Annotation of imach/src/imach.c, revision 1.325
1.325 ! brouard 1: /* $Id: imach.c,v 1.324 2022/07/23 17:44:26 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.325 ! brouard 4: Revision 1.324 2022/07/23 17:44:26 brouard
! 5: *** empty log message ***
! 6:
1.324 brouard 7: Revision 1.323 2022/07/22 12:30:08 brouard
8: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
9:
1.323 brouard 10: Revision 1.322 2022/07/22 12:27:48 brouard
11: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
12:
1.322 brouard 13: Revision 1.321 2022/07/22 12:04:24 brouard
14: Summary: r28
15:
16: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
17:
1.321 brouard 18: Revision 1.320 2022/06/02 05:10:11 brouard
19: *** empty log message ***
20:
1.320 brouard 21: Revision 1.319 2022/06/02 04:45:11 brouard
22: * imach.c (Module): Adding the Wald tests from the log to the main
23: htm for better display of the maximum likelihood estimators.
24:
1.319 brouard 25: Revision 1.318 2022/05/24 08:10:59 brouard
26: * imach.c (Module): Some attempts to find a bug of wrong estimates
27: of confidencce intervals with product in the equation modelC
28:
1.318 brouard 29: Revision 1.317 2022/05/15 15:06:23 brouard
30: * imach.c (Module): Some minor improvements
31:
1.317 brouard 32: Revision 1.316 2022/05/11 15:11:31 brouard
33: Summary: r27
34:
1.316 brouard 35: Revision 1.315 2022/05/11 15:06:32 brouard
36: *** empty log message ***
37:
1.315 brouard 38: Revision 1.314 2022/04/13 17:43:09 brouard
39: * imach.c (Module): Adding link to text data files
40:
1.314 brouard 41: Revision 1.313 2022/04/11 15:57:42 brouard
42: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
43:
1.313 brouard 44: Revision 1.312 2022/04/05 21:24:39 brouard
45: *** empty log message ***
46:
1.312 brouard 47: Revision 1.311 2022/04/05 21:03:51 brouard
48: Summary: Fixed quantitative covariates
49:
50: Fixed covariates (dummy or quantitative)
51: with missing values have never been allowed but are ERRORS and
52: program quits. Standard deviations of fixed covariates were
53: wrongly computed. Mean and standard deviations of time varying
54: covariates are still not computed.
55:
1.311 brouard 56: Revision 1.310 2022/03/17 08:45:53 brouard
57: Summary: 99r25
58:
59: Improving detection of errors: result lines should be compatible with
60: the model.
61:
1.310 brouard 62: Revision 1.309 2021/05/20 12:39:14 brouard
63: Summary: Version 0.99r24
64:
1.309 brouard 65: Revision 1.308 2021/03/31 13:11:57 brouard
66: Summary: Version 0.99r23
67:
68:
69: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
70:
1.308 brouard 71: Revision 1.307 2021/03/08 18:11:32 brouard
72: Summary: 0.99r22 fixed bug on result:
73:
1.307 brouard 74: Revision 1.306 2021/02/20 15:44:02 brouard
75: Summary: Version 0.99r21
76:
77: * imach.c (Module): Fix bug on quitting after result lines!
78: (Module): Version 0.99r21
79:
1.306 brouard 80: Revision 1.305 2021/02/20 15:28:30 brouard
81: * imach.c (Module): Fix bug on quitting after result lines!
82:
1.305 brouard 83: Revision 1.304 2021/02/12 11:34:20 brouard
84: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
85:
1.304 brouard 86: Revision 1.303 2021/02/11 19:50:15 brouard
87: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
88:
1.303 brouard 89: Revision 1.302 2020/02/22 21:00:05 brouard
90: * (Module): imach.c Update mle=-3 (for computing Life expectancy
91: and life table from the data without any state)
92:
1.302 brouard 93: Revision 1.301 2019/06/04 13:51:20 brouard
94: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
95:
1.301 brouard 96: Revision 1.300 2019/05/22 19:09:45 brouard
97: Summary: version 0.99r19 of May 2019
98:
1.300 brouard 99: Revision 1.299 2019/05/22 18:37:08 brouard
100: Summary: Cleaned 0.99r19
101:
1.299 brouard 102: Revision 1.298 2019/05/22 18:19:56 brouard
103: *** empty log message ***
104:
1.298 brouard 105: Revision 1.297 2019/05/22 17:56:10 brouard
106: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
107:
1.297 brouard 108: Revision 1.296 2019/05/20 13:03:18 brouard
109: Summary: Projection syntax simplified
110:
111:
112: We can now start projections, forward or backward, from the mean date
113: of inteviews up to or down to a number of years of projection:
114: prevforecast=1 yearsfproj=15.3 mobil_average=0
115: or
116: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
117: or
118: prevbackcast=1 yearsbproj=12.3 mobil_average=1
119: or
120: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
121:
1.296 brouard 122: Revision 1.295 2019/05/18 09:52:50 brouard
123: Summary: doxygen tex bug
124:
1.295 brouard 125: Revision 1.294 2019/05/16 14:54:33 brouard
126: Summary: There was some wrong lines added
127:
1.294 brouard 128: Revision 1.293 2019/05/09 15:17:34 brouard
129: *** empty log message ***
130:
1.293 brouard 131: Revision 1.292 2019/05/09 14:17:20 brouard
132: Summary: Some updates
133:
1.292 brouard 134: Revision 1.291 2019/05/09 13:44:18 brouard
135: Summary: Before ncovmax
136:
1.291 brouard 137: Revision 1.290 2019/05/09 13:39:37 brouard
138: Summary: 0.99r18 unlimited number of individuals
139:
140: 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.
141:
1.290 brouard 142: Revision 1.289 2018/12/13 09:16:26 brouard
143: Summary: Bug for young ages (<-30) will be in r17
144:
1.289 brouard 145: Revision 1.288 2018/05/02 20:58:27 brouard
146: Summary: Some bugs fixed
147:
1.288 brouard 148: Revision 1.287 2018/05/01 17:57:25 brouard
149: Summary: Bug fixed by providing frequencies only for non missing covariates
150:
1.287 brouard 151: Revision 1.286 2018/04/27 14:27:04 brouard
152: Summary: some minor bugs
153:
1.286 brouard 154: Revision 1.285 2018/04/21 21:02:16 brouard
155: Summary: Some bugs fixed, valgrind tested
156:
1.285 brouard 157: Revision 1.284 2018/04/20 05:22:13 brouard
158: Summary: Computing mean and stdeviation of fixed quantitative variables
159:
1.284 brouard 160: Revision 1.283 2018/04/19 14:49:16 brouard
161: Summary: Some minor bugs fixed
162:
1.283 brouard 163: Revision 1.282 2018/02/27 22:50:02 brouard
164: *** empty log message ***
165:
1.282 brouard 166: Revision 1.281 2018/02/27 19:25:23 brouard
167: Summary: Adding second argument for quitting
168:
1.281 brouard 169: Revision 1.280 2018/02/21 07:58:13 brouard
170: Summary: 0.99r15
171:
172: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
173:
1.280 brouard 174: Revision 1.279 2017/07/20 13:35:01 brouard
175: Summary: temporary working
176:
1.279 brouard 177: Revision 1.278 2017/07/19 14:09:02 brouard
178: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
179:
1.278 brouard 180: Revision 1.277 2017/07/17 08:53:49 brouard
181: Summary: BOM files can be read now
182:
1.277 brouard 183: Revision 1.276 2017/06/30 15:48:31 brouard
184: Summary: Graphs improvements
185:
1.276 brouard 186: Revision 1.275 2017/06/30 13:39:33 brouard
187: Summary: Saito's color
188:
1.275 brouard 189: Revision 1.274 2017/06/29 09:47:08 brouard
190: Summary: Version 0.99r14
191:
1.274 brouard 192: Revision 1.273 2017/06/27 11:06:02 brouard
193: Summary: More documentation on projections
194:
1.273 brouard 195: Revision 1.272 2017/06/27 10:22:40 brouard
196: Summary: Color of backprojection changed from 6 to 5(yellow)
197:
1.272 brouard 198: Revision 1.271 2017/06/27 10:17:50 brouard
199: Summary: Some bug with rint
200:
1.271 brouard 201: Revision 1.270 2017/05/24 05:45:29 brouard
202: *** empty log message ***
203:
1.270 brouard 204: Revision 1.269 2017/05/23 08:39:25 brouard
205: Summary: Code into subroutine, cleanings
206:
1.269 brouard 207: Revision 1.268 2017/05/18 20:09:32 brouard
208: Summary: backprojection and confidence intervals of backprevalence
209:
1.268 brouard 210: Revision 1.267 2017/05/13 10:25:05 brouard
211: Summary: temporary save for backprojection
212:
1.267 brouard 213: Revision 1.266 2017/05/13 07:26:12 brouard
214: Summary: Version 0.99r13 (improvements and bugs fixed)
215:
1.266 brouard 216: Revision 1.265 2017/04/26 16:22:11 brouard
217: Summary: imach 0.99r13 Some bugs fixed
218:
1.265 brouard 219: Revision 1.264 2017/04/26 06:01:29 brouard
220: Summary: Labels in graphs
221:
1.264 brouard 222: Revision 1.263 2017/04/24 15:23:15 brouard
223: Summary: to save
224:
1.263 brouard 225: Revision 1.262 2017/04/18 16:48:12 brouard
226: *** empty log message ***
227:
1.262 brouard 228: Revision 1.261 2017/04/05 10:14:09 brouard
229: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
230:
1.261 brouard 231: Revision 1.260 2017/04/04 17:46:59 brouard
232: Summary: Gnuplot indexations fixed (humm)
233:
1.260 brouard 234: Revision 1.259 2017/04/04 13:01:16 brouard
235: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
236:
1.259 brouard 237: Revision 1.258 2017/04/03 10:17:47 brouard
238: Summary: Version 0.99r12
239:
240: Some cleanings, conformed with updated documentation.
241:
1.258 brouard 242: Revision 1.257 2017/03/29 16:53:30 brouard
243: Summary: Temp
244:
1.257 brouard 245: Revision 1.256 2017/03/27 05:50:23 brouard
246: Summary: Temporary
247:
1.256 brouard 248: Revision 1.255 2017/03/08 16:02:28 brouard
249: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
250:
1.255 brouard 251: Revision 1.254 2017/03/08 07:13:00 brouard
252: Summary: Fixing data parameter line
253:
1.254 brouard 254: Revision 1.253 2016/12/15 11:59:41 brouard
255: Summary: 0.99 in progress
256:
1.253 brouard 257: Revision 1.252 2016/09/15 21:15:37 brouard
258: *** empty log message ***
259:
1.252 brouard 260: Revision 1.251 2016/09/15 15:01:13 brouard
261: Summary: not working
262:
1.251 brouard 263: Revision 1.250 2016/09/08 16:07:27 brouard
264: Summary: continue
265:
1.250 brouard 266: Revision 1.249 2016/09/07 17:14:18 brouard
267: Summary: Starting values from frequencies
268:
1.249 brouard 269: Revision 1.248 2016/09/07 14:10:18 brouard
270: *** empty log message ***
271:
1.248 brouard 272: Revision 1.247 2016/09/02 11:11:21 brouard
273: *** empty log message ***
274:
1.247 brouard 275: Revision 1.246 2016/09/02 08:49:22 brouard
276: *** empty log message ***
277:
1.246 brouard 278: Revision 1.245 2016/09/02 07:25:01 brouard
279: *** empty log message ***
280:
1.245 brouard 281: Revision 1.244 2016/09/02 07:17:34 brouard
282: *** empty log message ***
283:
1.244 brouard 284: Revision 1.243 2016/09/02 06:45:35 brouard
285: *** empty log message ***
286:
1.243 brouard 287: Revision 1.242 2016/08/30 15:01:20 brouard
288: Summary: Fixing a lots
289:
1.242 brouard 290: Revision 1.241 2016/08/29 17:17:25 brouard
291: Summary: gnuplot problem in Back projection to fix
292:
1.241 brouard 293: Revision 1.240 2016/08/29 07:53:18 brouard
294: Summary: Better
295:
1.240 brouard 296: Revision 1.239 2016/08/26 15:51:03 brouard
297: Summary: Improvement in Powell output in order to copy and paste
298:
299: Author:
300:
1.239 brouard 301: Revision 1.238 2016/08/26 14:23:35 brouard
302: Summary: Starting tests of 0.99
303:
1.238 brouard 304: Revision 1.237 2016/08/26 09:20:19 brouard
305: Summary: to valgrind
306:
1.237 brouard 307: Revision 1.236 2016/08/25 10:50:18 brouard
308: *** empty log message ***
309:
1.236 brouard 310: Revision 1.235 2016/08/25 06:59:23 brouard
311: *** empty log message ***
312:
1.235 brouard 313: Revision 1.234 2016/08/23 16:51:20 brouard
314: *** empty log message ***
315:
1.234 brouard 316: Revision 1.233 2016/08/23 07:40:50 brouard
317: Summary: not working
318:
1.233 brouard 319: Revision 1.232 2016/08/22 14:20:21 brouard
320: Summary: not working
321:
1.232 brouard 322: Revision 1.231 2016/08/22 07:17:15 brouard
323: Summary: not working
324:
1.231 brouard 325: Revision 1.230 2016/08/22 06:55:53 brouard
326: Summary: Not working
327:
1.230 brouard 328: Revision 1.229 2016/07/23 09:45:53 brouard
329: Summary: Completing for func too
330:
1.229 brouard 331: Revision 1.228 2016/07/22 17:45:30 brouard
332: Summary: Fixing some arrays, still debugging
333:
1.227 brouard 334: Revision 1.226 2016/07/12 18:42:34 brouard
335: Summary: temp
336:
1.226 brouard 337: Revision 1.225 2016/07/12 08:40:03 brouard
338: Summary: saving but not running
339:
1.225 brouard 340: Revision 1.224 2016/07/01 13:16:01 brouard
341: Summary: Fixes
342:
1.224 brouard 343: Revision 1.223 2016/02/19 09:23:35 brouard
344: Summary: temporary
345:
1.223 brouard 346: Revision 1.222 2016/02/17 08:14:50 brouard
347: Summary: Probably last 0.98 stable version 0.98r6
348:
1.222 brouard 349: Revision 1.221 2016/02/15 23:35:36 brouard
350: Summary: minor bug
351:
1.220 brouard 352: Revision 1.219 2016/02/15 00:48:12 brouard
353: *** empty log message ***
354:
1.219 brouard 355: Revision 1.218 2016/02/12 11:29:23 brouard
356: Summary: 0.99 Back projections
357:
1.218 brouard 358: Revision 1.217 2015/12/23 17:18:31 brouard
359: Summary: Experimental backcast
360:
1.217 brouard 361: Revision 1.216 2015/12/18 17:32:11 brouard
362: Summary: 0.98r4 Warning and status=-2
363:
364: Version 0.98r4 is now:
365: - displaying an error when status is -1, date of interview unknown and date of death known;
366: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
367: Older changes concerning s=-2, dating from 2005 have been supersed.
368:
1.216 brouard 369: Revision 1.215 2015/12/16 08:52:24 brouard
370: Summary: 0.98r4 working
371:
1.215 brouard 372: Revision 1.214 2015/12/16 06:57:54 brouard
373: Summary: temporary not working
374:
1.214 brouard 375: Revision 1.213 2015/12/11 18:22:17 brouard
376: Summary: 0.98r4
377:
1.213 brouard 378: Revision 1.212 2015/11/21 12:47:24 brouard
379: Summary: minor typo
380:
1.212 brouard 381: Revision 1.211 2015/11/21 12:41:11 brouard
382: Summary: 0.98r3 with some graph of projected cross-sectional
383:
384: Author: Nicolas Brouard
385:
1.211 brouard 386: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 387: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 388: Summary: Adding ftolpl parameter
389: Author: N Brouard
390:
391: We had difficulties to get smoothed confidence intervals. It was due
392: to the period prevalence which wasn't computed accurately. The inner
393: parameter ftolpl is now an outer parameter of the .imach parameter
394: file after estepm. If ftolpl is small 1.e-4 and estepm too,
395: computation are long.
396:
1.209 brouard 397: Revision 1.208 2015/11/17 14:31:57 brouard
398: Summary: temporary
399:
1.208 brouard 400: Revision 1.207 2015/10/27 17:36:57 brouard
401: *** empty log message ***
402:
1.207 brouard 403: Revision 1.206 2015/10/24 07:14:11 brouard
404: *** empty log message ***
405:
1.206 brouard 406: Revision 1.205 2015/10/23 15:50:53 brouard
407: Summary: 0.98r3 some clarification for graphs on likelihood contributions
408:
1.205 brouard 409: Revision 1.204 2015/10/01 16:20:26 brouard
410: Summary: Some new graphs of contribution to likelihood
411:
1.204 brouard 412: Revision 1.203 2015/09/30 17:45:14 brouard
413: Summary: looking at better estimation of the hessian
414:
415: Also a better criteria for convergence to the period prevalence And
416: therefore adding the number of years needed to converge. (The
417: prevalence in any alive state shold sum to one
418:
1.203 brouard 419: Revision 1.202 2015/09/22 19:45:16 brouard
420: Summary: Adding some overall graph on contribution to likelihood. Might change
421:
1.202 brouard 422: Revision 1.201 2015/09/15 17:34:58 brouard
423: Summary: 0.98r0
424:
425: - Some new graphs like suvival functions
426: - Some bugs fixed like model=1+age+V2.
427:
1.201 brouard 428: Revision 1.200 2015/09/09 16:53:55 brouard
429: Summary: Big bug thanks to Flavia
430:
431: Even model=1+age+V2. did not work anymore
432:
1.200 brouard 433: Revision 1.199 2015/09/07 14:09:23 brouard
434: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
435:
1.199 brouard 436: Revision 1.198 2015/09/03 07:14:39 brouard
437: Summary: 0.98q5 Flavia
438:
1.198 brouard 439: Revision 1.197 2015/09/01 18:24:39 brouard
440: *** empty log message ***
441:
1.197 brouard 442: Revision 1.196 2015/08/18 23:17:52 brouard
443: Summary: 0.98q5
444:
1.196 brouard 445: Revision 1.195 2015/08/18 16:28:39 brouard
446: Summary: Adding a hack for testing purpose
447:
448: After reading the title, ftol and model lines, if the comment line has
449: a q, starting with #q, the answer at the end of the run is quit. It
450: permits to run test files in batch with ctest. The former workaround was
451: $ echo q | imach foo.imach
452:
1.195 brouard 453: Revision 1.194 2015/08/18 13:32:00 brouard
454: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
455:
1.194 brouard 456: Revision 1.193 2015/08/04 07:17:42 brouard
457: Summary: 0.98q4
458:
1.193 brouard 459: Revision 1.192 2015/07/16 16:49:02 brouard
460: Summary: Fixing some outputs
461:
1.192 brouard 462: Revision 1.191 2015/07/14 10:00:33 brouard
463: Summary: Some fixes
464:
1.191 brouard 465: Revision 1.190 2015/05/05 08:51:13 brouard
466: Summary: Adding digits in output parameters (7 digits instead of 6)
467:
468: Fix 1+age+.
469:
1.190 brouard 470: Revision 1.189 2015/04/30 14:45:16 brouard
471: Summary: 0.98q2
472:
1.189 brouard 473: Revision 1.188 2015/04/30 08:27:53 brouard
474: *** empty log message ***
475:
1.188 brouard 476: Revision 1.187 2015/04/29 09:11:15 brouard
477: *** empty log message ***
478:
1.187 brouard 479: Revision 1.186 2015/04/23 12:01:52 brouard
480: Summary: V1*age is working now, version 0.98q1
481:
482: Some codes had been disabled in order to simplify and Vn*age was
483: working in the optimization phase, ie, giving correct MLE parameters,
484: but, as usual, outputs were not correct and program core dumped.
485:
1.186 brouard 486: Revision 1.185 2015/03/11 13:26:42 brouard
487: Summary: Inclusion of compile and links command line for Intel Compiler
488:
1.185 brouard 489: Revision 1.184 2015/03/11 11:52:39 brouard
490: Summary: Back from Windows 8. Intel Compiler
491:
1.184 brouard 492: Revision 1.183 2015/03/10 20:34:32 brouard
493: Summary: 0.98q0, trying with directest, mnbrak fixed
494:
495: We use directest instead of original Powell test; probably no
496: incidence on the results, but better justifications;
497: We fixed Numerical Recipes mnbrak routine which was wrong and gave
498: wrong results.
499:
1.183 brouard 500: Revision 1.182 2015/02/12 08:19:57 brouard
501: Summary: Trying to keep directest which seems simpler and more general
502: Author: Nicolas Brouard
503:
1.182 brouard 504: Revision 1.181 2015/02/11 23:22:24 brouard
505: Summary: Comments on Powell added
506:
507: Author:
508:
1.181 brouard 509: Revision 1.180 2015/02/11 17:33:45 brouard
510: Summary: Finishing move from main to function (hpijx and prevalence_limit)
511:
1.180 brouard 512: Revision 1.179 2015/01/04 09:57:06 brouard
513: Summary: back to OS/X
514:
1.179 brouard 515: Revision 1.178 2015/01/04 09:35:48 brouard
516: *** empty log message ***
517:
1.178 brouard 518: Revision 1.177 2015/01/03 18:40:56 brouard
519: Summary: Still testing ilc32 on OSX
520:
1.177 brouard 521: Revision 1.176 2015/01/03 16:45:04 brouard
522: *** empty log message ***
523:
1.176 brouard 524: Revision 1.175 2015/01/03 16:33:42 brouard
525: *** empty log message ***
526:
1.175 brouard 527: Revision 1.174 2015/01/03 16:15:49 brouard
528: Summary: Still in cross-compilation
529:
1.174 brouard 530: Revision 1.173 2015/01/03 12:06:26 brouard
531: Summary: trying to detect cross-compilation
532:
1.173 brouard 533: Revision 1.172 2014/12/27 12:07:47 brouard
534: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
535:
1.172 brouard 536: Revision 1.171 2014/12/23 13:26:59 brouard
537: Summary: Back from Visual C
538:
539: Still problem with utsname.h on Windows
540:
1.171 brouard 541: Revision 1.170 2014/12/23 11:17:12 brouard
542: Summary: Cleaning some \%% back to %%
543:
544: The escape was mandatory for a specific compiler (which one?), but too many warnings.
545:
1.170 brouard 546: Revision 1.169 2014/12/22 23:08:31 brouard
547: Summary: 0.98p
548:
549: Outputs some informations on compiler used, OS etc. Testing on different platforms.
550:
1.169 brouard 551: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 552: Summary: update
1.169 brouard 553:
1.168 brouard 554: Revision 1.167 2014/12/22 13:50:56 brouard
555: Summary: Testing uname and compiler version and if compiled 32 or 64
556:
557: Testing on Linux 64
558:
1.167 brouard 559: Revision 1.166 2014/12/22 11:40:47 brouard
560: *** empty log message ***
561:
1.166 brouard 562: Revision 1.165 2014/12/16 11:20:36 brouard
563: Summary: After compiling on Visual C
564:
565: * imach.c (Module): Merging 1.61 to 1.162
566:
1.165 brouard 567: Revision 1.164 2014/12/16 10:52:11 brouard
568: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
569:
570: * imach.c (Module): Merging 1.61 to 1.162
571:
1.164 brouard 572: Revision 1.163 2014/12/16 10:30:11 brouard
573: * imach.c (Module): Merging 1.61 to 1.162
574:
1.163 brouard 575: Revision 1.162 2014/09/25 11:43:39 brouard
576: Summary: temporary backup 0.99!
577:
1.162 brouard 578: Revision 1.1 2014/09/16 11:06:58 brouard
579: Summary: With some code (wrong) for nlopt
580:
581: Author:
582:
583: Revision 1.161 2014/09/15 20:41:41 brouard
584: Summary: Problem with macro SQR on Intel compiler
585:
1.161 brouard 586: Revision 1.160 2014/09/02 09:24:05 brouard
587: *** empty log message ***
588:
1.160 brouard 589: Revision 1.159 2014/09/01 10:34:10 brouard
590: Summary: WIN32
591: Author: Brouard
592:
1.159 brouard 593: Revision 1.158 2014/08/27 17:11:51 brouard
594: *** empty log message ***
595:
1.158 brouard 596: Revision 1.157 2014/08/27 16:26:55 brouard
597: Summary: Preparing windows Visual studio version
598: Author: Brouard
599:
600: In order to compile on Visual studio, time.h is now correct and time_t
601: and tm struct should be used. difftime should be used but sometimes I
602: just make the differences in raw time format (time(&now).
603: Trying to suppress #ifdef LINUX
604: Add xdg-open for __linux in order to open default browser.
605:
1.157 brouard 606: Revision 1.156 2014/08/25 20:10:10 brouard
607: *** empty log message ***
608:
1.156 brouard 609: Revision 1.155 2014/08/25 18:32:34 brouard
610: Summary: New compile, minor changes
611: Author: Brouard
612:
1.155 brouard 613: Revision 1.154 2014/06/20 17:32:08 brouard
614: Summary: Outputs now all graphs of convergence to period prevalence
615:
1.154 brouard 616: Revision 1.153 2014/06/20 16:45:46 brouard
617: Summary: If 3 live state, convergence to period prevalence on same graph
618: Author: Brouard
619:
1.153 brouard 620: Revision 1.152 2014/06/18 17:54:09 brouard
621: Summary: open browser, use gnuplot on same dir than imach if not found in the path
622:
1.152 brouard 623: Revision 1.151 2014/06/18 16:43:30 brouard
624: *** empty log message ***
625:
1.151 brouard 626: Revision 1.150 2014/06/18 16:42:35 brouard
627: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
628: Author: brouard
629:
1.150 brouard 630: Revision 1.149 2014/06/18 15:51:14 brouard
631: Summary: Some fixes in parameter files errors
632: Author: Nicolas Brouard
633:
1.149 brouard 634: Revision 1.148 2014/06/17 17:38:48 brouard
635: Summary: Nothing new
636: Author: Brouard
637:
638: Just a new packaging for OS/X version 0.98nS
639:
1.148 brouard 640: Revision 1.147 2014/06/16 10:33:11 brouard
641: *** empty log message ***
642:
1.147 brouard 643: Revision 1.146 2014/06/16 10:20:28 brouard
644: Summary: Merge
645: Author: Brouard
646:
647: Merge, before building revised version.
648:
1.146 brouard 649: Revision 1.145 2014/06/10 21:23:15 brouard
650: Summary: Debugging with valgrind
651: Author: Nicolas Brouard
652:
653: Lot of changes in order to output the results with some covariates
654: After the Edimburgh REVES conference 2014, it seems mandatory to
655: improve the code.
656: No more memory valgrind error but a lot has to be done in order to
657: continue the work of splitting the code into subroutines.
658: Also, decodemodel has been improved. Tricode is still not
659: optimal. nbcode should be improved. Documentation has been added in
660: the source code.
661:
1.144 brouard 662: Revision 1.143 2014/01/26 09:45:38 brouard
663: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
664:
665: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
666: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
667:
1.143 brouard 668: Revision 1.142 2014/01/26 03:57:36 brouard
669: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
670:
671: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
672:
1.142 brouard 673: Revision 1.141 2014/01/26 02:42:01 brouard
674: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
675:
1.141 brouard 676: Revision 1.140 2011/09/02 10:37:54 brouard
677: Summary: times.h is ok with mingw32 now.
678:
1.140 brouard 679: Revision 1.139 2010/06/14 07:50:17 brouard
680: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
681: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
682:
1.139 brouard 683: Revision 1.138 2010/04/30 18:19:40 brouard
684: *** empty log message ***
685:
1.138 brouard 686: Revision 1.137 2010/04/29 18:11:38 brouard
687: (Module): Checking covariates for more complex models
688: than V1+V2. A lot of change to be done. Unstable.
689:
1.137 brouard 690: Revision 1.136 2010/04/26 20:30:53 brouard
691: (Module): merging some libgsl code. Fixing computation
692: of likelione (using inter/intrapolation if mle = 0) in order to
693: get same likelihood as if mle=1.
694: Some cleaning of code and comments added.
695:
1.136 brouard 696: Revision 1.135 2009/10/29 15:33:14 brouard
697: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
698:
1.135 brouard 699: Revision 1.134 2009/10/29 13:18:53 brouard
700: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
701:
1.134 brouard 702: Revision 1.133 2009/07/06 10:21:25 brouard
703: just nforces
704:
1.133 brouard 705: Revision 1.132 2009/07/06 08:22:05 brouard
706: Many tings
707:
1.132 brouard 708: Revision 1.131 2009/06/20 16:22:47 brouard
709: Some dimensions resccaled
710:
1.131 brouard 711: Revision 1.130 2009/05/26 06:44:34 brouard
712: (Module): Max Covariate is now set to 20 instead of 8. A
713: lot of cleaning with variables initialized to 0. Trying to make
714: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
715:
1.130 brouard 716: Revision 1.129 2007/08/31 13:49:27 lievre
717: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
718:
1.129 lievre 719: Revision 1.128 2006/06/30 13:02:05 brouard
720: (Module): Clarifications on computing e.j
721:
1.128 brouard 722: Revision 1.127 2006/04/28 18:11:50 brouard
723: (Module): Yes the sum of survivors was wrong since
724: imach-114 because nhstepm was no more computed in the age
725: loop. Now we define nhstepma in the age loop.
726: (Module): In order to speed up (in case of numerous covariates) we
727: compute health expectancies (without variances) in a first step
728: and then all the health expectancies with variances or standard
729: deviation (needs data from the Hessian matrices) which slows the
730: computation.
