');
9800: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9801: lval=-1;
1.311 brouard 9802: coqvar[iv][i]=NAN;
9803: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 9804: }else{
1.225 brouard 9805: errno=0;
9806: /* what_kind_of_number(strb); */
9807: dval=strtod(strb,&endptr);
9808: /* if(strb != endptr && *endptr == '\0') */
9809: /* dval=dlval; */
9810: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9811: if( strb[0]=='\0' || (*endptr != '\0')){
9812: 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);
9813: 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);
9814: return 1;
9815: }
9816: coqvar[iv][i]=dval;
1.226 brouard 9817: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9818: }
9819: strcpy(line,stra);
9820: }/* end loop nqv */
1.136 brouard 9821:
1.223 brouard 9822: /* Covariate values */
1.136 brouard 9823: for (j=ncovcol;j>=1;j--){
9824: cutv(stra, strb,line,' ');
1.223 brouard 9825: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9826: lval=-1;
1.136 brouard 9827: }else{
1.225 brouard 9828: errno=0;
9829: lval=strtol(strb,&endptr,10);
9830: if( strb[0]=='\0' || (*endptr != '\0')){
9831: 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);
9832: 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);
9833: return 1;
9834: }
1.136 brouard 9835: }
9836: if(lval <-1 || lval >1){
1.225 brouard 9837: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9838: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9839: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9840: For example, for multinomial values like 1, 2 and 3,\n \
9841: build V1=0 V2=0 for the reference value (1),\n \
9842: V1=1 V2=0 for (2) \n \
1.136 brouard 9843: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9844: output of IMaCh is often meaningless.\n \
1.136 brouard 9845: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9846: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9847: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9848: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9849: For example, for multinomial values like 1, 2 and 3,\n \
9850: build V1=0 V2=0 for the reference value (1),\n \
9851: V1=1 V2=0 for (2) \n \
1.136 brouard 9852: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9853: output of IMaCh is often meaningless.\n \
1.136 brouard 9854: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9855: return 1;
1.136 brouard 9856: }
9857: covar[j][i]=(double)(lval);
9858: strcpy(line,stra);
9859: }
9860: lstra=strlen(stra);
1.225 brouard 9861:
1.136 brouard 9862: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9863: stratrunc = &(stra[lstra-9]);
9864: num[i]=atol(stratrunc);
9865: }
9866: else
9867: num[i]=atol(stra);
9868: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9869: 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;}*/
9870:
9871: i=i+1;
9872: } /* End loop reading data */
1.225 brouard 9873:
1.136 brouard 9874: *imax=i-1; /* Number of individuals */
9875: fclose(fic);
1.225 brouard 9876:
1.136 brouard 9877: return (0);
1.164 brouard 9878: /* endread: */
1.225 brouard 9879: printf("Exiting readdata: ");
9880: fclose(fic);
9881: return (1);
1.223 brouard 9882: }
1.126 brouard 9883:
1.234 brouard 9884: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9885: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9886: while (*p2 == ' ')
1.234 brouard 9887: p2++;
9888: /* while ((*p1++ = *p2++) !=0) */
9889: /* ; */
9890: /* do */
9891: /* while (*p2 == ' ') */
9892: /* p2++; */
9893: /* while (*p1++ == *p2++); */
9894: *stri=p2;
1.145 brouard 9895: }
9896:
1.235 brouard 9897: int decoderesult ( char resultline[], int nres)
1.230 brouard 9898: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9899: {
1.235 brouard 9900: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9901: char resultsav[MAXLINE];
1.234 brouard 9902: int resultmodel[MAXLINE];
9903: int modelresult[MAXLINE];
1.230 brouard 9904: char stra[80], strb[80], strc[80], strd[80],stre[80];
9905:
1.234 brouard 9906: removefirstspace(&resultline);
1.230 brouard 9907:
9908: if (strstr(resultline,"v") !=0){
9909: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9910: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9911: return 1;
9912: }
9913: trimbb(resultsav, resultline);
9914: if (strlen(resultsav) >1){
9915: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9916: }
1.253 brouard 9917: if(j == 0){ /* Resultline but no = */
9918: TKresult[nres]=0; /* Combination for the nresult and the model */
9919: return (0);
9920: }
1.234 brouard 9921: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.318 brouard 9922: printf("ERROR: the number of variables in this result line, %d, differs from the number of variables used in the model line, %d.\n",j, cptcovs);
1.310 brouard 9923: fprintf(ficlog,"ERROR: the number of variables in the resultline, %d, differs from the number of variables used in the model line, %d.\n",j, cptcovs);
1.234 brouard 9924: }
9925: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9926: if(nbocc(resultsav,'=') >1){
1.318 brouard 9927: 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" */
9928: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.234 brouard 9929: }else
9930: cutl(strc,strd,resultsav,'=');
1.318 brouard 9931: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 9932:
1.230 brouard 9933: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 9934: 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 9935: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9936: /* cptcovsel++; */
9937: if (nbocc(stra,'=') >0)
9938: strcpy(resultsav,stra); /* and analyzes it */
9939: }
1.235 brouard 9940: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 9941: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on model. model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9942: if(Typevar[k1]==0){ /* Single covariate in model *//*0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 9943: match=0;
1.318 brouard 9944: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9945: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9946: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 9947: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 9948: break;
9949: }
9950: }
9951: if(match == 0){
1.310 brouard 9952: printf("Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9953: fprintf(ficlog,"Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9954: return 1;
1.234 brouard 9955: }
9956: }
9957: }
1.235 brouard 9958: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 9959: for(k2=1; k2 <=j;k2++){ /* Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9960: match=0;
1.318 brouard 9961: for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.235 brouard 9962: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9963: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.318 brouard 9964: resultmodel[k1]=k2; /* k2th variable of the model corresponds to k1 variable of the model. resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9965: ++match;
9966: }
9967: }
9968: }
9969: if(match == 0){
9970: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
1.310 brouard 9971: fprintf(ficlog,"Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9972: return 1;
1.234 brouard 9973: }else if(match > 1){
9974: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 9975: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9976: return 1;
1.234 brouard 9977: }
9978: }
1.235 brouard 9979:
1.234 brouard 9980: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9981: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9982: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9983: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9984: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9985: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9986: /* 1 0 0 0 */
9987: /* 2 1 0 0 */
9988: /* 3 0 1 0 */
9989: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9990: /* 5 0 0 1 */
9991: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9992: /* 7 0 1 1 */
9993: /* 8 1 1 1 */
1.237 brouard 9994: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9995: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9996: /* V5*age V5 known which value for nres? */
9997: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.318 brouard 9998: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* loop on model line */
1.235 brouard 9999: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 10000: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 10001: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
10002: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 10003: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
10004: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
10005: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 10006: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
10007: k4++;;
10008: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
1.318 brouard 10009: k3q= resultmodel[k1]; /* resultmodel[1(V5)] = 25.1=k3q */
10010: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.237 brouard 10011: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10012: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
10013: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 10014: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
10015: k4q++;;
10016: }
10017: }
1.234 brouard 10018:
1.235 brouard 10019: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 10020: return (0);
10021: }
1.235 brouard 10022:
1.230 brouard 10023: int decodemodel( char model[], int lastobs)
10024: /**< This routine decodes the model and returns:
1.224 brouard 10025: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10026: * - nagesqr = 1 if age*age in the model, otherwise 0.
10027: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10028: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10029: * - cptcovage number of covariates with age*products =2
10030: * - cptcovs number of simple covariates
10031: * - 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
10032: * which is a new column after the 9 (ncovcol) variables.
1.319 brouard 10033: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10034: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10035: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10036: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10037: */
1.319 brouard 10038: /* 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 10039: {
1.238 brouard 10040: int i, j, k, ks, v;
1.227 brouard 10041: int j1, k1, k2, k3, k4;
1.136 brouard 10042: char modelsav[80];
1.145 brouard 10043: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10044: char *strpt;
1.136 brouard 10045:
1.145 brouard 10046: /*removespace(model);*/
1.136 brouard 10047: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10048: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10049: if (strstr(model,"AGE") !=0){
1.192 brouard 10050: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10051: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10052: return 1;
10053: }
1.141 brouard 10054: if (strstr(model,"v") !=0){
10055: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
10056: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
10057: return 1;
10058: }
1.187 brouard 10059: strcpy(modelsav,model);
10060: if ((strpt=strstr(model,"age*age")) !=0){
10061: printf(" strpt=%s, model=%s\n",strpt, model);
10062: if(strpt != model){
1.234 brouard 10063: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10064: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10065: corresponding column of parameters.\n",model);
1.234 brouard 10066: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10067: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10068: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10069: return 1;
1.225 brouard 10070: }
1.187 brouard 10071: nagesqr=1;
10072: if (strstr(model,"+age*age") !=0)
1.234 brouard 10073: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10074: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10075: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10076: else
1.234 brouard 10077: substrchaine(modelsav, model, "age*age");
1.187 brouard 10078: }else
10079: nagesqr=0;
10080: if (strlen(modelsav) >1){
10081: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10082: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10083: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10084: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10085: * cst, age and age*age
10086: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10087: /* including age products which are counted in cptcovage.
10088: * but the covariates which are products must be treated
10089: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10090: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10091: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10092:
10093:
1.187 brouard 10094: /* Design
10095: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10096: * < ncovcol=8 >
10097: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10098: * k= 1 2 3 4 5 6 7 8
10099: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10100: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10101: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10102: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10103: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10104: * Tage[++cptcovage]=k
10105: * if products, new covar are created after ncovcol with k1
10106: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10107: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10108: * 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
10109: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10110: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10111: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10112: * < ncovcol=8 >
10113: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10114: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10115: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10116: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10117: * p Tprod[1]@2={ 6, 5}
10118: *p Tvard[1][1]@4= {7, 8, 5, 6}
10119: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10120: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10121: *How to reorganize? Tvars(orted)
1.187 brouard 10122: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10123: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10124: * {2, 1, 4, 8, 5, 6, 3, 7}
10125: * Struct []
10126: */
1.225 brouard 10127:
1.187 brouard 10128: /* This loop fills the array Tvar from the string 'model'.*/
10129: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10130: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10131: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10132: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10133: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10134: /* k=1 Tvar[1]=2 (from V2) */
10135: /* k=5 Tvar[5] */
10136: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10137: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10138: /* } */
1.198 brouard 10139: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10140: /*
10141: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10142: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10143: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10144: }
1.187 brouard 10145: cptcovage=0;
1.319 brouard 10146: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10147: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10148: 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" */
10149: if (nbocc(modelsav,'+')==0)
10150: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10151: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10152: /*scanf("%d",i);*/
1.319 brouard 10153: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10154: 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 10155: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10156: /* covar is not filled and then is empty */
10157: cptcovprod--;
10158: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10159: 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 10160: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10161: cptcovage++; /* Counts the number of covariates which include age as a product */
10162: 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 10163: /*printf("stre=%s ", stre);*/
10164: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10165: cptcovprod--;
10166: cutl(stre,strb,strc,'V');
10167: Tvar[k]=atoi(stre);
10168: Typevar[k]=1; /* 1 for age product */
10169: cptcovage++;
10170: Tage[cptcovage]=k;
10171: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10172: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10173: cptcovn++;
10174: cptcovprodnoage++;k1++;
10175: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10176: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10177: because this model-covariate is a construction we invent a new column
10178: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.319 brouard 10179: If already ncovcol=4 and model=V2 + V1 +V1*V4 +age*V3 +V3*V2
10180: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
10181: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */
1.234 brouard 10182: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10183: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10184: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10185: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10186: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
10187: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
10188: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10189: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10190: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10191: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10192: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10193: for (i=1; i<=lastobs;i++){
10194: /* Computes the new covariate which is a product of
10195: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10196: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10197: }
10198: } /* End age is not in the model */
10199: } /* End if model includes a product */
1.319 brouard 10200: else { /* not a product */
1.234 brouard 10201: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10202: /* scanf("%d",i);*/
10203: cutl(strd,strc,strb,'V');
10204: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10205: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10206: Tvar[k]=atoi(strd);