731: In the future we should be able to stop the program is only health
732: expectancies and graph are needed without standard deviations.
733:
1.127 brouard 734: Revision 1.126 2006/04/28 17:23:28 brouard
735: (Module): Yes the sum of survivors was wrong since
736: imach-114 because nhstepm was no more computed in the age
737: loop. Now we define nhstepma in the age loop.
738: Version 0.98h
739:
1.126 brouard 740: Revision 1.125 2006/04/04 15:20:31 lievre
741: Errors in calculation of health expectancies. Age was not initialized.
742: Forecasting file added.
743:
744: Revision 1.124 2006/03/22 17:13:53 lievre
745: Parameters are printed with %lf instead of %f (more numbers after the comma).
746: The log-likelihood is printed in the log file
747:
748: Revision 1.123 2006/03/20 10:52:43 brouard
749: * imach.c (Module): <title> changed, corresponds to .htm file
750: name. <head> headers where missing.
751:
752: * imach.c (Module): Weights can have a decimal point as for
753: English (a comma might work with a correct LC_NUMERIC environment,
754: otherwise the weight is truncated).
755: Modification of warning when the covariates values are not 0 or
756: 1.
757: Version 0.98g
758:
759: Revision 1.122 2006/03/20 09:45:41 brouard
760: (Module): Weights can have a decimal point as for
761: English (a comma might work with a correct LC_NUMERIC environment,
762: otherwise the weight is truncated).
763: Modification of warning when the covariates values are not 0 or
764: 1.
765: Version 0.98g
766:
767: Revision 1.121 2006/03/16 17:45:01 lievre
768: * imach.c (Module): Comments concerning covariates added
769:
770: * imach.c (Module): refinements in the computation of lli if
771: status=-2 in order to have more reliable computation if stepm is
772: not 1 month. Version 0.98f
773:
774: Revision 1.120 2006/03/16 15:10:38 lievre
775: (Module): refinements in the computation of lli if
776: status=-2 in order to have more reliable computation if stepm is
777: not 1 month. Version 0.98f
778:
779: Revision 1.119 2006/03/15 17:42:26 brouard
780: (Module): Bug if status = -2, the loglikelihood was
781: computed as likelihood omitting the logarithm. Version O.98e
782:
783: Revision 1.118 2006/03/14 18:20:07 brouard
784: (Module): varevsij Comments added explaining the second
785: table of variances if popbased=1 .
786: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
787: (Module): Function pstamp added
788: (Module): Version 0.98d
789:
790: Revision 1.117 2006/03/14 17:16:22 brouard
791: (Module): varevsij Comments added explaining the second
792: table of variances if popbased=1 .
793: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
794: (Module): Function pstamp added
795: (Module): Version 0.98d
796:
797: Revision 1.116 2006/03/06 10:29:27 brouard
798: (Module): Variance-covariance wrong links and
799: varian-covariance of ej. is needed (Saito).
800:
801: Revision 1.115 2006/02/27 12:17:45 brouard
802: (Module): One freematrix added in mlikeli! 0.98c
803:
804: Revision 1.114 2006/02/26 12:57:58 brouard
805: (Module): Some improvements in processing parameter
806: filename with strsep.
807:
808: Revision 1.113 2006/02/24 14:20:24 brouard
809: (Module): Memory leaks checks with valgrind and:
810: datafile was not closed, some imatrix were not freed and on matrix
811: allocation too.
812:
813: Revision 1.112 2006/01/30 09:55:26 brouard
814: (Module): Back to gnuplot.exe instead of wgnuplot.exe
815:
816: Revision 1.111 2006/01/25 20:38:18 brouard
817: (Module): Lots of cleaning and bugs added (Gompertz)
818: (Module): Comments can be added in data file. Missing date values
819: can be a simple dot '.'.
820:
821: Revision 1.110 2006/01/25 00:51:50 brouard
822: (Module): Lots of cleaning and bugs added (Gompertz)
823:
824: Revision 1.109 2006/01/24 19:37:15 brouard
825: (Module): Comments (lines starting with a #) are allowed in data.
826:
827: Revision 1.108 2006/01/19 18:05:42 lievre
828: Gnuplot problem appeared...
829: To be fixed
830:
831: Revision 1.107 2006/01/19 16:20:37 brouard
832: Test existence of gnuplot in imach path
833:
834: Revision 1.106 2006/01/19 13:24:36 brouard
835: Some cleaning and links added in html output
836:
837: Revision 1.105 2006/01/05 20:23:19 lievre
838: *** empty log message ***
839:
840: Revision 1.104 2005/09/30 16:11:43 lievre
841: (Module): sump fixed, loop imx fixed, and simplifications.
842: (Module): If the status is missing at the last wave but we know
843: that the person is alive, then we can code his/her status as -2
844: (instead of missing=-1 in earlier versions) and his/her
845: contributions to the likelihood is 1 - Prob of dying from last
846: health status (= 1-p13= p11+p12 in the easiest case of somebody in
847: the healthy state at last known wave). Version is 0.98
848:
849: Revision 1.103 2005/09/30 15:54:49 lievre
850: (Module): sump fixed, loop imx fixed, and simplifications.
851:
852: Revision 1.102 2004/09/15 17:31:30 brouard
853: Add the possibility to read data file including tab characters.
854:
855: Revision 1.101 2004/09/15 10:38:38 brouard
856: Fix on curr_time
857:
858: Revision 1.100 2004/07/12 18:29:06 brouard
859: Add version for Mac OS X. Just define UNIX in Makefile
860:
861: Revision 1.99 2004/06/05 08:57:40 brouard
862: *** empty log message ***
863:
864: Revision 1.98 2004/05/16 15:05:56 brouard
865: New version 0.97 . First attempt to estimate force of mortality
866: directly from the data i.e. without the need of knowing the health
867: state at each age, but using a Gompertz model: log u =a + b*age .
868: This is the basic analysis of mortality and should be done before any
869: other analysis, in order to test if the mortality estimated from the
870: cross-longitudinal survey is different from the mortality estimated
871: from other sources like vital statistic data.
872:
873: The same imach parameter file can be used but the option for mle should be -3.
874:
1.324 brouard 875: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 876: former routines in order to include the new code within the former code.
877:
878: The output is very simple: only an estimate of the intercept and of
879: the slope with 95% confident intervals.
880:
881: Current limitations:
882: A) Even if you enter covariates, i.e. with the
883: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
884: B) There is no computation of Life Expectancy nor Life Table.
885:
886: Revision 1.97 2004/02/20 13:25:42 lievre
887: Version 0.96d. Population forecasting command line is (temporarily)
888: suppressed.
889:
890: Revision 1.96 2003/07/15 15:38:55 brouard
891: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
892: rewritten within the same printf. Workaround: many printfs.
893:
894: Revision 1.95 2003/07/08 07:54:34 brouard
895: * imach.c (Repository):
896: (Repository): Using imachwizard code to output a more meaningful covariance
897: matrix (cov(a12,c31) instead of numbers.
898:
899: Revision 1.94 2003/06/27 13:00:02 brouard
900: Just cleaning
901:
902: Revision 1.93 2003/06/25 16:33:55 brouard
903: (Module): On windows (cygwin) function asctime_r doesn't
904: exist so I changed back to asctime which exists.
905: (Module): Version 0.96b
906:
907: Revision 1.92 2003/06/25 16:30:45 brouard
908: (Module): On windows (cygwin) function asctime_r doesn't
909: exist so I changed back to asctime which exists.
910:
911: Revision 1.91 2003/06/25 15:30:29 brouard
912: * imach.c (Repository): Duplicated warning errors corrected.
913: (Repository): Elapsed time after each iteration is now output. It
914: helps to forecast when convergence will be reached. Elapsed time
915: is stamped in powell. We created a new html file for the graphs
916: concerning matrix of covariance. It has extension -cov.htm.
917:
918: Revision 1.90 2003/06/24 12:34:15 brouard
919: (Module): Some bugs corrected for windows. Also, when
920: mle=-1 a template is output in file "or"mypar.txt with the design
921: of the covariance matrix to be input.
922:
923: Revision 1.89 2003/06/24 12:30:52 brouard
924: (Module): Some bugs corrected for windows. Also, when
925: mle=-1 a template is output in file "or"mypar.txt with the design
926: of the covariance matrix to be input.
927:
928: Revision 1.88 2003/06/23 17:54:56 brouard
929: * 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.
930:
931: Revision 1.87 2003/06/18 12:26:01 brouard
932: Version 0.96
933:
934: Revision 1.86 2003/06/17 20:04:08 brouard
935: (Module): Change position of html and gnuplot routines and added
936: routine fileappend.
937:
938: Revision 1.85 2003/06/17 13:12:43 brouard
939: * imach.c (Repository): Check when date of death was earlier that
940: current date of interview. It may happen when the death was just
941: prior to the death. In this case, dh was negative and likelihood
942: was wrong (infinity). We still send an "Error" but patch by
943: assuming that the date of death was just one stepm after the
944: interview.
945: (Repository): Because some people have very long ID (first column)
946: we changed int to long in num[] and we added a new lvector for
947: memory allocation. But we also truncated to 8 characters (left
948: truncation)
949: (Repository): No more line truncation errors.
950:
951: Revision 1.84 2003/06/13 21:44:43 brouard
952: * imach.c (Repository): Replace "freqsummary" at a correct
953: place. It differs from routine "prevalence" which may be called
954: many times. Probs is memory consuming and must be used with
955: parcimony.
956: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
957:
958: Revision 1.83 2003/06/10 13:39:11 lievre
959: *** empty log message ***
960:
961: Revision 1.82 2003/06/05 15:57:20 brouard
962: Add log in imach.c and fullversion number is now printed.
963:
964: */
965: /*
966: Interpolated Markov Chain
967:
968: Short summary of the programme:
969:
1.227 brouard 970: This program computes Healthy Life Expectancies or State-specific
971: (if states aren't health statuses) Expectancies from
972: cross-longitudinal data. Cross-longitudinal data consist in:
973:
974: -1- a first survey ("cross") where individuals from different ages
975: are interviewed on their health status or degree of disability (in
976: the case of a health survey which is our main interest)
977:
978: -2- at least a second wave of interviews ("longitudinal") which
979: measure each change (if any) in individual health status. Health
980: expectancies are computed from the time spent in each health state
981: according to a model. More health states you consider, more time is
982: necessary to reach the Maximum Likelihood of the parameters involved
983: in the model. The simplest model is the multinomial logistic model
984: where pij is the probability to be observed in state j at the second
985: wave conditional to be observed in state i at the first
986: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
987: etc , where 'age' is age and 'sex' is a covariate. If you want to
988: have a more complex model than "constant and age", you should modify
989: the program where the markup *Covariates have to be included here
990: again* invites you to do it. More covariates you add, slower the
1.126 brouard 991: convergence.
992:
993: The advantage of this computer programme, compared to a simple
994: multinomial logistic model, is clear when the delay between waves is not
995: identical for each individual. Also, if a individual missed an
996: intermediate interview, the information is lost, but taken into
997: account using an interpolation or extrapolation.
998:
999: hPijx is the probability to be observed in state i at age x+h
1000: conditional to the observed state i at age x. The delay 'h' can be
1001: split into an exact number (nh*stepm) of unobserved intermediate
1002: states. This elementary transition (by month, quarter,
1003: semester or year) is modelled as a multinomial logistic. The hPx
1004: matrix is simply the matrix product of nh*stepm elementary matrices
1005: and the contribution of each individual to the likelihood is simply
1006: hPijx.
1007:
1008: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1009: of the life expectancies. It also computes the period (stable) prevalence.
1010:
1011: Back prevalence and projections:
1.227 brouard 1012:
1013: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1014: double agemaxpar, double ftolpl, int *ncvyearp, double
1015: dateprev1,double dateprev2, int firstpass, int lastpass, int
1016: mobilavproj)
1017:
1018: Computes the back prevalence limit for any combination of
1019: covariate values k at any age between ageminpar and agemaxpar and
1020: returns it in **bprlim. In the loops,
1021:
1022: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1023: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1024:
1025: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1026: Computes for any combination of covariates k and any age between bage and fage
1027: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1028: oldm=oldms;savm=savms;
1.227 brouard 1029:
1.267 brouard 1030: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1031: Computes the transition matrix starting at age 'age' over
1032: 'nhstepm*hstepm*stepm' months (i.e. until
1033: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1034: nhstepm*hstepm matrices.
1035:
1036: Returns p3mat[i][j][h] after calling
1037: p3mat[i][j][h]=matprod2(newm,
1038: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1039: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1040: oldm);
1.226 brouard 1041:
1042: Important routines
1043:
1044: - func (or funcone), computes logit (pij) distinguishing
1045: o fixed variables (single or product dummies or quantitative);
1046: o varying variables by:
1047: (1) wave (single, product dummies, quantitative),
1048: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1049: % fixed dummy (treated) or quantitative (not done because time-consuming);
1050: % varying dummy (not done) or quantitative (not done);
1051: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1052: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1053: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 ! brouard 1054: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1055: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1056:
1.226 brouard 1057:
1058:
1.324 brouard 1059: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1060: Institut national d'études démographiques, Paris.
1.126 brouard 1061: This software have been partly granted by Euro-REVES, a concerted action
1062: from the European Union.
1063: It is copyrighted identically to a GNU software product, ie programme and
1064: software can be distributed freely for non commercial use. Latest version
1065: can be accessed at http://euroreves.ined.fr/imach .
1066:
1067: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1068: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1069:
1070: **********************************************************************/
1071: /*
1072: main
1073: read parameterfile
1074: read datafile
1075: concatwav
1076: freqsummary
1077: if (mle >= 1)
1078: mlikeli
1079: print results files
1080: if mle==1
1081: computes hessian
1082: read end of parameter file: agemin, agemax, bage, fage, estepm
1083: begin-prev-date,...
1084: open gnuplot file
1085: open html file
1.145 brouard 1086: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1087: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1088: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1089: freexexit2 possible for memory heap.
1090:
1091: h Pij x | pij_nom ficrestpij
1092: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1093: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1094: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1095:
1096: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1097: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1098: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1099: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1100: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1101:
1.126 brouard 1102: forecasting if prevfcast==1 prevforecast call prevalence()
1103: health expectancies
1104: Variance-covariance of DFLE
1105: prevalence()
1106: movingaverage()
1107: varevsij()
1108: if popbased==1 varevsij(,popbased)
1109: total life expectancies
1110: Variance of period (stable) prevalence
1111: end
1112: */
1113:
1.187 brouard 1114: /* #define DEBUG */
1115: /* #define DEBUGBRENT */
1.203 brouard 1116: /* #define DEBUGLINMIN */
1117: /* #define DEBUGHESS */
1118: #define DEBUGHESSIJ
1.224 brouard 1119: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1120: #define POWELL /* Instead of NLOPT */
1.224 brouard 1121: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1122: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1123: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1124: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1125:
1126: #include <math.h>
1127: #include <stdio.h>
1128: #include <stdlib.h>
1129: #include <string.h>
1.226 brouard 1130: #include <ctype.h>
1.159 brouard 1131:
1132: #ifdef _WIN32
1133: #include <io.h>
1.172 brouard 1134: #include <windows.h>
1135: #include <tchar.h>
1.159 brouard 1136: #else
1.126 brouard 1137: #include <unistd.h>
1.159 brouard 1138: #endif
1.126 brouard 1139:
1140: #include <limits.h>
1141: #include <sys/types.h>
1.171 brouard 1142:
1143: #if defined(__GNUC__)
1144: #include <sys/utsname.h> /* Doesn't work on Windows */
1145: #endif
1146:
1.126 brouard 1147: #include <sys/stat.h>
1148: #include <errno.h>
1.159 brouard 1149: /* extern int errno; */
1.126 brouard 1150:
1.157 brouard 1151: /* #ifdef LINUX */
1152: /* #include <time.h> */
1153: /* #include "timeval.h" */
1154: /* #else */
1155: /* #include <sys/time.h> */
1156: /* #endif */
1157:
1.126 brouard 1158: #include <time.h>
1159:
1.136 brouard 1160: #ifdef GSL
1161: #include <gsl/gsl_errno.h>
1162: #include <gsl/gsl_multimin.h>
1163: #endif
1164:
1.167 brouard 1165:
1.162 brouard 1166: #ifdef NLOPT
1167: #include <nlopt.h>
1168: typedef struct {
1169: double (* function)(double [] );
1170: } myfunc_data ;
1171: #endif
1172:
1.126 brouard 1173: /* #include <libintl.h> */
1174: /* #define _(String) gettext (String) */
1175:
1.251 brouard 1176: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1177:
1178: #define GNUPLOTPROGRAM "gnuplot"
1179: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1180: #define FILENAMELENGTH 132
1181:
1182: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1183: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1184:
1.144 brouard 1185: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1186: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1187:
1188: #define NINTERVMAX 8
1.144 brouard 1189: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1190: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 ! brouard 1191: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1192: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1193: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1194: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1195: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1196: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1197: /* #define AGESUP 130 */
1.288 brouard 1198: /* #define AGESUP 150 */
1199: #define AGESUP 200
1.268 brouard 1200: #define AGEINF 0
1.218 brouard 1201: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1202: #define AGEBASE 40
1.194 brouard 1203: #define AGEOVERFLOW 1.e20
1.164 brouard 1204: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1205: #ifdef _WIN32
1206: #define DIRSEPARATOR '\\'
1207: #define CHARSEPARATOR "\\"
1208: #define ODIRSEPARATOR '/'
1209: #else
1.126 brouard 1210: #define DIRSEPARATOR '/'
1211: #define CHARSEPARATOR "/"
1212: #define ODIRSEPARATOR '\\'
1213: #endif
1214:
1.325 ! brouard 1215: /* $Id: imach.c,v 1.324 2022/07/23 17:44:26 brouard Exp $ */
1.126 brouard 1216: /* $State: Exp $ */
1.196 brouard 1217: #include "version.h"
1218: char version[]=__IMACH_VERSION__;
1.323 brouard 1219: 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";
1.325 ! brouard 1220: char fullversion[]="$Revision: 1.324 $ $Date: 2022/07/23 17:44:26 $";
1.126 brouard 1221: char strstart[80];
1222: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1223: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1224: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1225: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1226: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1227: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1228: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1229: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1230: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1231: int cptcovprodnoage=0; /**< Number of covariate products without age */
1232: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1233: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1234: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1235: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1236: int nsd=0; /**< Total number of single dummy variables (output) */
1237: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1238: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1239: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1240: int ntveff=0; /**< ntveff number of effective time varying variables */
1241: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1242: int cptcov=0; /* Working variable */
1.290 brouard 1243: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1244: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1245: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1246: int nlstate=2; /* Number of live states */
1247: int ndeath=1; /* Number of dead states */
1.130 brouard 1248: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1249: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1250: int popbased=0;
1251:
1252: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1253: int maxwav=0; /* Maxim number of waves */
1254: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1255: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1256: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1257: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1258: int mle=1, weightopt=0;
1.126 brouard 1259: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1260: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1261: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1262: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1263: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1264: int selected(int kvar); /* Is covariate kvar selected for printing results */
1265:
1.130 brouard 1266: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1267: double **matprod2(); /* test */
1.126 brouard 1268: double **oldm, **newm, **savm; /* Working pointers to matrices */
1269: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1270: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1271:
1.136 brouard 1272: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1273: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1274: FILE *ficlog, *ficrespow;
1.130 brouard 1275: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1276: double fretone; /* Only one call to likelihood */
1.130 brouard 1277: long ipmx=0; /* Number of contributions */
1.126 brouard 1278: double sw; /* Sum of weights */
1279: char filerespow[FILENAMELENGTH];
1280: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1281: FILE *ficresilk;
1282: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1283: FILE *ficresprobmorprev;
1284: FILE *fichtm, *fichtmcov; /* Html File */
1285: FILE *ficreseij;
1286: char filerese[FILENAMELENGTH];
1287: FILE *ficresstdeij;
1288: char fileresstde[FILENAMELENGTH];
1289: FILE *ficrescveij;
1290: char filerescve[FILENAMELENGTH];
1291: FILE *ficresvij;
1292: char fileresv[FILENAMELENGTH];
1.269 brouard 1293:
1.126 brouard 1294: char title[MAXLINE];
1.234 brouard 1295: char model[MAXLINE]; /**< The model line */
1.217 brouard 1296: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1297: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1298: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1299: char command[FILENAMELENGTH];
1300: int outcmd=0;
1301:
1.217 brouard 1302: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1303: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1304: char filelog[FILENAMELENGTH]; /* Log file */
1305: char filerest[FILENAMELENGTH];
1306: char fileregp[FILENAMELENGTH];
1307: char popfile[FILENAMELENGTH];
1308:
1309: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1310:
1.157 brouard 1311: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1312: /* struct timezone tzp; */
1313: /* extern int gettimeofday(); */
1314: struct tm tml, *gmtime(), *localtime();
1315:
1316: extern time_t time();
1317:
1318: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1319: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1320: struct tm tm;
1321:
1.126 brouard 1322: char strcurr[80], strfor[80];
1323:
1324: char *endptr;
1325: long lval;
1326: double dval;
1327:
1328: #define NR_END 1
1329: #define FREE_ARG char*
1330: #define FTOL 1.0e-10
1331:
1332: #define NRANSI
1.240 brouard 1333: #define ITMAX 200
1334: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1335:
1336: #define TOL 2.0e-4
1337:
1338: #define CGOLD 0.3819660
1339: #define ZEPS 1.0e-10
1340: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1341:
1342: #define GOLD 1.618034
1343: #define GLIMIT 100.0
1344: #define TINY 1.0e-20
1345:
1346: static double maxarg1,maxarg2;
1347: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1348: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1349:
1350: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1351: #define rint(a) floor(a+0.5)
1.166 brouard 1352: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1353: #define mytinydouble 1.0e-16
1.166 brouard 1354: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1355: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1356: /* static double dsqrarg; */
1357: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1358: static double sqrarg;
1359: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1360: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1361: int agegomp= AGEGOMP;
1362:
1363: int imx;
1364: int stepm=1;
1365: /* Stepm, step in month: minimum step interpolation*/
1366:
1367: int estepm;
1368: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1369:
1370: int m,nb;
1371: long *num;
1.197 brouard 1372: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1373: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1374: covariate for which somebody answered excluding
1375: undefined. Usually 2: 0 and 1. */
1376: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1377: covariate for which somebody answered including
1378: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1379: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1380: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1381: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1382: double *ageexmed,*agecens;
1383: double dateintmean=0;
1.296 brouard 1384: double anprojd, mprojd, jprojd; /* For eventual projections */
1385: double anprojf, mprojf, jprojf;
1.126 brouard 1386:
1.296 brouard 1387: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1388: double anbackf, mbackf, jbackf;
1389: double jintmean,mintmean,aintmean;
1.126 brouard 1390: double *weight;
1391: int **s; /* Status */
1.141 brouard 1392: double *agedc;
1.145 brouard 1393: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1394: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1395: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1396: double **coqvar; /* Fixed quantitative covariate nqv */
1397: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1398: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1399: double idx;
1400: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1401: /* Some documentation */
1402: /* Design original data
1403: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1404: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1405: * ntv=3 nqtv=1
1406: * cptcovn number of covariates (not including constant and age) = # of + plus 1 = 10+1=11
1407: * For time varying covariate, quanti or dummies
1408: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1409: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1410: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1411: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1412: * covar[k,i], value of kth fixed covariate dummy or quanti :
1413: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1414: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1415: * k= 1 2 3 4 5 6 7 8 9 10 11
1416: */
1417: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1418: /* 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
1419: # States 1=Coresidence, 2 Living alone, 3 Institution
1420: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1421: */
1.319 brouard 1422: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1423: /* k 1 2 3 4 5 6 7 8 9 */
1424: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1425: /* fixed or varying), 1 for age product, 2 for*/
1426: /* product */
1427: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1428: /*(single or product without age), 2 dummy*/
1429: /* with age product, 3 quant with age product*/
1430: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1431: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1432: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1433: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1434: /* nsq 1 2 */ /* Counting single quantit tv */
1435: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1436: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1437: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1438: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1439: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1440: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1441: /* 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 1442: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1443: /* Type */
1444: /* V 1 2 3 4 5 */
1445: /* F F V V V */
1446: /* D Q D D Q */
1447: /* */
1448: int *TvarsD;
1449: int *TvarsDind;
1450: int *TvarsQ;
1451: int *TvarsQind;
1452:
1.318 brouard 1453: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1454: int nresult=0;
1.258 brouard 1455: int parameterline=0; /* # of the parameter (type) line */
1.318 brouard 1456: int TKresult[MAXRESULTLINESPONE];
1457: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1458: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1459: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */
1460: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1461: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1462: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , variable # (output) */
1463:
1464: /* 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
1465: # States 1=Coresidence, 2 Living alone, 3 Institution
1466: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1467: */
1.234 brouard 1468: /* 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 1469: 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 */
1470: 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 */
1471: 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 */
1472: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1473: 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 */
1474: 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 1475: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1476: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1477: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1478: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1479: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1480: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1481: 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 */
1482: 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 */
1483:
1.230 brouard 1484: int *Tvarsel; /**< Selected covariates for output */
1485: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1486: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1487: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1488: 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 1489: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1490: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1491: int *Tage;
1.227 brouard 1492: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1493: 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 1494: 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*/
1495: 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 1496: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1497: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1498: int **Tvard;
1499: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1500: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1501: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1502: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1503: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1504: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1505: double *lsurv, *lpop, *tpop;
1506:
1.231 brouard 1507: #define FD 1; /* Fixed dummy covariate */
1508: #define FQ 2; /* Fixed quantitative covariate */
1509: #define FP 3; /* Fixed product covariate */
1510: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1511: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1512: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1513: #define VD 10; /* Varying dummy covariate */
1514: #define VQ 11; /* Varying quantitative covariate */
1515: #define VP 12; /* Varying product covariate */
1516: #define VPDD 13; /* Varying product dummy*dummy covariate */
1517: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1518: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1519: #define APFD 16; /* Age product * fixed dummy covariate */
1520: #define APFQ 17; /* Age product * fixed quantitative covariate */
1521: #define APVD 18; /* Age product * varying dummy covariate */
1522: #define APVQ 19; /* Age product * varying quantitative covariate */
1523:
1524: #define FTYPE 1; /* Fixed covariate */
1525: #define VTYPE 2; /* Varying covariate (loop in wave) */
1526: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1527:
1528: struct kmodel{
1529: int maintype; /* main type */
1530: int subtype; /* subtype */
1531: };
1532: struct kmodel modell[NCOVMAX];
1533:
1.143 brouard 1534: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1535: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1536:
1537: /**************** split *************************/
1538: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1539: {
1540: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1541: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1542: */
1543: char *ss; /* pointer */
1.186 brouard 1544: int l1=0, l2=0; /* length counters */
1.126 brouard 1545:
1546: l1 = strlen(path ); /* length of path */
1547: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1548: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1549: if ( ss == NULL ) { /* no directory, so determine current directory */
1550: strcpy( name, path ); /* we got the fullname name because no directory */
1551: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1552: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1553: /* get current working directory */
1554: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1555: #ifdef WIN32
1556: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1557: #else
1558: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1559: #endif
1.126 brouard 1560: return( GLOCK_ERROR_GETCWD );
1561: }
1562: /* got dirc from getcwd*/
1563: printf(" DIRC = %s \n",dirc);
1.205 brouard 1564: } else { /* strip directory from path */
1.126 brouard 1565: ss++; /* after this, the filename */
1566: l2 = strlen( ss ); /* length of filename */
1567: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1568: strcpy( name, ss ); /* save file name */
1569: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1570: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1571: printf(" DIRC2 = %s \n",dirc);
1572: }
1573: /* We add a separator at the end of dirc if not exists */
1574: l1 = strlen( dirc ); /* length of directory */
1575: if( dirc[l1-1] != DIRSEPARATOR ){
1576: dirc[l1] = DIRSEPARATOR;
1577: dirc[l1+1] = 0;
1578: printf(" DIRC3 = %s \n",dirc);
1579: }
1580: ss = strrchr( name, '.' ); /* find last / */
1581: if (ss >0){
1582: ss++;
1583: strcpy(ext,ss); /* save extension */
1584: l1= strlen( name);
1585: l2= strlen(ss)+1;
1586: strncpy( finame, name, l1-l2);
1587: finame[l1-l2]= 0;
1588: }
1589:
1590: return( 0 ); /* we're done */
1591: }
1592:
1593:
1594: /******************************************/
1595:
1596: void replace_back_to_slash(char *s, char*t)
1597: {
1598: int i;
1599: int lg=0;
1600: i=0;
1601: lg=strlen(t);
1602: for(i=0; i<= lg; i++) {
1603: (s[i] = t[i]);
1604: if (t[i]== '\\') s[i]='/';
1605: }
1606: }
1607:
1.132 brouard 1608: char *trimbb(char *out, char *in)
1.137 brouard 1609: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1610: char *s;
1611: s=out;
1612: while (*in != '\0'){
1.137 brouard 1613: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1614: in++;
1615: }
1616: *out++ = *in++;
1617: }
1618: *out='\0';
1619: return s;
1620: }
1621:
1.187 brouard 1622: /* char *substrchaine(char *out, char *in, char *chain) */
1623: /* { */
1624: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1625: /* char *s, *t; */
1626: /* t=in;s=out; */
1627: /* while ((*in != *chain) && (*in != '\0')){ */
1628: /* *out++ = *in++; */
1629: /* } */
1630:
1631: /* /\* *in matches *chain *\/ */
1632: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1633: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1634: /* } */
1635: /* in--; chain--; */
1636: /* while ( (*in != '\0')){ */
1637: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1638: /* *out++ = *in++; */
1639: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1640: /* } */
1641: /* *out='\0'; */
1642: /* out=s; */
1643: /* return out; */
1644: /* } */
1645: char *substrchaine(char *out, char *in, char *chain)
1646: {
1647: /* Substract chain 'chain' from 'in', return and output 'out' */
1648: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1649:
1650: char *strloc;
1651:
1652: strcpy (out, in);
1653: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1654: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1655: if(strloc != NULL){
1656: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1657: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1658: /* strcpy (strloc, strloc +strlen(chain));*/
1659: }
1660: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1661: return out;
1662: }
1663:
1664:
1.145 brouard 1665: char *cutl(char *blocc, char *alocc, char *in, char occ)
1666: {
1.187 brouard 1667: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1668: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1669: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1670: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1671: */
1.160 brouard 1672: char *s, *t;
1.145 brouard 1673: t=in;s=in;
1674: while ((*in != occ) && (*in != '\0')){
1675: *alocc++ = *in++;
1676: }
1677: if( *in == occ){
1678: *(alocc)='\0';
1679: s=++in;
1680: }
1681:
1682: if (s == t) {/* occ not found */
1683: *(alocc-(in-s))='\0';
1684: in=s;
1685: }
1686: while ( *in != '\0'){
1687: *blocc++ = *in++;
1688: }
1689:
1690: *blocc='\0';
1691: return t;
1692: }
1.137 brouard 1693: char *cutv(char *blocc, char *alocc, char *in, char occ)
1694: {
1.187 brouard 1695: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1696: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1697: gives blocc="abcdef2ghi" and alocc="j".