10207: Typevar[k]=0; /* 0 for simple covariates */
10208: }
10209: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10210: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10211: scanf("%d",i);*/
1.187 brouard 10212: } /* end of loop + on total covariates */
10213: } /* end if strlen(modelsave == 0) age*age might exist */
10214: } /* end if strlen(model == 0) */
1.136 brouard 10215:
10216: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10217: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10218:
1.136 brouard 10219: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10220: printf("cptcovprod=%d ", cptcovprod);
10221: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10222: scanf("%d ",i);*/
10223:
10224:
1.230 brouard 10225: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10226: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10227: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10228: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10229: k = 1 2 3 4 5 6 7 8 9
10230: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 10231: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 10232: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10233: Dummy[k] 1 0 0 0 3 1 1 2 3
10234: Tmodelind[combination of covar]=k;
1.225 brouard 10235: */
10236: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10237: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10238: /* 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 10239: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 10240: printf("Model=1+age+%s\n\
1.227 brouard 10241: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10242: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10243: 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 10244: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10245: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10246: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10247: 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 10248: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10249: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0;k<=cptcovt; k++){ /* or cptocvt */
10250: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10251: Fixed[k]= 0;
10252: Dummy[k]= 0;
1.225 brouard 10253: ncoveff++;
1.232 brouard 10254: ncovf++;
1.234 brouard 10255: nsd++;
10256: modell[k].maintype= FTYPE;
10257: TvarsD[nsd]=Tvar[k];
10258: TvarsDind[nsd]=k;
10259: TvarF[ncovf]=Tvar[k];
10260: TvarFind[ncovf]=k;
10261: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10262: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10263: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10264: Fixed[k]= 0;
10265: Dummy[k]= 0;
10266: ncoveff++;
10267: ncovf++;
10268: modell[k].maintype= FTYPE;
10269: TvarF[ncovf]=Tvar[k];
10270: TvarFind[ncovf]=k;
1.230 brouard 10271: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10272: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10273: }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 10274: Fixed[k]= 0;
10275: Dummy[k]= 1;
1.230 brouard 10276: nqfveff++;
1.234 brouard 10277: modell[k].maintype= FTYPE;
10278: modell[k].subtype= FQ;
10279: nsq++;
10280: TvarsQ[nsq]=Tvar[k];
10281: TvarsQind[nsq]=k;
1.232 brouard 10282: ncovf++;
1.234 brouard 10283: TvarF[ncovf]=Tvar[k];
10284: TvarFind[ncovf]=k;
1.231 brouard 10285: 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 10286: 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 10287: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10288: Fixed[k]= 1;
10289: Dummy[k]= 0;
1.225 brouard 10290: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10291: modell[k].maintype= VTYPE;
10292: modell[k].subtype= VD;
10293: nsd++;
10294: TvarsD[nsd]=Tvar[k];
10295: TvarsDind[nsd]=k;
10296: ncovv++; /* Only simple time varying variables */
10297: TvarV[ncovv]=Tvar[k];
1.242 brouard 10298: 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 10299: 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 */
10300: 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 10301: 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);
10302: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10303: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10304: Fixed[k]= 1;
10305: Dummy[k]= 1;
10306: nqtveff++;
10307: modell[k].maintype= VTYPE;
10308: modell[k].subtype= VQ;
10309: ncovv++; /* Only simple time varying variables */
10310: nsq++;
1.319 brouard 10311: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */
1.234 brouard 10312: TvarsQind[nsq]=k;
10313: TvarV[ncovv]=Tvar[k];
1.242 brouard 10314: 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 10315: 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 */
10316: 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 10317: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10318: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10319: 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 10320: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10321: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10322: ncova++;
10323: TvarA[ncova]=Tvar[k];
10324: TvarAind[ncova]=k;
1.231 brouard 10325: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10326: Fixed[k]= 2;
10327: Dummy[k]= 2;
10328: modell[k].maintype= ATYPE;
10329: modell[k].subtype= APFD;
10330: /* ncoveff++; */
1.227 brouard 10331: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10332: Fixed[k]= 2;
10333: Dummy[k]= 3;
10334: modell[k].maintype= ATYPE;
10335: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10336: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10337: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10338: Fixed[k]= 3;
10339: Dummy[k]= 2;
10340: modell[k].maintype= ATYPE;
10341: modell[k].subtype= APVD; /* Product age * varying dummy */
10342: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10343: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10344: Fixed[k]= 3;
10345: Dummy[k]= 3;
10346: modell[k].maintype= ATYPE;
10347: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10348: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10349: }
10350: }else if (Typevar[k] == 2) { /* product without age */
10351: k1=Tposprod[k];
10352: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10353: if(Tvard[k1][2] <=ncovcol){
10354: Fixed[k]= 1;
10355: Dummy[k]= 0;
10356: modell[k].maintype= FTYPE;
10357: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10358: ncovf++; /* Fixed variables without age */
10359: TvarF[ncovf]=Tvar[k];
10360: TvarFind[ncovf]=k;
10361: }else if(Tvard[k1][2] <=ncovcol+nqv){
10362: Fixed[k]= 0; /* or 2 ?*/
10363: Dummy[k]= 1;
10364: modell[k].maintype= FTYPE;
10365: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10366: ncovf++; /* Varying variables without age */
10367: TvarF[ncovf]=Tvar[k];
10368: TvarFind[ncovf]=k;
10369: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10370: Fixed[k]= 1;
10371: Dummy[k]= 0;
10372: modell[k].maintype= VTYPE;
10373: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10374: ncovv++; /* Varying variables without age */
10375: TvarV[ncovv]=Tvar[k];
10376: TvarVind[ncovv]=k;
10377: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10378: Fixed[k]= 1;
10379: Dummy[k]= 1;
10380: modell[k].maintype= VTYPE;
10381: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10382: ncovv++; /* Varying variables without age */
10383: TvarV[ncovv]=Tvar[k];
10384: TvarVind[ncovv]=k;
10385: }
1.227 brouard 10386: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10387: if(Tvard[k1][2] <=ncovcol){
10388: Fixed[k]= 0; /* or 2 ?*/
10389: Dummy[k]= 1;
10390: modell[k].maintype= FTYPE;
10391: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10392: ncovf++; /* Fixed variables without age */
10393: TvarF[ncovf]=Tvar[k];
10394: TvarFind[ncovf]=k;
10395: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10396: Fixed[k]= 1;
10397: Dummy[k]= 1;
10398: modell[k].maintype= VTYPE;
10399: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10400: ncovv++; /* Varying variables without age */
10401: TvarV[ncovv]=Tvar[k];
10402: TvarVind[ncovv]=k;
10403: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10404: Fixed[k]= 1;
10405: Dummy[k]= 1;
10406: modell[k].maintype= VTYPE;
10407: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10408: ncovv++; /* Varying variables without age */
10409: TvarV[ncovv]=Tvar[k];
10410: TvarVind[ncovv]=k;
10411: ncovv++; /* Varying variables without age */
10412: TvarV[ncovv]=Tvar[k];
10413: TvarVind[ncovv]=k;
10414: }
1.227 brouard 10415: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10416: if(Tvard[k1][2] <=ncovcol){
10417: Fixed[k]= 1;
10418: Dummy[k]= 1;
10419: modell[k].maintype= VTYPE;
10420: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10421: ncovv++; /* Varying variables without age */
10422: TvarV[ncovv]=Tvar[k];
10423: TvarVind[ncovv]=k;
10424: }else if(Tvard[k1][2] <=ncovcol+nqv){
10425: Fixed[k]= 1;
10426: Dummy[k]= 1;
10427: modell[k].maintype= VTYPE;
10428: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10429: ncovv++; /* Varying variables without age */
10430: TvarV[ncovv]=Tvar[k];
10431: TvarVind[ncovv]=k;
10432: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10433: Fixed[k]= 1;
10434: Dummy[k]= 0;
10435: modell[k].maintype= VTYPE;
10436: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10437: ncovv++; /* Varying variables without age */
10438: TvarV[ncovv]=Tvar[k];
10439: TvarVind[ncovv]=k;
10440: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10441: Fixed[k]= 1;
10442: Dummy[k]= 1;
10443: modell[k].maintype= VTYPE;
10444: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10445: ncovv++; /* Varying variables without age */
10446: TvarV[ncovv]=Tvar[k];
10447: TvarVind[ncovv]=k;
10448: }
1.227 brouard 10449: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10450: if(Tvard[k1][2] <=ncovcol){
10451: Fixed[k]= 1;
10452: Dummy[k]= 1;
10453: modell[k].maintype= VTYPE;
10454: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10455: ncovv++; /* Varying variables without age */
10456: TvarV[ncovv]=Tvar[k];
10457: TvarVind[ncovv]=k;
10458: }else if(Tvard[k1][2] <=ncovcol+nqv){
10459: Fixed[k]= 1;
10460: Dummy[k]= 1;
10461: modell[k].maintype= VTYPE;
10462: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10463: ncovv++; /* Varying variables without age */
10464: TvarV[ncovv]=Tvar[k];
10465: TvarVind[ncovv]=k;
10466: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10467: Fixed[k]= 1;
10468: Dummy[k]= 1;
10469: modell[k].maintype= VTYPE;
10470: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10471: ncovv++; /* Varying variables without age */
10472: TvarV[ncovv]=Tvar[k];
10473: TvarVind[ncovv]=k;
10474: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10475: Fixed[k]= 1;
10476: Dummy[k]= 1;
10477: modell[k].maintype= VTYPE;
10478: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10479: ncovv++; /* Varying variables without age */
10480: TvarV[ncovv]=Tvar[k];
10481: TvarVind[ncovv]=k;
10482: }
1.227 brouard 10483: }else{
1.240 brouard 10484: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10485: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10486: } /*end k1*/
1.225 brouard 10487: }else{
1.226 brouard 10488: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10489: 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 10490: }
1.227 brouard 10491: 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 10492: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10493: 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]);
10494: }
10495: /* Searching for doublons in the model */
10496: for(k1=1; k1<= cptcovt;k1++){
10497: for(k2=1; k2 <k1;k2++){
1.285 brouard 10498: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10499: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10500: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10501: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10502: printf("Error duplication in the model=%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]);
10503: fprintf(ficlog,"Error duplication in the model=%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 10504: return(1);
10505: }
10506: }else if (Typevar[k1] ==2){
10507: k3=Tposprod[k1];
10508: k4=Tposprod[k2];
10509: 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])) ){
10510: printf("Error duplication in the model=%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]]);
10511: fprintf(ficlog,"Error duplication in the model=%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);
10512: return(1);
10513: }
10514: }
1.227 brouard 10515: }
10516: }
1.225 brouard 10517: }
10518: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10519: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10520: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10521: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10522: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10523: /*endread:*/
1.225 brouard 10524: printf("Exiting decodemodel: ");
10525: return (1);
1.136 brouard 10526: }
10527:
1.169 brouard 10528: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10529: {/* Check ages at death */
1.136 brouard 10530: int i, m;
1.218 brouard 10531: int firstone=0;
10532:
1.136 brouard 10533: for (i=1; i<=imx; i++) {
10534: for(m=2; (m<= maxwav); m++) {
10535: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10536: anint[m][i]=9999;
1.216 brouard 10537: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10538: s[m][i]=-1;
1.136 brouard 10539: }
10540: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10541: *nberr = *nberr + 1;
1.218 brouard 10542: if(firstone == 0){
10543: firstone=1;
1.260 brouard 10544: 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 10545: }
1.262 brouard 10546: 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 10547: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10548: }
10549: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10550: (*nberr)++;
1.259 brouard 10551: 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 10552: 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 10553: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10554: }
10555: }
10556: }
10557:
10558: for (i=1; i<=imx; i++) {
10559: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10560: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10561: 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 10562: if (s[m][i] >= nlstate+1) {
1.169 brouard 10563: if(agedc[i]>0){
10564: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10565: agev[m][i]=agedc[i];
1.214 brouard 10566: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10567: }else {
1.136 brouard 10568: if ((int)andc[i]!=9999){
10569: nbwarn++;
10570: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10571: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10572: agev[m][i]=-1;
10573: }
10574: }
1.169 brouard 10575: } /* agedc > 0 */
1.214 brouard 10576: } /* end if */
1.136 brouard 10577: else if(s[m][i] !=9){ /* Standard case, age in fractional
10578: years but with the precision of a month */
10579: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10580: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10581: agev[m][i]=1;
10582: else if(agev[m][i] < *agemin){
10583: *agemin=agev[m][i];
10584: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10585: }
10586: else if(agev[m][i] >*agemax){
10587: *agemax=agev[m][i];
1.156 brouard 10588: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10589: }
10590: /*agev[m][i]=anint[m][i]-annais[i];*/
10591: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10592: } /* en if 9*/
1.136 brouard 10593: else { /* =9 */
1.214 brouard 10594: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10595: agev[m][i]=1;
10596: s[m][i]=-1;
10597: }
10598: }
1.214 brouard 10599: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10600: agev[m][i]=1;
1.214 brouard 10601: else{
10602: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10603: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10604: agev[m][i]=0;
10605: }
10606: } /* End for lastpass */
10607: }
1.136 brouard 10608:
10609: for (i=1; i<=imx; i++) {
10610: for(m=firstpass; (m<=lastpass); m++){
10611: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10612: (*nberr)++;
1.136 brouard 10613: 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);
10614: 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);
10615: return 1;
10616: }
10617: }
10618: }
10619:
10620: /*for (i=1; i<=imx; i++){
10621: for (m=firstpass; (m<lastpass); m++){
10622: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10623: }
10624:
10625: }*/
10626:
10627:
1.139 brouard 10628: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10629: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10630:
10631: return (0);
1.164 brouard 10632: /* endread:*/
1.136 brouard 10633: printf("Exiting calandcheckages: ");
10634: return (1);
10635: }
10636:
1.172 brouard 10637: #if defined(_MSC_VER)
10638: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10639: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10640: //#include "stdafx.h"
10641: //#include <stdio.h>
10642: //#include <tchar.h>
10643: //#include <windows.h>
10644: //#include <iostream>
10645: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10646:
10647: LPFN_ISWOW64PROCESS fnIsWow64Process;
10648:
10649: BOOL IsWow64()
10650: {
10651: BOOL bIsWow64 = FALSE;
10652:
10653: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10654: // (HANDLE, PBOOL);
10655:
10656: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10657:
10658: HMODULE module = GetModuleHandle(_T("kernel32"));
10659: const char funcName[] = "IsWow64Process";
10660: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10661: GetProcAddress(module, funcName);
10662:
10663: if (NULL != fnIsWow64Process)
10664: {
10665: if (!fnIsWow64Process(GetCurrentProcess(),
10666: &bIsWow64))
10667: //throw std::exception("Unknown error");
10668: printf("Unknown error\n");
10669: }
10670: return bIsWow64 != FALSE;
10671: }
10672: #endif
1.177 brouard 10673:
1.191 brouard 10674: void syscompilerinfo(int logged)
1.292 brouard 10675: {
10676: #include <stdint.h>
10677:
10678: /* #include "syscompilerinfo.h"*/
1.185 brouard 10679: /* command line Intel compiler 32bit windows, XP compatible:*/
10680: /* /GS /W3 /Gy
10681: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10682: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10683: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10684: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10685: */
10686: /* 64 bits */
1.185 brouard 10687: /*
10688: /GS /W3 /Gy