1698: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1699: */
1700: char *s, *t;
1701: t=in;s=in;
1702: while (*in != '\0'){
1703: while( *in == occ){
1704: *blocc++ = *in++;
1705: s=in;
1706: }
1707: *blocc++ = *in++;
1708: }
1709: if (s == t) /* occ not found */
1710: *(blocc-(in-s))='\0';
1711: else
1712: *(blocc-(in-s)-1)='\0';
1713: in=s;
1714: while ( *in != '\0'){
1715: *alocc++ = *in++;
1716: }
1717:
1718: *alocc='\0';
1719: return s;
1720: }
1721:
1.126 brouard 1722: int nbocc(char *s, char occ)
1723: {
1724: int i,j=0;
1725: int lg=20;
1726: i=0;
1727: lg=strlen(s);
1728: for(i=0; i<= lg; i++) {
1.234 brouard 1729: if (s[i] == occ ) j++;
1.126 brouard 1730: }
1731: return j;
1732: }
1733:
1.137 brouard 1734: /* void cutv(char *u,char *v, char*t, char occ) */
1735: /* { */
1736: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1737: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1738: /* gives u="abcdef2ghi" and v="j" *\/ */
1739: /* int i,lg,j,p=0; */
1740: /* i=0; */
1741: /* lg=strlen(t); */
1742: /* for(j=0; j<=lg-1; j++) { */
1743: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1744: /* } */
1.126 brouard 1745:
1.137 brouard 1746: /* for(j=0; j<p; j++) { */
1747: /* (u[j] = t[j]); */
1748: /* } */
1749: /* u[p]='\0'; */
1.126 brouard 1750:
1.137 brouard 1751: /* for(j=0; j<= lg; j++) { */
1752: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1753: /* } */
1754: /* } */
1.126 brouard 1755:
1.160 brouard 1756: #ifdef _WIN32
1757: char * strsep(char **pp, const char *delim)
1758: {
1759: char *p, *q;
1760:
1761: if ((p = *pp) == NULL)
1762: return 0;
1763: if ((q = strpbrk (p, delim)) != NULL)
1764: {
1765: *pp = q + 1;
1766: *q = '\0';
1767: }
1768: else
1769: *pp = 0;
1770: return p;
1771: }
1772: #endif
1773:
1.126 brouard 1774: /********************** nrerror ********************/
1775:
1776: void nrerror(char error_text[])
1777: {
1778: fprintf(stderr,"ERREUR ...\n");
1779: fprintf(stderr,"%s\n",error_text);
1780: exit(EXIT_FAILURE);
1781: }
1782: /*********************** vector *******************/
1783: double *vector(int nl, int nh)
1784: {
1785: double *v;
1786: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1787: if (!v) nrerror("allocation failure in vector");
1788: return v-nl+NR_END;
1789: }
1790:
1791: /************************ free vector ******************/
1792: void free_vector(double*v, int nl, int nh)
1793: {
1794: free((FREE_ARG)(v+nl-NR_END));
1795: }
1796:
1797: /************************ivector *******************************/
1798: int *ivector(long nl,long nh)
1799: {
1800: int *v;
1801: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1802: if (!v) nrerror("allocation failure in ivector");
1803: return v-nl+NR_END;
1804: }
1805:
1806: /******************free ivector **************************/
1807: void free_ivector(int *v, long nl, long nh)
1808: {
1809: free((FREE_ARG)(v+nl-NR_END));
1810: }
1811:
1812: /************************lvector *******************************/
1813: long *lvector(long nl,long nh)
1814: {
1815: long *v;
1816: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1817: if (!v) nrerror("allocation failure in ivector");
1818: return v-nl+NR_END;
1819: }
1820:
1821: /******************free lvector **************************/
1822: void free_lvector(long *v, long nl, long nh)
1823: {
1824: free((FREE_ARG)(v+nl-NR_END));
1825: }
1826:
1827: /******************* imatrix *******************************/
1828: int **imatrix(long nrl, long nrh, long ncl, long nch)
1829: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1830: {
1831: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1832: int **m;
1833:
1834: /* allocate pointers to rows */
1835: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1836: if (!m) nrerror("allocation failure 1 in matrix()");
1837: m += NR_END;
1838: m -= nrl;
1839:
1840:
1841: /* allocate rows and set pointers to them */
1842: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1843: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1844: m[nrl] += NR_END;
1845: m[nrl] -= ncl;
1846:
1847: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1848:
1849: /* return pointer to array of pointers to rows */
1850: return m;
1851: }
1852:
1853: /****************** free_imatrix *************************/
1854: void free_imatrix(m,nrl,nrh,ncl,nch)
1855: int **m;
1856: long nch,ncl,nrh,nrl;
1857: /* free an int matrix allocated by imatrix() */
1858: {
1859: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1860: free((FREE_ARG) (m+nrl-NR_END));
1861: }
1862:
1863: /******************* matrix *******************************/
1864: double **matrix(long nrl, long nrh, long ncl, long nch)
1865: {
1866: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1867: double **m;
1868:
1869: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1870: if (!m) nrerror("allocation failure 1 in matrix()");
1871: m += NR_END;
1872: m -= nrl;
1873:
1874: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1875: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1876: m[nrl] += NR_END;
1877: m[nrl] -= ncl;
1878:
1879: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1880: return m;
1.145 brouard 1881: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1882: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1883: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1884: */
1885: }
1886:
1887: /*************************free matrix ************************/
1888: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1889: {
1890: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1891: free((FREE_ARG)(m+nrl-NR_END));
1892: }
1893:
1894: /******************* ma3x *******************************/
1895: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1896: {
1897: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1898: double ***m;
1899:
1900: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1901: if (!m) nrerror("allocation failure 1 in matrix()");
1902: m += NR_END;
1903: m -= nrl;
1904:
1905: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1906: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1907: m[nrl] += NR_END;
1908: m[nrl] -= ncl;
1909:
1910: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1911:
1912: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1913: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1914: m[nrl][ncl] += NR_END;
1915: m[nrl][ncl] -= nll;
1916: for (j=ncl+1; j<=nch; j++)
1917: m[nrl][j]=m[nrl][j-1]+nlay;
1918:
1919: for (i=nrl+1; i<=nrh; i++) {
1920: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1921: for (j=ncl+1; j<=nch; j++)
1922: m[i][j]=m[i][j-1]+nlay;
1923: }
1924: return m;
1925: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1926: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1927: */
1928: }
1929:
1930: /*************************free ma3x ************************/
1931: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1932: {
1933: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1934: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1935: free((FREE_ARG)(m+nrl-NR_END));
1936: }
1937:
1938: /*************** function subdirf ***********/
1939: char *subdirf(char fileres[])
1940: {
1941: /* Caution optionfilefiname is hidden */
1942: strcpy(tmpout,optionfilefiname);
1943: strcat(tmpout,"/"); /* Add to the right */
1944: strcat(tmpout,fileres);
1945: return tmpout;
1946: }
1947:
1948: /*************** function subdirf2 ***********/
1949: char *subdirf2(char fileres[], char *preop)
1950: {
1.314 brouard 1951: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
1952: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 1953: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 1954: /* Caution optionfilefiname is hidden */
1955: strcpy(tmpout,optionfilefiname);
1956: strcat(tmpout,"/");
1957: strcat(tmpout,preop);
1958: strcat(tmpout,fileres);
1959: return tmpout;
1960: }
1961:
1962: /*************** function subdirf3 ***********/
1963: char *subdirf3(char fileres[], char *preop, char *preop2)
1964: {
1965:
1966: /* Caution optionfilefiname is hidden */
1967: strcpy(tmpout,optionfilefiname);
1968: strcat(tmpout,"/");
1969: strcat(tmpout,preop);
1970: strcat(tmpout,preop2);
1971: strcat(tmpout,fileres);
1972: return tmpout;
1973: }
1.213 brouard 1974:
1975: /*************** function subdirfext ***********/
1976: char *subdirfext(char fileres[], char *preop, char *postop)
1977: {
1978:
1979: strcpy(tmpout,preop);
1980: strcat(tmpout,fileres);
1981: strcat(tmpout,postop);
1982: return tmpout;
1983: }
1.126 brouard 1984:
1.213 brouard 1985: /*************** function subdirfext3 ***********/
1986: char *subdirfext3(char fileres[], char *preop, char *postop)
1987: {
1988:
1989: /* Caution optionfilefiname is hidden */
1990: strcpy(tmpout,optionfilefiname);
1991: strcat(tmpout,"/");
1992: strcat(tmpout,preop);
1993: strcat(tmpout,fileres);
1994: strcat(tmpout,postop);
1995: return tmpout;
1996: }
1997:
1.162 brouard 1998: char *asc_diff_time(long time_sec, char ascdiff[])
1999: {
2000: long sec_left, days, hours, minutes;
2001: days = (time_sec) / (60*60*24);
2002: sec_left = (time_sec) % (60*60*24);
2003: hours = (sec_left) / (60*60) ;
2004: sec_left = (sec_left) %(60*60);
2005: minutes = (sec_left) /60;
2006: sec_left = (sec_left) % (60);
2007: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2008: return ascdiff;
2009: }
2010:
1.126 brouard 2011: /***************** f1dim *************************/
2012: extern int ncom;
2013: extern double *pcom,*xicom;
2014: extern double (*nrfunc)(double []);
2015:
2016: double f1dim(double x)
2017: {
2018: int j;
2019: double f;
2020: double *xt;
2021:
2022: xt=vector(1,ncom);
2023: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2024: f=(*nrfunc)(xt);
2025: free_vector(xt,1,ncom);
2026: return f;
2027: }
2028:
2029: /*****************brent *************************/
2030: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2031: {
2032: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2033: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2034: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2035: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2036: * returned function value.
2037: */
1.126 brouard 2038: int iter;
2039: double a,b,d,etemp;
1.159 brouard 2040: double fu=0,fv,fw,fx;
1.164 brouard 2041: double ftemp=0.;
1.126 brouard 2042: double p,q,r,tol1,tol2,u,v,w,x,xm;
2043: double e=0.0;
2044:
2045: a=(ax < cx ? ax : cx);
2046: b=(ax > cx ? ax : cx);
2047: x=w=v=bx;
2048: fw=fv=fx=(*f)(x);
2049: for (iter=1;iter<=ITMAX;iter++) {
2050: xm=0.5*(a+b);
2051: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2052: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2053: printf(".");fflush(stdout);
2054: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2055: #ifdef DEBUGBRENT
1.126 brouard 2056: 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);
2057: 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);
2058: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2059: #endif
2060: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2061: *xmin=x;
2062: return fx;
2063: }
2064: ftemp=fu;
2065: if (fabs(e) > tol1) {
2066: r=(x-w)*(fx-fv);
2067: q=(x-v)*(fx-fw);
2068: p=(x-v)*q-(x-w)*r;
2069: q=2.0*(q-r);
2070: if (q > 0.0) p = -p;
2071: q=fabs(q);
2072: etemp=e;
2073: e=d;
2074: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2075: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2076: else {
1.224 brouard 2077: d=p/q;
2078: u=x+d;
2079: if (u-a < tol2 || b-u < tol2)
2080: d=SIGN(tol1,xm-x);
1.126 brouard 2081: }
2082: } else {
2083: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2084: }
2085: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2086: fu=(*f)(u);
2087: if (fu <= fx) {
2088: if (u >= x) a=x; else b=x;
2089: SHFT(v,w,x,u)
1.183 brouard 2090: SHFT(fv,fw,fx,fu)
2091: } else {
2092: if (u < x) a=u; else b=u;
2093: if (fu <= fw || w == x) {
1.224 brouard 2094: v=w;
2095: w=u;
2096: fv=fw;
2097: fw=fu;
1.183 brouard 2098: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2099: v=u;
2100: fv=fu;
1.183 brouard 2101: }
2102: }
1.126 brouard 2103: }
2104: nrerror("Too many iterations in brent");
2105: *xmin=x;
2106: return fx;
2107: }
2108:
2109: /****************** mnbrak ***********************/
2110:
2111: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2112: double (*func)(double))
1.183 brouard 2113: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2114: the downhill direction (defined by the function as evaluated at the initial points) and returns
2115: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2116: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2117: */
1.126 brouard 2118: double ulim,u,r,q, dum;
2119: double fu;
1.187 brouard 2120:
2121: double scale=10.;
2122: int iterscale=0;
2123:
2124: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2125: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2126:
2127:
2128: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2129: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2130: /* *bx = *ax - (*ax - *bx)/scale; */
2131: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2132: /* } */
2133:
1.126 brouard 2134: if (*fb > *fa) {
2135: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2136: SHFT(dum,*fb,*fa,dum)
2137: }
1.126 brouard 2138: *cx=(*bx)+GOLD*(*bx-*ax);
2139: *fc=(*func)(*cx);
1.183 brouard 2140: #ifdef DEBUG
1.224 brouard 2141: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2142: 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 2143: #endif
1.224 brouard 2144: 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 2145: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2146: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2147: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2148: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2149: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2150: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2151: fu=(*func)(u);
1.163 brouard 2152: #ifdef DEBUG
2153: /* f(x)=A(x-u)**2+f(u) */
2154: double A, fparabu;
2155: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2156: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2157: 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);
2158: 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 2159: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2160: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2161: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2162: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2163: #endif
1.184 brouard 2164: #ifdef MNBRAKORIGINAL
1.183 brouard 2165: #else
1.191 brouard 2166: /* if (fu > *fc) { */
2167: /* #ifdef DEBUG */
2168: /* printf("mnbrak4 fu > fc \n"); */
2169: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2170: /* #endif */
2171: /* /\* 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 *\\/ *\/ */
2172: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2173: /* dum=u; /\* Shifting c and u *\/ */
2174: /* u = *cx; */
2175: /* *cx = dum; */
2176: /* dum = fu; */
2177: /* fu = *fc; */
2178: /* *fc =dum; */
2179: /* } else { /\* end *\/ */
2180: /* #ifdef DEBUG */
2181: /* printf("mnbrak3 fu < fc \n"); */
2182: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2183: /* #endif */
2184: /* dum=u; /\* Shifting c and u *\/ */
2185: /* u = *cx; */
2186: /* *cx = dum; */
2187: /* dum = fu; */
2188: /* fu = *fc; */
2189: /* *fc =dum; */
2190: /* } */
1.224 brouard 2191: #ifdef DEBUGMNBRAK
2192: double A, fparabu;
2193: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2194: fparabu= *fa - A*(*ax-u)*(*ax-u);
2195: 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);
2196: 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 2197: #endif
1.191 brouard 2198: dum=u; /* Shifting c and u */
2199: u = *cx;
2200: *cx = dum;
2201: dum = fu;
2202: fu = *fc;
2203: *fc =dum;
1.183 brouard 2204: #endif
1.162 brouard 2205: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2206: #ifdef DEBUG
1.224 brouard 2207: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2208: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2209: #endif
1.126 brouard 2210: fu=(*func)(u);
2211: if (fu < *fc) {
1.183 brouard 2212: #ifdef DEBUG
1.224 brouard 2213: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2214: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2215: #endif
2216: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2217: SHFT(*fb,*fc,fu,(*func)(u))
2218: #ifdef DEBUG
2219: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2220: #endif
2221: }
1.162 brouard 2222: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2223: #ifdef DEBUG
1.224 brouard 2224: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2225: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2226: #endif
1.126 brouard 2227: u=ulim;
2228: fu=(*func)(u);
1.183 brouard 2229: } else { /* u could be left to b (if r > q parabola has a maximum) */
2230: #ifdef DEBUG
1.224 brouard 2231: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2232: 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 2233: #endif
1.126 brouard 2234: u=(*cx)+GOLD*(*cx-*bx);
2235: fu=(*func)(u);
1.224 brouard 2236: #ifdef DEBUG
2237: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2238: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2239: #endif
1.183 brouard 2240: } /* end tests */
1.126 brouard 2241: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2242: SHFT(*fa,*fb,*fc,fu)
2243: #ifdef DEBUG
1.224 brouard 2244: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2245: 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 2246: #endif
2247: } /* 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 2248: }
2249:
2250: /*************** linmin ************************/
1.162 brouard 2251: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2252: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2253: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2254: the value of func at the returned location p . This is actually all accomplished by calling the
2255: routines mnbrak and brent .*/
1.126 brouard 2256: int ncom;
2257: double *pcom,*xicom;
2258: double (*nrfunc)(double []);
2259:
1.224 brouard 2260: #ifdef LINMINORIGINAL
1.126 brouard 2261: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2262: #else
2263: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2264: #endif
1.126 brouard 2265: {
2266: double brent(double ax, double bx, double cx,
2267: double (*f)(double), double tol, double *xmin);
2268: double f1dim(double x);
2269: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2270: double *fc, double (*func)(double));
2271: int j;
2272: double xx,xmin,bx,ax;
2273: double fx,fb,fa;
1.187 brouard 2274:
1.203 brouard 2275: #ifdef LINMINORIGINAL
2276: #else
2277: double scale=10., axs, xxs; /* Scale added for infinity */
2278: #endif
2279:
1.126 brouard 2280: ncom=n;
2281: pcom=vector(1,n);
2282: xicom=vector(1,n);
2283: nrfunc=func;
2284: for (j=1;j<=n;j++) {
2285: pcom[j]=p[j];
1.202 brouard 2286: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2287: }
1.187 brouard 2288:
1.203 brouard 2289: #ifdef LINMINORIGINAL
2290: xx=1.;
2291: #else
2292: axs=0.0;
2293: xxs=1.;
2294: do{
2295: xx= xxs;
2296: #endif
1.187 brouard 2297: ax=0.;
2298: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2299: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2300: /* 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)) */
2301: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2302: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2303: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2304: /* 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 2305: #ifdef LINMINORIGINAL
2306: #else
2307: if (fx != fx){
1.224 brouard 2308: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2309: printf("|");
2310: fprintf(ficlog,"|");
1.203 brouard 2311: #ifdef DEBUGLINMIN
1.224 brouard 2312: 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 2313: #endif
2314: }
1.224 brouard 2315: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2316: #endif
2317:
1.191 brouard 2318: #ifdef DEBUGLINMIN
2319: 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 2320: 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 2321: #endif
1.224 brouard 2322: #ifdef LINMINORIGINAL
2323: #else
1.317 brouard 2324: if(fb == fx){ /* Flat function in the direction */
2325: xmin=xx;
1.224 brouard 2326: *flat=1;
1.317 brouard 2327: }else{
1.224 brouard 2328: *flat=0;
2329: #endif
2330: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2331: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2332: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2333: /* fmin = f(p[j] + xmin * xi[j]) */
2334: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2335: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2336: #ifdef DEBUG
1.224 brouard 2337: 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);
2338: 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);
2339: #endif
2340: #ifdef LINMINORIGINAL
2341: #else
2342: }
1.126 brouard 2343: #endif
1.191 brouard 2344: #ifdef DEBUGLINMIN
2345: printf("linmin end ");
1.202 brouard 2346: fprintf(ficlog,"linmin end ");
1.191 brouard 2347: #endif
1.126 brouard 2348: for (j=1;j<=n;j++) {
1.203 brouard 2349: #ifdef LINMINORIGINAL
2350: xi[j] *= xmin;
2351: #else
2352: #ifdef DEBUGLINMIN
2353: if(xxs <1.0)
2354: printf(" before xi[%d]=%12.8f", j,xi[j]);
2355: #endif
2356: 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) */
2357: #ifdef DEBUGLINMIN
2358: if(xxs <1.0)
2359: 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 );
2360: #endif
2361: #endif
1.187 brouard 2362: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2363: }
1.191 brouard 2364: #ifdef DEBUGLINMIN
1.203 brouard 2365: printf("\n");
1.191 brouard 2366: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2367: 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 2368: for (j=1;j<=n;j++) {
1.202 brouard 2369: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2370: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2371: if(j % ncovmodel == 0){
1.191 brouard 2372: printf("\n");
1.202 brouard 2373: fprintf(ficlog,"\n");
2374: }
1.191 brouard 2375: }
1.203 brouard 2376: #else
1.191 brouard 2377: #endif
1.126 brouard 2378: free_vector(xicom,1,n);
2379: free_vector(pcom,1,n);
2380: }
2381:
2382:
2383: /*************** powell ************************/
1.162 brouard 2384: /*
1.317 brouard 2385: Minimization of a function func of n variables. Input consists in an initial starting point
2386: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2387: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2388: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2389: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2390: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2391: */
1.224 brouard 2392: #ifdef LINMINORIGINAL
2393: #else
2394: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2395: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2396: #endif
1.126 brouard 2397: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2398: double (*func)(double []))
2399: {
1.224 brouard 2400: #ifdef LINMINORIGINAL
2401: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2402: double (*func)(double []));
1.224 brouard 2403: #else
1.241 brouard 2404: void linmin(double p[], double xi[], int n, double *fret,
2405: double (*func)(double []),int *flat);
1.224 brouard 2406: #endif
1.239 brouard 2407: int i,ibig,j,jk,k;
1.126 brouard 2408: double del,t,*pt,*ptt,*xit;
1.181 brouard 2409: double directest;
1.126 brouard 2410: double fp,fptt;
2411: double *xits;
2412: int niterf, itmp;
2413:
2414: pt=vector(1,n);
2415: ptt=vector(1,n);
2416: xit=vector(1,n);
2417: xits=vector(1,n);
2418: *fret=(*func)(p);
2419: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2420: rcurr_time = time(NULL);
1.126 brouard 2421: for (*iter=1;;++(*iter)) {
2422: ibig=0;
2423: del=0.0;
1.157 brouard 2424: rlast_time=rcurr_time;
2425: /* (void) gettimeofday(&curr_time,&tzp); */
2426: rcurr_time = time(NULL);
2427: curr_time = *localtime(&rcurr_time);
1.324 brouard 2428: printf("\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2429: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
1.157 brouard 2430: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2431: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2432: for (i=1;i<=n;i++) {
1.126 brouard 2433: fprintf(ficrespow," %.12lf", p[i]);
2434: }
1.239 brouard 2435: fprintf(ficrespow,"\n");fflush(ficrespow);
2436: printf("\n#model= 1 + age ");
2437: fprintf(ficlog,"\n#model= 1 + age ");
2438: if(nagesqr==1){
1.241 brouard 2439: printf(" + age*age ");
2440: fprintf(ficlog," + age*age ");
1.239 brouard 2441: }
2442: for(j=1;j <=ncovmodel-2;j++){
2443: if(Typevar[j]==0) {
2444: printf(" + V%d ",Tvar[j]);
2445: fprintf(ficlog," + V%d ",Tvar[j]);
2446: }else if(Typevar[j]==1) {
2447: printf(" + V%d*age ",Tvar[j]);
2448: fprintf(ficlog," + V%d*age ",Tvar[j]);
2449: }else if(Typevar[j]==2) {
2450: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2451: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2452: }
2453: }
1.126 brouard 2454: printf("\n");
1.239 brouard 2455: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2456: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2457: fprintf(ficlog,"\n");
1.239 brouard 2458: for(i=1,jk=1; i <=nlstate; i++){
2459: for(k=1; k <=(nlstate+ndeath); k++){
2460: if (k != i) {
2461: printf("%d%d ",i,k);
2462: fprintf(ficlog,"%d%d ",i,k);
2463: for(j=1; j <=ncovmodel; j++){
2464: printf("%12.7f ",p[jk]);
2465: fprintf(ficlog,"%12.7f ",p[jk]);
2466: jk++;
2467: }
2468: printf("\n");
2469: fprintf(ficlog,"\n");
2470: }
2471: }
2472: }
1.241 brouard 2473: if(*iter <=3 && *iter >1){
1.157 brouard 2474: tml = *localtime(&rcurr_time);
2475: strcpy(strcurr,asctime(&tml));
2476: rforecast_time=rcurr_time;
1.126 brouard 2477: itmp = strlen(strcurr);
2478: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2479: strcurr[itmp-1]='\0';
1.162 brouard 2480: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2481: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2482: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2483: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2484: forecast_time = *localtime(&rforecast_time);
2485: strcpy(strfor,asctime(&forecast_time));
2486: itmp = strlen(strfor);
2487: if(strfor[itmp-1]=='\n')
2488: strfor[itmp-1]='\0';
2489: 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);
2490: 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 2491: }
2492: }
1.187 brouard 2493: for (i=1;i<=n;i++) { /* For each direction i */
2494: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2495: fptt=(*fret);
2496: #ifdef DEBUG
1.203 brouard 2497: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2498: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2499: #endif
1.203 brouard 2500: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2501: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2502: #ifdef LINMINORIGINAL
1.188 brouard 2503: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2504: #else
2505: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2506: flatdir[i]=flat; /* Function is vanishing in that direction i */
2507: #endif
2508: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2509: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2510: /* because that direction will be replaced unless the gain del is small */
2511: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2512: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2513: /* with the new direction. */
2514: del=fabs(fptt-(*fret));
2515: ibig=i;
1.126 brouard 2516: }
2517: #ifdef DEBUG
2518: printf("%d %.12e",i,(*fret));
2519: fprintf(ficlog,"%d %.12e",i,(*fret));
2520: for (j=1;j<=n;j++) {
1.224 brouard 2521: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2522: printf(" x(%d)=%.12e",j,xit[j]);
2523: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2524: }
2525: for(j=1;j<=n;j++) {
1.225 brouard 2526: printf(" p(%d)=%.12e",j,p[j]);
2527: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2528: }
2529: printf("\n");
2530: fprintf(ficlog,"\n");
2531: #endif
1.187 brouard 2532: } /* end loop on each direction i */
2533: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2534: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2535: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2536: for(j=1;j<=n;j++) {
2537: if(flatdir[j] >0){
2538: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2539: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2540: }
1.319 brouard 2541: /* printf("\n"); */
2542: /* fprintf(ficlog,"\n"); */
2543: }
1.243 brouard 2544: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2545: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2546: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2547: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2548: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2549: /* decreased of more than 3.84 */
2550: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2551: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2552: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2553:
1.188 brouard 2554: /* Starting the program with initial values given by a former maximization will simply change */
2555: /* the scales of the directions and the directions, because the are reset to canonical directions */
2556: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2557: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2558: #ifdef DEBUG
2559: int k[2],l;
2560: k[0]=1;
2561: k[1]=-1;
2562: printf("Max: %.12e",(*func)(p));
2563: fprintf(ficlog,"Max: %.12e",(*func)(p));
2564: for (j=1;j<=n;j++) {
2565: printf(" %.12e",p[j]);
2566: fprintf(ficlog," %.12e",p[j]);
2567: }
2568: printf("\n");
2569: fprintf(ficlog,"\n");
2570: for(l=0;l<=1;l++) {
2571: for (j=1;j<=n;j++) {
2572: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2573: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2574: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2575: }
2576: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2577: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2578: }
2579: #endif
2580:
2581: free_vector(xit,1,n);
2582: free_vector(xits,1,n);
2583: free_vector(ptt,1,n);
2584: free_vector(pt,1,n);
2585: return;
1.192 brouard 2586: } /* enough precision */
1.240 brouard 2587: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2588: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2589: ptt[j]=2.0*p[j]-pt[j];
2590: xit[j]=p[j]-pt[j];
2591: pt[j]=p[j];
2592: }
1.181 brouard 2593: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2594: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2595: if (*iter <=4) {
1.225 brouard 2596: #else
2597: #endif
1.224 brouard 2598: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2599: #else
1.161 brouard 2600: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2601: #endif
1.162 brouard 2602: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2603: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2604: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2605: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2606: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2607: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2608: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2609: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2610: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2611: /* Even if f3 <f1, directest can be negative and t >0 */
2612: /* mu² and del² are equal when f3=f1 */
2613: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2614: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2615: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2616: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2617: #ifdef NRCORIGINAL
2618: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2619: #else
2620: 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 2621: t= t- del*SQR(fp-fptt);
1.183 brouard 2622: #endif
1.202 brouard 2623: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2624: #ifdef DEBUG
1.181 brouard 2625: 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);
2626: 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 2627: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2628: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2629: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2630: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2631: 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);
2632: 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);
2633: #endif
1.183 brouard 2634: #ifdef POWELLORIGINAL
2635: if (t < 0.0) { /* Then we use it for new direction */
2636: #else
1.182 brouard 2637: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2638: 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 2639: 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 2640: 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 2641: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2642: }
1.181 brouard 2643: if (directest < 0.0) { /* Then we use it for new direction */
2644: #endif
1.191 brouard 2645: #ifdef DEBUGLINMIN
1.234 brouard 2646: printf("Before linmin in direction P%d-P0\n",n);
2647: for (j=1;j<=n;j++) {
2648: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2649: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2650: if(j % ncovmodel == 0){
2651: printf("\n");
2652: fprintf(ficlog,"\n");
2653: }
2654: }
1.224 brouard 2655: #endif
2656: #ifdef LINMINORIGINAL
1.234 brouard 2657: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2658: #else
1.234 brouard 2659: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2660: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2661: #endif
1.234 brouard 2662:
1.191 brouard 2663: #ifdef DEBUGLINMIN
1.234 brouard 2664: for (j=1;j<=n;j++) {
2665: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2666: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2667: if(j % ncovmodel == 0){
2668: printf("\n");
2669: fprintf(ficlog,"\n");
2670: }
2671: }
1.224 brouard 2672: #endif
1.234 brouard 2673: for (j=1;j<=n;j++) {
2674: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2675: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2676: }
1.224 brouard 2677: #ifdef LINMINORIGINAL
2678: #else
1.234 brouard 2679: for (j=1, flatd=0;j<=n;j++) {
2680: if(flatdir[j]>0)
2681: flatd++;
2682: }
2683: if(flatd >0){
1.255 brouard 2684: printf("%d flat directions: ",flatd);
2685: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2686: for (j=1;j<=n;j++) {
2687: if(flatdir[j]>0){
2688: printf("%d ",j);
2689: fprintf(ficlog,"%d ",j);
2690: }
2691: }
2692: printf("\n");
2693: fprintf(ficlog,"\n");
1.319 brouard 2694: #ifdef FLATSUP
2695: free_vector(xit,1,n);
2696: free_vector(xits,1,n);
2697: free_vector(ptt,1,n);
2698: free_vector(pt,1,n);
2699: return;
2700: #endif
1.234 brouard 2701: }
1.191 brouard 2702: #endif
1.234 brouard 2703: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2704: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2705:
1.126 brouard 2706: #ifdef DEBUG
1.234 brouard 2707: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2708: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2709: for(j=1;j<=n;j++){
2710: printf(" %lf",xit[j]);
2711: fprintf(ficlog," %lf",xit[j]);
2712: }
2713: printf("\n");
2714: fprintf(ficlog,"\n");
1.126 brouard 2715: #endif
1.192 brouard 2716: } /* end of t or directest negative */
1.224 brouard 2717: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2718: #else
1.234 brouard 2719: } /* end if (fptt < fp) */
1.192 brouard 2720: #endif
1.225 brouard 2721: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2722: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2723: #else
1.224 brouard 2724: #endif
1.234 brouard 2725: } /* loop iteration */
1.126 brouard 2726: }
1.234 brouard 2727:
1.126 brouard 2728: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2729:
1.235 brouard 2730: 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 2731: {
1.279 brouard 2732: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2733: * (and selected quantitative values in nres)
2734: * by left multiplying the unit
2735: * matrix by transitions matrix until convergence is reached with precision ftolpl
2736: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2737: * Wx is row vector: population in state 1, population in state 2, population dead
2738: * or prevalence in state 1, prevalence in state 2, 0
2739: * newm is the matrix after multiplications, its rows are identical at a factor.