10689: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10690: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10691: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10692: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10693: /* Optimization are useless and O3 is slower than O2 */
10694: /*
10695: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10696: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10697: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10698: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10699: */
1.186 brouard 10700: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10701: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10702: /PDB:"visual studio
10703: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10704: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10705: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10706: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10707: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10708: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10709: uiAccess='false'"
10710: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10711: /NOLOGO /TLBID:1
10712: */
1.292 brouard 10713:
10714:
1.177 brouard 10715: #if defined __INTEL_COMPILER
1.178 brouard 10716: #if defined(__GNUC__)
10717: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10718: #endif
1.177 brouard 10719: #elif defined(__GNUC__)
1.179 brouard 10720: #ifndef __APPLE__
1.174 brouard 10721: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10722: #endif
1.177 brouard 10723: struct utsname sysInfo;
1.178 brouard 10724: int cross = CROSS;
10725: if (cross){
10726: printf("Cross-");
1.191 brouard 10727: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10728: }
1.174 brouard 10729: #endif
10730:
1.191 brouard 10731: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10732: #if defined(__clang__)
1.191 brouard 10733: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10734: #endif
10735: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10736: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10737: #endif
10738: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10739: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10740: #endif
10741: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10742: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10743: #endif
10744: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10745: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10746: #endif
10747: #if defined(_MSC_VER)
1.191 brouard 10748: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10749: #endif
10750: #if defined(__PGI)
1.191 brouard 10751: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10752: #endif
10753: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10754: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10755: #endif
1.191 brouard 10756: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10757:
1.167 brouard 10758: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10759: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10760: // Windows (x64 and x86)
1.191 brouard 10761: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10762: #elif __unix__ // all unices, not all compilers
10763: // Unix
1.191 brouard 10764: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10765: #elif __linux__
10766: // linux
1.191 brouard 10767: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10768: #elif __APPLE__
1.174 brouard 10769: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10770: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10771: #endif
10772:
10773: /* __MINGW32__ */
10774: /* __CYGWIN__ */
10775: /* __MINGW64__ */
10776: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10777: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10778: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10779: /* _WIN64 // Defined for applications for Win64. */
10780: /* _M_X64 // Defined for compilations that target x64 processors. */
10781: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10782:
1.167 brouard 10783: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10784: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10785: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10786: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10787: #else
1.191 brouard 10788: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10789: #endif
10790:
1.169 brouard 10791: #if defined(__GNUC__)
10792: # if defined(__GNUC_PATCHLEVEL__)
10793: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10794: + __GNUC_MINOR__ * 100 \
10795: + __GNUC_PATCHLEVEL__)
10796: # else
10797: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10798: + __GNUC_MINOR__ * 100)
10799: # endif
1.174 brouard 10800: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10801: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10802:
10803: if (uname(&sysInfo) != -1) {
10804: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10805: 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 10806: }
10807: else
10808: perror("uname() error");
1.179 brouard 10809: //#ifndef __INTEL_COMPILER
10810: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10811: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10812: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10813: #endif
1.169 brouard 10814: #endif
1.172 brouard 10815:
1.286 brouard 10816: // void main ()
1.172 brouard 10817: // {
1.169 brouard 10818: #if defined(_MSC_VER)
1.174 brouard 10819: if (IsWow64()){
1.191 brouard 10820: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10821: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10822: }
10823: else{
1.191 brouard 10824: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10825: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10826: }
1.172 brouard 10827: // printf("\nPress Enter to continue...");
10828: // getchar();
10829: // }
10830:
1.169 brouard 10831: #endif
10832:
1.167 brouard 10833:
1.219 brouard 10834: }
1.136 brouard 10835:
1.219 brouard 10836: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10837: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10838: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10839: /* double ftolpl = 1.e-10; */
1.180 brouard 10840: double age, agebase, agelim;
1.203 brouard 10841: double tot;
1.180 brouard 10842:
1.202 brouard 10843: strcpy(filerespl,"PL_");
10844: strcat(filerespl,fileresu);
10845: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10846: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10847: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10848: }
1.288 brouard 10849: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10850: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10851: pstamp(ficrespl);
1.288 brouard 10852: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10853: fprintf(ficrespl,"#Age ");
10854: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10855: fprintf(ficrespl,"\n");
1.180 brouard 10856:
1.219 brouard 10857: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10858:
1.219 brouard 10859: agebase=ageminpar;
10860: agelim=agemaxpar;
1.180 brouard 10861:
1.227 brouard 10862: /* i1=pow(2,ncoveff); */
1.234 brouard 10863: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10864: if (cptcovn < 1){i1=1;}
1.180 brouard 10865:
1.238 brouard 10866: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10867: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10868: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10869: continue;
1.235 brouard 10870:
1.238 brouard 10871: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10872: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10873: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10874: /* k=k+1; */
10875: /* to clean */
10876: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10877: fprintf(ficrespl,"#******");
10878: printf("#******");
10879: fprintf(ficlog,"#******");
10880: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10881: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10882: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10883: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10884: }
10885: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10886: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10887: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10888: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10889: }
10890: fprintf(ficrespl,"******\n");
10891: printf("******\n");
10892: fprintf(ficlog,"******\n");
10893: if(invalidvarcomb[k]){
10894: printf("\nCombination (%d) ignored because no case \n",k);
10895: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10896: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10897: continue;
10898: }
1.219 brouard 10899:
1.238 brouard 10900: fprintf(ficrespl,"#Age ");
10901: for(j=1;j<=cptcoveff;j++) {
10902: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10903: }
10904: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10905: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10906:
1.238 brouard 10907: for (age=agebase; age<=agelim; age++){
10908: /* for (age=agebase; age<=agebase; age++){ */
10909: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10910: fprintf(ficrespl,"%.0f ",age );
10911: for(j=1;j<=cptcoveff;j++)
10912: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10913: tot=0.;
10914: for(i=1; i<=nlstate;i++){
10915: tot += prlim[i][i];
10916: fprintf(ficrespl," %.5f", prlim[i][i]);
10917: }
10918: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10919: } /* Age */
10920: /* was end of cptcod */
10921: } /* cptcov */
10922: } /* nres */
1.219 brouard 10923: return 0;
1.180 brouard 10924: }
10925:
1.218 brouard 10926: 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 10927: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10928:
10929: /* Computes the back prevalence limit for any combination of covariate values
10930: * at any age between ageminpar and agemaxpar
10931: */
1.235 brouard 10932: int i, j, k, i1, nres=0 ;
1.217 brouard 10933: /* double ftolpl = 1.e-10; */
10934: double age, agebase, agelim;
10935: double tot;
1.218 brouard 10936: /* double ***mobaverage; */
10937: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10938:
10939: strcpy(fileresplb,"PLB_");
10940: strcat(fileresplb,fileresu);
10941: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10942: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10943: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10944: }
1.288 brouard 10945: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10946: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10947: pstamp(ficresplb);
1.288 brouard 10948: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10949: fprintf(ficresplb,"#Age ");
10950: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10951: fprintf(ficresplb,"\n");
10952:
1.218 brouard 10953:
10954: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10955:
10956: agebase=ageminpar;
10957: agelim=agemaxpar;
10958:
10959:
1.227 brouard 10960: i1=pow(2,cptcoveff);
1.218 brouard 10961: if (cptcovn < 1){i1=1;}
1.227 brouard 10962:
1.238 brouard 10963: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10964: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10965: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10966: continue;
10967: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10968: fprintf(ficresplb,"#******");
10969: printf("#******");
10970: fprintf(ficlog,"#******");
10971: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10972: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10973: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10974: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10975: }
10976: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10977: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10978: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10979: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10980: }
10981: fprintf(ficresplb,"******\n");
10982: printf("******\n");
10983: fprintf(ficlog,"******\n");
10984: if(invalidvarcomb[k]){
10985: printf("\nCombination (%d) ignored because no cases \n",k);
10986: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10987: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10988: continue;
10989: }
1.218 brouard 10990:
1.238 brouard 10991: fprintf(ficresplb,"#Age ");
10992: for(j=1;j<=cptcoveff;j++) {
10993: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10994: }
10995: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10996: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10997:
10998:
1.238 brouard 10999: for (age=agebase; age<=agelim; age++){
11000: /* for (age=agebase; age<=agebase; age++){ */
11001: if(mobilavproj > 0){
11002: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11003: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11004: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11005: }else if (mobilavproj == 0){
11006: 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);
11007: 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);
11008: exit(1);
11009: }else{
11010: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11011: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11012: /* printf("TOTOT\n"); */
11013: /* exit(1); */
1.238 brouard 11014: }
11015: fprintf(ficresplb,"%.0f ",age );
11016: for(j=1;j<=cptcoveff;j++)
11017: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11018: tot=0.;
11019: for(i=1; i<=nlstate;i++){
11020: tot += bprlim[i][i];
11021: fprintf(ficresplb," %.5f", bprlim[i][i]);
11022: }
11023: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11024: } /* Age */
11025: /* was end of cptcod */
1.255 brouard 11026: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 11027: } /* end of any combination */
11028: } /* end of nres */
1.218 brouard 11029: /* hBijx(p, bage, fage); */
11030: /* fclose(ficrespijb); */
11031:
11032: return 0;
1.217 brouard 11033: }
1.218 brouard 11034:
1.180 brouard 11035: int hPijx(double *p, int bage, int fage){
11036: /*------------- h Pij x at various ages ------------*/
11037:
11038: int stepsize;
11039: int agelim;
11040: int hstepm;
11041: int nhstepm;
1.235 brouard 11042: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11043:
11044: double agedeb;
11045: double ***p3mat;
11046:
1.201 brouard 11047: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 11048: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11049: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11050: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11051: }
11052: printf("Computing pij: result on file '%s' \n", filerespij);
11053: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11054:
11055: stepsize=(int) (stepm+YEARM-1)/YEARM;
11056: /*if (stepm<=24) stepsize=2;*/
11057:
11058: agelim=AGESUP;
11059: hstepm=stepsize*YEARM; /* Every year of age */
11060: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 11061:
1.180 brouard 11062: /* hstepm=1; aff par mois*/
11063: pstamp(ficrespij);
11064: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 11065: i1= pow(2,cptcoveff);
1.218 brouard 11066: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11067: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11068: /* k=k+1; */
1.235 brouard 11069: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11070: for(k=1; k<=i1;k++){
1.253 brouard 11071: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11072: continue;
1.183 brouard 11073: fprintf(ficrespij,"\n#****** ");
1.227 brouard 11074: for(j=1;j<=cptcoveff;j++)
1.198 brouard 11075: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11076: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11077: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11078: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11079: }
1.183 brouard 11080: fprintf(ficrespij,"******\n");
11081:
11082: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11083: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11084: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11085:
11086: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 11087:
1.183 brouard 11088: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11089: oldm=oldms;savm=savms;
1.235 brouard 11090: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 11091: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11092: for(i=1; i<=nlstate;i++)
11093: for(j=1; j<=nlstate+ndeath;j++)
11094: fprintf(ficrespij," %1d-%1d",i,j);
11095: fprintf(ficrespij,"\n");
11096: for (h=0; h<=nhstepm; h++){
11097: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11098: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 11099: for(i=1; i<=nlstate;i++)
11100: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 11101: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 11102: fprintf(ficrespij,"\n");
11103: }
1.183 brouard 11104: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11105: fprintf(ficrespij,"\n");
11106: }
1.180 brouard 11107: /*}*/
11108: }
1.218 brouard 11109: return 0;
1.180 brouard 11110: }
1.218 brouard 11111:
11112: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11113: /*------------- h Bij x at various ages ------------*/
11114:
11115: int stepsize;
1.218 brouard 11116: /* int agelim; */
11117: int ageminl;
1.217 brouard 11118: int hstepm;
11119: int nhstepm;
1.238 brouard 11120: int h, i, i1, j, k, nres;
1.218 brouard 11121:
1.217 brouard 11122: double agedeb;
11123: double ***p3mat;
1.218 brouard 11124:
11125: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11126: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11127: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11128: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11129: }
11130: printf("Computing pij back: result on file '%s' \n", filerespijb);
11131: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11132:
11133: stepsize=(int) (stepm+YEARM-1)/YEARM;
11134: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11135:
1.218 brouard 11136: /* agelim=AGESUP; */
1.289 brouard 11137: ageminl=AGEINF; /* was 30 */
1.218 brouard 11138: hstepm=stepsize*YEARM; /* Every year of age */
11139: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11140:
11141: /* hstepm=1; aff par mois*/
11142: pstamp(ficrespijb);
1.255 brouard 11143: 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 11144: i1= pow(2,cptcoveff);
1.218 brouard 11145: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11146: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11147: /* k=k+1; */
1.238 brouard 11148: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11149: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11150: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11151: continue;
11152: fprintf(ficrespijb,"\n#****** ");
11153: for(j=1;j<=cptcoveff;j++)
11154: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11155: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11156: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11157: }
11158: fprintf(ficrespijb,"******\n");
1.264 brouard 11159: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 11160: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
11161: continue;
11162: }
11163:
11164: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11165: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11166: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 11167: 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 */
11168: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 11169:
11170: /* nhstepm=nhstepm*YEARM; aff par mois*/
11171:
1.266 brouard 11172: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11173: /* and memory limitations if stepm is small */
11174:
1.238 brouard 11175: /* oldm=oldms;savm=savms; */
11176: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 11177: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 11178: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 11179: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 11180: for(i=1; i<=nlstate;i++)
11181: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 11182: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 11183: fprintf(ficrespijb,"\n");
1.238 brouard 11184: for (h=0; h<=nhstepm; h++){
11185: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11186: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11187: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
11188: for(i=1; i<=nlstate;i++)
11189: for(j=1; j<=nlstate+ndeath;j++)
11190: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
11191: fprintf(ficrespijb,"\n");
11192: }
11193: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11194: fprintf(ficrespijb,"\n");
11195: } /* end age deb */
11196: } /* end combination */
11197: } /* end nres */
1.218 brouard 11198: return 0;
11199: } /* hBijx */
1.217 brouard 11200:
1.180 brouard 11201:
1.136 brouard 11202: /***********************************************/
11203: /**************** Main Program *****************/
11204: /***********************************************/
11205:
11206: int main(int argc, char *argv[])
11207: {
11208: #ifdef GSL
11209: const gsl_multimin_fminimizer_type *T;
11210: size_t iteri = 0, it;
11211: int rval = GSL_CONTINUE;
11212: int status = GSL_SUCCESS;
11213: double ssval;
11214: #endif
11215: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11216: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11217: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11218: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11219: int jj, ll, li, lj, lk;
1.136 brouard 11220: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11221: int num_filled;
1.136 brouard 11222: int itimes;
11223: int NDIM=2;
11224: int vpopbased=0;
1.235 brouard 11225: int nres=0;
1.258 brouard 11226: int endishere=0;
1.277 brouard 11227: int noffset=0;
1.274 brouard 11228: int ncurrv=0; /* Temporary variable */
11229:
1.164 brouard 11230: char ca[32], cb[32];
1.136 brouard 11231: /* FILE *fichtm; *//* Html File */
11232: /* FILE *ficgp;*/ /*Gnuplot File */
11233: struct stat info;
1.191 brouard 11234: double agedeb=0.;
1.194 brouard 11235:
11236: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11237: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11238:
1.165 brouard 11239: double fret;
1.191 brouard 11240: double dum=0.; /* Dummy variable */
1.136 brouard 11241: double ***p3mat;
1.218 brouard 11242: /* double ***mobaverage; */
1.319 brouard 11243: double wald;
1.164 brouard 11244:
11245: char line[MAXLINE];
1.197 brouard 11246: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11247:
1.234 brouard 11248: char modeltemp[MAXLINE];
1.230 brouard 11249: char resultline[MAXLINE];
11250:
1.136 brouard 11251: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11252: char *tok, *val; /* pathtot */
1.290 brouard 11253: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 11254: int c, h , cpt, c2;
1.191 brouard 11255: int jl=0;
11256: int i1, j1, jk, stepsize=0;
1.194 brouard 11257: int count=0;
11258:
1.164 brouard 11259: int *tab;
1.136 brouard 11260: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11261: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11262: /* double anprojf, mprojf, jprojf; */
11263: /* double jintmean,mintmean,aintmean; */
11264: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11265: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11266: double yrfproj= 10.0; /* Number of years of forward projections */
11267: double yrbproj= 10.0; /* Number of years of backward projections */
11268: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11269: int mobilav=0,popforecast=0;
1.191 brouard 11270: int hstepm=0, nhstepm=0;
1.136 brouard 11271: int agemortsup;
11272: float sumlpop=0.;
11273: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11274: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11275:
1.191 brouard 11276: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11277: double ftolpl=FTOL;
11278: double **prlim;
1.217 brouard 11279: double **bprlim;
1.317 brouard 11280: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
11281: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 11282: double ***paramstart; /* Matrix of starting parameter values */
11283: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11284: double **matcov; /* Matrix of covariance */
1.203 brouard 11285: double **hess; /* Hessian matrix */
1.136 brouard 11286: double ***delti3; /* Scale */
11287: double *delti; /* Scale */
11288: double ***eij, ***vareij;
11289: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11290:
1.136 brouard 11291: double *epj, vepp;
1.164 brouard 11292:
1.273 brouard 11293: double dateprev1, dateprev2;
1.296 brouard 11294: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11295: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11296:
1.217 brouard 11297:
1.136 brouard 11298: double **ximort;
1.145 brouard 11299: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11300: int *dcwave;
11301:
1.164 brouard 11302: char z[1]="c";
1.136 brouard 11303:
11304: /*char *strt;*/
11305: char strtend[80];
1.126 brouard 11306:
1.164 brouard 11307:
1.126 brouard 11308: /* setlocale (LC_ALL, ""); */
11309: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11310: /* textdomain (PACKAGE); */
11311: /* setlocale (LC_CTYPE, ""); */
11312: /* setlocale (LC_MESSAGES, ""); */
11313:
11314: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11315: rstart_time = time(NULL);
11316: /* (void) gettimeofday(&start_time,&tzp);*/
11317: start_time = *localtime(&rstart_time);
1.126 brouard 11318: curr_time=start_time;
1.157 brouard 11319: /*tml = *localtime(&start_time.tm_sec);*/
11320: /* strcpy(strstart,asctime(&tml)); */
11321: strcpy(strstart,asctime(&start_time));
1.126 brouard 11322:
11323: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11324: /* tp.tm_sec = tp.tm_sec +86400; */
11325: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11326: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11327: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11328: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11329: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11330: /* strt=asctime(&tmg); */
11331: /* printf("Time(after) =%s",strstart); */
11332: /* (void) time (&time_value);
11333: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11334: * tm = *localtime(&time_value);
11335: * strstart=asctime(&tm);
11336: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11337: */
11338:
11339: nberr=0; /* Number of errors and warnings */
11340: nbwarn=0;
1.184 brouard 11341: #ifdef WIN32
11342: _getcwd(pathcd, size);
11343: #else
1.126 brouard 11344: getcwd(pathcd, size);
1.184 brouard 11345: #endif
1.191 brouard 11346: syscompilerinfo(0);
1.196 brouard 11347: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11348: if(argc <=1){
11349: printf("\nEnter the parameter file name: ");
1.205 brouard 11350: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11351: printf("ERROR Empty parameter file name\n");
11352: goto end;
11353: }
1.126 brouard 11354: i=strlen(pathr);
11355: if(pathr[i-1]=='\n')
11356: pathr[i-1]='\0';
1.156 brouard 11357: i=strlen(pathr);
1.205 brouard 11358: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11359: pathr[i-1]='\0';
1.205 brouard 11360: }
11361: i=strlen(pathr);
11362: if( i==0 ){
11363: printf("ERROR Empty parameter file name\n");
11364: goto end;
11365: }
11366: for (tok = pathr; tok != NULL; ){
1.126 brouard 11367: printf("Pathr |%s|\n",pathr);
11368: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11369: printf("val= |%s| pathr=%s\n",val,pathr);
11370: strcpy (pathtot, val);
11371: if(pathr[0] == '\0') break; /* Dirty */
11372: }
11373: }
1.281 brouard 11374: else if (argc<=2){
11375: strcpy(pathtot,argv[1]);
11376: }
1.126 brouard 11377: else{
11378: strcpy(pathtot,argv[1]);
1.281 brouard 11379: strcpy(z,argv[2]);
11380: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11381: }
11382: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11383: /*cygwin_split_path(pathtot,path,optionfile);
11384: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11385: /* cutv(path,optionfile,pathtot,'\\');*/
11386:
11387: /* Split argv[0], imach program to get pathimach */
11388: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11389: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11390: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11391: /* strcpy(pathimach,argv[0]); */
11392: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11393: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11394: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11395: #ifdef WIN32
11396: _chdir(path); /* Can be a relative path */
11397: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11398: #else
1.126 brouard 11399: chdir(path); /* Can be a relative path */
1.184 brouard 11400: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11401: #endif
11402: printf("Current directory %s!\n",pathcd);
1.126 brouard 11403: strcpy(command,"mkdir ");
11404: strcat(command,optionfilefiname);
11405: if((outcmd=system(command)) != 0){
1.169 brouard 11406: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11407: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11408: /* fclose(ficlog); */
11409: /* exit(1); */
11410: }
11411: /* if((imk=mkdir(optionfilefiname))<0){ */
11412: /* perror("mkdir"); */
11413: /* } */
11414:
11415: /*-------- arguments in the command line --------*/
11416:
1.186 brouard 11417: /* Main Log file */
1.126 brouard 11418: strcat(filelog, optionfilefiname);
11419: strcat(filelog,".log"); /* */
11420: if((ficlog=fopen(filelog,"w"))==NULL) {
11421: printf("Problem with logfile %s\n",filelog);
11422: goto end;
11423: }
11424: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11425: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11426: fprintf(ficlog,"\nEnter the parameter file name: \n");
11427: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11428: path=%s \n\
11429: optionfile=%s\n\
11430: optionfilext=%s\n\
1.156 brouard 11431: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11432:
1.197 brouard 11433: syscompilerinfo(1);
1.167 brouard 11434:
1.126 brouard 11435: printf("Local time (at start):%s",strstart);
11436: fprintf(ficlog,"Local time (at start): %s",strstart);
11437: fflush(ficlog);
11438: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11439: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11440:
11441: /* */
11442: strcpy(fileres,"r");
11443: strcat(fileres, optionfilefiname);
1.201 brouard 11444: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11445: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11446: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11447:
1.186 brouard 11448: /* Main ---------arguments file --------*/
1.126 brouard 11449:
11450: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11451: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11452: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11453: fflush(ficlog);
1.149 brouard 11454: /* goto end; */
11455: exit(70);
1.126 brouard 11456: }
11457:
11458: strcpy(filereso,"o");
1.201 brouard 11459: strcat(filereso,fileresu);
1.126 brouard 11460: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11461: printf("Problem with Output resultfile: %s\n", filereso);
11462: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11463: fflush(ficlog);
11464: goto end;
11465: }
1.278 brouard 11466: /*-------- Rewriting parameter file ----------*/
11467: strcpy(rfileres,"r"); /* "Rparameterfile */
11468: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11469: strcat(rfileres,"."); /* */
11470: strcat(rfileres,optionfilext); /* Other files have txt extension */
11471: if((ficres =fopen(rfileres,"w"))==NULL) {
11472: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11473: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11474: fflush(ficlog);
11475: goto end;
11476: }
11477: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11478:
1.278 brouard 11479:
1.126 brouard 11480: /* Reads comments: lines beginning with '#' */
11481: numlinepar=0;
1.277 brouard 11482: /* Is it a BOM UTF-8 Windows file? */
11483: /* First parameter line */
1.197 brouard 11484: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11485: noffset=0;
11486: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11487: {
11488: noffset=noffset+3;
11489: printf("# File is an UTF8 Bom.\n"); // 0xBF
11490: }
1.302 brouard 11491: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11492: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11493: {
11494: noffset=noffset+2;
11495: printf("# File is an UTF16BE BOM file\n");
11496: }
11497: else if( line[0] == 0 && line[1] == 0)
11498: {
11499: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11500: noffset=noffset+4;
11501: printf("# File is an UTF16BE BOM file\n");
11502: }
11503: } else{
11504: ;/*printf(" Not a BOM file\n");*/
11505: }
11506:
1.197 brouard 11507: /* If line starts with a # it is a comment */
1.277 brouard 11508: if (line[noffset] == '#') {
1.197 brouard 11509: numlinepar++;
11510: fputs(line,stdout);
11511: fputs(line,ficparo);
1.278 brouard 11512: fputs(line,ficres);
1.197 brouard 11513: fputs(line,ficlog);
11514: continue;
11515: }else
11516: break;
11517: }
11518: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11519: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11520: if (num_filled != 5) {
11521: printf("Should be 5 parameters\n");
1.283 brouard 11522: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11523: }
1.126 brouard 11524: numlinepar++;
1.197 brouard 11525: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11526: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11527: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11528: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11529: }
11530: /* Second parameter line */
11531: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11532: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11533: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11534: if (line[0] == '#') {
11535: numlinepar++;
1.283 brouard 11536: printf("%s",line);
11537: fprintf(ficres,"%s",line);
11538: fprintf(ficparo,"%s",line);
11539: fprintf(ficlog,"%s",line);
1.197 brouard 11540: continue;
11541: }else
11542: break;
11543: }
1.223 brouard 11544: 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", \
11545: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11546: if (num_filled != 11) {
11547: 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 11548: printf("but line=%s\n",line);
1.283 brouard 11549: 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");
11550: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11551: }
1.286 brouard 11552: if( lastpass > maxwav){
11553: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11554: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11555: fflush(ficlog);
11556: goto end;
11557: }
11558: 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 11559: 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 11560: 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 11561: 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 11562: }
1.203 brouard 11563: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11564: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11565: /* Third parameter line */
11566: while(fgets(line, MAXLINE, ficpar)) {
11567: /* If line starts with a # it is a comment */
11568: if (line[0] == '#') {
11569: numlinepar++;
1.283 brouard 11570: printf("%s",line);
11571: fprintf(ficres,"%s",line);
11572: fprintf(ficparo,"%s",line);
11573: fprintf(ficlog,"%s",line);
1.197 brouard 11574: continue;
11575: }else
11576: break;
11577: }
1.201 brouard 11578: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11579: if (num_filled != 1){
1.302 brouard 11580: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
11581: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 11582: model[0]='\0';
11583: goto end;
11584: }
11585: else{
11586: if (model[0]=='+'){
11587: for(i=1; i<=strlen(model);i++)
11588: modeltemp[i-1]=model[i];
1.201 brouard 11589: strcpy(model,modeltemp);
1.197 brouard 11590: }
11591: }
1.199 brouard 11592: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11593: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11594: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11595: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11596: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11597: }
11598: /* 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); */
11599: /* numlinepar=numlinepar+3; /\* In general *\/ */
11600: /* 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 11601: /* 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); */
11602: /* 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 11603: fflush(ficlog);
1.190 brouard 11604: /* if(model[0]=='#'|| model[0]== '\0'){ */
11605: if(model[0]=='#'){
1.279 brouard 11606: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11607: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11608: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11609: if(mle != -1){
1.279 brouard 11610: 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 11611: exit(1);
11612: }
11613: }
1.126 brouard 11614: while((c=getc(ficpar))=='#' && c!= EOF){