2740: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2741: * Output is prlim.
2742: * Initial matrix pimij
2743: */
1.206 brouard 2744: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2745: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2746: /* 0, 0 , 1} */
2747: /*
2748: * and after some iteration: */
2749: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2750: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2751: /* 0, 0 , 1} */
2752: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2753: /* {0.51571254859325999, 0.4842874514067399, */
2754: /* 0.51326036147820708, 0.48673963852179264} */
2755: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2756:
1.126 brouard 2757: int i, ii,j,k;
1.209 brouard 2758: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2759: /* double **matprod2(); */ /* test */
1.218 brouard 2760: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2761: double **newm;
1.209 brouard 2762: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2763: int ncvloop=0;
1.288 brouard 2764: int first=0;
1.169 brouard 2765:
1.209 brouard 2766: min=vector(1,nlstate);
2767: max=vector(1,nlstate);
2768: meandiff=vector(1,nlstate);
2769:
1.218 brouard 2770: /* Starting with matrix unity */
1.126 brouard 2771: for (ii=1;ii<=nlstate+ndeath;ii++)
2772: for (j=1;j<=nlstate+ndeath;j++){
2773: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2774: }
1.169 brouard 2775:
2776: cov[1]=1.;
2777:
2778: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2779: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2780: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2781: ncvloop++;
1.126 brouard 2782: newm=savm;
2783: /* Covariates have to be included here again */
1.138 brouard 2784: cov[2]=agefin;
1.319 brouard 2785: if(nagesqr==1){
2786: cov[3]= agefin*agefin;
2787: }
1.234 brouard 2788: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2789: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2790: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.319 brouard 2791: /* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; */
1.235 brouard 2792: /* 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 2793: }
2794: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2795: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 2796: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2797: /* cov[++k1]=Tqresult[nres][k]; */
1.235 brouard 2798: /* 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 2799: }
1.237 brouard 2800: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2801: if(Dummy[Tage[k]]==2){ /* dummy with age */
1.234 brouard 2802: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2803: /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
2804: } else if(Dummy[Tage[k]]==3){ /* quantitative with age */
2805: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2806: /* cov[++k1]=Tqresult[nres][k]; */
1.234 brouard 2807: }
1.235 brouard 2808: /* 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 2809: }
1.237 brouard 2810: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2811: /* 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 2812: if(Dummy[Tvard[k][1]==0]){
2813: if(Dummy[Tvard[k][2]==0]){
2814: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
1.319 brouard 2815: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.237 brouard 2816: }else{
2817: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
1.319 brouard 2818: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */
1.237 brouard 2819: }
2820: }else{
2821: if(Dummy[Tvard[k][2]==0]){
2822: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
1.319 brouard 2823: /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */
1.237 brouard 2824: }else{
2825: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
1.319 brouard 2826: /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
1.237 brouard 2827: }
2828: }
1.234 brouard 2829: }
1.138 brouard 2830: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2831: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2832: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2833: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2834: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2835: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2836: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2837:
1.126 brouard 2838: savm=oldm;
2839: oldm=newm;
1.209 brouard 2840:
2841: for(j=1; j<=nlstate; j++){
2842: max[j]=0.;
2843: min[j]=1.;
2844: }
2845: for(i=1;i<=nlstate;i++){
2846: sumnew=0;
2847: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2848: for(j=1; j<=nlstate; j++){
2849: prlim[i][j]= newm[i][j]/(1-sumnew);
2850: max[j]=FMAX(max[j],prlim[i][j]);
2851: min[j]=FMIN(min[j],prlim[i][j]);
2852: }
2853: }
2854:
1.126 brouard 2855: maxmax=0.;
1.209 brouard 2856: for(j=1; j<=nlstate; j++){
2857: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2858: maxmax=FMAX(maxmax,meandiff[j]);
2859: /* 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 2860: } /* j loop */
1.203 brouard 2861: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2862: /* 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 2863: if(maxmax < ftolpl){
1.209 brouard 2864: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2865: free_vector(min,1,nlstate);
2866: free_vector(max,1,nlstate);
2867: free_vector(meandiff,1,nlstate);
1.126 brouard 2868: return prlim;
2869: }
1.288 brouard 2870: } /* agefin loop */
1.208 brouard 2871: /* After some age loop it doesn't converge */
1.288 brouard 2872: if(!first){
2873: first=1;
2874: 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 2875: 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);
2876: }else if (first >=1 && first <10){
2877: 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);
2878: first++;
2879: }else if (first ==10){
2880: 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);
2881: 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");
2882: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
2883: first++;
1.288 brouard 2884: }
2885:
1.209 brouard 2886: /* 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); */
2887: free_vector(min,1,nlstate);
2888: free_vector(max,1,nlstate);
2889: free_vector(meandiff,1,nlstate);
1.208 brouard 2890:
1.169 brouard 2891: return prlim; /* should not reach here */
1.126 brouard 2892: }
2893:
1.217 brouard 2894:
2895: /**** Back Prevalence limit (stable or period prevalence) ****************/
2896:
1.218 brouard 2897: /* 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) */
2898: /* 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 2899: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2900: {
1.264 brouard 2901: /* 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 2902: matrix by transitions matrix until convergence is reached with precision ftolpl */
2903: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2904: /* Wx is row vector: population in state 1, population in state 2, population dead */
2905: /* or prevalence in state 1, prevalence in state 2, 0 */
2906: /* newm is the matrix after multiplications, its rows are identical at a factor */
2907: /* Initial matrix pimij */
2908: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2909: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2910: /* 0, 0 , 1} */
2911: /*
2912: * and after some iteration: */
2913: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2914: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2915: /* 0, 0 , 1} */
2916: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2917: /* {0.51571254859325999, 0.4842874514067399, */
2918: /* 0.51326036147820708, 0.48673963852179264} */
2919: /* If we start from prlim again, prlim tends to a constant matrix */
2920:
2921: int i, ii,j,k;
1.247 brouard 2922: int first=0;
1.217 brouard 2923: double *min, *max, *meandiff, maxmax,sumnew=0.;
2924: /* double **matprod2(); */ /* test */
2925: double **out, cov[NCOVMAX+1], **bmij();
2926: double **newm;
1.218 brouard 2927: double **dnewm, **doldm, **dsavm; /* for use */
2928: double **oldm, **savm; /* for use */
2929:
1.217 brouard 2930: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2931: int ncvloop=0;
2932:
2933: min=vector(1,nlstate);
2934: max=vector(1,nlstate);
2935: meandiff=vector(1,nlstate);
2936:
1.266 brouard 2937: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2938: oldm=oldms; savm=savms;
2939:
2940: /* Starting with matrix unity */
2941: for (ii=1;ii<=nlstate+ndeath;ii++)
2942: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2943: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2944: }
2945:
2946: cov[1]=1.;
2947:
2948: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2949: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2950: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2951: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2952: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2953: ncvloop++;
1.218 brouard 2954: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2955: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2956: /* Covariates have to be included here again */
2957: cov[2]=agefin;
1.319 brouard 2958: if(nagesqr==1){
1.217 brouard 2959: cov[3]= agefin*agefin;;
1.319 brouard 2960: }
1.242 brouard 2961: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2962: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2963: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2964: /* 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 2965: }
2966: /* for (k=1; k<=cptcovn;k++) { */
2967: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2968: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2969: /* /\* 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])]); *\/ */
2970: /* } */
2971: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2972: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2973: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2974: /* 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]); */
2975: }
2976: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2977: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2978: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2979: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2980: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2981: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ ERROR ???*/
2982: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.242 brouard 2983: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2984: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
2985: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.242 brouard 2986: }
2987: /* 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]); */
2988: }
2989: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2990: /* 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]); */
2991: if(Dummy[Tvard[k][1]==0]){
2992: if(Dummy[Tvard[k][2]==0]){
2993: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2994: }else{
2995: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2996: }
2997: }else{
2998: if(Dummy[Tvard[k][2]==0]){
2999: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
3000: }else{
3001: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3002: }
3003: }
1.217 brouard 3004: }
3005:
3006: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3007: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3008: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3009: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3010: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3011: /* ij should be linked to the correct index of cov */
3012: /* age and covariate values ij are in 'cov', but we need to pass
3013: * ij for the observed prevalence at age and status and covariate
3014: * number: prevacurrent[(int)agefin][ii][ij]
3015: */
3016: /* 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 *\/ */
3017: /* 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 *\/ */
3018: 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 3019: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3020: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3021: /* for(i=1; i<=nlstate+ndeath; i++) { */
3022: /* printf("%d newm= ",i); */
3023: /* for(j=1;j<=nlstate+ndeath;j++) { */
3024: /* printf("%f ",newm[i][j]); */
3025: /* } */
3026: /* printf("oldm * "); */
3027: /* for(j=1;j<=nlstate+ndeath;j++) { */
3028: /* printf("%f ",oldm[i][j]); */
3029: /* } */
1.268 brouard 3030: /* printf(" bmmij "); */
1.266 brouard 3031: /* for(j=1;j<=nlstate+ndeath;j++) { */
3032: /* printf("%f ",pmmij[i][j]); */
3033: /* } */
3034: /* printf("\n"); */
3035: /* } */
3036: /* } */
1.217 brouard 3037: savm=oldm;
3038: oldm=newm;
1.266 brouard 3039:
1.217 brouard 3040: for(j=1; j<=nlstate; j++){
3041: max[j]=0.;
3042: min[j]=1.;
3043: }
3044: for(j=1; j<=nlstate; j++){
3045: for(i=1;i<=nlstate;i++){
1.234 brouard 3046: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3047: bprlim[i][j]= newm[i][j];
3048: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3049: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3050: }
3051: }
1.218 brouard 3052:
1.217 brouard 3053: maxmax=0.;
3054: for(i=1; i<=nlstate; i++){
1.318 brouard 3055: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3056: maxmax=FMAX(maxmax,meandiff[i]);
3057: /* 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 3058: } /* i loop */
1.217 brouard 3059: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3060: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3061: if(maxmax < ftolpl){
1.220 brouard 3062: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3063: free_vector(min,1,nlstate);
3064: free_vector(max,1,nlstate);
3065: free_vector(meandiff,1,nlstate);
3066: return bprlim;
3067: }
1.288 brouard 3068: } /* agefin loop */
1.217 brouard 3069: /* After some age loop it doesn't converge */
1.288 brouard 3070: if(!first){
1.247 brouard 3071: first=1;
3072: 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\
3073: 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);
3074: }
3075: 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 3076: 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);
3077: /* 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); */
3078: free_vector(min,1,nlstate);
3079: free_vector(max,1,nlstate);
3080: free_vector(meandiff,1,nlstate);
3081:
3082: return bprlim; /* should not reach here */
3083: }
3084:
1.126 brouard 3085: /*************** transition probabilities ***************/
3086:
3087: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3088: {
1.138 brouard 3089: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3090: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3091: model to the ncovmodel covariates (including constant and age).
3092: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3093: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3094: ncth covariate in the global vector x is given by the formula:
3095: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3096: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3097: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3098: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3099: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3100: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3101: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3102: */
3103: double s1, lnpijopii;
1.126 brouard 3104: /*double t34;*/
1.164 brouard 3105: int i,j, nc, ii, jj;
1.126 brouard 3106:
1.223 brouard 3107: for(i=1; i<= nlstate; i++){
3108: for(j=1; j<i;j++){
3109: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3110: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3111: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3112: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3113: }
3114: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3115: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3116: }
3117: for(j=i+1; j<=nlstate+ndeath;j++){
3118: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3119: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3120: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3121: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3122: }
3123: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3124: }
3125: }
1.218 brouard 3126:
1.223 brouard 3127: for(i=1; i<= nlstate; i++){
3128: s1=0;
3129: for(j=1; j<i; j++){
3130: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3131: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3132: }
3133: for(j=i+1; j<=nlstate+ndeath; j++){
3134: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3135: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3136: }
3137: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3138: ps[i][i]=1./(s1+1.);
3139: /* Computing other pijs */
3140: for(j=1; j<i; j++)
1.325 ! brouard 3141: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3142: for(j=i+1; j<=nlstate+ndeath; j++)
3143: ps[i][j]= exp(ps[i][j])*ps[i][i];
3144: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3145: } /* end i */
1.218 brouard 3146:
1.223 brouard 3147: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3148: for(jj=1; jj<= nlstate+ndeath; jj++){
3149: ps[ii][jj]=0;
3150: ps[ii][ii]=1;
3151: }
3152: }
1.294 brouard 3153:
3154:
1.223 brouard 3155: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3156: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3157: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3158: /* } */
3159: /* printf("\n "); */
3160: /* } */
3161: /* printf("\n ");printf("%lf ",cov[2]);*/
3162: /*
3163: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3164: goto end;*/
1.266 brouard 3165: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3166: }
3167:
1.218 brouard 3168: /*************** backward transition probabilities ***************/
3169:
3170: /* 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 ) */
3171: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3172: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3173: {
1.302 brouard 3174: /* 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 3175: * 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 3176: */
1.218 brouard 3177: int i, ii, j,k;
1.222 brouard 3178:
3179: double **out, **pmij();
3180: double sumnew=0.;
1.218 brouard 3181: double agefin;
1.292 brouard 3182: 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 3183: double **dnewm, **dsavm, **doldm;
3184: double **bbmij;
3185:
1.218 brouard 3186: doldm=ddoldms; /* global pointers */
1.222 brouard 3187: dnewm=ddnewms;
3188: dsavm=ddsavms;
1.318 brouard 3189:
3190: /* Debug */
3191: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3192: agefin=cov[2];
1.268 brouard 3193: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3194: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3195: the observed prevalence (with this covariate ij) at beginning of transition */
3196: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3197:
3198: /* P_x */
1.325 ! brouard 3199: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3200: /* outputs pmmij which is a stochastic matrix in row */
3201:
3202: /* Diag(w_x) */
1.292 brouard 3203: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3204: sumnew=0.;
1.269 brouard 3205: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3206: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3207: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3208: sumnew+=prevacurrent[(int)agefin][ii][ij];
3209: }
3210: if(sumnew >0.01){ /* At least some value in the prevalence */
3211: for (ii=1;ii<=nlstate+ndeath;ii++){
3212: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3213: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3214: }
3215: }else{
3216: for (ii=1;ii<=nlstate+ndeath;ii++){
3217: for (j=1;j<=nlstate+ndeath;j++)
3218: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3219: }
3220: /* if(sumnew <0.9){ */
3221: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3222: /* } */
3223: }
3224: k3=0.0; /* We put the last diagonal to 0 */
3225: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3226: doldm[ii][ii]= k3;
3227: }
3228: /* End doldm, At the end doldm is diag[(w_i)] */
3229:
1.292 brouard 3230: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3231: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3232:
1.292 brouard 3233: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3234: /* 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 3235: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3236: sumnew=0.;
1.222 brouard 3237: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3238: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3239: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3240: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3241: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3242: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3243: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3244: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3245: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3246: /* }else */
1.268 brouard 3247: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3248: } /*End ii */
3249: } /* 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 */
3250:
1.292 brouard 3251: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3252: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3253: /* end bmij */
1.266 brouard 3254: return ps; /*pointer is unchanged */
1.218 brouard 3255: }
1.217 brouard 3256: /*************** transition probabilities ***************/
3257:
1.218 brouard 3258: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3259: {
3260: /* According to parameters values stored in x and the covariate's values stored in cov,
3261: computes the probability to be observed in state j being in state i by appying the
3262: model to the ncovmodel covariates (including constant and age).
3263: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3264: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3265: ncth covariate in the global vector x is given by the formula:
3266: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3267: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3268: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3269: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3270: Outputs ps[i][j] the probability to be observed in j being in j according to
3271: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3272: */
3273: double s1, lnpijopii;
3274: /*double t34;*/
3275: int i,j, nc, ii, jj;
3276:
1.234 brouard 3277: for(i=1; i<= nlstate; i++){
3278: for(j=1; j<i;j++){
3279: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3280: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3281: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3282: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3283: }
3284: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3285: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3286: }
3287: for(j=i+1; j<=nlstate+ndeath;j++){
3288: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3289: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3290: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3291: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3292: }
3293: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3294: }
3295: }
3296:
3297: for(i=1; i<= nlstate; i++){
3298: s1=0;
3299: for(j=1; j<i; j++){
3300: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3301: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3302: }
3303: for(j=i+1; j<=nlstate+ndeath; j++){
3304: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3305: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3306: }
3307: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3308: ps[i][i]=1./(s1+1.);
3309: /* Computing other pijs */
3310: for(j=1; j<i; j++)
3311: ps[i][j]= exp(ps[i][j])*ps[i][i];
3312: for(j=i+1; j<=nlstate+ndeath; j++)
3313: ps[i][j]= exp(ps[i][j])*ps[i][i];
3314: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3315: } /* end i */
3316:
3317: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3318: for(jj=1; jj<= nlstate+ndeath; jj++){
3319: ps[ii][jj]=0;
3320: ps[ii][ii]=1;
3321: }
3322: }
1.296 brouard 3323: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3324: for(jj=1; jj<= nlstate+ndeath; jj++){
3325: s1=0.;
3326: for(ii=1; ii<= nlstate+ndeath; ii++){
3327: s1+=ps[ii][jj];
3328: }
3329: for(ii=1; ii<= nlstate; ii++){
3330: ps[ii][jj]=ps[ii][jj]/s1;
3331: }
3332: }
3333: /* Transposition */
3334: for(jj=1; jj<= nlstate+ndeath; jj++){
3335: for(ii=jj; ii<= nlstate+ndeath; ii++){
3336: s1=ps[ii][jj];
3337: ps[ii][jj]=ps[jj][ii];
3338: ps[jj][ii]=s1;
3339: }
3340: }
3341: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3342: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3343: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3344: /* } */
3345: /* printf("\n "); */
3346: /* } */
3347: /* printf("\n ");printf("%lf ",cov[2]);*/
3348: /*
3349: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3350: goto end;*/
3351: return ps;
1.217 brouard 3352: }
3353:
3354:
1.126 brouard 3355: /**************** Product of 2 matrices ******************/
3356:
1.145 brouard 3357: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3358: {
3359: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3360: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3361: /* in, b, out are matrice of pointers which should have been initialized
3362: before: only the contents of out is modified. The function returns
3363: a pointer to pointers identical to out */
1.145 brouard 3364: int i, j, k;
1.126 brouard 3365: for(i=nrl; i<= nrh; i++)
1.145 brouard 3366: for(k=ncolol; k<=ncoloh; k++){
3367: out[i][k]=0.;
3368: for(j=ncl; j<=nch; j++)
3369: out[i][k] +=in[i][j]*b[j][k];
3370: }
1.126 brouard 3371: return out;
3372: }
3373:
3374:
3375: /************* Higher Matrix Product ***************/
3376:
1.235 brouard 3377: 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 3378: {
1.218 brouard 3379: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3380: 'nhstepm*hstepm*stepm' months (i.e. until
3381: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3382: nhstepm*hstepm matrices.
3383: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3384: (typically every 2 years instead of every month which is too big
3385: for the memory).
3386: Model is determined by parameters x and covariates have to be
3387: included manually here.
3388:
3389: */
3390:
3391: int i, j, d, h, k;
1.131 brouard 3392: double **out, cov[NCOVMAX+1];
1.126 brouard 3393: double **newm;
1.187 brouard 3394: double agexact;
1.214 brouard 3395: double agebegin, ageend;
1.126 brouard 3396:
3397: /* Hstepm could be zero and should return the unit matrix */
3398: for (i=1;i<=nlstate+ndeath;i++)
3399: for (j=1;j<=nlstate+ndeath;j++){
3400: oldm[i][j]=(i==j ? 1.0 : 0.0);
3401: po[i][j][0]=(i==j ? 1.0 : 0.0);
3402: }
3403: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3404: for(h=1; h <=nhstepm; h++){
3405: for(d=1; d <=hstepm; d++){
3406: newm=savm;
3407: /* Covariates have to be included here again */
3408: cov[1]=1.;
1.214 brouard 3409: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3410: cov[2]=agexact;
1.319 brouard 3411: if(nagesqr==1){
1.227 brouard 3412: cov[3]= agexact*agexact;
1.319 brouard 3413: }
1.235 brouard 3414: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
1.319 brouard 3415: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3416: /* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 */
3417: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3418: /* k 1 2 3 4 5 6 7 8 9 */
3419: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
3420: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
3421: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
3422: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1.235 brouard 3423: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3424: /* 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)); */
3425: }
3426: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3427: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 3428: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
1.235 brouard 3429: /* 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]); */
3430: }
1.319 brouard 3431: for (k=1; k<=cptcovage;k++){ /* For product with age V1+V1*age +V4 +age*V3 */
3432: /* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*/
3433: /* */
3434: if(Dummy[Tage[k]]== 2){ /* dummy with age */
3435: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ */
1.235 brouard 3436: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3437: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
3438: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.235 brouard 3439: }
3440: /* 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]); */
3441: }
1.319 brouard 3442: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 3443: /* 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 3444: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
3445: if(Dummy[Tvard[k][1]==0]){
3446: if(Dummy[Tvard[k][2]==0]){
3447: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3448: }else{
3449: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
3450: }
3451: }else{
3452: if(Dummy[Tvard[k][2]==0]){
3453: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
3454: }else{
3455: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3456: }
3457: }
1.235 brouard 3458: }
3459: /* for (k=1; k<=cptcovn;k++) */
3460: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3461: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3462: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3463: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3464: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3465:
3466:
1.126 brouard 3467: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3468: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3469: /* right multiplication of oldm by the current matrix */
1.126 brouard 3470: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3471: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3472: /* if((int)age == 70){ */
3473: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3474: /* for(i=1; i<=nlstate+ndeath; i++) { */
3475: /* printf("%d pmmij ",i); */
3476: /* for(j=1;j<=nlstate+ndeath;j++) { */
3477: /* printf("%f ",pmmij[i][j]); */
3478: /* } */
3479: /* printf(" oldm "); */
3480: /* for(j=1;j<=nlstate+ndeath;j++) { */
3481: /* printf("%f ",oldm[i][j]); */
3482: /* } */
3483: /* printf("\n"); */
3484: /* } */
3485: /* } */
1.126 brouard 3486: savm=oldm;
3487: oldm=newm;
3488: }
3489: for(i=1; i<=nlstate+ndeath; i++)
3490: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3491: po[i][j][h]=newm[i][j];
3492: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3493: }
1.128 brouard 3494: /*printf("h=%d ",h);*/
1.126 brouard 3495: } /* end h */
1.267 brouard 3496: /* printf("\n H=%d \n",h); */
1.126 brouard 3497: return po;
3498: }
3499:
1.217 brouard 3500: /************* Higher Back Matrix Product ***************/
1.218 brouard 3501: /* 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 3502: 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 3503: {
1.266 brouard 3504: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3505: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3506: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3507: nhstepm*hstepm matrices.
3508: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3509: (typically every 2 years instead of every month which is too big
1.217 brouard 3510: for the memory).
1.218 brouard 3511: Model is determined by parameters x and covariates have to be
1.266 brouard 3512: included manually here. Then we use a call to bmij(x and cov)
3513: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3514: */
1.217 brouard 3515:
3516: int i, j, d, h, k;
1.266 brouard 3517: double **out, cov[NCOVMAX+1], **bmij();
3518: double **newm, ***newmm;
1.217 brouard 3519: double agexact;
3520: double agebegin, ageend;
1.222 brouard 3521: double **oldm, **savm;
1.217 brouard 3522:
1.266 brouard 3523: newmm=po; /* To be saved */
3524: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3525: /* Hstepm could be zero and should return the unit matrix */
3526: for (i=1;i<=nlstate+ndeath;i++)
3527: for (j=1;j<=nlstate+ndeath;j++){
3528: oldm[i][j]=(i==j ? 1.0 : 0.0);
3529: po[i][j][0]=(i==j ? 1.0 : 0.0);
3530: }
3531: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3532: for(h=1; h <=nhstepm; h++){
3533: for(d=1; d <=hstepm; d++){
3534: newm=savm;
3535: /* Covariates have to be included here again */
3536: cov[1]=1.;
1.271 brouard 3537: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3538: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3539: /* Debug */
3540: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3541: cov[2]=agexact;
3542: if(nagesqr==1)
1.222 brouard 3543: cov[3]= agexact*agexact;
1.325 ! brouard 3544: for (k=1; k<=nsd;k++){ /* For single dummy covariates only *//* cptcovn error */
1.266 brouard 3545: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3546: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
1.325 ! brouard 3547: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];/* Bug valgrind */
1.266 brouard 3548: /* 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)); */
3549: }
1.267 brouard 3550: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3551: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3552: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3553: /* 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]); */
3554: }
1.319 brouard 3555: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 *//* For product with age */
3556: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age error!!!*\/ */
3557: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.267 brouard 3558: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3559: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
1.267 brouard 3560: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3561: }
3562: /* 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]); */
3563: }
3564: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3565: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.325 ! brouard 3566: if(Dummy[Tvard[k][1]==0]){
! 3567: if(Dummy[Tvard[k][2]==0]){
! 3568: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
! 3569: }else{
! 3570: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
! 3571: }
! 3572: }else{
! 3573: if(Dummy[Tvard[k][2]==0]){
! 3574: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
! 3575: }else{
! 3576: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
! 3577: }
! 3578: }
1.267 brouard 3579: }
1.217 brouard 3580: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3581: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3582:
1.218 brouard 3583: /* Careful transposed matrix */
1.266 brouard 3584: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3585: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3586: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3587: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 ! brouard 3588: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3589: /* if((int)age == 70){ */
3590: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3591: /* for(i=1; i<=nlstate+ndeath; i++) { */
3592: /* printf("%d pmmij ",i); */
3593: /* for(j=1;j<=nlstate+ndeath;j++) { */
3594: /* printf("%f ",pmmij[i][j]); */
3595: /* } */
3596: /* printf(" oldm "); */
3597: /* for(j=1;j<=nlstate+ndeath;j++) { */
3598: /* printf("%f ",oldm[i][j]); */
3599: /* } */
3600: /* printf("\n"); */
3601: /* } */
3602: /* } */
3603: savm=oldm;
3604: oldm=newm;
3605: }
3606: for(i=1; i<=nlstate+ndeath; i++)
3607: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3608: po[i][j][h]=newm[i][j];
1.268 brouard 3609: /* if(h==nhstepm) */
3610: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3611: }
1.268 brouard 3612: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3613: } /* end h */
1.268 brouard 3614: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3615: return po;
3616: }
3617:
3618:
1.162 brouard 3619: #ifdef NLOPT
3620: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3621: double fret;
3622: double *xt;
3623: int j;
3624: myfunc_data *d2 = (myfunc_data *) pd;
3625: /* xt = (p1-1); */
3626: xt=vector(1,n);
3627: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3628:
3629: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3630: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3631: printf("Function = %.12lf ",fret);
3632: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3633: printf("\n");
3634: free_vector(xt,1,n);
3635: return fret;
3636: }
3637: #endif
1.126 brouard 3638:
3639: /*************** log-likelihood *************/
3640: double func( double *x)
3641: {
1.226 brouard 3642: int i, ii, j, k, mi, d, kk;
3643: int ioffset=0;
3644: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3645: double **out;
3646: double lli; /* Individual log likelihood */
3647: int s1, s2;
1.228 brouard 3648: 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 3649: double bbh, survp;
3650: long ipmx;
3651: double agexact;
3652: /*extern weight */
3653: /* We are differentiating ll according to initial status */
3654: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3655: /*for(i=1;i<imx;i++)
3656: printf(" %d\n",s[4][i]);
3657: */
1.162 brouard 3658:
1.226 brouard 3659: ++countcallfunc;
1.162 brouard 3660:
1.226 brouard 3661: cov[1]=1.;
1.126 brouard 3662:
1.226 brouard 3663: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3664: ioffset=0;
1.226 brouard 3665: if(mle==1){
3666: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3667: /* Computes the values of the ncovmodel covariates of the model
3668: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3669: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3670: to be observed in j being in i according to the model.