11615: ungetc(c,ficpar);
11616: fgets(line, MAXLINE, ficpar);
11617: numlinepar++;
1.195 brouard 11618: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11619: z[0]=line[1];
11620: }
11621: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11622: fputs(line, stdout);
11623: //puts(line);
1.126 brouard 11624: fputs(line,ficparo);
11625: fputs(line,ficlog);
11626: }
11627: ungetc(c,ficpar);
11628:
11629:
1.290 brouard 11630: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11631: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11632: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11633: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11634: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11635: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11636: v1+v2*age+v2*v3 makes cptcovn = 3
11637: */
11638: if (strlen(model)>1)
1.187 brouard 11639: 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 11640: else
1.187 brouard 11641: ncovmodel=2; /* Constant and age */
1.133 brouard 11642: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11643: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11644: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11645: 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);
11646: 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);
11647: fflush(stdout);
11648: fclose (ficlog);
11649: goto end;
11650: }
1.126 brouard 11651: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11652: delti=delti3[1][1];
11653: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11654: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11655: /* We could also provide initial parameters values giving by simple logistic regression
11656: * only one way, that is without matrix product. We will have nlstate maximizations */
11657: /* for(i=1;i<nlstate;i++){ */
11658: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11659: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11660: /* } */
1.126 brouard 11661: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11662: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11663: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11664: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11665: fclose (ficparo);
11666: fclose (ficlog);
11667: goto end;
11668: exit(0);
1.220 brouard 11669: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11670: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11671: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11672: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11673: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11674: matcov=matrix(1,npar,1,npar);
1.203 brouard 11675: hess=matrix(1,npar,1,npar);
1.220 brouard 11676: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11677: /* Read guessed parameters */
1.126 brouard 11678: /* Reads comments: lines beginning with '#' */
11679: while((c=getc(ficpar))=='#' && c!= EOF){
11680: ungetc(c,ficpar);
11681: fgets(line, MAXLINE, ficpar);
11682: numlinepar++;
1.141 brouard 11683: fputs(line,stdout);
1.126 brouard 11684: fputs(line,ficparo);
11685: fputs(line,ficlog);
11686: }
11687: ungetc(c,ficpar);
11688:
11689: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11690: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11691: for(i=1; i <=nlstate; i++){
1.234 brouard 11692: j=0;
1.126 brouard 11693: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11694: if(jj==i) continue;
11695: j++;
1.292 brouard 11696: while((c=getc(ficpar))=='#' && c!= EOF){
11697: ungetc(c,ficpar);
11698: fgets(line, MAXLINE, ficpar);
11699: numlinepar++;
11700: fputs(line,stdout);
11701: fputs(line,ficparo);
11702: fputs(line,ficlog);
11703: }
11704: ungetc(c,ficpar);
1.234 brouard 11705: fscanf(ficpar,"%1d%1d",&i1,&j1);
11706: if ((i1 != i) || (j1 != jj)){
11707: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11708: It might be a problem of design; if ncovcol and the model are correct\n \
11709: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11710: exit(1);
11711: }
11712: fprintf(ficparo,"%1d%1d",i1,j1);
11713: if(mle==1)
11714: printf("%1d%1d",i,jj);
11715: fprintf(ficlog,"%1d%1d",i,jj);
11716: for(k=1; k<=ncovmodel;k++){
11717: fscanf(ficpar," %lf",¶m[i][j][k]);
11718: if(mle==1){
11719: printf(" %lf",param[i][j][k]);
11720: fprintf(ficlog," %lf",param[i][j][k]);
11721: }
11722: else
11723: fprintf(ficlog," %lf",param[i][j][k]);
11724: fprintf(ficparo," %lf",param[i][j][k]);
11725: }
11726: fscanf(ficpar,"\n");
11727: numlinepar++;
11728: if(mle==1)
11729: printf("\n");
11730: fprintf(ficlog,"\n");
11731: fprintf(ficparo,"\n");
1.126 brouard 11732: }
11733: }
11734: fflush(ficlog);
1.234 brouard 11735:
1.251 brouard 11736: /* Reads parameters values */
1.126 brouard 11737: p=param[1][1];
1.251 brouard 11738: pstart=paramstart[1][1];
1.126 brouard 11739:
11740: /* Reads comments: lines beginning with '#' */
11741: while((c=getc(ficpar))=='#' && c!= EOF){
11742: ungetc(c,ficpar);
11743: fgets(line, MAXLINE, ficpar);
11744: numlinepar++;
1.141 brouard 11745: fputs(line,stdout);
1.126 brouard 11746: fputs(line,ficparo);
11747: fputs(line,ficlog);
11748: }
11749: ungetc(c,ficpar);
11750:
11751: for(i=1; i <=nlstate; i++){
11752: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11753: fscanf(ficpar,"%1d%1d",&i1,&j1);
11754: if ( (i1-i) * (j1-j) != 0){
11755: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11756: exit(1);
11757: }
11758: printf("%1d%1d",i,j);
11759: fprintf(ficparo,"%1d%1d",i1,j1);
11760: fprintf(ficlog,"%1d%1d",i1,j1);
11761: for(k=1; k<=ncovmodel;k++){
11762: fscanf(ficpar,"%le",&delti3[i][j][k]);
11763: printf(" %le",delti3[i][j][k]);
11764: fprintf(ficparo," %le",delti3[i][j][k]);
11765: fprintf(ficlog," %le",delti3[i][j][k]);
11766: }
11767: fscanf(ficpar,"\n");
11768: numlinepar++;
11769: printf("\n");
11770: fprintf(ficparo,"\n");
11771: fprintf(ficlog,"\n");
1.126 brouard 11772: }
11773: }
11774: fflush(ficlog);
1.234 brouard 11775:
1.145 brouard 11776: /* Reads covariance matrix */
1.126 brouard 11777: delti=delti3[1][1];
1.220 brouard 11778:
11779:
1.126 brouard 11780: /* 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 11781:
1.126 brouard 11782: /* Reads comments: lines beginning with '#' */
11783: while((c=getc(ficpar))=='#' && c!= EOF){
11784: ungetc(c,ficpar);
11785: fgets(line, MAXLINE, ficpar);
11786: numlinepar++;
1.141 brouard 11787: fputs(line,stdout);
1.126 brouard 11788: fputs(line,ficparo);
11789: fputs(line,ficlog);
11790: }
11791: ungetc(c,ficpar);
1.220 brouard 11792:
1.126 brouard 11793: matcov=matrix(1,npar,1,npar);
1.203 brouard 11794: hess=matrix(1,npar,1,npar);
1.131 brouard 11795: for(i=1; i <=npar; i++)
11796: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11797:
1.194 brouard 11798: /* Scans npar lines */
1.126 brouard 11799: for(i=1; i <=npar; i++){
1.226 brouard 11800: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11801: if(count != 3){
1.226 brouard 11802: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11803: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11804: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11805: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11806: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11807: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11808: exit(1);
1.220 brouard 11809: }else{
1.226 brouard 11810: if(mle==1)
11811: printf("%1d%1d%d",i1,j1,jk);
11812: }
11813: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11814: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11815: for(j=1; j <=i; j++){
1.226 brouard 11816: fscanf(ficpar," %le",&matcov[i][j]);
11817: if(mle==1){
11818: printf(" %.5le",matcov[i][j]);
11819: }
11820: fprintf(ficlog," %.5le",matcov[i][j]);
11821: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11822: }
11823: fscanf(ficpar,"\n");
11824: numlinepar++;
11825: if(mle==1)
1.220 brouard 11826: printf("\n");
1.126 brouard 11827: fprintf(ficlog,"\n");
11828: fprintf(ficparo,"\n");
11829: }
1.194 brouard 11830: /* End of read covariance matrix npar lines */
1.126 brouard 11831: for(i=1; i <=npar; i++)
11832: for(j=i+1;j<=npar;j++)
1.226 brouard 11833: matcov[i][j]=matcov[j][i];
1.126 brouard 11834:
11835: if(mle==1)
11836: printf("\n");
11837: fprintf(ficlog,"\n");
11838:
11839: fflush(ficlog);
11840:
11841: } /* End of mle != -3 */
1.218 brouard 11842:
1.186 brouard 11843: /* Main data
11844: */
1.290 brouard 11845: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11846: /* num=lvector(1,n); */
11847: /* moisnais=vector(1,n); */
11848: /* annais=vector(1,n); */
11849: /* moisdc=vector(1,n); */
11850: /* andc=vector(1,n); */
11851: /* weight=vector(1,n); */
11852: /* agedc=vector(1,n); */
11853: /* cod=ivector(1,n); */
11854: /* for(i=1;i<=n;i++){ */
11855: num=lvector(firstobs,lastobs);
11856: moisnais=vector(firstobs,lastobs);
11857: annais=vector(firstobs,lastobs);
11858: moisdc=vector(firstobs,lastobs);
11859: andc=vector(firstobs,lastobs);
11860: weight=vector(firstobs,lastobs);
11861: agedc=vector(firstobs,lastobs);
11862: cod=ivector(firstobs,lastobs);
11863: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11864: num[i]=0;
11865: moisnais[i]=0;
11866: annais[i]=0;
11867: moisdc[i]=0;
11868: andc[i]=0;
11869: agedc[i]=0;
11870: cod[i]=0;
11871: weight[i]=1.0; /* Equal weights, 1 by default */
11872: }
1.290 brouard 11873: mint=matrix(1,maxwav,firstobs,lastobs);
11874: anint=matrix(1,maxwav,firstobs,lastobs);
11875: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11876: tab=ivector(1,NCOVMAX);
1.144 brouard 11877: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11878: 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 11879:
1.136 brouard 11880: /* Reads data from file datafile */
11881: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11882: goto end;
11883:
11884: /* Calculation of the number of parameters from char model */
1.234 brouard 11885: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11886: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11887: k=3 V4 Tvar[k=3]= 4 (from V4)
11888: k=2 V1 Tvar[k=2]= 1 (from V1)
11889: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11890: */
11891:
11892: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11893: TvarsDind=ivector(1,NCOVMAX); /* */
11894: TvarsD=ivector(1,NCOVMAX); /* */
11895: TvarsQind=ivector(1,NCOVMAX); /* */
11896: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11897: TvarF=ivector(1,NCOVMAX); /* */
11898: TvarFind=ivector(1,NCOVMAX); /* */
11899: TvarV=ivector(1,NCOVMAX); /* */
11900: TvarVind=ivector(1,NCOVMAX); /* */
11901: TvarA=ivector(1,NCOVMAX); /* */
11902: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11903: TvarFD=ivector(1,NCOVMAX); /* */
11904: TvarFDind=ivector(1,NCOVMAX); /* */
11905: TvarFQ=ivector(1,NCOVMAX); /* */
11906: TvarFQind=ivector(1,NCOVMAX); /* */
11907: TvarVD=ivector(1,NCOVMAX); /* */
11908: TvarVDind=ivector(1,NCOVMAX); /* */
11909: TvarVQ=ivector(1,NCOVMAX); /* */
11910: TvarVQind=ivector(1,NCOVMAX); /* */
11911:
1.230 brouard 11912: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11913: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11914: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11915: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11916: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11917: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11918: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11919: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11920: */
11921: /* For model-covariate k tells which data-covariate to use but
11922: because this model-covariate is a construction we invent a new column
11923: ncovcol + k1
11924: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11925: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11926: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11927: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11928: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11929: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11930: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11931: */
1.145 brouard 11932: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11933: 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 11934: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11935: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11936: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11937: 4 covariates (3 plus signs)
11938: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11939: */
1.230 brouard 11940: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11941: * individual dummy, fixed or varying:
11942: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11943: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11944: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11945: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11946: * Tmodelind[1]@9={9,0,3,2,}*/
11947: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11948: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11949: * individual quantitative, fixed or varying:
11950: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11951: * 3, 1, 0, 0, 0, 0, 0, 0},
11952: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11953: /* Main decodemodel */
11954:
1.187 brouard 11955:
1.223 brouard 11956: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11957: goto end;
11958:
1.137 brouard 11959: if((double)(lastobs-imx)/(double)imx > 1.10){
11960: nbwarn++;
11961: 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);
11962: 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);
11963: }
1.136 brouard 11964: /* if(mle==1){*/
1.137 brouard 11965: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11966: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11967: }
11968:
11969: /*-calculation of age at interview from date of interview and age at death -*/
11970: agev=matrix(1,maxwav,1,imx);
11971:
11972: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11973: goto end;
11974:
1.126 brouard 11975:
1.136 brouard 11976: agegomp=(int)agemin;
1.290 brouard 11977: free_vector(moisnais,firstobs,lastobs);
11978: free_vector(annais,firstobs,lastobs);
1.126 brouard 11979: /* free_matrix(mint,1,maxwav,1,n);
11980: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11981: /* free_vector(moisdc,1,n); */
11982: /* free_vector(andc,1,n); */
1.145 brouard 11983: /* */
11984:
1.126 brouard 11985: wav=ivector(1,imx);
1.214 brouard 11986: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11987: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11988: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11989: 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.*/
11990: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11991: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11992:
11993: /* Concatenates waves */
1.214 brouard 11994: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11995: Death is a valid wave (if date is known).
11996: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11997: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11998: and mw[mi+1][i]. dh depends on stepm.
11999: */
12000:
1.126 brouard 12001: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12002: /* Concatenates waves */
1.145 brouard 12003:
1.290 brouard 12004: free_vector(moisdc,firstobs,lastobs);
12005: free_vector(andc,firstobs,lastobs);
1.215 brouard 12006:
1.126 brouard 12007: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12008: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12009: ncodemax[1]=1;
1.145 brouard 12010: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12011: cptcoveff=0;
1.220 brouard 12012: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
12013: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 12014: }
12015:
12016: ncovcombmax=pow(2,cptcoveff);
12017: invalidvarcomb=ivector(1, ncovcombmax);
12018: for(i=1;i<ncovcombmax;i++)
12019: invalidvarcomb[i]=0;
12020:
1.211 brouard 12021: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12022: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12023: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12024:
1.200 brouard 12025: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12026: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12027: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12028: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12029: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12030: * (currently 0 or 1) in the data.
12031: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12032: * corresponding modality (h,j).
12033: */
12034:
1.145 brouard 12035: h=0;
12036: /*if (cptcovn > 0) */
1.126 brouard 12037: m=pow(2,cptcoveff);
12038:
1.144 brouard 12039: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12040: * For k=4 covariates, h goes from 1 to m=2**k
12041: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12042: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 12043: * h\k 1 2 3 4
1.143 brouard 12044: *______________________________
12045: * 1 i=1 1 i=1 1 i=1 1 i=1 1
12046: * 2 2 1 1 1
12047: * 3 i=2 1 2 1 1
12048: * 4 2 2 1 1
12049: * 5 i=3 1 i=2 1 2 1
12050: * 6 2 1 2 1
12051: * 7 i=4 1 2 2 1
12052: * 8 2 2 2 1
1.197 brouard 12053: * 9 i=5 1 i=3 1 i=2 1 2
12054: * 10 2 1 1 2
12055: * 11 i=6 1 2 1 2
12056: * 12 2 2 1 2
12057: * 13 i=7 1 i=4 1 2 2
12058: * 14 2 1 2 2
12059: * 15 i=8 1 2 2 2
12060: * 16 2 2 2 2
1.143 brouard 12061: */
1.212 brouard 12062: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12063: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12064: * and the value of each covariate?
12065: * V1=1, V2=1, V3=2, V4=1 ?
12066: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12067: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12068: * In order to get the real value in the data, we use nbcode
12069: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12070: * We are keeping this crazy system in order to be able (in the future?)
12071: * to have more than 2 values (0 or 1) for a covariate.
12072: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12073: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12074: * bbbbbbbb
12075: * 76543210
12076: * h-1 00000101 (6-1=5)
1.219 brouard 12077: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12078: * &
12079: * 1 00000001 (1)
1.219 brouard 12080: * 00000000 = 1 & ((h-1) >> (k-1))
12081: * +1= 00000001 =1
1.211 brouard 12082: *
12083: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12084: * h' 1101 =2^3+2^2+0x2^1+2^0
12085: * >>k' 11
12086: * & 00000001
12087: * = 00000001
12088: * +1 = 00000010=2 = codtabm(14,3)
12089: * Reverse h=6 and m=16?