3671: */
1.243 brouard 3672: ioffset=2+nagesqr ;
1.233 brouard 3673: /* Fixed */
1.319 brouard 3674: for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */
3675: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3676: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3677: /* 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 3678: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.319 brouard 3679: 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)*/
3680: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3681: }
1.226 brouard 3682: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3683: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3684: has been calculated etc */
3685: /* For an individual i, wav[i] gives the number of effective waves */
3686: /* We compute the contribution to Likelihood of each effective transition
3687: mw[mi][i] is real wave of the mi th effectve wave */
3688: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3689: s2=s[mw[mi+1][i]][i];
3690: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3691: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3692: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3693: */
3694: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3695: 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*/
3696: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */
1.242 brouard 3697: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3698: }
3699: for (ii=1;ii<=nlstate+ndeath;ii++)
3700: for (j=1;j<=nlstate+ndeath;j++){
3701: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3702: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3703: }
3704: for(d=0; d<dh[mi][i]; d++){
3705: newm=savm;
3706: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3707: cov[2]=agexact;
3708: if(nagesqr==1)
3709: cov[3]= agexact*agexact; /* Should be changed here */
3710: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3711: if(!FixedV[Tvar[Tage[kk]]])
3712: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3713: else
3714: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3715: }
3716: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3717: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3718: savm=oldm;
3719: oldm=newm;
3720: } /* end mult */
3721:
3722: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3723: /* But now since version 0.9 we anticipate for bias at large stepm.
3724: * If stepm is larger than one month (smallest stepm) and if the exact delay
3725: * (in months) between two waves is not a multiple of stepm, we rounded to
3726: * the nearest (and in case of equal distance, to the lowest) interval but now
3727: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3728: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3729: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3730: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3731: * -stepm/2 to stepm/2 .
3732: * For stepm=1 the results are the same as for previous versions of Imach.
3733: * For stepm > 1 the results are less biased than in previous versions.
3734: */
1.234 brouard 3735: s1=s[mw[mi][i]][i];
3736: s2=s[mw[mi+1][i]][i];
3737: bbh=(double)bh[mi][i]/(double)stepm;
3738: /* bias bh is positive if real duration
3739: * is higher than the multiple of stepm and negative otherwise.
3740: */
3741: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3742: if( s2 > nlstate){
3743: /* i.e. if s2 is a death state and if the date of death is known
3744: then the contribution to the likelihood is the probability to
3745: die between last step unit time and current step unit time,
3746: which is also equal to probability to die before dh
3747: minus probability to die before dh-stepm .
3748: In version up to 0.92 likelihood was computed
3749: as if date of death was unknown. Death was treated as any other
3750: health state: the date of the interview describes the actual state
3751: and not the date of a change in health state. The former idea was
3752: to consider that at each interview the state was recorded
3753: (healthy, disable or death) and IMaCh was corrected; but when we
3754: introduced the exact date of death then we should have modified
3755: the contribution of an exact death to the likelihood. This new
3756: contribution is smaller and very dependent of the step unit
3757: stepm. It is no more the probability to die between last interview
3758: and month of death but the probability to survive from last
3759: interview up to one month before death multiplied by the
3760: probability to die within a month. Thanks to Chris
3761: Jackson for correcting this bug. Former versions increased
3762: mortality artificially. The bad side is that we add another loop
3763: which slows down the processing. The difference can be up to 10%
3764: lower mortality.
3765: */
3766: /* If, at the beginning of the maximization mostly, the
3767: cumulative probability or probability to be dead is
3768: constant (ie = 1) over time d, the difference is equal to
3769: 0. out[s1][3] = savm[s1][3]: probability, being at state
3770: s1 at precedent wave, to be dead a month before current
3771: wave is equal to probability, being at state s1 at
3772: precedent wave, to be dead at mont of the current
3773: wave. Then the observed probability (that this person died)
3774: is null according to current estimated parameter. In fact,
3775: it should be very low but not zero otherwise the log go to
3776: infinity.
3777: */
1.183 brouard 3778: /* #ifdef INFINITYORIGINAL */
3779: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3780: /* #else */
3781: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3782: /* lli=log(mytinydouble); */
3783: /* else */
3784: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3785: /* #endif */
1.226 brouard 3786: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3787:
1.226 brouard 3788: } else if ( s2==-1 ) { /* alive */
3789: for (j=1,survp=0. ; j<=nlstate; j++)
3790: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3791: /*survp += out[s1][j]; */
3792: lli= log(survp);
3793: }
3794: else if (s2==-4) {
3795: for (j=3,survp=0. ; j<=nlstate; j++)
3796: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3797: lli= log(survp);
3798: }
3799: else if (s2==-5) {
3800: for (j=1,survp=0. ; j<=2; j++)
3801: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3802: lli= log(survp);
3803: }
3804: else{
3805: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3806: /* 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 */
3807: }
3808: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3809: /*if(lli ==000.0)*/
3810: /*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); */
3811: ipmx +=1;
3812: sw += weight[i];
3813: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3814: /* if (lli < log(mytinydouble)){ */
3815: /* 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); */
3816: /* 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]); */
3817: /* } */
3818: } /* end of wave */
3819: } /* end of individual */
3820: } else if(mle==2){
3821: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 3822: ioffset=2+nagesqr ;
3823: for (k=1; k<=ncovf;k++)
3824: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 3825: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3826: for(k=1; k <= ncovv ; k++){
3827: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3828: }
1.226 brouard 3829: for (ii=1;ii<=nlstate+ndeath;ii++)
3830: for (j=1;j<=nlstate+ndeath;j++){
3831: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3832: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3833: }
3834: for(d=0; d<=dh[mi][i]; d++){
3835: newm=savm;
3836: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3837: cov[2]=agexact;
3838: if(nagesqr==1)
3839: cov[3]= agexact*agexact;
3840: for (kk=1; kk<=cptcovage;kk++) {
3841: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3842: }
3843: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3844: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3845: savm=oldm;
3846: oldm=newm;
3847: } /* end mult */
3848:
3849: s1=s[mw[mi][i]][i];
3850: s2=s[mw[mi+1][i]][i];
3851: bbh=(double)bh[mi][i]/(double)stepm;
3852: 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 */
3853: ipmx +=1;
3854: sw += weight[i];
3855: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3856: } /* end of wave */
3857: } /* end of individual */
3858: } else if(mle==3){ /* exponential inter-extrapolation */
3859: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3860: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3861: for(mi=1; mi<= wav[i]-1; mi++){
3862: for (ii=1;ii<=nlstate+ndeath;ii++)
3863: for (j=1;j<=nlstate+ndeath;j++){
3864: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3865: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3866: }
3867: for(d=0; d<dh[mi][i]; d++){
3868: newm=savm;
3869: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3870: cov[2]=agexact;
3871: if(nagesqr==1)
3872: cov[3]= agexact*agexact;
3873: for (kk=1; kk<=cptcovage;kk++) {
3874: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3875: }
3876: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3877: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3878: savm=oldm;
3879: oldm=newm;
3880: } /* end mult */
3881:
3882: s1=s[mw[mi][i]][i];
3883: s2=s[mw[mi+1][i]][i];
3884: bbh=(double)bh[mi][i]/(double)stepm;
3885: 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 */
3886: ipmx +=1;
3887: sw += weight[i];
3888: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3889: } /* end of wave */
3890: } /* end of individual */
3891: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3892: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3893: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3894: for(mi=1; mi<= wav[i]-1; mi++){
3895: for (ii=1;ii<=nlstate+ndeath;ii++)
3896: for (j=1;j<=nlstate+ndeath;j++){
3897: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3898: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3899: }
3900: for(d=0; d<dh[mi][i]; d++){
3901: newm=savm;
3902: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3903: cov[2]=agexact;
3904: if(nagesqr==1)
3905: cov[3]= agexact*agexact;
3906: for (kk=1; kk<=cptcovage;kk++) {
3907: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3908: }
1.126 brouard 3909:
1.226 brouard 3910: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3911: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3912: savm=oldm;
3913: oldm=newm;
3914: } /* end mult */
3915:
3916: s1=s[mw[mi][i]][i];
3917: s2=s[mw[mi+1][i]][i];
3918: if( s2 > nlstate){
3919: lli=log(out[s1][s2] - savm[s1][s2]);
3920: } else if ( s2==-1 ) { /* alive */
3921: for (j=1,survp=0. ; j<=nlstate; j++)
3922: survp += out[s1][j];
3923: lli= log(survp);
3924: }else{
3925: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3926: }
3927: ipmx +=1;
3928: sw += weight[i];
3929: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3930: /* 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 3931: } /* end of wave */
3932: } /* end of individual */
3933: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3934: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3935: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3936: for(mi=1; mi<= wav[i]-1; mi++){
3937: for (ii=1;ii<=nlstate+ndeath;ii++)
3938: for (j=1;j<=nlstate+ndeath;j++){
3939: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3940: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3941: }
3942: for(d=0; d<dh[mi][i]; d++){
3943: newm=savm;
3944: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3945: cov[2]=agexact;
3946: if(nagesqr==1)
3947: cov[3]= agexact*agexact;
3948: for (kk=1; kk<=cptcovage;kk++) {
3949: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3950: }
1.126 brouard 3951:
1.226 brouard 3952: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3953: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3954: savm=oldm;
3955: oldm=newm;
3956: } /* end mult */
3957:
3958: s1=s[mw[mi][i]][i];
3959: s2=s[mw[mi+1][i]][i];
3960: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3961: ipmx +=1;
3962: sw += weight[i];
3963: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3964: /*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]);*/
3965: } /* end of wave */
3966: } /* end of individual */
3967: } /* End of if */
3968: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3969: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3970: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3971: return -l;
1.126 brouard 3972: }
3973:
3974: /*************** log-likelihood *************/
3975: double funcone( double *x)
3976: {
1.228 brouard 3977: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3978: int i, ii, j, k, mi, d, kk;
1.228 brouard 3979: int ioffset=0;
1.131 brouard 3980: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3981: double **out;
3982: double lli; /* Individual log likelihood */
3983: double llt;
3984: int s1, s2;
1.228 brouard 3985: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3986:
1.126 brouard 3987: double bbh, survp;
1.187 brouard 3988: double agexact;
1.214 brouard 3989: double agebegin, ageend;
1.126 brouard 3990: /*extern weight */
3991: /* We are differentiating ll according to initial status */
3992: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3993: /*for(i=1;i<imx;i++)
3994: printf(" %d\n",s[4][i]);
3995: */
3996: cov[1]=1.;
3997:
3998: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3999: ioffset=0;
4000: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 4001: /* ioffset=2+nagesqr+cptcovage; */
4002: ioffset=2+nagesqr;
1.232 brouard 4003: /* Fixed */
1.224 brouard 4004: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4005: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 4006: 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 4007: 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)*/
4008: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4009: /* cov[2+6]=covar[Tvar[6]][i]; */
4010: /* cov[2+6]=covar[2][i]; V2 */
4011: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4012: /* cov[2+7]=covar[Tvar[7]][i]; */
4013: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4014: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4015: /* cov[2+9]=covar[Tvar[9]][i]; */
4016: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4017: }
1.232 brouard 4018: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4019: /* 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?)*\/ */
4020: /* } */
1.231 brouard 4021: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4022: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4023: /* } */
1.225 brouard 4024:
1.233 brouard 4025:
4026: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 4027: /* Wave varying (but not age varying) */
4028: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 4029: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
4030: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4031: }
1.232 brouard 4032: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 4033: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4034: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4035: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4036: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4037: /* 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 4038: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4039: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4040: /* /\* 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]); *\/ */
4041: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4042: /* } */
1.126 brouard 4043: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4044: for (j=1;j<=nlstate+ndeath;j++){
4045: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4046: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4047: }
1.214 brouard 4048:
4049: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4050: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4051: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4052: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4053: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4054: and mw[mi+1][i]. dh depends on stepm.*/
4055: newm=savm;
1.247 brouard 4056: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4057: cov[2]=agexact;
4058: if(nagesqr==1)
4059: cov[3]= agexact*agexact;
4060: for (kk=1; kk<=cptcovage;kk++) {
4061: if(!FixedV[Tvar[Tage[kk]]])
4062: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4063: else
4064: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
4065: }
4066: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4067: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4068: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4069: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4070: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4071: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4072: savm=oldm;
4073: oldm=newm;
1.126 brouard 4074: } /* end mult */
4075:
4076: s1=s[mw[mi][i]][i];
4077: s2=s[mw[mi+1][i]][i];
1.217 brouard 4078: /* if(s2==-1){ */
1.268 brouard 4079: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4080: /* /\* exit(1); *\/ */
4081: /* } */
1.126 brouard 4082: bbh=(double)bh[mi][i]/(double)stepm;
4083: /* bias is positive if real duration
4084: * is higher than the multiple of stepm and negative otherwise.
4085: */
4086: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4087: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4088: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4089: for (j=1,survp=0. ; j<=nlstate; j++)
4090: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4091: lli= log(survp);
1.126 brouard 4092: }else if (mle==1){
1.242 brouard 4093: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4094: } else if(mle==2){
1.242 brouard 4095: 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 4096: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4097: 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 4098: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4099: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4100: } else{ /* mle=0 back to 1 */
1.242 brouard 4101: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4102: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4103: } /* End of if */
4104: ipmx +=1;
4105: sw += weight[i];
4106: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 4107: /*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 4108: if(globpr){
1.246 brouard 4109: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4110: %11.6f %11.6f %11.6f ", \
1.242 brouard 4111: 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 4112: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 4113: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4114: llt +=ll[k]*gipmx/gsw;
4115: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
4116: }
4117: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 4118: }
1.232 brouard 4119: } /* end of wave */
4120: } /* end of individual */
4121: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4122: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4123: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4124: if(globpr==0){ /* First time we count the contributions and weights */
4125: gipmx=ipmx;
4126: gsw=sw;
4127: }
4128: return -l;
1.126 brouard 4129: }
4130:
4131:
4132: /*************** function likelione ***********/
1.292 brouard 4133: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4134: {
4135: /* This routine should help understanding what is done with
4136: the selection of individuals/waves and
4137: to check the exact contribution to the likelihood.
4138: Plotting could be done.
4139: */
4140: int k;
4141:
4142: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4143: strcpy(fileresilk,"ILK_");
1.202 brouard 4144: strcat(fileresilk,fileresu);
1.126 brouard 4145: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4146: printf("Problem with resultfile: %s\n", fileresilk);
4147: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4148: }
1.214 brouard 4149: 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");
4150: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4151: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4152: for(k=1; k<=nlstate; k++)
4153: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4154: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4155: }
4156:
1.292 brouard 4157: *fretone=(*func)(p);
1.126 brouard 4158: if(*globpri !=0){
4159: fclose(ficresilk);
1.205 brouard 4160: if (mle ==0)
4161: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4162: else if(mle >=1)
4163: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4164: 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 4165: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4166:
4167: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4168: 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 4169: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4170: }
1.207 brouard 4171: 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 4172: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4173: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4174: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4175: fflush(fichtm);
1.205 brouard 4176: }
1.126 brouard 4177: return;
4178: }
4179:
4180:
4181: /*********** Maximum Likelihood Estimation ***************/
4182:
4183: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4184: {
1.319 brouard 4185: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4186: double **xi;
4187: double fret;
4188: double fretone; /* Only one call to likelihood */
4189: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4190:
4191: #ifdef NLOPT
4192: int creturn;
4193: nlopt_opt opt;
4194: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4195: double *lb;
4196: double minf; /* the minimum objective value, upon return */
4197: double * p1; /* Shifted parameters from 0 instead of 1 */
4198: myfunc_data dinst, *d = &dinst;
4199: #endif
4200:
4201:
1.126 brouard 4202: xi=matrix(1,npar,1,npar);
4203: for (i=1;i<=npar;i++)
4204: for (j=1;j<=npar;j++)
4205: xi[i][j]=(i==j ? 1.0 : 0.0);
4206: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4207: strcpy(filerespow,"POW_");
1.126 brouard 4208: strcat(filerespow,fileres);
4209: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4210: printf("Problem with resultfile: %s\n", filerespow);
4211: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4212: }
4213: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4214: for (i=1;i<=nlstate;i++)
4215: for(j=1;j<=nlstate+ndeath;j++)
4216: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4217: fprintf(ficrespow,"\n");
1.162 brouard 4218: #ifdef POWELL
1.319 brouard 4219: #ifdef LINMINORIGINAL
4220: #else /* LINMINORIGINAL */
4221:
4222: flatdir=ivector(1,npar);
4223: for (j=1;j<=npar;j++) flatdir[j]=0;
4224: #endif /*LINMINORIGINAL */
4225:
4226: #ifdef FLATSUP
4227: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4228: /* reorganizing p by suppressing flat directions */
4229: for(i=1, jk=1; i <=nlstate; i++){
4230: for(k=1; k <=(nlstate+ndeath); k++){
4231: if (k != i) {
4232: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4233: if(flatdir[jk]==1){
4234: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4235: }
4236: for(j=1; j <=ncovmodel; j++){
4237: printf("%12.7f ",p[jk]);
4238: jk++;
4239: }
4240: printf("\n");
4241: }
4242: }
4243: }
4244: /* skipping */
4245: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4246: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4247: for(k=1; k <=(nlstate+ndeath); k++){
4248: if (k != i) {
4249: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4250: if(flatdir[jk]==1){
4251: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4252: for(j=1; j <=ncovmodel; jk++,j++){
4253: printf(" p[%d]=%12.7f",jk, p[jk]);
4254: /*q[jjk]=p[jk];*/
4255: }
4256: }else{
4257: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4258: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4259: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4260: /*q[jjk]=p[jk];*/
4261: }
4262: }
4263: printf("\n");
4264: }
4265: fflush(stdout);
4266: }
4267: }
4268: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4269: #else /* FLATSUP */
1.126 brouard 4270: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4271: #endif /* FLATSUP */
4272:
4273: #ifdef LINMINORIGINAL
4274: #else
4275: free_ivector(flatdir,1,npar);
4276: #endif /* LINMINORIGINAL*/
4277: #endif /* POWELL */
1.126 brouard 4278:
1.162 brouard 4279: #ifdef NLOPT
4280: #ifdef NEWUOA
4281: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4282: #else
4283: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4284: #endif
4285: lb=vector(0,npar-1);
4286: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4287: nlopt_set_lower_bounds(opt, lb);
4288: nlopt_set_initial_step1(opt, 0.1);
4289:
4290: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4291: d->function = func;
4292: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4293: nlopt_set_min_objective(opt, myfunc, d);
4294: nlopt_set_xtol_rel(opt, ftol);
4295: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4296: printf("nlopt failed! %d\n",creturn);
4297: }
4298: else {
4299: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4300: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4301: iter=1; /* not equal */
4302: }
4303: nlopt_destroy(opt);
4304: #endif
1.319 brouard 4305: #ifdef FLATSUP
4306: /* npared = npar -flatd/ncovmodel; */
4307: /* xired= matrix(1,npared,1,npared); */
4308: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4309: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4310: /* free_matrix(xire,1,npared,1,npared); */
4311: #else /* FLATSUP */
4312: #endif /* FLATSUP */
1.126 brouard 4313: free_matrix(xi,1,npar,1,npar);
4314: fclose(ficrespow);
1.203 brouard 4315: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4316: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4317: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4318:
4319: }
4320:
4321: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4322: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4323: {
4324: double **a,**y,*x,pd;
1.203 brouard 4325: /* double **hess; */
1.164 brouard 4326: int i, j;
1.126 brouard 4327: int *indx;
4328:
4329: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4330: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4331: void lubksb(double **a, int npar, int *indx, double b[]) ;
4332: void ludcmp(double **a, int npar, int *indx, double *d) ;
4333: double gompertz(double p[]);
1.203 brouard 4334: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4335:
4336: printf("\nCalculation of the hessian matrix. Wait...\n");
4337: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4338: for (i=1;i<=npar;i++){
1.203 brouard 4339: printf("%d-",i);fflush(stdout);
4340: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4341:
4342: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4343:
4344: /* printf(" %f ",p[i]);
4345: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4346: }
4347:
4348: for (i=1;i<=npar;i++) {
4349: for (j=1;j<=npar;j++) {
4350: if (j>i) {
1.203 brouard 4351: printf(".%d-%d",i,j);fflush(stdout);
4352: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4353: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4354:
4355: hess[j][i]=hess[i][j];
4356: /*printf(" %lf ",hess[i][j]);*/
4357: }
4358: }
4359: }
4360: printf("\n");
4361: fprintf(ficlog,"\n");
4362:
4363: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4364: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4365:
4366: a=matrix(1,npar,1,npar);
4367: y=matrix(1,npar,1,npar);
4368: x=vector(1,npar);
4369: indx=ivector(1,npar);
4370: for (i=1;i<=npar;i++)
4371: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4372: ludcmp(a,npar,indx,&pd);
4373:
4374: for (j=1;j<=npar;j++) {
4375: for (i=1;i<=npar;i++) x[i]=0;
4376: x[j]=1;
4377: lubksb(a,npar,indx,x);
4378: for (i=1;i<=npar;i++){
4379: matcov[i][j]=x[i];
4380: }
4381: }
4382:
4383: printf("\n#Hessian matrix#\n");
4384: fprintf(ficlog,"\n#Hessian matrix#\n");
4385: for (i=1;i<=npar;i++) {
4386: for (j=1;j<=npar;j++) {
1.203 brouard 4387: printf("%.6e ",hess[i][j]);
4388: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4389: }
4390: printf("\n");
4391: fprintf(ficlog,"\n");
4392: }
4393:
1.203 brouard 4394: /* printf("\n#Covariance matrix#\n"); */
4395: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4396: /* for (i=1;i<=npar;i++) { */
4397: /* for (j=1;j<=npar;j++) { */
4398: /* printf("%.6e ",matcov[i][j]); */
4399: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4400: /* } */
4401: /* printf("\n"); */
4402: /* fprintf(ficlog,"\n"); */
4403: /* } */
4404:
1.126 brouard 4405: /* Recompute Inverse */
1.203 brouard 4406: /* for (i=1;i<=npar;i++) */
4407: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4408: /* ludcmp(a,npar,indx,&pd); */
4409:
4410: /* printf("\n#Hessian matrix recomputed#\n"); */
4411:
4412: /* for (j=1;j<=npar;j++) { */
4413: /* for (i=1;i<=npar;i++) x[i]=0; */
4414: /* x[j]=1; */
4415: /* lubksb(a,npar,indx,x); */
4416: /* for (i=1;i<=npar;i++){ */
4417: /* y[i][j]=x[i]; */
4418: /* printf("%.3e ",y[i][j]); */
4419: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4420: /* } */
4421: /* printf("\n"); */
4422: /* fprintf(ficlog,"\n"); */
4423: /* } */
4424:
4425: /* Verifying the inverse matrix */
4426: #ifdef DEBUGHESS
4427: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4428:
1.203 brouard 4429: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4430: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4431:
4432: for (j=1;j<=npar;j++) {
4433: for (i=1;i<=npar;i++){
1.203 brouard 4434: printf("%.2f ",y[i][j]);
4435: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4436: }
4437: printf("\n");
4438: fprintf(ficlog,"\n");
4439: }
1.203 brouard 4440: #endif
1.126 brouard 4441:
4442: free_matrix(a,1,npar,1,npar);
4443: free_matrix(y,1,npar,1,npar);
4444: free_vector(x,1,npar);
4445: free_ivector(indx,1,npar);
1.203 brouard 4446: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4447:
4448:
4449: }
4450:
4451: /*************** hessian matrix ****************/
4452: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4453: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4454: int i;
4455: int l=1, lmax=20;
1.203 brouard 4456: double k1,k2, res, fx;
1.132 brouard 4457: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4458: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4459: int k=0,kmax=10;
4460: double l1;
4461:
4462: fx=func(x);
4463: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4464: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4465: l1=pow(10,l);
4466: delts=delt;
4467: for(k=1 ; k <kmax; k=k+1){
4468: delt = delta*(l1*k);
4469: p2[theta]=x[theta] +delt;
1.145 brouard 4470: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4471: p2[theta]=x[theta]-delt;
4472: k2=func(p2)-fx;
4473: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4474: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4475:
1.203 brouard 4476: #ifdef DEBUGHESSII
1.126 brouard 4477: 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);
4478: 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);
4479: #endif
4480: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4481: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4482: k=kmax;
4483: }
4484: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4485: k=kmax; l=lmax*10;
1.126 brouard 4486: }
4487: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4488: delts=delt;
4489: }
1.203 brouard 4490: } /* End loop k */
1.126 brouard 4491: }
4492: delti[theta]=delts;
4493: return res;
4494:
4495: }
4496:
1.203 brouard 4497: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4498: {
4499: int i;
1.164 brouard 4500: int l=1, lmax=20;
1.126 brouard 4501: double k1,k2,k3,k4,res,fx;
1.132 brouard 4502: double p2[MAXPARM+1];
1.203 brouard 4503: int k, kmax=1;
4504: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4505:
4506: int firstime=0;
1.203 brouard 4507:
1.126 brouard 4508: fx=func(x);
1.203 brouard 4509: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4510: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4511: p2[thetai]=x[thetai]+delti[thetai]*k;
4512: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4513: k1=func(p2)-fx;
4514:
1.203 brouard 4515: p2[thetai]=x[thetai]+delti[thetai]*k;
4516: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4517: k2=func(p2)-fx;
4518:
1.203 brouard 4519: p2[thetai]=x[thetai]-delti[thetai]*k;
4520: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4521: k3=func(p2)-fx;
4522:
1.203 brouard 4523: p2[thetai]=x[thetai]-delti[thetai]*k;
4524: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4525: k4=func(p2)-fx;
1.203 brouard 4526: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4527: if(k1*k2*k3*k4 <0.){
1.208 brouard 4528: firstime=1;
1.203 brouard 4529: kmax=kmax+10;
1.208 brouard 4530: }
4531: if(kmax >=10 || firstime ==1){
1.246 brouard 4532: 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);
4533: 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 4534: 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);
4535: 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);
4536: }
4537: #ifdef DEBUGHESSIJ
4538: v1=hess[thetai][thetai];
4539: v2=hess[thetaj][thetaj];
4540: cv12=res;
4541: /* Computing eigen value of Hessian matrix */
4542: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4543: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4544: if ((lc2 <0) || (lc1 <0) ){
4545: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4546: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4547: 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);
4548: 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);
4549: }
1.126 brouard 4550: #endif
4551: }
4552: return res;
4553: }
4554:
1.203 brouard 4555: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4556: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4557: /* { */
4558: /* int i; */
4559: /* int l=1, lmax=20; */
4560: /* double k1,k2,k3,k4,res,fx; */
4561: /* double p2[MAXPARM+1]; */
4562: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4563: /* int k=0,kmax=10; */
4564: /* double l1; */
4565:
4566: /* fx=func(x); */
4567: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4568: /* l1=pow(10,l); */
4569: /* delts=delt; */
4570: /* for(k=1 ; k <kmax; k=k+1){ */
4571: /* delt = delti*(l1*k); */
4572: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4573: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4574: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4575: /* k1=func(p2)-fx; */
4576:
4577: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4578: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4579: /* k2=func(p2)-fx; */
4580:
4581: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4582: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4583: /* k3=func(p2)-fx; */
4584:
4585: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4586: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4587: /* k4=func(p2)-fx; */
4588: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4589: /* #ifdef DEBUGHESSIJ */
4590: /* 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); */
4591: /* 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); */
4592: /* #endif */
4593: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4594: /* k=kmax; */
4595: /* } */
4596: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4597: /* k=kmax; l=lmax*10; */
4598: /* } */
4599: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4600: /* delts=delt; */
4601: /* } */
4602: /* } /\* End loop k *\/ */
4603: /* } */
4604: /* delti[theta]=delts; */
4605: /* return res; */
4606: /* } */
4607:
4608:
1.126 brouard 4609: /************** Inverse of matrix **************/
4610: void ludcmp(double **a, int n, int *indx, double *d)
4611: {
4612: int i,imax,j,k;
4613: double big,dum,sum,temp;
4614: double *vv;
4615:
4616: vv=vector(1,n);
4617: *d=1.0;
4618: for (i=1;i<=n;i++) {
4619: big=0.0;
4620: for (j=1;j<=n;j++)
4621: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4622: if (big == 0.0){
4623: printf(" Singular Hessian matrix at row %d:\n",i);
4624: for (j=1;j<=n;j++) {
4625: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4626: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4627: }
4628: fflush(ficlog);
4629: fclose(ficlog);
4630: nrerror("Singular matrix in routine ludcmp");
4631: }
1.126 brouard 4632: vv[i]=1.0/big;
4633: }
4634: for (j=1;j<=n;j++) {
4635: for (i=1;i<j;i++) {
4636: sum=a[i][j];
4637: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4638: a[i][j]=sum;
4639: }
4640: big=0.0;
4641: for (i=j;i<=n;i++) {
4642: sum=a[i][j];
4643: for (k=1;k<j;k++)
4644: sum -= a[i][k]*a[k][j];
4645: a[i][j]=sum;
4646: if ( (dum=vv[i]*fabs(sum)) >= big) {
4647: big=dum;
4648: imax=i;
4649: }
4650: }
4651: if (j != imax) {
4652: for (k=1;k<=n;k++) {
4653: dum=a[imax][k];
4654: a[imax][k]=a[j][k];
4655: a[j][k]=dum;
4656: }
4657: *d = -(*d);
4658: vv[imax]=vv[j];
4659: }
4660: indx[j]=imax;
4661: if (a[j][j] == 0.0) a[j][j]=TINY;
4662: if (j != n) {
4663: dum=1.0/(a[j][j]);
4664: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4665: }
4666: }
4667: free_vector(vv,1,n); /* Doesn't work */
4668: ;
4669: }
4670:
4671: void lubksb(double **a, int n, int *indx, double b[])
4672: {
4673: int i,ii=0,ip,j;
4674: double sum;
4675:
4676: for (i=1;i<=n;i++) {
4677: ip=indx[i];
4678: sum=b[ip];
4679: b[ip]=b[i];
4680: if (ii)
4681: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4682: else if (sum) ii=i;
4683: b[i]=sum;
4684: }
4685: for (i=n;i>=1;i--) {
4686: sum=b[i];
4687: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4688: b[i]=sum/a[i][i];
4689: }
4690: }
4691:
4692: void pstamp(FILE *fichier)
4693: {
1.196 brouard 4694: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4695: }
4696:
1.297 brouard 4697: void date2dmy(double date,double *day, double *month, double *year){
4698: double yp=0., yp1=0., yp2=0.;
4699:
4700: yp1=modf(date,&yp);/* extracts integral of date in yp and
4701: fractional in yp1 */
4702: *year=yp;
4703: yp2=modf((yp1*12),&yp);
4704: *month=yp;
4705: yp1=modf((yp2*30.5),&yp);
4706: *day=yp;
4707: if(*day==0) *day=1;
4708: if(*month==0) *month=1;
4709: }
4710:
1.253 brouard 4711:
4712:
1.126 brouard 4713: /************ Frequencies ********************/
1.251 brouard 4714: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4715: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4716: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4717: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4718:
1.265 brouard 4719: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4720: int iind=0, iage=0;
4721: int mi; /* Effective wave */
4722: int first;
4723: double ***freq; /* Frequencies */
1.268 brouard 4724: 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 */
4725: 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 4726: double *meanq, *stdq, *idq;
1.226 brouard 4727: double **meanqt;
4728: double *pp, **prop, *posprop, *pospropt;
4729: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4730: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4731: double agebegin, ageend;
4732:
4733: pp=vector(1,nlstate);
1.251 brouard 4734: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4735: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4736: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4737: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4738: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4739: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4740: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4741: meanqt=matrix(1,lastpass,1,nqtveff);
4742: strcpy(fileresp,"P_");
4743: strcat(fileresp,fileresu);
4744: /*strcat(fileresphtm,fileresu);*/
4745: if((ficresp=fopen(fileresp,"w"))==NULL) {
4746: printf("Problem with prevalence resultfile: %s\n", fileresp);
4747: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4748: exit(0);
4749: }
1.240 brouard 4750:
1.226 brouard 4751: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4752: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4753: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4754: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4755: fflush(ficlog);
4756: exit(70);
4757: }
4758: else{
4759: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4760: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4761: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4762: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4763: }
1.319 brouard 4764: 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 4765:
1.226 brouard 4766: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4767: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4768: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4769: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4770: fflush(ficlog);
4771: exit(70);
1.240 brouard 4772: } else{
1.226 brouard 4773: 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 4774: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4775: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4776: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4777: }
1.319 brouard 4778: 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 4779:
1.253 brouard 4780: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4781: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4782: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4783: j1=0;
1.126 brouard 4784:
1.227 brouard 4785: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4786: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4787: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4788:
4789:
1.226 brouard 4790: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4791: reference=low_education V1=0,V2=0
4792: med_educ V1=1 V2=0,
4793: high_educ V1=0 V2=1
4794: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4795: */
1.249 brouard 4796: dateintsum=0;
4797: k2cpt=0;
4798:
1.253 brouard 4799: if(cptcoveff == 0 )
1.265 brouard 4800: nl=1; /* Constant and age model only */
1.253 brouard 4801: else
4802: nl=2;
1.265 brouard 4803:
4804: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4805: /* Loop on nj=1 or 2 if dummy covariates j!=0
4806: * Loop on j1(1 to 2**cptcoveff) covariate combination
4807: * freq[s1][s2][iage] =0.