12090: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12091: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12092: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12093: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12094: * V3=decodtabm(14,3,2**4)=2
12095: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12096: *(h-1) >> (j-1) 0011 =13 >> 2
12097: * &1 000000001
12098: * = 000000001
12099: * +1= 000000010 =2
12100: * 2211
12101: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12102: * V3=2
1.220 brouard 12103: * codtabm and decodtabm are identical
1.211 brouard 12104: */
12105:
1.145 brouard 12106:
12107: free_ivector(Ndum,-1,NCOVMAX);
12108:
12109:
1.126 brouard 12110:
1.186 brouard 12111: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12112: strcpy(optionfilegnuplot,optionfilefiname);
12113: if(mle==-3)
1.201 brouard 12114: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12115: strcat(optionfilegnuplot,".gp");
12116:
12117: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12118: printf("Problem with file %s",optionfilegnuplot);
12119: }
12120: else{
1.204 brouard 12121: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12122: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12123: //fprintf(ficgp,"set missing 'NaNq'\n");
12124: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12125: }
12126: /* fclose(ficgp);*/
1.186 brouard 12127:
12128:
12129: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12130:
12131: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12132: if(mle==-3)
1.201 brouard 12133: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12134: strcat(optionfilehtm,".htm");
12135: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12136: printf("Problem with %s \n",optionfilehtm);
12137: exit(0);
1.126 brouard 12138: }
12139:
12140: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
12141: strcat(optionfilehtmcov,"-cov.htm");
12142: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
12143: printf("Problem with %s \n",optionfilehtmcov), exit(0);
12144: }
12145: else{
12146: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
12147: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12148: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 12149: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
12150: }
12151:
1.213 brouard 12152: fprintf(fichtm,"<html><head>\n<head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<title>IMaCh %s</title></head>\n <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n<font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>-EUROREVES-Institut de longévité-2013-2016-Japan Society for the Promotion of Sciences 日本å¦è¡“振興会 (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \
1.204 brouard 12153: <hr size=\"2\" color=\"#EC5E5E\"> \n\
12154: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 12155: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12156: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 12157: \n\
12158: <hr size=\"2\" color=\"#EC5E5E\">\
12159: <ul><li><h4>Parameter files</h4>\n\
12160: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
12161: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
12162: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12163: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12164: - Date and time at start: %s</ul>\n",\
12165: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
12166: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12167: fileres,fileres,\
12168: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12169: fflush(fichtm);
12170:
12171: strcpy(pathr,path);
12172: strcat(pathr,optionfilefiname);
1.184 brouard 12173: #ifdef WIN32
12174: _chdir(optionfilefiname); /* Move to directory named optionfile */
12175: #else
1.126 brouard 12176: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12177: #endif
12178:
1.126 brouard 12179:
1.220 brouard 12180: /* Calculates basic frequencies. Computes observed prevalence at single age
12181: and for any valid combination of covariates
1.126 brouard 12182: and prints on file fileres'p'. */
1.251 brouard 12183: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12184: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12185:
12186: fprintf(fichtm,"\n");
1.286 brouard 12187: 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 12188: ftol, stepm);
12189: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12190: ncurrv=1;
12191: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12192: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12193: ncurrv=i;
12194: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12195: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12196: ncurrv=i;
12197: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12198: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12199: ncurrv=i;
12200: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12201: 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", \
12202: nlstate, ndeath, maxwav, mle, weightopt);
12203:
12204: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12205: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12206:
12207:
1.317 brouard 12208: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12209: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12210: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12211: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12212: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12213: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12214: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12215: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12216: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12217:
1.126 brouard 12218: /* For Powell, parameters are in a vector p[] starting at p[1]
12219: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12220: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12221:
12222: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12223: /* For mortality only */
1.126 brouard 12224: if (mle==-3){
1.136 brouard 12225: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12226: for(i=1;i<=NDIM;i++)
12227: for(j=1;j<=NDIM;j++)
12228: ximort[i][j]=0.;
1.186 brouard 12229: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12230: cens=ivector(firstobs,lastobs);
12231: ageexmed=vector(firstobs,lastobs);
12232: agecens=vector(firstobs,lastobs);
12233: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12234:
1.126 brouard 12235: for (i=1; i<=imx; i++){
12236: dcwave[i]=-1;
12237: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12238: if (s[m][i]>nlstate) {
12239: dcwave[i]=m;
12240: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12241: break;
12242: }
1.126 brouard 12243: }
1.226 brouard 12244:
1.126 brouard 12245: for (i=1; i<=imx; i++) {
12246: if (wav[i]>0){
1.226 brouard 12247: ageexmed[i]=agev[mw[1][i]][i];
12248: j=wav[i];
12249: agecens[i]=1.;
12250:
12251: if (ageexmed[i]> 1 && wav[i] > 0){
12252: agecens[i]=agev[mw[j][i]][i];
12253: cens[i]= 1;
12254: }else if (ageexmed[i]< 1)
12255: cens[i]= -1;
12256: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12257: cens[i]=0 ;
1.126 brouard 12258: }
12259: else cens[i]=-1;
12260: }
12261:
12262: for (i=1;i<=NDIM;i++) {
12263: for (j=1;j<=NDIM;j++)
1.226 brouard 12264: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12265: }
12266:
1.302 brouard 12267: p[1]=0.0268; p[NDIM]=0.083;
12268: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12269:
12270:
1.136 brouard 12271: #ifdef GSL
12272: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12273: #else
1.126 brouard 12274: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12275: #endif
1.201 brouard 12276: strcpy(filerespow,"POW-MORT_");
12277: strcat(filerespow,fileresu);
1.126 brouard 12278: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12279: printf("Problem with resultfile: %s\n", filerespow);
12280: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12281: }
1.136 brouard 12282: #ifdef GSL
12283: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12284: #else
1.126 brouard 12285: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12286: #endif
1.126 brouard 12287: /* for (i=1;i<=nlstate;i++)
12288: for(j=1;j<=nlstate+ndeath;j++)
12289: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12290: */
12291: fprintf(ficrespow,"\n");
1.136 brouard 12292: #ifdef GSL
12293: /* gsl starts here */
12294: T = gsl_multimin_fminimizer_nmsimplex;
12295: gsl_multimin_fminimizer *sfm = NULL;
12296: gsl_vector *ss, *x;
12297: gsl_multimin_function minex_func;
12298:
12299: /* Initial vertex size vector */
12300: ss = gsl_vector_alloc (NDIM);
12301:
12302: if (ss == NULL){
12303: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12304: }
12305: /* Set all step sizes to 1 */
12306: gsl_vector_set_all (ss, 0.001);
12307:
12308: /* Starting point */
1.126 brouard 12309:
1.136 brouard 12310: x = gsl_vector_alloc (NDIM);
12311:
12312: if (x == NULL){
12313: gsl_vector_free(ss);
12314: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12315: }
12316:
12317: /* Initialize method and iterate */
12318: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12319: /* gsl_vector_set(x, 0, 0.0268); */
12320: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12321: gsl_vector_set(x, 0, p[1]);
12322: gsl_vector_set(x, 1, p[2]);
12323:
12324: minex_func.f = &gompertz_f;
12325: minex_func.n = NDIM;
12326: minex_func.params = (void *)&p; /* ??? */
12327:
12328: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12329: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12330:
12331: printf("Iterations beginning .....\n\n");
12332: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12333:
12334: iteri=0;
12335: while (rval == GSL_CONTINUE){
12336: iteri++;
12337: status = gsl_multimin_fminimizer_iterate(sfm);
12338:
12339: if (status) printf("error: %s\n", gsl_strerror (status));
12340: fflush(0);
12341:
12342: if (status)
12343: break;
12344:
12345: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12346: ssval = gsl_multimin_fminimizer_size (sfm);
12347:
12348: if (rval == GSL_SUCCESS)
12349: printf ("converged to a local maximum at\n");
12350:
12351: printf("%5d ", iteri);
12352: for (it = 0; it < NDIM; it++){
12353: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12354: }
12355: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12356: }
12357:
12358: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12359:
12360: gsl_vector_free(x); /* initial values */
12361: gsl_vector_free(ss); /* inital step size */
12362: for (it=0; it<NDIM; it++){
12363: p[it+1]=gsl_vector_get(sfm->x,it);
12364: fprintf(ficrespow," %.12lf", p[it]);
12365: }
12366: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12367: #endif
12368: #ifdef POWELL
12369: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12370: #endif
1.126 brouard 12371: fclose(ficrespow);
12372:
1.203 brouard 12373: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12374:
12375: for(i=1; i <=NDIM; i++)
12376: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12377: matcov[i][j]=matcov[j][i];
1.126 brouard 12378:
12379: printf("\nCovariance matrix\n ");
1.203 brouard 12380: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12381: for(i=1; i <=NDIM; i++) {
12382: for(j=1;j<=NDIM;j++){
1.220 brouard 12383: printf("%f ",matcov[i][j]);
12384: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12385: }
1.203 brouard 12386: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12387: }
12388:
12389: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12390: for (i=1;i<=NDIM;i++) {
1.126 brouard 12391: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12392: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12393: }
1.302 brouard 12394: lsurv=vector(agegomp,AGESUP);
12395: lpop=vector(agegomp,AGESUP);
12396: tpop=vector(agegomp,AGESUP);
1.126 brouard 12397: lsurv[agegomp]=100000;
12398:
12399: for (k=agegomp;k<=AGESUP;k++) {
12400: agemortsup=k;
12401: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12402: }
12403:
12404: for (k=agegomp;k<agemortsup;k++)
12405: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12406:
12407: for (k=agegomp;k<agemortsup;k++){
12408: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12409: sumlpop=sumlpop+lpop[k];
12410: }
12411:
12412: tpop[agegomp]=sumlpop;
12413: for (k=agegomp;k<(agemortsup-3);k++){
12414: /* tpop[k+1]=2;*/
12415: tpop[k+1]=tpop[k]-lpop[k];
12416: }
12417:
12418:
12419: printf("\nAge lx qx dx Lx Tx e(x)\n");
12420: for (k=agegomp;k<(agemortsup-2);k++)
12421: 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]);
12422:
12423:
12424: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12425: ageminpar=50;
12426: agemaxpar=100;
1.194 brouard 12427: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12428: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12429: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12430: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12431: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12432: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12433: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12434: }else{
12435: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12436: 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 12437: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12438: }
1.201 brouard 12439: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12440: stepm, weightopt,\
12441: model,imx,p,matcov,agemortsup);
12442:
1.302 brouard 12443: free_vector(lsurv,agegomp,AGESUP);
12444: free_vector(lpop,agegomp,AGESUP);
12445: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12446: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12447: free_ivector(dcwave,firstobs,lastobs);
12448: free_vector(agecens,firstobs,lastobs);
12449: free_vector(ageexmed,firstobs,lastobs);
12450: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12451: #ifdef GSL
1.136 brouard 12452: #endif
1.186 brouard 12453: } /* Endof if mle==-3 mortality only */
1.205 brouard 12454: /* Standard */
12455: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12456: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12457: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12458: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12459: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12460: for (k=1; k<=npar;k++)
12461: printf(" %d %8.5f",k,p[k]);
12462: printf("\n");
1.205 brouard 12463: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12464: /* mlikeli uses func not funcone */
1.247 brouard 12465: /* for(i=1;i<nlstate;i++){ */
12466: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12467: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12468: /* } */
1.205 brouard 12469: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12470: }
12471: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12472: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12473: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12474: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12475: }
12476: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12477: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12478: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12479: for (k=1; k<=npar;k++)
12480: printf(" %d %8.5f",k,p[k]);
12481: printf("\n");
12482:
12483: /*--------- results files --------------*/
1.283 brouard 12484: /* 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 12485:
12486:
12487: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12488: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 12489: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12490:
12491: printf("#model= 1 + age ");
12492: fprintf(ficres,"#model= 1 + age ");
12493: fprintf(ficlog,"#model= 1 + age ");
12494: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
12495: </ul>", model);
12496:
12497: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
12498: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
12499: if(nagesqr==1){
12500: printf(" + age*age ");
12501: fprintf(ficres," + age*age ");
12502: fprintf(ficlog," + age*age ");
12503: fprintf(fichtm, "<th>+ age*age</th>");
12504: }
12505: for(j=1;j <=ncovmodel-2;j++){
12506: if(Typevar[j]==0) {
12507: printf(" + V%d ",Tvar[j]);
12508: fprintf(ficres," + V%d ",Tvar[j]);
12509: fprintf(ficlog," + V%d ",Tvar[j]);
12510: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12511: }else if(Typevar[j]==1) {
12512: printf(" + V%d*age ",Tvar[j]);
12513: fprintf(ficres," + V%d*age ",Tvar[j]);
12514: fprintf(ficlog," + V%d*age ",Tvar[j]);
12515: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12516: }else if(Typevar[j]==2) {
12517: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12518: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12519: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12520: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12521: }
12522: }
12523: printf("\n");
12524: fprintf(ficres,"\n");
12525: fprintf(ficlog,"\n");
12526: fprintf(fichtm, "</tr>");
12527: fprintf(fichtm, "\n");
12528:
12529:
1.126 brouard 12530: for(i=1,jk=1; i <=nlstate; i++){
12531: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12532: if (k != i) {
1.319 brouard 12533: fprintf(fichtm, "<tr>");
1.225 brouard 12534: printf("%d%d ",i,k);
12535: fprintf(ficlog,"%d%d ",i,k);
12536: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 12537: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12538: for(j=1; j <=ncovmodel; j++){
12539: printf("%12.7f ",p[jk]);
12540: fprintf(ficlog,"%12.7f ",p[jk]);
12541: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 12542: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 12543: jk++;
12544: }
12545: printf("\n");
12546: fprintf(ficlog,"\n");
12547: fprintf(ficres,"\n");
1.319 brouard 12548: fprintf(fichtm, "</tr>\n");
1.225 brouard 12549: }
1.126 brouard 12550: }
12551: }
1.319 brouard 12552: /* fprintf(fichtm,"</tr>\n"); */
12553: fprintf(fichtm,"</table>\n");
12554: fprintf(fichtm, "\n");
12555:
1.203 brouard 12556: if(mle != 0){
12557: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12558: ftolhess=ftol; /* Usually correct */
1.203 brouard 12559: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12560: 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");
12561: 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 12562: 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 12563: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
12564: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
12565: if(nagesqr==1){
12566: printf(" + age*age ");
12567: fprintf(ficres," + age*age ");
12568: fprintf(ficlog," + age*age ");
12569: fprintf(fichtm, "<th>+ age*age</th>");
12570: }
12571: for(j=1;j <=ncovmodel-2;j++){
12572: if(Typevar[j]==0) {
12573: printf(" + V%d ",Tvar[j]);
12574: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12575: }else if(Typevar[j]==1) {
12576: printf(" + V%d*age ",Tvar[j]);
12577: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12578: }else if(Typevar[j]==2) {