4808: * Loop on iind
4809: * ++freq[s1][s2][iage] weighted
4810: * end iind
4811: * if covariate and j!0
4812: * headers Variable on one line
4813: * endif cov j!=0
4814: * header of frequency table by age
4815: * Loop on age
4816: * pp[s1]+=freq[s1][s2][iage] weighted
4817: * pos+=freq[s1][s2][iage] weighted
4818: * Loop on s1 initial state
4819: * fprintf(ficresp
4820: * end s1
4821: * end age
4822: * if j!=0 computes starting values
4823: * end compute starting values
4824: * end j1
4825: * end nl
4826: */
1.253 brouard 4827: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4828: if(nj==1)
4829: j=0; /* First pass for the constant */
1.265 brouard 4830: else{
1.253 brouard 4831: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4832: }
1.251 brouard 4833: first=1;
1.265 brouard 4834: 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 4835: posproptt=0.;
4836: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4837: scanf("%d", i);*/
4838: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4839: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4840: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4841: freq[i][s2][m]=0;
1.251 brouard 4842:
4843: for (i=1; i<=nlstate; i++) {
1.240 brouard 4844: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4845: prop[i][m]=0;
4846: posprop[i]=0;
4847: pospropt[i]=0;
4848: }
1.283 brouard 4849: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4850: idq[z1]=0.;
4851: meanq[z1]=0.;
4852: stdq[z1]=0.;
1.283 brouard 4853: }
4854: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4855: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4856: /* meanqt[m][z1]=0.; */
4857: /* } */
4858: /* } */
1.251 brouard 4859: /* dateintsum=0; */
4860: /* k2cpt=0; */
4861:
1.265 brouard 4862: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4863: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4864: bool=1;
4865: if(j !=0){
4866: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4867: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4868: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4869: /* if(Tvaraff[z1] ==-20){ */
4870: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4871: /* }else if(Tvaraff[z1] ==-10){ */
4872: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4873: /* }else */
4874: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4875: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4876: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4877: /* 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",
4878: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4879: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4880: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4881: } /* Onlyf fixed */
4882: } /* end z1 */
4883: } /* cptcovn > 0 */
4884: } /* end any */
4885: }/* end j==0 */
1.265 brouard 4886: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4887: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4888: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4889: m=mw[mi][iind];
4890: if(j!=0){
4891: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4892: for (z1=1; z1<=cptcoveff; z1++) {
4893: if( Fixed[Tmodelind[z1]]==1){
4894: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4895: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4896: value is -1, we don't select. It differs from the
4897: constant and age model which counts them. */
4898: bool=0; /* not selected */
4899: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4900: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4901: bool=0;
4902: }
4903: }
4904: }
4905: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4906: } /* end j==0 */
4907: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4908: if(bool==1){ /*Selected */
1.251 brouard 4909: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4910: and mw[mi+1][iind]. dh depends on stepm. */
4911: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4912: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4913: if(m >=firstpass && m <=lastpass){
4914: k2=anint[m][iind]+(mint[m][iind]/12.);
4915: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4916: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4917: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4918: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4919: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4920: if (m<lastpass) {
4921: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4922: /* 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]); */
4923: if(s[m][iind]==-1)
4924: 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.));
4925: 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 4926: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
4927: if(!isnan(covar[ncovcol+z1][iind])){
4928: idq[z1]=idq[z1]+weight[iind];
4929: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4930: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
4931: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4932: }
1.284 brouard 4933: }
1.251 brouard 4934: /* if((int)agev[m][iind] == 55) */
4935: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4936: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4937: 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 4938: }
1.251 brouard 4939: } /* end if between passes */
4940: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4941: dateintsum=dateintsum+k2; /* on all covariates ?*/
4942: k2cpt++;
4943: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4944: }
1.251 brouard 4945: }else{
4946: bool=1;
4947: }/* end bool 2 */
4948: } /* end m */
1.284 brouard 4949: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4950: /* idq[z1]=idq[z1]+weight[iind]; */
4951: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4952: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4953: /* } */
1.251 brouard 4954: } /* end bool */
4955: } /* end iind = 1 to imx */
1.319 brouard 4956: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 4957: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4958:
4959:
4960: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4961: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4962: pstamp(ficresp);
1.251 brouard 4963: if (cptcoveff>0 && j!=0){
1.265 brouard 4964: pstamp(ficresp);
1.251 brouard 4965: printf( "\n#********** Variable ");
4966: fprintf(ficresp, "\n#********** Variable ");
4967: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4968: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4969: fprintf(ficlog, "\n#********** Variable ");
4970: for (z1=1; z1<=cptcoveff; z1++){
4971: if(!FixedV[Tvaraff[z1]]){
4972: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4973: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4974: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4975: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4976: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4977: }else{
1.251 brouard 4978: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4979: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4980: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4981: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4982: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4983: }
4984: }
4985: printf( "**********\n#");
4986: fprintf(ficresp, "**********\n#");
4987: fprintf(ficresphtm, "**********</h3>\n");
4988: fprintf(ficresphtmfr, "**********</h3>\n");
4989: fprintf(ficlog, "**********\n");
4990: }
1.284 brouard 4991: /*
4992: Printing means of quantitative variables if any
4993: */
4994: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 4995: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 4996: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 4997: if(weightopt==1){
4998: printf(" Weighted mean and standard deviation of");
4999: fprintf(ficlog," Weighted mean and standard deviation of");
5000: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5001: }
1.311 brouard 5002: /* mu = \frac{w x}{\sum w}
5003: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5004: */
5005: 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]));
5006: 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]));
5007: 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 5008: }
5009: /* for (z1=1; z1<= nqtveff; z1++) { */
5010: /* for(m=1;m<=lastpass;m++){ */
5011: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5012: /* } */
5013: /* } */
1.283 brouard 5014:
1.251 brouard 5015: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 5016: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
5017: fprintf(ficresp, " Age");
5018: 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 5019: for(i=1; i<=nlstate;i++) {
1.265 brouard 5020: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5021: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5022: }
1.265 brouard 5023: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5024: fprintf(ficresphtm, "\n");
5025:
5026: /* Header of frequency table by age */
5027: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5028: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5029: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5030: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5031: if(s2!=0 && m!=0)
5032: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5033: }
1.226 brouard 5034: }
1.251 brouard 5035: fprintf(ficresphtmfr, "\n");
5036:
5037: /* For each age */
5038: for(iage=iagemin; iage <= iagemax+3; iage++){
5039: fprintf(ficresphtm,"<tr>");
5040: if(iage==iagemax+1){
5041: fprintf(ficlog,"1");
5042: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5043: }else if(iage==iagemax+2){
5044: fprintf(ficlog,"0");
5045: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5046: }else if(iage==iagemax+3){
5047: fprintf(ficlog,"Total");
5048: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5049: }else{
1.240 brouard 5050: if(first==1){
1.251 brouard 5051: first=0;
5052: printf("See log file for details...\n");
5053: }
5054: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5055: fprintf(ficlog,"Age %d", iage);
5056: }
1.265 brouard 5057: for(s1=1; s1 <=nlstate ; s1++){
5058: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5059: pp[s1] += freq[s1][m][iage];
1.251 brouard 5060: }
1.265 brouard 5061: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5062: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5063: pos += freq[s1][m][iage];
5064: if(pp[s1]>=1.e-10){
1.251 brouard 5065: if(first==1){
1.265 brouard 5066: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5067: }
1.265 brouard 5068: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5069: }else{
5070: if(first==1)
1.265 brouard 5071: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5072: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5073: }
5074: }
5075:
1.265 brouard 5076: for(s1=1; s1 <=nlstate ; s1++){
5077: /* posprop[s1]=0; */
5078: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5079: pp[s1] += freq[s1][m][iage];
5080: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5081:
5082: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5083: pos += pp[s1]; /* pos is the total number of transitions until this age */
5084: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5085: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5086: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5087: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5088: }
5089:
5090: /* Writing ficresp */
5091: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5092: if( iage <= iagemax){
5093: fprintf(ficresp," %d",iage);
5094: }
5095: }else if( nj==2){
5096: if( iage <= iagemax){
5097: fprintf(ficresp," %d",iage);
5098: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
5099: }
1.240 brouard 5100: }
1.265 brouard 5101: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5102: if(pos>=1.e-5){
1.251 brouard 5103: if(first==1)
1.265 brouard 5104: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5105: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5106: }else{
5107: if(first==1)
1.265 brouard 5108: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5109: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5110: }
5111: if( iage <= iagemax){
5112: if(pos>=1.e-5){
1.265 brouard 5113: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5114: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5115: }else if( nj==2){
5116: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5117: }
5118: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5119: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5120: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5121: } else{
5122: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
5123: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5124: }
1.240 brouard 5125: }
1.265 brouard 5126: pospropt[s1] +=posprop[s1];
5127: } /* end loop s1 */
1.251 brouard 5128: /* pospropt=0.; */
1.265 brouard 5129: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5130: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5131: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5132: if(first==1){
1.265 brouard 5133: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5134: }
1.265 brouard 5135: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5136: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5137: }
1.265 brouard 5138: if(s1!=0 && m!=0)
5139: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5140: }
1.265 brouard 5141: } /* end loop s1 */
1.251 brouard 5142: posproptt=0.;
1.265 brouard 5143: for(s1=1; s1 <=nlstate; s1++){
5144: posproptt += pospropt[s1];
1.251 brouard 5145: }
5146: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5147: fprintf(ficresphtm,"</tr>\n");
5148: if((cptcoveff==0 && nj==1)|| nj==2 ) {
5149: if(iage <= iagemax)
5150: fprintf(ficresp,"\n");
1.240 brouard 5151: }
1.251 brouard 5152: if(first==1)
5153: printf("Others in log...\n");
5154: fprintf(ficlog,"\n");
5155: } /* end loop age iage */
1.265 brouard 5156:
1.251 brouard 5157: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5158: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5159: if(posproptt < 1.e-5){
1.265 brouard 5160: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5161: }else{
1.265 brouard 5162: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5163: }
1.226 brouard 5164: }
1.251 brouard 5165: fprintf(ficresphtm,"</tr>\n");
5166: fprintf(ficresphtm,"</table>\n");
5167: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5168: if(posproptt < 1.e-5){
1.251 brouard 5169: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5170: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5171: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5172: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5173: invalidvarcomb[j1]=1;
1.226 brouard 5174: }else{
1.251 brouard 5175: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
5176: invalidvarcomb[j1]=0;
1.226 brouard 5177: }
1.251 brouard 5178: fprintf(ficresphtmfr,"</table>\n");
5179: fprintf(ficlog,"\n");
5180: if(j!=0){
5181: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5182: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5183: for(k=1; k <=(nlstate+ndeath); k++){
5184: if (k != i) {
1.265 brouard 5185: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5186: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5187: if(j1==1){ /* All dummy covariates to zero */
5188: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5189: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5190: printf("%d%d ",i,k);
5191: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5192: 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]));
5193: 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]));
5194: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5195: }
1.253 brouard 5196: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5197: for(iage=iagemin; iage <= iagemax+3; iage++){
5198: x[iage]= (double)iage;
5199: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5200: /* 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 5201: }
1.268 brouard 5202: /* Some are not finite, but linreg will ignore these ages */
5203: no=0;
1.253 brouard 5204: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5205: pstart[s1]=b;
5206: pstart[s1-1]=a;
1.252 brouard 5207: }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 */
5208: 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]);
5209: 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 5210: 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 5211: printf("%d%d ",i,k);
5212: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5213: 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 5214: }else{ /* Other cases, like quantitative fixed or varying covariates */
5215: ;
5216: }
5217: /* printf("%12.7f )", param[i][jj][k]); */
5218: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5219: s1++;
1.251 brouard 5220: } /* end jj */
5221: } /* end k!= i */
5222: } /* end k */
1.265 brouard 5223: } /* end i, s1 */
1.251 brouard 5224: } /* end j !=0 */
5225: } /* end selected combination of covariate j1 */
5226: if(j==0){ /* We can estimate starting values from the occurences in each case */
5227: printf("#Freqsummary: Starting values for the constants:\n");
5228: fprintf(ficlog,"\n");
1.265 brouard 5229: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5230: for(k=1; k <=(nlstate+ndeath); k++){
5231: if (k != i) {
5232: printf("%d%d ",i,k);
5233: fprintf(ficlog,"%d%d ",i,k);
5234: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5235: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5236: if(jj==1){ /* Age has to be done */
1.265 brouard 5237: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5238: 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]));
5239: 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 5240: }
5241: /* printf("%12.7f )", param[i][jj][k]); */
5242: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5243: s1++;
1.250 brouard 5244: }
1.251 brouard 5245: printf("\n");
5246: fprintf(ficlog,"\n");
1.250 brouard 5247: }
5248: }
1.284 brouard 5249: } /* end of state i */
1.251 brouard 5250: printf("#Freqsummary\n");
5251: fprintf(ficlog,"\n");
1.265 brouard 5252: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5253: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5254: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5255: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5256: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5257: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5258: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5259: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5260: /* } */
5261: }
1.265 brouard 5262: } /* end loop s1 */
1.251 brouard 5263:
5264: printf("\n");
5265: fprintf(ficlog,"\n");
5266: } /* end j=0 */
1.249 brouard 5267: } /* end j */
1.252 brouard 5268:
1.253 brouard 5269: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5270: for(i=1, jk=1; i <=nlstate; i++){
5271: for(j=1; j <=nlstate+ndeath; j++){
5272: if(j!=i){
5273: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5274: printf("%1d%1d",i,j);
5275: fprintf(ficparo,"%1d%1d",i,j);
5276: for(k=1; k<=ncovmodel;k++){
5277: /* printf(" %lf",param[i][j][k]); */
5278: /* fprintf(ficparo," %lf",param[i][j][k]); */
5279: p[jk]=pstart[jk];
5280: printf(" %f ",pstart[jk]);
5281: fprintf(ficparo," %f ",pstart[jk]);
5282: jk++;
5283: }
5284: printf("\n");
5285: fprintf(ficparo,"\n");
5286: }
5287: }
5288: }
5289: } /* end mle=-2 */
1.226 brouard 5290: dateintmean=dateintsum/k2cpt;
1.296 brouard 5291: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5292:
1.226 brouard 5293: fclose(ficresp);
5294: fclose(ficresphtm);
5295: fclose(ficresphtmfr);
1.283 brouard 5296: free_vector(idq,1,nqfveff);
1.226 brouard 5297: free_vector(meanq,1,nqfveff);
1.284 brouard 5298: free_vector(stdq,1,nqfveff);
1.226 brouard 5299: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5300: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5301: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5302: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5303: free_vector(pospropt,1,nlstate);
5304: free_vector(posprop,1,nlstate);
1.251 brouard 5305: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5306: free_vector(pp,1,nlstate);
5307: /* End of freqsummary */
5308: }
1.126 brouard 5309:
1.268 brouard 5310: /* Simple linear regression */
5311: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5312:
5313: /* y=a+bx regression */
5314: double sumx = 0.0; /* sum of x */
5315: double sumx2 = 0.0; /* sum of x**2 */
5316: double sumxy = 0.0; /* sum of x * y */
5317: double sumy = 0.0; /* sum of y */
5318: double sumy2 = 0.0; /* sum of y**2 */
5319: double sume2 = 0.0; /* sum of square or residuals */
5320: double yhat;
5321:
5322: double denom=0;
5323: int i;
5324: int ne=*no;
5325:
5326: for ( i=ifi, ne=0;i<=ila;i++) {
5327: if(!isfinite(x[i]) || !isfinite(y[i])){
5328: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5329: continue;
5330: }
5331: ne=ne+1;
5332: sumx += x[i];
5333: sumx2 += x[i]*x[i];
5334: sumxy += x[i] * y[i];
5335: sumy += y[i];
5336: sumy2 += y[i]*y[i];
5337: denom = (ne * sumx2 - sumx*sumx);
5338: /* 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); */
5339: }
5340:
5341: denom = (ne * sumx2 - sumx*sumx);
5342: if (denom == 0) {
5343: // vertical, slope m is infinity
5344: *b = INFINITY;
5345: *a = 0;
5346: if (r) *r = 0;
5347: return 1;
5348: }
5349:
5350: *b = (ne * sumxy - sumx * sumy) / denom;
5351: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5352: if (r!=NULL) {
5353: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5354: sqrt((sumx2 - sumx*sumx/ne) *
5355: (sumy2 - sumy*sumy/ne));
5356: }
5357: *no=ne;
5358: for ( i=ifi, ne=0;i<=ila;i++) {
5359: if(!isfinite(x[i]) || !isfinite(y[i])){
5360: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5361: continue;
5362: }
5363: ne=ne+1;
5364: yhat = y[i] - *a -*b* x[i];
5365: sume2 += yhat * yhat ;
5366:
5367: denom = (ne * sumx2 - sumx*sumx);
5368: /* 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); */
5369: }
5370: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5371: *sa= *sb * sqrt(sumx2/ne);
5372:
5373: return 0;
5374: }
5375:
1.126 brouard 5376: /************ Prevalence ********************/
1.227 brouard 5377: 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)
5378: {
5379: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5380: in each health status at the date of interview (if between dateprev1 and dateprev2).
5381: We still use firstpass and lastpass as another selection.
5382: */
1.126 brouard 5383:
1.227 brouard 5384: int i, m, jk, j1, bool, z1,j, iv;
5385: int mi; /* Effective wave */
5386: int iage;
5387: double agebegin, ageend;
5388:
5389: double **prop;
5390: double posprop;
5391: double y2; /* in fractional years */
5392: int iagemin, iagemax;
5393: int first; /** to stop verbosity which is redirected to log file */
5394:
5395: iagemin= (int) agemin;
5396: iagemax= (int) agemax;
5397: /*pp=vector(1,nlstate);*/
1.251 brouard 5398: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5399: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5400: j1=0;
1.222 brouard 5401:
1.227 brouard 5402: /*j=cptcoveff;*/
5403: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5404:
1.288 brouard 5405: first=0;
1.227 brouard 5406: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5407: for (i=1; i<=nlstate; i++)
1.251 brouard 5408: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5409: prop[i][iage]=0.0;
5410: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5411: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5412: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5413:
5414: for (i=1; i<=imx; i++) { /* Each individual */
5415: bool=1;
5416: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5417: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5418: m=mw[mi][i];
5419: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5420: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5421: for (z1=1; z1<=cptcoveff; z1++){
5422: if( Fixed[Tmodelind[z1]]==1){
5423: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5424: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5425: bool=0;
5426: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5427: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5428: bool=0;
5429: }
5430: }
5431: if(bool==1){ /* Otherwise we skip that wave/person */
5432: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5433: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5434: if(m >=firstpass && m <=lastpass){
5435: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5436: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5437: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5438: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5439: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5440: 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);
5441: exit(1);
5442: }
5443: if (s[m][i]>0 && s[m][i]<=nlstate) {
5444: /*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]]);*/
5445: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5446: prop[s[m][i]][iagemax+3] += weight[i];
5447: } /* end valid statuses */
5448: } /* end selection of dates */
5449: } /* end selection of waves */
5450: } /* end bool */
5451: } /* end wave */
5452: } /* end individual */
5453: for(i=iagemin; i <= iagemax+3; i++){
5454: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5455: posprop += prop[jk][i];
5456: }
5457:
5458: for(jk=1; jk <=nlstate ; jk++){
5459: if( i <= iagemax){
5460: if(posprop>=1.e-5){
5461: probs[i][jk][j1]= prop[jk][i]/posprop;
5462: } else{
1.288 brouard 5463: if(!first){
5464: first=1;
1.266 brouard 5465: 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]);
5466: }else{
1.288 brouard 5467: 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 5468: }
5469: }
5470: }
5471: }/* end jk */
5472: }/* end i */
1.222 brouard 5473: /*} *//* end i1 */
1.227 brouard 5474: } /* end j1 */
1.222 brouard 5475:
1.227 brouard 5476: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5477: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5478: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5479: } /* End of prevalence */
1.126 brouard 5480:
5481: /************* Waves Concatenation ***************/
5482:
5483: 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)
5484: {
1.298 brouard 5485: /* 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 5486: Death is a valid wave (if date is known).
5487: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5488: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5489: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5490: */
1.126 brouard 5491:
1.224 brouard 5492: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5493: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5494: double sum=0., jmean=0.;*/
1.224 brouard 5495: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5496: int j, k=0,jk, ju, jl;
5497: double sum=0.;
5498: first=0;
1.214 brouard 5499: firstwo=0;
1.217 brouard 5500: firsthree=0;
1.218 brouard 5501: firstfour=0;
1.164 brouard 5502: jmin=100000;
1.126 brouard 5503: jmax=-1;
5504: jmean=0.;
1.224 brouard 5505:
5506: /* Treating live states */
1.214 brouard 5507: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5508: mi=0; /* First valid wave */
1.227 brouard 5509: mli=0; /* Last valid wave */
1.309 brouard 5510: m=firstpass; /* Loop on waves */
5511: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5512: 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 */
5513: mli=m-1;/* mw[++mi][i]=m-1; */
5514: }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 5515: 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 5516: mli=m;
1.224 brouard 5517: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5518: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5519: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5520: }
1.309 brouard 5521: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5522: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5523: break;
1.224 brouard 5524: #else
1.317 brouard 5525: 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 5526: if(firsthree == 0){
1.302 brouard 5527: 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 5528: firsthree=1;
1.317 brouard 5529: }else if(firsthree >=1 && firsthree < 10){
5530: 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);
5531: firsthree++;
5532: }else if(firsthree == 10){
5533: printf("Information, too many Information flags: no more reported to log either\n");
5534: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5535: firsthree++;
5536: }else{
5537: firsthree++;
1.227 brouard 5538: }
1.309 brouard 5539: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5540: mli=m;
5541: }
5542: if(s[m][i]==-2){ /* Vital status is really unknown */
5543: nbwarn++;
1.309 brouard 5544: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5545: 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);
5546: 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);
5547: }
5548: break;
5549: }
5550: break;
1.224 brouard 5551: #endif
1.227 brouard 5552: }/* End m >= lastpass */
1.126 brouard 5553: }/* end while */
1.224 brouard 5554:
1.227 brouard 5555: /* 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 5556: /* After last pass */
1.224 brouard 5557: /* Treating death states */
1.214 brouard 5558: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5559: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5560: /* } */
1.126 brouard 5561: mi++; /* Death is another wave */
5562: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5563: /* Only death is a correct wave */
1.126 brouard 5564: mw[mi][i]=m;
1.257 brouard 5565: } /* else not in a death state */
1.224 brouard 5566: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5567: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5568: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5569: 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 5570: nbwarn++;
5571: if(firstfiv==0){
1.309 brouard 5572: 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 5573: firstfiv=1;
5574: }else{
1.309 brouard 5575: 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 5576: }
1.309 brouard 5577: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5578: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5579: nberr++;
5580: if(firstwo==0){
1.309 brouard 5581: 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 5582: firstwo=1;
5583: }
1.309 brouard 5584: 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 5585: }
1.257 brouard 5586: }else{ /* if date of interview is unknown */
1.227 brouard 5587: /* death is known but not confirmed by death status at any wave */
5588: if(firstfour==0){
1.309 brouard 5589: 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 5590: firstfour=1;
5591: }
1.309 brouard 5592: 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 5593: }
1.224 brouard 5594: } /* end if date of death is known */
5595: #endif
1.309 brouard 5596: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5597: /* wav[i]=mw[mi][i]; */
1.126 brouard 5598: if(mi==0){
5599: nbwarn++;
5600: if(first==0){
1.227 brouard 5601: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5602: first=1;
1.126 brouard 5603: }
5604: if(first==1){
1.227 brouard 5605: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5606: }
5607: } /* end mi==0 */
5608: } /* End individuals */
1.214 brouard 5609: /* wav and mw are no more changed */
1.223 brouard 5610:
1.317 brouard 5611: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5612: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5613:
5614:
1.126 brouard 5615: for(i=1; i<=imx; i++){
5616: for(mi=1; mi<wav[i];mi++){
5617: if (stepm <=0)
1.227 brouard 5618: dh[mi][i]=1;
1.126 brouard 5619: else{
1.260 brouard 5620: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5621: if (agedc[i] < 2*AGESUP) {
5622: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5623: if(j==0) j=1; /* Survives at least one month after exam */
5624: else if(j<0){
5625: nberr++;
5626: 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]);
5627: j=1; /* Temporary Dangerous patch */
5628: 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);
5629: 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]);
5630: 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);
5631: }
5632: k=k+1;
5633: if (j >= jmax){
5634: jmax=j;
5635: ijmax=i;
5636: }
5637: if (j <= jmin){
5638: jmin=j;
5639: ijmin=i;
5640: }
5641: sum=sum+j;
5642: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5643: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5644: }
5645: }
5646: else{
5647: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5648: /* 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 5649:
1.227 brouard 5650: k=k+1;
5651: if (j >= jmax) {
5652: jmax=j;
5653: ijmax=i;
5654: }
5655: else if (j <= jmin){
5656: jmin=j;
5657: ijmin=i;
5658: }
5659: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5660: /*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]);*/
5661: if(j<0){
5662: nberr++;
5663: 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]);
5664: 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]);
5665: }
5666: sum=sum+j;
5667: }
5668: jk= j/stepm;
5669: jl= j -jk*stepm;
5670: ju= j -(jk+1)*stepm;
5671: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5672: if(jl==0){
5673: dh[mi][i]=jk;
5674: bh[mi][i]=0;
5675: }else{ /* We want a negative bias in order to only have interpolation ie
5676: * to avoid the price of an extra matrix product in likelihood */
5677: dh[mi][i]=jk+1;
5678: bh[mi][i]=ju;
5679: }
5680: }else{
5681: if(jl <= -ju){
5682: dh[mi][i]=jk;
5683: bh[mi][i]=jl; /* bias is positive if real duration
5684: * is higher than the multiple of stepm and negative otherwise.
5685: */
5686: }
5687: else{
5688: dh[mi][i]=jk+1;
5689: bh[mi][i]=ju;
5690: }
5691: if(dh[mi][i]==0){
5692: dh[mi][i]=1; /* At least one step */
5693: bh[mi][i]=ju; /* At least one step */
5694: /* 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);*/
5695: }
5696: } /* end if mle */
1.126 brouard 5697: }
5698: } /* end wave */
5699: }
5700: jmean=sum/k;
5701: 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 5702: 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 5703: }
1.126 brouard 5704:
5705: /*********** Tricode ****************************/
1.220 brouard 5706: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5707: {
5708: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5709: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5710: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5711: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5712: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5713: */
1.130 brouard 5714:
1.242 brouard 5715: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5716: int modmaxcovj=0; /* Modality max of covariates j */
5717: int cptcode=0; /* Modality max of covariates j */
5718: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5719:
5720:
1.242 brouard 5721: /* cptcoveff=0; */
5722: /* *cptcov=0; */
1.126 brouard 5723:
1.242 brouard 5724: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5725: for (k=1; k <= maxncov; k++)
5726: for(j=1; j<=2; j++)
5727: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5728:
1.242 brouard 5729: /* Loop on covariates without age and products and no quantitative variable */
5730: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5731: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5732: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5733: switch(Fixed[k]) {
5734: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5735: modmaxcovj=0;
5736: modmincovj=0;
1.242 brouard 5737: 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*/
5738: ij=(int)(covar[Tvar[k]][i]);
5739: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5740: * If product of Vn*Vm, still boolean *:
5741: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5742: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5743: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5744: modality of the nth covariate of individual i. */
5745: if (ij > modmaxcovj)
5746: modmaxcovj=ij;
5747: else if (ij < modmincovj)
5748: modmincovj=ij;
1.287 brouard 5749: if (ij <0 || ij >1 ){
1.311 brouard 5750: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5751: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5752: fflush(ficlog);
5753: exit(1);
1.287 brouard 5754: }
5755: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5756: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5757: exit(1);
5758: }else
5759: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5760: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5761: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5762: /* getting the maximum value of the modality of the covariate
5763: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5764: female ies 1, then modmaxcovj=1.
5765: */
5766: } /* end for loop on individuals i */
5767: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5768: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5769: cptcode=modmaxcovj;
5770: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5771: /*for (i=0; i<=cptcode; i++) {*/
5772: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5773: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5774: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5775: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5776: if( j != -1){
5777: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5778: covariate for which somebody answered excluding
5779: undefined. Usually 2: 0 and 1. */
5780: }
5781: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5782: covariate for which somebody answered including
5783: undefined. Usually 3: -1, 0 and 1. */
5784: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5785: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5786: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5787:
1.242 brouard 5788: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5789: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5790: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5791: /* modmincovj=3; modmaxcovj = 7; */
5792: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5793: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5794: /* defining two dummy variables: variables V1_1 and V1_2.*/
5795: /* nbcode[Tvar[j]][ij]=k; */
5796: /* nbcode[Tvar[j]][1]=0; */
5797: /* nbcode[Tvar[j]][2]=1; */
5798: /* nbcode[Tvar[j]][3]=2; */
5799: /* To be continued (not working yet). */
5800: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5801:
5802: /* 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*/
5803: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5804: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5805: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5806: /*, could be restored in the future */
5807: 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 5808: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5809: break;
5810: }
5811: ij++;
1.287 brouard 5812: 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 5813: cptcode = ij; /* New max modality for covar j */
5814: } /* end of loop on modality i=-1 to 1 or more */
5815: break;
5816: case 1: /* Testing on varying covariate, could be simple and
5817: * should look at waves or product of fixed *
5818: * varying. No time to test -1, assuming 0 and 1 only */
5819: ij=0;
5820: for(i=0; i<=1;i++){
5821: nbcode[Tvar[k]][++ij]=i;
5822: }
5823: break;
5824: default:
5825: break;
5826: } /* end switch */
5827: } /* end dummy test */
1.311 brouard 5828: if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5829: 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*/
5830: if(isnan(covar[Tvar[k]][i])){
5831: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5832: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5833: fflush(ficlog);
5834: exit(1);
5835: }
5836: }
5837: }
1.287 brouard 5838: } /* 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 5839:
5840: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5841: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5842: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5843: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5844: 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 */
5845: 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 */
5846: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5847: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5848:
5849: ij=0;
5850: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5851: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5852: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5853: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5854: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5855: /* If product not in single variable we don't print results */
5856: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5857: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5858: 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*/
5859: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5860: 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 */
5861: if(Fixed[k]!=0)
5862: anyvaryingduminmodel=1;
5863: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5864: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5865: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5866: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5867: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5868: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5869: }
5870: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5871: /* ij--; */
5872: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5873: *cptcov=ij; /*Number of total real effective covariates: effective
5874: * because they can be excluded from the model and real
5875: * if in the model but excluded because missing values, but how to get k from ij?*/
5876: for(j=ij+1; j<= cptcovt; j++){
5877: Tvaraff[j]=0;
5878: Tmodelind[j]=0;
5879: }
5880: for(j=ntveff+1; j<= cptcovt; j++){
5881: TmodelInvind[j]=0;
5882: }
5883: /* To be sorted */
5884: ;
5885: }
1.126 brouard 5886:
1.145 brouard 5887:
1.126 brouard 5888: /*********** Health Expectancies ****************/
5889:
1.235 brouard 5890: 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 5891:
5892: {
5893: /* Health expectancies, no variances */
1.164 brouard 5894: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5895: int nhstepma, nstepma; /* Decreasing with age */
5896: double age, agelim, hf;
5897: double ***p3mat;
5898: double eip;
5899:
1.238 brouard 5900: /* pstamp(ficreseij); */
1.126 brouard 5901: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5902: fprintf(ficreseij,"# Age");
5903: for(i=1; i<=nlstate;i++){
5904: for(j=1; j<=nlstate;j++){
5905: fprintf(ficreseij," e%1d%1d ",i,j);
5906: }
5907: fprintf(ficreseij," e%1d. ",i);
5908: }
5909: fprintf(ficreseij,"\n");
5910:
5911:
5912: if(estepm < stepm){
5913: printf ("Problem %d lower than %d\n",estepm, stepm);
5914: }
5915: else hstepm=estepm;
5916: /* We compute the life expectancy from trapezoids spaced every estepm months
5917: * This is mainly to measure the difference between two models: for example
5918: * if stepm=24 months pijx are given only every 2 years and by summing them
5919: * we are calculating an estimate of the Life Expectancy assuming a linear
5920: * progression in between and thus overestimating or underestimating according
5921: * to the curvature of the survival function. If, for the same date, we
5922: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5923: * to compare the new estimate of Life expectancy with the same linear
5924: * hypothesis. A more precise result, taking into account a more precise
5925: * curvature will be obtained if estepm is as small as stepm. */
5926:
5927: /* For example we decided to compute the life expectancy with the smallest unit */
5928: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5929: nhstepm is the number of hstepm from age to agelim
5930: nstepm is the number of stepm from age to agelin.
1.270 brouard 5931: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5932: and note for a fixed period like estepm months */
5933: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5934: survival function given by stepm (the optimization length). Unfortunately it
5935: means that if the survival funtion is printed only each two years of age and if
5936: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5937: results. So we changed our mind and took the option of the best precision.
5938: */
5939: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5940:
5941: agelim=AGESUP;
5942: /* If stepm=6 months */
5943: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5944: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5945:
5946: /* nhstepm age range expressed in number of stepm */
5947: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5948: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5949: /* if (stepm >= YEARM) hstepm=1;*/
5950: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5951: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5952:
5953: for (age=bage; age<=fage; age ++){
5954: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5955: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5956: /* if (stepm >= YEARM) hstepm=1;*/
5957: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5958:
5959: /* If stepm=6 months */
5960: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5961: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5962:
1.235 brouard 5963: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5964:
5965: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5966:
5967: printf("%d|",(int)age);fflush(stdout);
5968: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5969:
5970: /* Computing expectancies */
5971: for(i=1; i<=nlstate;i++)
5972: for(j=1; j<=nlstate;j++)
5973: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5974: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5975:
5976: /* 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]);*/
5977:
5978: }
5979:
5980: fprintf(ficreseij,"%3.0f",age );
5981: for(i=1; i<=nlstate;i++){
5982: eip=0;
5983: for(j=1; j<=nlstate;j++){
5984: eip +=eij[i][j][(int)age];
5985: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5986: }
5987: fprintf(ficreseij,"%9.4f", eip );
5988: }
5989: fprintf(ficreseij,"\n");
5990:
5991: }
5992: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5993: printf("\n");
5994: fprintf(ficlog,"\n");
5995:
5996: }
5997:
1.235 brouard 5998: 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 5999:
6000: {
6001: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6002: to initial status i, ei. .
1.126 brouard 6003: */
6004: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6005: int nhstepma, nstepma; /* Decreasing with age */
6006: double age, agelim, hf;
6007: double ***p3matp, ***p3matm, ***varhe;
6008: double **dnewm,**doldm;
6009: double *xp, *xm;
6010: double **gp, **gm;
6011: double ***gradg, ***trgradg;
6012: int theta;
6013:
6014: double eip, vip;
6015:
6016: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6017: xp=vector(1,npar);
6018: xm=vector(1,npar);
6019: dnewm=matrix(1,nlstate*nlstate,1,npar);
6020: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6021:
6022: pstamp(ficresstdeij);
6023: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6024: fprintf(ficresstdeij,"# Age");
6025: for(i=1; i<=nlstate;i++){
6026: for(j=1; j<=nlstate;j++)
6027: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6028: fprintf(ficresstdeij," e%1d. ",i);
6029: }
6030: fprintf(ficresstdeij,"\n");
6031:
6032: pstamp(ficrescveij);
6033: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6034: fprintf(ficrescveij,"# Age");
6035: for(i=1; i<=nlstate;i++)
6036: for(j=1; j<=nlstate;j++){
6037: cptj= (j-1)*nlstate+i;
6038: for(i2=1; i2<=nlstate;i2++)
6039: for(j2=1; j2<=nlstate;j2++){
6040: cptj2= (j2-1)*nlstate+i2;
6041: if(cptj2 <= cptj)
6042: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6043: }
6044: }
6045: fprintf(ficrescveij,"\n");
6046:
6047: if(estepm < stepm){
6048: printf ("Problem %d lower than %d\n",estepm, stepm);
6049: }
6050: else hstepm=estepm;
6051: /* We compute the life expectancy from trapezoids spaced every estepm months
6052: * This is mainly to measure the difference between two models: for example
6053: * if stepm=24 months pijx are given only every 2 years and by summing them
6054: * we are calculating an estimate of the Life Expectancy assuming a linear
6055: * progression in between and thus overestimating or underestimating according
6056: * to the curvature of the survival function. If, for the same date, we
6057: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6058: * to compare the new estimate of Life expectancy with the same linear
6059: * hypothesis. A more precise result, taking into account a more precise
6060: * curvature will be obtained if estepm is as small as stepm. */
6061:
6062: /* For example we decided to compute the life expectancy with the smallest unit */
6063: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6064: nhstepm is the number of hstepm from age to agelim
6065: nstepm is the number of stepm from age to agelin.
6066: Look at hpijx to understand the reason of that which relies in memory size
6067: and note for a fixed period like estepm months */
6068: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6069: survival function given by stepm (the optimization length). Unfortunately it
6070: means that if the survival funtion is printed only each two years of age and if
6071: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6072: results. So we changed our mind and took the option of the best precision.
6073: */
6074: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6075:
6076: /* If stepm=6 months */
6077: /* nhstepm age range expressed in number of stepm */
6078: agelim=AGESUP;
6079: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6080: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6081: /* if (stepm >= YEARM) hstepm=1;*/
6082: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6083:
6084: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6085: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6086: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6087: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6088: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6089: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6090:
6091: for (age=bage; age<=fage; age ++){
6092: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6093: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6094: /* if (stepm >= YEARM) hstepm=1;*/
6095: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6096:
1.126 brouard 6097: /* If stepm=6 months */
6098: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6099: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6100:
6101: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6102:
1.126 brouard 6103: /* Computing Variances of health expectancies */
6104: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6105: decrease memory allocation */
6106: for(theta=1; theta <=npar; theta++){
6107: for(i=1; i<=npar; i++){
1.222 brouard 6108: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6109: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6110: }
1.235 brouard 6111: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6112: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6113:
1.126 brouard 6114: for(j=1; j<= nlstate; j++){
1.222 brouard 6115: for(i=1; i<=nlstate; i++){
6116: for(h=0; h<=nhstepm-1; h++){
6117: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6118: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6119: }
6120: }
1.126 brouard 6121: }
1.218 brouard 6122:
1.126 brouard 6123: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6124: for(h=0; h<=nhstepm-1; h++){
6125: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6126: }
1.126 brouard 6127: }/* End theta */
6128:
6129:
6130: for(h=0; h<=nhstepm-1; h++)
6131: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6132: for(theta=1; theta <=npar; theta++)
6133: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6134:
1.218 brouard 6135:
1.222 brouard 6136: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6137: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6138: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6139:
1.222 brouard 6140: printf("%d|",(int)age);fflush(stdout);
6141: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6142: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6143: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6144: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6145: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6146: for(ij=1;ij<=nlstate*nlstate;ij++)
6147: for(ji=1;ji<=nlstate*nlstate;ji++)
6148: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6149: }
6150: }
1.320 brouard 6151: /* if((int)age ==50){ */
6152: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6153: /* } */
1.126 brouard 6154: /* Computing expectancies */
1.235 brouard 6155: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6156: for(i=1; i<=nlstate;i++)
6157: for(j=1; j<=nlstate;j++)
1.222 brouard 6158: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6159: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6160:
1.222 brouard 6161: /* 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 6162:
1.222 brouard 6163: }
1.269 brouard 6164:
6165: /* Standard deviation of expectancies ij */
1.126 brouard 6166: fprintf(ficresstdeij,"%3.0f",age );
6167: for(i=1; i<=nlstate;i++){
6168: eip=0.;
6169: vip=0.;
6170: for(j=1; j<=nlstate;j++){
1.222 brouard 6171: eip += eij[i][j][(int)age];
6172: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6173: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6174: 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 6175: }
6176: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6177: }
6178: fprintf(ficresstdeij,"\n");
1.218 brouard 6179:
1.269 brouard 6180: /* Variance of expectancies ij */
1.126 brouard 6181: fprintf(ficrescveij,"%3.0f",age );
6182: for(i=1; i<=nlstate;i++)
6183: for(j=1; j<=nlstate;j++){
1.222 brouard 6184: cptj= (j-1)*nlstate+i;
6185: for(i2=1; i2<=nlstate;i2++)
6186: for(j2=1; j2<=nlstate;j2++){
6187: cptj2= (j2-1)*nlstate+i2;
6188: if(cptj2 <= cptj)
6189: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6190: }
1.126 brouard 6191: }
6192: fprintf(ficrescveij,"\n");
1.218 brouard 6193:
1.126 brouard 6194: }
6195: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6196: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6197: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6198: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6199: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6200: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6201: printf("\n");
6202: fprintf(ficlog,"\n");
1.218 brouard 6203:
1.126 brouard 6204: free_vector(xm,1,npar);
6205: free_vector(xp,1,npar);
6206: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6207: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6208: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6209: }
1.218 brouard 6210:
1.126 brouard 6211: /************ Variance ******************/
1.235 brouard 6212: 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 6213: {
1.279 brouard 6214: /** Variance of health expectancies
6215: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6216: * double **newm;
6217: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6218: */
1.218 brouard 6219:
6220: /* int movingaverage(); */
6221: double **dnewm,**doldm;
6222: double **dnewmp,**doldmp;
6223: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6224: int first=0;
1.218 brouard 6225: int k;
6226: double *xp;
1.279 brouard 6227: double **gp, **gm; /**< for var eij */
6228: double ***gradg, ***trgradg; /**< for var eij */
6229: double **gradgp, **trgradgp; /**< for var p point j */
6230: double *gpp, *gmp; /**< for var p point j */
6231: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6232: double ***p3mat;
6233: double age,agelim, hf;
6234: /* double ***mobaverage; */
6235: int theta;
6236: char digit[4];
6237: char digitp[25];
6238:
6239: char fileresprobmorprev[FILENAMELENGTH];
6240:
6241: if(popbased==1){
6242: if(mobilav!=0)
6243: strcpy(digitp,"-POPULBASED-MOBILAV_");
6244: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6245: }
6246: else
6247: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6248:
1.218 brouard 6249: /* if (mobilav!=0) { */
6250: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6251: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6252: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6253: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6254: /* } */
6255: /* } */
6256:
6257: strcpy(fileresprobmorprev,"PRMORPREV-");
6258: sprintf(digit,"%-d",ij);
6259: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6260: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6261: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6262: strcat(fileresprobmorprev,fileresu);
6263: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6264: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6265: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6266: }
6267: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6268: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6269: pstamp(ficresprobmorprev);
6270: 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 6271: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
6272: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
6273: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
6274: }
6275: for(j=1;j<=cptcoveff;j++)
6276: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
6277: fprintf(ficresprobmorprev,"\n");
6278:
1.218 brouard 6279: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6280: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6281: fprintf(ficresprobmorprev," p.%-d SE",j);
6282: for(i=1; i<=nlstate;i++)
6283: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6284: }
6285: fprintf(ficresprobmorprev,"\n");
6286:
6287: fprintf(ficgp,"\n# Routine varevsij");
6288: fprintf(ficgp,"\nunset title \n");
6289: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6290: 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");
6291: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6292:
1.218 brouard 6293: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6294: pstamp(ficresvij);
6295: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6296: if(popbased==1)
6297: 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);
6298: else
6299: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6300: fprintf(ficresvij,"# Age");
6301: for(i=1; i<=nlstate;i++)
6302: for(j=1; j<=nlstate;j++)
6303: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6304: fprintf(ficresvij,"\n");
6305:
6306: xp=vector(1,npar);
6307: dnewm=matrix(1,nlstate,1,npar);
6308: doldm=matrix(1,nlstate,1,nlstate);
6309: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6310: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6311:
6312: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6313: gpp=vector(nlstate+1,nlstate+ndeath);
6314: gmp=vector(nlstate+1,nlstate+ndeath);
6315: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6316:
1.218 brouard 6317: if(estepm < stepm){
6318: printf ("Problem %d lower than %d\n",estepm, stepm);
6319: }
6320: else hstepm=estepm;
6321: /* For example we decided to compute the life expectancy with the smallest unit */
6322: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6323: nhstepm is the number of hstepm from age to agelim
6324: nstepm is the number of stepm from age to agelim.
6325: Look at function hpijx to understand why because of memory size limitations,
6326: we decided (b) to get a life expectancy respecting the most precise curvature of the
6327: survival function given by stepm (the optimization length). Unfortunately it
6328: means that if the survival funtion is printed every two years of age and if
6329: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6330: results. So we changed our mind and took the option of the best precision.
6331: */
6332: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6333: agelim = AGESUP;
6334: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6335: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6336: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6337: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6338: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6339: gp=matrix(0,nhstepm,1,nlstate);
6340: gm=matrix(0,nhstepm,1,nlstate);
6341:
6342:
6343: for(theta=1; theta <=npar; theta++){
6344: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6345: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6346: }
1.279 brouard 6347: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6348: * returns into prlim .
1.288 brouard 6349: */
1.242 brouard 6350: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6351:
6352: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6353: if (popbased==1) {
6354: if(mobilav ==0){
6355: for(i=1; i<=nlstate;i++)
6356: prlim[i][i]=probs[(int)age][i][ij];
6357: }else{ /* mobilav */
6358: for(i=1; i<=nlstate;i++)
6359: prlim[i][i]=mobaverage[(int)age][i][ij];
6360: }
6361: }
1.295 brouard 6362: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6363: */
6364: 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 6365: /**< 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 6366: * at horizon h in state j including mortality.
6367: */
1.218 brouard 6368: for(j=1; j<= nlstate; j++){
6369: for(h=0; h<=nhstepm; h++){
6370: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6371: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6372: }
6373: }
1.279 brouard 6374: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6375: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6376: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6377: */
6378: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6379: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6380: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6381: }
6382:
6383: /* Again with minus shift */
1.218 brouard 6384:
6385: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6386: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6387:
1.242 brouard 6388: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6389:
6390: if (popbased==1) {
6391: if(mobilav ==0){
6392: for(i=1; i<=nlstate;i++)
6393: prlim[i][i]=probs[(int)age][i][ij];
6394: }else{ /* mobilav */
6395: for(i=1; i<=nlstate;i++)
6396: prlim[i][i]=mobaverage[(int)age][i][ij];
6397: }
6398: }
6399:
1.235 brouard 6400: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6401:
6402: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6403: for(h=0; h<=nhstepm; h++){
6404: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6405: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6406: }
6407: }
6408: /* This for computing probability of death (h=1 means
6409: computed over hstepm matrices product = hstepm*stepm months)
6410: as a weighted average of prlim.
6411: */
6412: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6413: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6414: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6415: }
1.279 brouard 6416: /* end shifting computations */
6417:
6418: /**< Computing gradient matrix at horizon h
6419: */
1.218 brouard 6420: for(j=1; j<= nlstate; j++) /* vareij */
6421: for(h=0; h<=nhstepm; h++){
6422: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6423: }
1.279 brouard 6424: /**< Gradient of overall mortality p.3 (or p.j)
6425: */
6426: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6427: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6428: }
6429:
6430: } /* End theta */
1.279 brouard 6431:
6432: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6433: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6434:
6435: for(h=0; h<=nhstepm; h++) /* veij */
6436: for(j=1; j<=nlstate;j++)
6437: for(theta=1; theta <=npar; theta++)
6438: trgradg[h][j][theta]=gradg[h][theta][j];
6439:
6440: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6441: for(theta=1; theta <=npar; theta++)
6442: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6443: /**< as well as its transposed matrix
6444: */
1.218 brouard 6445:
6446: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6447: for(i=1;i<=nlstate;i++)
6448: for(j=1;j<=nlstate;j++)
6449: vareij[i][j][(int)age] =0.;
1.279 brouard 6450:
6451: /* Computing trgradg by matcov by gradg at age and summing over h
6452: * and k (nhstepm) formula 15 of article
6453: * Lievre-Brouard-Heathcote
6454: */
6455:
1.218 brouard 6456: for(h=0;h<=nhstepm;h++){
6457: for(k=0;k<=nhstepm;k++){
6458: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6459: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6460: for(i=1;i<=nlstate;i++)
6461: for(j=1;j<=nlstate;j++)
6462: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6463: }
6464: }
6465:
1.279 brouard 6466: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6467: * p.j overall mortality formula 49 but computed directly because
6468: * we compute the grad (wix pijx) instead of grad (pijx),even if
6469: * wix is independent of theta.
6470: */
1.218 brouard 6471: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6472: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6473: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6474: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6475: varppt[j][i]=doldmp[j][i];
6476: /* end ppptj */
6477: /* x centered again */
6478:
1.242 brouard 6479: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6480:
6481: if (popbased==1) {
6482: if(mobilav ==0){
6483: for(i=1; i<=nlstate;i++)
6484: prlim[i][i]=probs[(int)age][i][ij];
6485: }else{ /* mobilav */
6486: for(i=1; i<=nlstate;i++)
6487: prlim[i][i]=mobaverage[(int)age][i][ij];
6488: }
6489: }
6490:
6491: /* This for computing probability of death (h=1 means
6492: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6493: as a weighted average of prlim.