12579: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12580: }
12581: }
12582: fprintf(fichtm, "</tr>\n");
12583:
1.203 brouard 12584: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12585: for(k=1; k <=(nlstate+ndeath); k++){
12586: if (k != i) {
1.319 brouard 12587: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 12588: printf("%d%d ",i,k);
12589: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 12590: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12591: for(j=1; j <=ncovmodel; j++){
1.319 brouard 12592: wald=p[jk]/sqrt(matcov[jk][jk]);
1.321 brouard 12593: printf("%12.7f(%12.7f) sqrt(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]));
12594: fprintf(ficlog,"%12.7f(%12.7f) sqrt(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 12595: if(fabs(wald) > 1.96){
1.321 brouard 12596: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 12597: }else{
12598: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
12599: }
1.321 brouard 12600: fprintf(fichtm,"sqrt(W)=%8.3f</br>",wald);
1.319 brouard 12601: 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 12602: jk++;
12603: }
12604: printf("\n");
12605: fprintf(ficlog,"\n");
1.319 brouard 12606: fprintf(fichtm, "</tr>\n");
1.225 brouard 12607: }
12608: }
1.193 brouard 12609: }
1.203 brouard 12610: } /* end of hesscov and Wald tests */
1.319 brouard 12611: fprintf(fichtm,"</table>\n");
1.225 brouard 12612:
1.203 brouard 12613: /* */
1.126 brouard 12614: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12615: printf("# Scales (for hessian or gradient estimation)\n");
12616: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12617: for(i=1,jk=1; i <=nlstate; i++){
12618: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12619: if (j!=i) {
12620: fprintf(ficres,"%1d%1d",i,j);
12621: printf("%1d%1d",i,j);
12622: fprintf(ficlog,"%1d%1d",i,j);
12623: for(k=1; k<=ncovmodel;k++){
12624: printf(" %.5e",delti[jk]);
12625: fprintf(ficlog," %.5e",delti[jk]);
12626: fprintf(ficres," %.5e",delti[jk]);
12627: jk++;
12628: }
12629: printf("\n");
12630: fprintf(ficlog,"\n");
12631: fprintf(ficres,"\n");
12632: }
1.126 brouard 12633: }
12634: }
12635:
12636: 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 12637: if(mle >= 1) /* To big for the screen */
1.126 brouard 12638: 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");
12639: 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");
12640: /* # 121 Var(a12)\n\ */
12641: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12642: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12643: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12644: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12645: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12646: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12647: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12648:
12649:
12650: /* Just to have a covariance matrix which will be more understandable
12651: even is we still don't want to manage dictionary of variables
12652: */
12653: for(itimes=1;itimes<=2;itimes++){
12654: jj=0;
12655: for(i=1; i <=nlstate; i++){
1.225 brouard 12656: for(j=1; j <=nlstate+ndeath; j++){
12657: if(j==i) continue;
12658: for(k=1; k<=ncovmodel;k++){
12659: jj++;
12660: ca[0]= k+'a'-1;ca[1]='\0';
12661: if(itimes==1){
12662: if(mle>=1)
12663: printf("#%1d%1d%d",i,j,k);
12664: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12665: fprintf(ficres,"#%1d%1d%d",i,j,k);
12666: }else{
12667: if(mle>=1)
12668: printf("%1d%1d%d",i,j,k);
12669: fprintf(ficlog,"%1d%1d%d",i,j,k);
12670: fprintf(ficres,"%1d%1d%d",i,j,k);
12671: }
12672: ll=0;
12673: for(li=1;li <=nlstate; li++){
12674: for(lj=1;lj <=nlstate+ndeath; lj++){
12675: if(lj==li) continue;
12676: for(lk=1;lk<=ncovmodel;lk++){
12677: ll++;
12678: if(ll<=jj){
12679: cb[0]= lk +'a'-1;cb[1]='\0';
12680: if(ll<jj){
12681: if(itimes==1){
12682: if(mle>=1)
12683: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12684: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12685: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12686: }else{
12687: if(mle>=1)
12688: printf(" %.5e",matcov[jj][ll]);
12689: fprintf(ficlog," %.5e",matcov[jj][ll]);
12690: fprintf(ficres," %.5e",matcov[jj][ll]);
12691: }
12692: }else{
12693: if(itimes==1){
12694: if(mle>=1)
12695: printf(" Var(%s%1d%1d)",ca,i,j);
12696: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12697: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12698: }else{
12699: if(mle>=1)
12700: printf(" %.7e",matcov[jj][ll]);
12701: fprintf(ficlog," %.7e",matcov[jj][ll]);
12702: fprintf(ficres," %.7e",matcov[jj][ll]);
12703: }
12704: }
12705: }
12706: } /* end lk */
12707: } /* end lj */
12708: } /* end li */
12709: if(mle>=1)
12710: printf("\n");
12711: fprintf(ficlog,"\n");
12712: fprintf(ficres,"\n");
12713: numlinepar++;
12714: } /* end k*/
12715: } /*end j */
1.126 brouard 12716: } /* end i */
12717: } /* end itimes */
12718:
12719: fflush(ficlog);
12720: fflush(ficres);
1.225 brouard 12721: while(fgets(line, MAXLINE, ficpar)) {
12722: /* If line starts with a # it is a comment */
12723: if (line[0] == '#') {
12724: numlinepar++;
12725: fputs(line,stdout);
12726: fputs(line,ficparo);
12727: fputs(line,ficlog);
1.299 brouard 12728: fputs(line,ficres);
1.225 brouard 12729: continue;
12730: }else
12731: break;
12732: }
12733:
1.209 brouard 12734: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12735: /* ungetc(c,ficpar); */
12736: /* fgets(line, MAXLINE, ficpar); */
12737: /* fputs(line,stdout); */
12738: /* fputs(line,ficparo); */
12739: /* } */
12740: /* ungetc(c,ficpar); */
1.126 brouard 12741:
12742: estepm=0;
1.209 brouard 12743: 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 12744:
12745: if (num_filled != 6) {
12746: 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);
12747: 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);
12748: goto end;
12749: }
12750: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12751: }
12752: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12753: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12754:
1.209 brouard 12755: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12756: if (estepm==0 || estepm < stepm) estepm=stepm;
12757: if (fage <= 2) {
12758: bage = ageminpar;
12759: fage = agemaxpar;
12760: }
12761:
12762: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12763: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12764: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12765:
1.186 brouard 12766: /* Other stuffs, more or less useful */
1.254 brouard 12767: while(fgets(line, MAXLINE, ficpar)) {
12768: /* If line starts with a # it is a comment */
12769: if (line[0] == '#') {
12770: numlinepar++;
12771: fputs(line,stdout);
12772: fputs(line,ficparo);
12773: fputs(line,ficlog);
1.299 brouard 12774: fputs(line,ficres);
1.254 brouard 12775: continue;
12776: }else
12777: break;
12778: }
12779:
12780: 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){
12781:
12782: if (num_filled != 7) {
12783: 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);
12784: 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);
12785: goto end;
12786: }
12787: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12788: 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);
12789: 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);
12790: 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 12791: }
1.254 brouard 12792:
12793: while(fgets(line, MAXLINE, ficpar)) {
12794: /* If line starts with a # it is a comment */
12795: if (line[0] == '#') {
12796: numlinepar++;
12797: fputs(line,stdout);
12798: fputs(line,ficparo);
12799: fputs(line,ficlog);
1.299 brouard 12800: fputs(line,ficres);
1.254 brouard 12801: continue;
12802: }else
12803: break;
1.126 brouard 12804: }
12805:
12806:
12807: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12808: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12809:
1.254 brouard 12810: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12811: if (num_filled != 1) {
12812: 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);
12813: 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);
12814: goto end;
12815: }
12816: printf("pop_based=%d\n",popbased);
12817: fprintf(ficlog,"pop_based=%d\n",popbased);
12818: fprintf(ficparo,"pop_based=%d\n",popbased);
12819: fprintf(ficres,"pop_based=%d\n",popbased);
12820: }
12821:
1.258 brouard 12822: /* Results */
1.307 brouard 12823: endishere=0;
1.258 brouard 12824: nresult=0;
1.308 brouard 12825: parameterline=0;
1.258 brouard 12826: do{
12827: if(!fgets(line, MAXLINE, ficpar)){
12828: endishere=1;
1.308 brouard 12829: parameterline=15;
1.258 brouard 12830: }else if (line[0] == '#') {
12831: /* If line starts with a # it is a comment */
1.254 brouard 12832: numlinepar++;
12833: fputs(line,stdout);
12834: fputs(line,ficparo);
12835: fputs(line,ficlog);
1.299 brouard 12836: fputs(line,ficres);
1.254 brouard 12837: continue;
1.258 brouard 12838: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12839: parameterline=11;
1.296 brouard 12840: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12841: parameterline=12;
1.307 brouard 12842: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 12843: parameterline=13;
1.307 brouard 12844: }
1.258 brouard 12845: else{
12846: parameterline=14;
1.254 brouard 12847: }
1.308 brouard 12848: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 12849: case 11:
1.296 brouard 12850: 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)){
12851: 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 12852: 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);
12853: 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);
12854: 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);
12855: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12856: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12857: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 12858: prvforecast = 1;
12859: }
12860: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 12861: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12862: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12863: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 12864: prvforecast = 2;
12865: }
12866: else {
12867: 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);
12868: 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);
12869: goto end;
1.258 brouard 12870: }
1.254 brouard 12871: break;
1.258 brouard 12872: case 12:
1.296 brouard 12873: 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)){
12874: 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);
12875: 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);
12876: 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);
12877: 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);
12878: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 12879: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12880: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 12881: prvbackcast = 1;
12882: }
12883: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 12884: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12885: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12886: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 12887: prvbackcast = 2;
12888: }
12889: else {
12890: 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);
12891: 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);
12892: goto end;
1.258 brouard 12893: }
1.230 brouard 12894: break;
1.258 brouard 12895: case 13:
1.307 brouard 12896: num_filled=sscanf(line,"result:%[^\n]\n",resultline);
12897: nresult++; /* Sum of resultlines */
12898: printf("Result %d: result:%s\n",nresult, resultline);
1.318 brouard 12899: if(nresult > MAXRESULTLINESPONE-1){
12900: 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);
12901: 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 12902: goto end;
12903: }
1.310 brouard 12904: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 12905: fprintf(ficparo,"result: %s\n",resultline);
12906: fprintf(ficres,"result: %s\n",resultline);
12907: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 12908: } else
12909: goto end;
1.307 brouard 12910: break;
12911: case 14:
12912: printf("Error: Unknown command '%s'\n",line);
12913: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 12914: if(line[0] == ' ' || line[0] == '\n'){
12915: printf("It should not be an empty line '%s'\n",line);
12916: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
12917: }
1.307 brouard 12918: if(ncovmodel >=2 && nresult==0 ){
12919: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
12920: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12921: }
1.307 brouard 12922: /* goto end; */
12923: break;
1.308 brouard 12924: case 15:
12925: printf("End of resultlines.\n");
12926: fprintf(ficlog,"End of resultlines.\n");
12927: break;
12928: default: /* parameterline =0 */
1.307 brouard 12929: nresult=1;
12930: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 12931: } /* End switch parameterline */
12932: }while(endishere==0); /* End do */
1.126 brouard 12933:
1.230 brouard 12934: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12935: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12936:
12937: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12938: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12939: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12940: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12941: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12942: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12943: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12944: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12945: }else{
1.270 brouard 12946: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 12947: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
12948: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
12949: if(prvforecast==1){
12950: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
12951: jprojd=jproj1;
12952: mprojd=mproj1;
12953: anprojd=anproj1;
12954: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
12955: jprojf=jproj2;
12956: mprojf=mproj2;
12957: anprojf=anproj2;
12958: } else if(prvforecast == 2){
12959: dateprojd=dateintmean;
12960: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
12961: dateprojf=dateintmean+yrfproj;
12962: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
12963: }
12964: if(prvbackcast==1){
12965: datebackd=(jback1+12*mback1+365*anback1)/365;
12966: jbackd=jback1;
12967: mbackd=mback1;
12968: anbackd=anback1;
12969: datebackf=(jback2+12*mback2+365*anback2)/365;
12970: jbackf=jback2;
12971: mbackf=mback2;
12972: anbackf=anback2;
12973: } else if(prvbackcast == 2){
12974: datebackd=dateintmean;
12975: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
12976: datebackf=dateintmean-yrbproj;
12977: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
12978: }
12979:
12980: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 12981: }
12982: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 12983: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
12984: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 12985:
1.225 brouard 12986: /*------------ free_vector -------------*/
12987: /* chdir(path); */
1.220 brouard 12988:
1.215 brouard 12989: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12990: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12991: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12992: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12993: free_lvector(num,firstobs,lastobs);
12994: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12995: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12996: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12997: fclose(ficparo);
12998: fclose(ficres);
1.220 brouard 12999:
13000:
1.186 brouard 13001: /* Other results (useful)*/
1.220 brouard 13002:
13003:
1.126 brouard 13004: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13005: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13006: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 13007: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13008: fclose(ficrespl);
13009:
13010: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13011: /*#include "hpijx.h"*/
13012: hPijx(p, bage, fage);
1.145 brouard 13013: fclose(ficrespij);
1.227 brouard 13014:
1.220 brouard 13015: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 13016: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 13017: k=1;
1.126 brouard 13018: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13019:
1.269 brouard 13020: /* Prevalence for each covariate combination in probs[age][status][cov] */
13021: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13022: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13023: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13024: for(k=1;k<=ncovcombmax;k++)
13025: probs[i][j][k]=0.;
1.269 brouard 13026: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13027: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13028: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13029: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13030: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13031: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13032: for(k=1;k<=ncovcombmax;k++)
13033: mobaverages[i][j][k]=0.;
1.219 brouard 13034: mobaverage=mobaverages;
13035: if (mobilav!=0) {
1.235 brouard 13036: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13037: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13038: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13039: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13040: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13041: }
1.269 brouard 13042: } else if (mobilavproj !=0) {
1.235 brouard 13043: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13044: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13045: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13046: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13047: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13048: }
1.269 brouard 13049: }else{
13050: printf("Internal error moving average\n");
13051: fflush(stdout);
13052: exit(1);
1.219 brouard 13053: }
13054: }/* end if moving average */
1.227 brouard 13055:
1.126 brouard 13056: /*---------- Forecasting ------------------*/
1.296 brouard 13057: if(prevfcast==1){
13058: /* /\* if(stepm ==1){*\/ */
13059: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13060: /*This done previously after freqsummary.*/
13061: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13062: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13063:
13064: /* } else if (prvforecast==2){ */
13065: /* /\* if(stepm ==1){*\/ */
13066: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13067: /* } */
13068: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13069: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13070: }
1.269 brouard 13071:
1.296 brouard 13072: /* Prevbcasting */
13073: if(prevbcast==1){
1.219 brouard 13074: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13075: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13076: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13077:
13078: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13079:
13080: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13081:
1.219 brouard 13082: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13083: fclose(ficresplb);
13084:
1.222 brouard 13085: hBijx(p, bage, fage, mobaverage);
13086: fclose(ficrespijb);
1.219 brouard 13087:
1.296 brouard 13088: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13089: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13090: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13091: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13092: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13093: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13094:
13095:
1.269 brouard 13096: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13097:
13098:
1.269 brouard 13099: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13100: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13101: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13102: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13103: } /* end Prevbcasting */
1.268 brouard 13104:
1.186 brouard 13105:
13106: /* ------ Other prevalence ratios------------ */
1.126 brouard 13107:
1.215 brouard 13108: free_ivector(wav,1,imx);
13109: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13110: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13111: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13112:
13113:
1.127 brouard 13114: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 13115:
1.201 brouard 13116: strcpy(filerese,"E_");
13117: strcat(filerese,fileresu);
1.126 brouard 13118: if((ficreseij=fopen(filerese,"w"))==NULL) {
13119: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13120: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13121: }
1.208 brouard 13122: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
13123: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 13124:
13125: pstamp(ficreseij);
1.219 brouard 13126:
1.235 brouard 13127: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13128: if (cptcovn < 1){i1=1;}
13129:
13130: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13131: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13132: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13133: continue;
1.219 brouard 13134: fprintf(ficreseij,"\n#****** ");
1.235 brouard 13135: printf("\n#****** ");
1.225 brouard 13136: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13137: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13138: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13139: }
13140: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13141: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13142: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 13143: }
13144: fprintf(ficreseij,"******\n");
1.235 brouard 13145: printf("******\n");
1.219 brouard 13146:
13147: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13148: oldm=oldms;savm=savms;
1.235 brouard 13149: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 13150:
1.219 brouard 13151: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 13152: }
13153: fclose(ficreseij);
1.208 brouard 13154: printf("done evsij\n");fflush(stdout);
13155: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 13156:
1.218 brouard 13157:
1.227 brouard 13158: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 13159:
1.201 brouard 13160: strcpy(filerest,"T_");
13161: strcat(filerest,fileresu);
1.127 brouard 13162: if((ficrest=fopen(filerest,"w"))==NULL) {
13163: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
13164: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
13165: }
1.208 brouard 13166: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
13167: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 13168: strcpy(fileresstde,"STDE_");
13169: strcat(fileresstde,fileresu);
1.126 brouard 13170: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 13171: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
13172: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 13173: }
1.227 brouard 13174: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
13175: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 13176:
1.201 brouard 13177: strcpy(filerescve,"CVE_");
13178: strcat(filerescve,fileresu);
1.126 brouard 13179: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 13180: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
13181: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 13182: }
1.227 brouard 13183: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
13184: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 13185:
1.201 brouard 13186: strcpy(fileresv,"V_");
13187: strcat(fileresv,fileresu);
1.126 brouard 13188: if((ficresvij=fopen(fileresv,"w"))==NULL) {
13189: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
13190: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
13191: }
1.227 brouard 13192: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
13193: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 13194:
1.235 brouard 13195: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13196: if (cptcovn < 1){i1=1;}
13197:
13198: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13199: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13200: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13201: continue;
1.321 brouard 13202: printf("\n# model %s \n#****** Result for:", model);
13203: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
13204: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.227 brouard 13205: for(j=1;j<=cptcoveff;j++){
13206: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13207: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13208: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13209: }
1.235 brouard 13210: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13211: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13212: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13213: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13214: }
1.208 brouard 13215: fprintf(ficrest,"******\n");
1.227 brouard 13216: fprintf(ficlog,"******\n");
13217: printf("******\n");
1.208 brouard 13218:
13219: fprintf(ficresstdeij,"\n#****** ");
13220: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 13221: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13222: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13223: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 13224: }
1.235 brouard 13225: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13226: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13227: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13228: }
1.208 brouard 13229: fprintf(ficresstdeij,"******\n");
13230: fprintf(ficrescveij,"******\n");
13231:
13232: fprintf(ficresvij,"\n#****** ");
1.238 brouard 13233: /* pstamp(ficresvij); */
1.225 brouard 13234: for(j=1;j<=cptcoveff;j++)
1.227 brouard 13235: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13236: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13237: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13238: }
1.208 brouard 13239: fprintf(ficresvij,"******\n");
13240:
13241: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13242: oldm=oldms;savm=savms;
1.235 brouard 13243: printf(" cvevsij ");
13244: fprintf(ficlog, " cvevsij ");
13245: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 13246: printf(" end cvevsij \n ");
13247: fprintf(ficlog, " end cvevsij \n ");
13248:
13249: /*
13250: */
13251: /* goto endfree; */
13252:
13253: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13254: pstamp(ficrest);
13255:
1.269 brouard 13256: epj=vector(1,nlstate+1);
1.208 brouard 13257: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 13258: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
13259: cptcod= 0; /* To be deleted */
13260: printf("varevsij vpopbased=%d \n",vpopbased);
13261: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 13262: 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 13263: 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 ");
13264: if(vpopbased==1)
13265: 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);
13266: else
1.288 brouard 13267: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13268: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
13269: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
13270: fprintf(ficrest,"\n");
13271: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 13272: printf("Computing age specific forward period (stable) prevalences in each health state \n");
13273: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13274: for(age=bage; age <=fage ;age++){
1.235 brouard 13275: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 13276: if (vpopbased==1) {
13277: if(mobilav ==0){
13278: for(i=1; i<=nlstate;i++)
13279: prlim[i][i]=probs[(int)age][i][k];
13280: }else{ /* mobilav */
13281: for(i=1; i<=nlstate;i++)
13282: prlim[i][i]=mobaverage[(int)age][i][k];
13283: }
13284: }
1.219 brouard 13285:
1.227 brouard 13286: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
13287: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
13288: /* printf(" age %4.0f ",age); */
13289: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
13290: for(i=1, epj[j]=0.;i <=nlstate;i++) {
13291: epj[j] += prlim[i][i]*eij[i][j][(int)age];
13292: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
13293: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
13294: }
13295: epj[nlstate+1] +=epj[j];
13296: }
13297: /* printf(" age %4.0f \n",age); */
1.219 brouard 13298:
1.227 brouard 13299: for(i=1, vepp=0.;i <=nlstate;i++)
13300: for(j=1;j <=nlstate;j++)
13301: vepp += vareij[i][j][(int)age];
13302: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
13303: for(j=1;j <=nlstate;j++){
13304: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
13305: }
13306: fprintf(ficrest,"\n");
13307: }
1.208 brouard 13308: } /* End vpopbased */
1.269 brouard 13309: free_vector(epj,1,nlstate+1);
1.208 brouard 13310: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
13311: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 13312: printf("done selection\n");fflush(stdout);
13313: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 13314:
1.235 brouard 13315: } /* End k selection */
1.227 brouard 13316:
13317: printf("done State-specific expectancies\n");fflush(stdout);
13318: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
13319:
1.288 brouard 13320: /* variance-covariance of forward period prevalence*/
1.269 brouard 13321: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13322:
1.227 brouard 13323:
1.290 brouard 13324: free_vector(weight,firstobs,lastobs);
1.227 brouard 13325: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 13326: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
13327: free_matrix(anint,1,maxwav,firstobs,lastobs);
13328: free_matrix(mint,1,maxwav,firstobs,lastobs);
13329: free_ivector(cod,firstobs,lastobs);
1.227 brouard 13330: free_ivector(tab,1,NCOVMAX);
13331: fclose(ficresstdeij);
13332: fclose(ficrescveij);
13333: fclose(ficresvij);
13334: fclose(ficrest);
13335: fclose(ficpar);
13336:
13337:
1.126 brouard 13338: /*---------- End : free ----------------*/
1.219 brouard 13339: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 13340: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
13341: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 13342: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
13343: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 13344: } /* mle==-3 arrives here for freeing */
1.227 brouard 13345: /* endfree:*/
13346: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
13347: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
13348: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 13349: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13350: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13351: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13352: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13353: free_matrix(matcov,1,npar,1,npar);
13354: free_matrix(hess,1,npar,1,npar);
13355: /*free_vector(delti,1,npar);*/
13356: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13357: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13358: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13359: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13360:
13361: free_ivector(ncodemax,1,NCOVMAX);
13362: free_ivector(ncodemaxwundef,1,NCOVMAX);
13363: free_ivector(Dummy,-1,NCOVMAX);
13364: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13365: free_ivector(DummyV,1,NCOVMAX);
13366: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13367: free_ivector(Typevar,-1,NCOVMAX);
13368: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13369: free_ivector(TvarsQ,1,NCOVMAX);
13370: free_ivector(TvarsQind,1,NCOVMAX);
13371: free_ivector(TvarsD,1,NCOVMAX);
13372: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13373: free_ivector(TvarFD,1,NCOVMAX);
13374: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13375: free_ivector(TvarF,1,NCOVMAX);
13376: free_ivector(TvarFind,1,NCOVMAX);
13377: free_ivector(TvarV,1,NCOVMAX);
13378: free_ivector(TvarVind,1,NCOVMAX);
13379: free_ivector(TvarA,1,NCOVMAX);
13380: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13381: free_ivector(TvarFQ,1,NCOVMAX);
13382: free_ivector(TvarFQind,1,NCOVMAX);
13383: free_ivector(TvarVD,1,NCOVMAX);
13384: free_ivector(TvarVDind,1,NCOVMAX);
13385: free_ivector(TvarVQ,1,NCOVMAX);
13386: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13387: free_ivector(Tvarsel,1,NCOVMAX);
13388: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13389: free_ivector(Tposprod,1,NCOVMAX);
13390: free_ivector(Tprod,1,NCOVMAX);
13391: free_ivector(Tvaraff,1,NCOVMAX);
13392: free_ivector(invalidvarcomb,1,ncovcombmax);
13393: free_ivector(Tage,1,NCOVMAX);
13394: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 13395: free_ivector(TmodelInvind,1,NCOVMAX);
13396: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 13397:
13398: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
13399: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 13400: fflush(fichtm);
13401: fflush(ficgp);
13402:
1.227 brouard 13403:
1.126 brouard 13404: if((nberr >0) || (nbwarn>0)){
1.216 brouard 13405: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
13406: 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 13407: }else{
13408: printf("End of Imach\n");
13409: fprintf(ficlog,"End of Imach\n");
13410: }
13411: printf("See log file on %s\n",filelog);
13412: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 13413: /*(void) gettimeofday(&end_time,&tzp);*/
13414: rend_time = time(NULL);
13415: end_time = *localtime(&rend_time);
13416: /* tml = *localtime(&end_time.tm_sec); */
13417: strcpy(strtend,asctime(&end_time));
1.126 brouard 13418: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13419: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13420: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13421:
1.157 brouard 13422: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13423: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13424: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13425: /* printf("Total time was %d uSec.\n", total_usecs);*/
13426: /* if(fileappend(fichtm,optionfilehtm)){ */
13427: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13428: fclose(fichtm);
13429: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13430: fclose(fichtmcov);
13431: fclose(ficgp);
13432: fclose(ficlog);
13433: /*------ End -----------*/
1.227 brouard 13434:
1.281 brouard 13435:
13436: /* Executes gnuplot */
1.227 brouard 13437:
13438: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13439: #ifdef WIN32
1.227 brouard 13440: if (_chdir(pathcd) != 0)
13441: printf("Can't move to directory %s!\n",path);
13442: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13443: #else
1.227 brouard 13444: if(chdir(pathcd) != 0)
13445: printf("Can't move to directory %s!\n", path);
13446: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13447: #endif
1.126 brouard 13448: printf("Current directory %s!\n",pathcd);
13449: /*strcat(plotcmd,CHARSEPARATOR);*/
13450: sprintf(plotcmd,"gnuplot");
1.157 brouard 13451: #ifdef _WIN32
1.126 brouard 13452: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13453: #endif
13454: if(!stat(plotcmd,&info)){
1.158 brouard 13455: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13456: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13457: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13458: }else
13459: strcpy(pplotcmd,plotcmd);
1.157 brouard 13460: #ifdef __unix
1.126 brouard 13461: strcpy(plotcmd,GNUPLOTPROGRAM);
13462: if(!stat(plotcmd,&info)){
1.158 brouard 13463: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13464: }else
13465: strcpy(pplotcmd,plotcmd);
13466: #endif
13467: }else
13468: strcpy(pplotcmd,plotcmd);
13469:
13470: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13471: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13472: strcpy(pplotcmd,plotcmd);
1.227 brouard 13473:
1.126 brouard 13474: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13475: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13476: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13477: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13478: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13479: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13480: strcpy(plotcmd,pplotcmd);
13481: }
1.126 brouard 13482: }
1.158 brouard 13483: printf(" Successful, please wait...");
1.126 brouard 13484: while (z[0] != 'q') {
13485: /* chdir(path); */
1.154 brouard 13486: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13487: scanf("%s",z);
13488: /* if (z[0] == 'c') system("./imach"); */
13489: if (z[0] == 'e') {
1.158 brouard 13490: #ifdef __APPLE__
1.152 brouard 13491: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13492: #elif __linux
13493: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13494: #else
1.152 brouard 13495: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13496: #endif
13497: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13498: system(pplotcmd);
1.126 brouard 13499: }
13500: else if (z[0] == 'g') system(plotcmd);
13501: else if (z[0] == 'q') exit(0);
13502: }
1.227 brouard 13503: end:
1.126 brouard 13504: while (z[0] != 'q') {
1.195 brouard 13505: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13506: scanf("%s",z);
13507: }
1.283 brouard 13508: printf("End\n");
1.282 brouard 13509: exit(0);
1.126 brouard 13510: }
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