6494: */
1.235 brouard 6495: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6496: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6497: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6498: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6499: }
6500: /* end probability of death */
6501:
6502: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6503: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6504: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6505: for(i=1; i<=nlstate;i++){
6506: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6507: }
6508: }
6509: fprintf(ficresprobmorprev,"\n");
6510:
6511: fprintf(ficresvij,"%.0f ",age );
6512: for(i=1; i<=nlstate;i++)
6513: for(j=1; j<=nlstate;j++){
6514: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6515: }
6516: fprintf(ficresvij,"\n");
6517: free_matrix(gp,0,nhstepm,1,nlstate);
6518: free_matrix(gm,0,nhstepm,1,nlstate);
6519: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6520: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6521: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6522: } /* End age */
6523: free_vector(gpp,nlstate+1,nlstate+ndeath);
6524: free_vector(gmp,nlstate+1,nlstate+ndeath);
6525: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6526: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6527: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6528: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6529: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6530: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6531: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6532: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6533: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6534: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6535: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6536: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6537: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6538: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6539: 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);
6540: /* 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 6541: */
1.218 brouard 6542: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6543: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6544:
1.218 brouard 6545: free_vector(xp,1,npar);
6546: free_matrix(doldm,1,nlstate,1,nlstate);
6547: free_matrix(dnewm,1,nlstate,1,npar);
6548: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6549: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6550: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6551: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6552: fclose(ficresprobmorprev);
6553: fflush(ficgp);
6554: fflush(fichtm);
6555: } /* end varevsij */
1.126 brouard 6556:
6557: /************ Variance of prevlim ******************/
1.269 brouard 6558: 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 6559: {
1.205 brouard 6560: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6561: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6562:
1.268 brouard 6563: double **dnewmpar,**doldm;
1.126 brouard 6564: int i, j, nhstepm, hstepm;
6565: double *xp;
6566: double *gp, *gm;
6567: double **gradg, **trgradg;
1.208 brouard 6568: double **mgm, **mgp;
1.126 brouard 6569: double age,agelim;
6570: int theta;
6571:
6572: pstamp(ficresvpl);
1.288 brouard 6573: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6574: fprintf(ficresvpl,"# Age ");
6575: if(nresult >=1)
6576: fprintf(ficresvpl," Result# ");
1.126 brouard 6577: for(i=1; i<=nlstate;i++)
6578: fprintf(ficresvpl," %1d-%1d",i,i);
6579: fprintf(ficresvpl,"\n");
6580:
6581: xp=vector(1,npar);
1.268 brouard 6582: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6583: doldm=matrix(1,nlstate,1,nlstate);
6584:
6585: hstepm=1*YEARM; /* Every year of age */
6586: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6587: agelim = AGESUP;
6588: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6589: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6590: if (stepm >= YEARM) hstepm=1;
6591: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6592: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6593: mgp=matrix(1,npar,1,nlstate);
6594: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6595: gp=vector(1,nlstate);
6596: gm=vector(1,nlstate);
6597:
6598: for(theta=1; theta <=npar; theta++){
6599: for(i=1; i<=npar; i++){ /* Computes gradient */
6600: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6601: }
1.288 brouard 6602: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6603: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6604: /* else */
6605: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6606: for(i=1;i<=nlstate;i++){
1.126 brouard 6607: gp[i] = prlim[i][i];
1.208 brouard 6608: mgp[theta][i] = prlim[i][i];
6609: }
1.126 brouard 6610: for(i=1; i<=npar; i++) /* Computes gradient */
6611: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6612: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6613: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6614: /* else */
6615: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6616: for(i=1;i<=nlstate;i++){
1.126 brouard 6617: gm[i] = prlim[i][i];
1.208 brouard 6618: mgm[theta][i] = prlim[i][i];
6619: }
1.126 brouard 6620: for(i=1;i<=nlstate;i++)
6621: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6622: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6623: } /* End theta */
6624:
6625: trgradg =matrix(1,nlstate,1,npar);
6626:
6627: for(j=1; j<=nlstate;j++)
6628: for(theta=1; theta <=npar; theta++)
6629: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6630: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6631: /* printf("\nmgm mgp %d ",(int)age); */
6632: /* for(j=1; j<=nlstate;j++){ */
6633: /* printf(" %d ",j); */
6634: /* for(theta=1; theta <=npar; theta++) */
6635: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6636: /* printf("\n "); */
6637: /* } */
6638: /* } */
6639: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6640: /* printf("\n gradg %d ",(int)age); */
6641: /* for(j=1; j<=nlstate;j++){ */
6642: /* printf("%d ",j); */
6643: /* for(theta=1; theta <=npar; theta++) */
6644: /* printf("%d %lf ",theta,gradg[theta][j]); */
6645: /* printf("\n "); */
6646: /* } */
6647: /* } */
1.126 brouard 6648:
6649: for(i=1;i<=nlstate;i++)
6650: varpl[i][(int)age] =0.;
1.209 brouard 6651: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6652: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6653: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6654: }else{
1.268 brouard 6655: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6656: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6657: }
1.126 brouard 6658: for(i=1;i<=nlstate;i++)
6659: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6660:
6661: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6662: if(nresult >=1)
6663: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6664: for(i=1; i<=nlstate;i++){
1.126 brouard 6665: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6666: /* for(j=1;j<=nlstate;j++) */
6667: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6668: }
1.126 brouard 6669: fprintf(ficresvpl,"\n");
6670: free_vector(gp,1,nlstate);
6671: free_vector(gm,1,nlstate);
1.208 brouard 6672: free_matrix(mgm,1,npar,1,nlstate);
6673: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6674: free_matrix(gradg,1,npar,1,nlstate);
6675: free_matrix(trgradg,1,nlstate,1,npar);
6676: } /* End age */
6677:
6678: free_vector(xp,1,npar);
6679: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6680: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6681:
6682: }
6683:
6684:
6685: /************ Variance of backprevalence limit ******************/
1.269 brouard 6686: 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 6687: {
6688: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6689: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6690:
6691: double **dnewmpar,**doldm;
6692: int i, j, nhstepm, hstepm;
6693: double *xp;
6694: double *gp, *gm;
6695: double **gradg, **trgradg;
6696: double **mgm, **mgp;
6697: double age,agelim;
6698: int theta;
6699:
6700: pstamp(ficresvbl);
6701: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6702: fprintf(ficresvbl,"# Age ");
6703: if(nresult >=1)
6704: fprintf(ficresvbl," Result# ");
6705: for(i=1; i<=nlstate;i++)
6706: fprintf(ficresvbl," %1d-%1d",i,i);
6707: fprintf(ficresvbl,"\n");
6708:
6709: xp=vector(1,npar);
6710: dnewmpar=matrix(1,nlstate,1,npar);
6711: doldm=matrix(1,nlstate,1,nlstate);
6712:
6713: hstepm=1*YEARM; /* Every year of age */
6714: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6715: agelim = AGEINF;
6716: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6717: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6718: if (stepm >= YEARM) hstepm=1;
6719: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6720: gradg=matrix(1,npar,1,nlstate);
6721: mgp=matrix(1,npar,1,nlstate);
6722: mgm=matrix(1,npar,1,nlstate);
6723: gp=vector(1,nlstate);
6724: gm=vector(1,nlstate);
6725:
6726: for(theta=1; theta <=npar; theta++){
6727: for(i=1; i<=npar; i++){ /* Computes gradient */
6728: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6729: }
6730: if(mobilavproj > 0 )
6731: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6732: else
6733: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6734: for(i=1;i<=nlstate;i++){
6735: gp[i] = bprlim[i][i];
6736: mgp[theta][i] = bprlim[i][i];
6737: }
6738: for(i=1; i<=npar; i++) /* Computes gradient */
6739: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6740: if(mobilavproj > 0 )
6741: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6742: else
6743: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6744: for(i=1;i<=nlstate;i++){
6745: gm[i] = bprlim[i][i];
6746: mgm[theta][i] = bprlim[i][i];
6747: }
6748: for(i=1;i<=nlstate;i++)
6749: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6750: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6751: } /* End theta */
6752:
6753: trgradg =matrix(1,nlstate,1,npar);
6754:
6755: for(j=1; j<=nlstate;j++)
6756: for(theta=1; theta <=npar; theta++)
6757: trgradg[j][theta]=gradg[theta][j];
6758: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6759: /* printf("\nmgm mgp %d ",(int)age); */
6760: /* for(j=1; j<=nlstate;j++){ */
6761: /* printf(" %d ",j); */
6762: /* for(theta=1; theta <=npar; theta++) */
6763: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6764: /* printf("\n "); */
6765: /* } */
6766: /* } */
6767: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6768: /* printf("\n gradg %d ",(int)age); */
6769: /* for(j=1; j<=nlstate;j++){ */
6770: /* printf("%d ",j); */
6771: /* for(theta=1; theta <=npar; theta++) */
6772: /* printf("%d %lf ",theta,gradg[theta][j]); */
6773: /* printf("\n "); */
6774: /* } */
6775: /* } */
6776:
6777: for(i=1;i<=nlstate;i++)
6778: varbpl[i][(int)age] =0.;
6779: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6780: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6781: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6782: }else{
6783: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6784: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6785: }
6786: for(i=1;i<=nlstate;i++)
6787: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6788:
6789: fprintf(ficresvbl,"%.0f ",age );
6790: if(nresult >=1)
6791: fprintf(ficresvbl,"%d ",nres );
6792: for(i=1; i<=nlstate;i++)
6793: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6794: fprintf(ficresvbl,"\n");
6795: free_vector(gp,1,nlstate);
6796: free_vector(gm,1,nlstate);
6797: free_matrix(mgm,1,npar,1,nlstate);
6798: free_matrix(mgp,1,npar,1,nlstate);
6799: free_matrix(gradg,1,npar,1,nlstate);
6800: free_matrix(trgradg,1,nlstate,1,npar);
6801: } /* End age */
6802:
6803: free_vector(xp,1,npar);
6804: free_matrix(doldm,1,nlstate,1,npar);
6805: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6806:
6807: }
6808:
6809: /************ Variance of one-step probabilities ******************/
6810: 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 6811: {
6812: int i, j=0, k1, l1, tj;
6813: int k2, l2, j1, z1;
6814: int k=0, l;
6815: int first=1, first1, first2;
6816: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6817: double **dnewm,**doldm;
6818: double *xp;
6819: double *gp, *gm;
6820: double **gradg, **trgradg;
6821: double **mu;
6822: double age, cov[NCOVMAX+1];
6823: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6824: int theta;
6825: char fileresprob[FILENAMELENGTH];
6826: char fileresprobcov[FILENAMELENGTH];
6827: char fileresprobcor[FILENAMELENGTH];
6828: double ***varpij;
6829:
6830: strcpy(fileresprob,"PROB_");
6831: strcat(fileresprob,fileres);
6832: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6833: printf("Problem with resultfile: %s\n", fileresprob);
6834: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6835: }
6836: strcpy(fileresprobcov,"PROBCOV_");
6837: strcat(fileresprobcov,fileresu);
6838: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6839: printf("Problem with resultfile: %s\n", fileresprobcov);
6840: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6841: }
6842: strcpy(fileresprobcor,"PROBCOR_");
6843: strcat(fileresprobcor,fileresu);
6844: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6845: printf("Problem with resultfile: %s\n", fileresprobcor);
6846: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6847: }
6848: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6849: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6850: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6851: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6852: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6853: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6854: pstamp(ficresprob);
6855: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6856: fprintf(ficresprob,"# Age");
6857: pstamp(ficresprobcov);
6858: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6859: fprintf(ficresprobcov,"# Age");
6860: pstamp(ficresprobcor);
6861: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6862: fprintf(ficresprobcor,"# Age");
1.126 brouard 6863:
6864:
1.222 brouard 6865: for(i=1; i<=nlstate;i++)
6866: for(j=1; j<=(nlstate+ndeath);j++){
6867: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6868: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6869: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6870: }
6871: /* fprintf(ficresprob,"\n");
6872: fprintf(ficresprobcov,"\n");
6873: fprintf(ficresprobcor,"\n");
6874: */
6875: xp=vector(1,npar);
6876: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6877: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6878: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6879: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6880: first=1;
6881: fprintf(ficgp,"\n# Routine varprob");
6882: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6883: fprintf(fichtm,"\n");
6884:
1.288 brouard 6885: 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 6886: 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);
6887: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6888: and drawn. It helps understanding how is the covariance between two incidences.\
6889: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6890: 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 6891: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6892: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6893: standard deviations wide on each axis. <br>\
6894: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6895: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6896: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6897:
1.222 brouard 6898: cov[1]=1;
6899: /* tj=cptcoveff; */
1.225 brouard 6900: tj = (int) pow(2,cptcoveff);
1.222 brouard 6901: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6902: j1=0;
1.224 brouard 6903: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6904: if (cptcovn>0) {
6905: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6906: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6907: fprintf(ficresprob, "**********\n#\n");
6908: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6909: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6910: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6911:
1.222 brouard 6912: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6913: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6914: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6915:
6916:
1.222 brouard 6917: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.319 brouard 6918: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); */
6919: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtmcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6920: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6921:
1.222 brouard 6922: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6923: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6924: fprintf(ficresprobcor, "**********\n#");
6925: if(invalidvarcomb[j1]){
6926: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6927: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6928: continue;
6929: }
6930: }
6931: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6932: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6933: gp=vector(1,(nlstate)*(nlstate+ndeath));
6934: gm=vector(1,(nlstate)*(nlstate+ndeath));
6935: for (age=bage; age<=fage; age ++){
6936: cov[2]=age;
6937: if(nagesqr==1)
6938: cov[3]= age*age;
6939: for (k=1; k<=cptcovn;k++) {
6940: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6941: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6942: * 1 1 1 1 1
6943: * 2 2 1 1 1
6944: * 3 1 2 1 1
6945: */
6946: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6947: }
1.319 brouard 6948: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
6949: /* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] */
6950: /*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6951: for (k=1; k<=cptcovage;k++)
6952: cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.222 brouard 6953: for (k=1; k<=cptcovprod;k++)
6954: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6955:
6956:
1.222 brouard 6957: for(theta=1; theta <=npar; theta++){
6958: for(i=1; i<=npar; i++)
6959: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6960:
1.222 brouard 6961: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6962:
1.222 brouard 6963: k=0;
6964: for(i=1; i<= (nlstate); i++){
6965: for(j=1; j<=(nlstate+ndeath);j++){
6966: k=k+1;
6967: gp[k]=pmmij[i][j];
6968: }
6969: }
1.220 brouard 6970:
1.222 brouard 6971: for(i=1; i<=npar; i++)
6972: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6973:
1.222 brouard 6974: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6975: k=0;
6976: for(i=1; i<=(nlstate); i++){
6977: for(j=1; j<=(nlstate+ndeath);j++){
6978: k=k+1;
6979: gm[k]=pmmij[i][j];
6980: }
6981: }
1.220 brouard 6982:
1.222 brouard 6983: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6984: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6985: }
1.126 brouard 6986:
1.222 brouard 6987: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6988: for(theta=1; theta <=npar; theta++)
6989: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6990:
1.222 brouard 6991: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6992: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6993:
1.222 brouard 6994: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6995:
1.222 brouard 6996: k=0;
6997: for(i=1; i<=(nlstate); i++){
6998: for(j=1; j<=(nlstate+ndeath);j++){
6999: k=k+1;
7000: mu[k][(int) age]=pmmij[i][j];
7001: }
7002: }
7003: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7004: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7005: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7006:
1.222 brouard 7007: /*printf("\n%d ",(int)age);
7008: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7009: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7010: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7011: }*/
1.220 brouard 7012:
1.222 brouard 7013: fprintf(ficresprob,"\n%d ",(int)age);
7014: fprintf(ficresprobcov,"\n%d ",(int)age);
7015: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7016:
1.222 brouard 7017: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7018: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7019: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7020: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7021: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7022: }
7023: i=0;
7024: for (k=1; k<=(nlstate);k++){
7025: for (l=1; l<=(nlstate+ndeath);l++){
7026: i++;
7027: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7028: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7029: for (j=1; j<=i;j++){
7030: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7031: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7032: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7033: }
7034: }
7035: }/* end of loop for state */
7036: } /* end of loop for age */
7037: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7038: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7039: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7040: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7041:
7042: /* Confidence intervalle of pij */
7043: /*
7044: fprintf(ficgp,"\nunset parametric;unset label");
7045: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7046: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7047: 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);
7048: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7049: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7050: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7051: */
7052:
7053: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7054: first1=1;first2=2;
7055: for (k2=1; k2<=(nlstate);k2++){
7056: for (l2=1; l2<=(nlstate+ndeath);l2++){
7057: if(l2==k2) continue;
7058: j=(k2-1)*(nlstate+ndeath)+l2;
7059: for (k1=1; k1<=(nlstate);k1++){
7060: for (l1=1; l1<=(nlstate+ndeath);l1++){
7061: if(l1==k1) continue;
7062: i=(k1-1)*(nlstate+ndeath)+l1;
7063: if(i<=j) continue;
7064: for (age=bage; age<=fage; age ++){
7065: if ((int)age %5==0){
7066: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7067: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7068: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7069: mu1=mu[i][(int) age]/stepm*YEARM ;
7070: mu2=mu[j][(int) age]/stepm*YEARM;
7071: c12=cv12/sqrt(v1*v2);
7072: /* Computing eigen value of matrix of covariance */
7073: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7074: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7075: if ((lc2 <0) || (lc1 <0) ){
7076: if(first2==1){
7077: first1=0;
7078: 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);
7079: }
7080: 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);
7081: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7082: /* lc2=fabs(lc2); */
7083: }
1.220 brouard 7084:
1.222 brouard 7085: /* Eigen vectors */
1.280 brouard 7086: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7087: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7088: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7089: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7090: }else
7091: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7092: /*v21=sqrt(1.-v11*v11); *//* error */
7093: v21=(lc1-v1)/cv12*v11;
7094: v12=-v21;
7095: v22=v11;
7096: tnalp=v21/v11;
7097: if(first1==1){
7098: first1=0;
7099: 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);
7100: }
7101: 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);
7102: /*printf(fignu*/
7103: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7104: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7105: if(first==1){
7106: first=0;
7107: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7108: fprintf(ficgp,"\nset parametric;unset label");
7109: 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);
7110: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7111: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7112: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7113: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7114: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7115: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7116: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7117: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7118: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7119: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7120: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7121: 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 7122: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7123: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7124: }else{
7125: first=0;
7126: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7127: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7128: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7129: 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 7130: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7131: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7132: }/* if first */
7133: } /* age mod 5 */
7134: } /* end loop age */
7135: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7136: first=1;
7137: } /*l12 */
7138: } /* k12 */
7139: } /*l1 */
7140: }/* k1 */
7141: } /* loop on combination of covariates j1 */
7142: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7143: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7144: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7145: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7146: free_vector(xp,1,npar);
7147: fclose(ficresprob);
7148: fclose(ficresprobcov);
7149: fclose(ficresprobcor);
7150: fflush(ficgp);
7151: fflush(fichtmcov);
7152: }
1.126 brouard 7153:
7154:
7155: /******************* Printing html file ***********/
1.201 brouard 7156: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7157: int lastpass, int stepm, int weightopt, char model[],\
7158: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7159: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7160: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7161: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7162: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7163: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7164: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7165: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7166: </ul>");
1.319 brouard 7167: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7168: /* </ul>", model); */
1.214 brouard 7169: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7170: 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",
7171: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
7172: 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 7173: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7174: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7175: fprintf(fichtm,"\
7176: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7177: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7178: fprintf(fichtm,"\
1.217 brouard 7179: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7180: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7181: fprintf(fichtm,"\
1.288 brouard 7182: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7183: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7184: fprintf(fichtm,"\
1.288 brouard 7185: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7186: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7187: fprintf(fichtm,"\
1.211 brouard 7188: - (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 7189: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7190: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7191: if(prevfcast==1){
7192: fprintf(fichtm,"\
7193: - Prevalence projections by age and states: \
1.201 brouard 7194: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7195: }
1.126 brouard 7196:
7197:
1.225 brouard 7198: m=pow(2,cptcoveff);
1.222 brouard 7199: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7200:
1.317 brouard 7201: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7202:
7203: jj1=0;
7204:
7205: fprintf(fichtm," \n<ul>");
7206: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7207: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7208: if(m != 1 && TKresult[nres]!= k1)
7209: continue;
7210: jj1++;
7211: if (cptcovn > 0) {
7212: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
7213: for (cpt=1; cpt<=cptcoveff;cpt++){
7214: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7215: }
7216: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7217: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7218: }
7219: fprintf(fichtm,"\">");
7220:
7221: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7222: fprintf(fichtm,"************ Results for covariates");
7223: for (cpt=1; cpt<=cptcoveff;cpt++){
7224: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7225: }
7226: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7227: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7228: }
7229: if(invalidvarcomb[k1]){
7230: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7231: continue;
7232: }
7233: fprintf(fichtm,"</a></li>");
7234: } /* cptcovn >0 */
7235: }
1.317 brouard 7236: fprintf(fichtm," \n</ul>");
1.264 brouard 7237:
1.222 brouard 7238: jj1=0;
1.237 brouard 7239:
7240: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7241: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7242: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7243: continue;
1.220 brouard 7244:
1.222 brouard 7245: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7246: jj1++;
7247: if (cptcovn > 0) {
1.264 brouard 7248: fprintf(fichtm,"\n<p><a name=\"rescov");
7249: for (cpt=1; cpt<=cptcoveff;cpt++){
7250: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7251: }
7252: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7253: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7254: }
7255: fprintf(fichtm,"\"</a>");
7256:
1.222 brouard 7257: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7258: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7259: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7260: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7261: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7262: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7263: }
1.237 brouard 7264: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7265: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7266: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7267: }
7268:
1.230 brouard 7269: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.321 brouard 7270: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7271: if(invalidvarcomb[k1]){
7272: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7273: printf("\nCombination (%d) ignored because no cases \n",k1);
7274: continue;
7275: }
7276: }
7277: /* aij, bij */
1.259 brouard 7278: 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 7279: <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 7280: /* Pij */
1.241 brouard 7281: 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> \
7282: <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 7283: /* Quasi-incidences */
7284: 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 7285: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7286: 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 7287: 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> \
7288: <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 7289: /* Survival functions (period) in state j */
7290: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7291: 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 7292: <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 7293: }
7294: /* State specific survival functions (period) */
7295: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7296: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7297: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 7298: <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 7299: }
1.288 brouard 7300: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7301: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7302: 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> \
7303: <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 7304: }
1.296 brouard 7305: if(prevbcast==1){
1.288 brouard 7306: /* Backward prevalence in each health state */
1.222 brouard 7307: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7308: 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 7309: <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 7310: }
1.217 brouard 7311: }
1.222 brouard 7312: if(prevfcast==1){
1.288 brouard 7313: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7314: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7315: 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);
7316: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7317: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7318: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7319: }
7320: }
1.296 brouard 7321: if(prevbcast==1){
1.268 brouard 7322: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7323: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7324: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7325: 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 \
7326: 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 7327: 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);
7328: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7329: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7330: }
7331: }
1.220 brouard 7332:
1.222 brouard 7333: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7334: 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);
7335: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7336: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7337: }
7338: /* } /\* end i1 *\/ */
7339: }/* End k1 */
7340: fprintf(fichtm,"</ul>");
1.126 brouard 7341:
1.222 brouard 7342: fprintf(fichtm,"\
1.126 brouard 7343: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7344: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7345: - 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 7346: But because parameters are usually highly correlated (a higher incidence of disability \
7347: and a higher incidence of recovery can give very close observed transition) it might \
7348: be very useful to look not only at linear confidence intervals estimated from the \
7349: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7350: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7351: covariance matrix of the one-step probabilities. \
7352: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7353:
1.222 brouard 7354: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7355: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7356: fprintf(fichtm,"\
1.126 brouard 7357: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7358: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7359:
1.222 brouard 7360: fprintf(fichtm,"\
1.126 brouard 7361: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7362: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7363: fprintf(fichtm,"\
1.126 brouard 7364: - 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): \
7365: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7366: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7367: fprintf(fichtm,"\
1.126 brouard 7368: - (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): \
7369: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7370: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7371: fprintf(fichtm,"\
1.288 brouard 7372: - 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 7373: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7374: fprintf(fichtm,"\
1.128 brouard 7375: - 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 7376: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7377: fprintf(fichtm,"\
1.288 brouard 7378: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7379: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7380:
7381: /* if(popforecast==1) fprintf(fichtm,"\n */
7382: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7383: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7384: /* <br>",fileres,fileres,fileres,fileres); */
7385: /* else */
7386: /* 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 7387: fflush(fichtm);
1.126 brouard 7388:
1.225 brouard 7389: m=pow(2,cptcoveff);
1.222 brouard 7390: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7391:
1.317 brouard 7392: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7393:
7394: jj1=0;
7395:
7396: fprintf(fichtm," \n<ul>");
7397: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7398: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7399: if(m != 1 && TKresult[nres]!= k1)
7400: continue;
7401: jj1++;
7402: if (cptcovn > 0) {
7403: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
7404: for (cpt=1; cpt<=cptcoveff;cpt++){
7405: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7406: }
7407: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7408: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7409: }
7410: fprintf(fichtm,"\">");
7411:
7412: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7413: fprintf(fichtm,"************ Results for covariates");
7414: for (cpt=1; cpt<=cptcoveff;cpt++){
7415: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7416: }
7417: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7418: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7419: }
7420: if(invalidvarcomb[k1]){
7421: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7422: continue;
7423: }
7424: fprintf(fichtm,"</a></li>");
7425: } /* cptcovn >0 */
7426: }
7427: fprintf(fichtm," \n</ul>");
7428:
1.222 brouard 7429: jj1=0;
1.237 brouard 7430:
1.241 brouard 7431: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7432: for(k1=1; k1<=m;k1++){
1.253 brouard 7433: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7434: continue;
1.222 brouard 7435: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7436: jj1++;
1.126 brouard 7437: if (cptcovn > 0) {
1.317 brouard 7438: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
7439: for (cpt=1; cpt<=cptcoveff;cpt++){
7440: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7441: }
7442: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7443: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7444: }
7445: fprintf(fichtm,"\"</a>");
7446:
1.126 brouard 7447: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.317 brouard 7448: for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */
1.237 brouard 7449: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
1.317 brouard 7450: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
1.237 brouard 7451: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7452: }
1.237 brouard 7453: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7454: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7455: }
7456:
1.321 brouard 7457: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7458:
1.222 brouard 7459: if(invalidvarcomb[k1]){
7460: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7461: continue;
7462: }
1.126 brouard 7463: }
7464: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7465: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7466: 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);
7467: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7468: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7469: }
7470: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7471: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7472: true period expectancies (those weighted with period prevalences are also\
7473: drawn in addition to the population based expectancies computed using\
1.314 brouard 7474: 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);
7475: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7476: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7477: /* } /\* end i1 *\/ */
7478: }/* End k1 */
1.241 brouard 7479: }/* End nres */
1.222 brouard 7480: fprintf(fichtm,"</ul>");
7481: fflush(fichtm);
1.126 brouard 7482: }
7483:
7484: /******************* Gnuplot file **************/
1.296 brouard 7485: 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 7486:
7487: char dirfileres[132],optfileres[132];
1.264 brouard 7488: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7489: 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 7490: int lv=0, vlv=0, kl=0;
1.130 brouard 7491: int ng=0;
1.201 brouard 7492: int vpopbased;
1.223 brouard 7493: int ioffset; /* variable offset for columns */
1.270 brouard 7494: int iyearc=1; /* variable column for year of projection */
7495: int iagec=1; /* variable column for age of projection */
1.235 brouard 7496: int nres=0; /* Index of resultline */
1.266 brouard 7497: int istart=1; /* For starting graphs in projections */
1.219 brouard 7498:
1.126 brouard 7499: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7500: /* printf("Problem with file %s",optionfilegnuplot); */
7501: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7502: /* } */
7503:
7504: /*#ifdef windows */
7505: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7506: /*#endif */
1.225 brouard 7507: m=pow(2,cptcoveff);
1.126 brouard 7508:
1.274 brouard 7509: /* diagram of the model */
7510: fprintf(ficgp,"\n#Diagram of the model \n");
7511: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7512: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7513: 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);
7514:
7515: 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);
7516: fprintf(ficgp,"\n#show arrow\nunset label\n");
7517: 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);
7518: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7519: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7520: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7521: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7522:
1.202 brouard 7523: /* Contribution to likelihood */
7524: /* Plot the probability implied in the likelihood */
1.223 brouard 7525: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7526: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7527: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7528: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7529: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7530: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7531: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7532: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7533: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7534: 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));
7535: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7536: 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));
7537: for (i=1; i<= nlstate ; i ++) {
7538: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7539: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7540: 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);
7541: for (j=2; j<= nlstate+ndeath ; j ++) {
7542: 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);
7543: }
7544: fprintf(ficgp,";\nset out; unset ylabel;\n");
7545: }
7546: /* 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 */
7547: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7548: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7549: fprintf(ficgp,"\nset out;unset log\n");
7550: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7551:
1.126 brouard 7552: strcpy(dirfileres,optionfilefiname);
7553: strcpy(optfileres,"vpl");
1.223 brouard 7554: /* 1eme*/
1.238 brouard 7555: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7556: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7557: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7558: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7559: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7560: continue;
7561: /* We are interested in selected combination by the resultline */
1.246 brouard 7562: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7563: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7564: strcpy(gplotlabel,"(");
1.238 brouard 7565: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7566: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7567: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7568: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7569: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7570: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7571: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7572: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7573: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7574: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7575: }
7576: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7577: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7578: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7579: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7580: }
7581: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7582: /* printf("\n#\n"); */
1.238 brouard 7583: fprintf(ficgp,"\n#\n");
7584: if(invalidvarcomb[k1]){
1.260 brouard 7585: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7586: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7587: continue;
7588: }
1.235 brouard 7589:
1.241 brouard 7590: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7591: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7592: /* 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 7593: fprintf(ficgp,"set title \"Alive state %d %s model=%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 7594: 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);
7595: /* 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); */
7596: /* k1-1 error should be nres-1*/
1.238 brouard 7597: for (i=1; i<= nlstate ; i ++) {
7598: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7599: else fprintf(ficgp," %%*lf (%%*lf)");
7600: }
1.288 brouard 7601: 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 7602: for (i=1; i<= nlstate ; i ++) {
7603: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7604: else fprintf(ficgp," %%*lf (%%*lf)");
7605: }
1.260 brouard 7606: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7607: for (i=1; i<= nlstate ; i ++) {
7608: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7609: else fprintf(ficgp," %%*lf (%%*lf)");
7610: }
1.265 brouard 7611: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7612:
7613: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7614: if(cptcoveff ==0){
1.271 brouard 7615: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7616: }else{
7617: kl=0;
7618: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7619: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7620: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7621: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7622: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7623: vlv= nbcode[Tvaraff[k]][lv];
7624: kl++;
7625: /* 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 *\/ */
7626: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7627: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7628: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7629: if(k==cptcoveff){
7630: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7631: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7632: }else{
7633: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7634: kl++;
7635: }
7636: } /* end covariate */
7637: } /* end if no covariate */
7638:
1.296 brouard 7639: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7640: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7641: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7642: if(cptcoveff ==0){
1.245 brouard 7643: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7644: }else{
7645: kl=0;
7646: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7647: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7648: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7649: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7650: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7651: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7652: kl++;
1.238 brouard 7653: /* 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 *\/ */
7654: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7655: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7656: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7657: if(k==cptcoveff){
1.245 brouard 7658: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7659: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7660: }else{
7661: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7662: kl++;
7663: }
7664: } /* end covariate */
7665: } /* end if no covariate */
1.296 brouard 7666: if(prevbcast == 1){
1.268 brouard 7667: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7668: /* k1-1 error should be nres-1*/
7669: for (i=1; i<= nlstate ; i ++) {
7670: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7671: else fprintf(ficgp," %%*lf (%%*lf)");
7672: }
1.271 brouard 7673: 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 7674: for (i=1; i<= nlstate ; i ++) {
7675: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7676: else fprintf(ficgp," %%*lf (%%*lf)");
7677: }
1.276 brouard 7678: 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 7679: for (i=1; i<= nlstate ; i ++) {
7680: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7681: else fprintf(ficgp," %%*lf (%%*lf)");
7682: }
1.274 brouard 7683: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7684: } /* end if backprojcast */
1.296 brouard 7685: } /* end if prevbcast */
1.276 brouard 7686: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7687: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7688: } /* nres */
1.201 brouard 7689: } /* k1 */
7690: } /* cpt */
1.235 brouard 7691:
7692:
1.126 brouard 7693: /*2 eme*/
1.238 brouard 7694: for (k1=1; k1<= m ; k1 ++){
7695: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7696: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7697: continue;
7698: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7699: strcpy(gplotlabel,"(");
1.238 brouard 7700: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7701: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7702: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7703: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7704: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7705: vlv= nbcode[Tvaraff[k]][lv];
7706: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7707: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7708: }
1.237 brouard 7709: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7710: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7711: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7712: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7713: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7714: }
1.264 brouard 7715: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7716: fprintf(ficgp,"\n#\n");
1.223 brouard 7717: if(invalidvarcomb[k1]){
7718: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7719: continue;
7720: }
1.219 brouard 7721:
1.241 brouard 7722: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7723: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7724: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7725: if(vpopbased==0){
1.238 brouard 7726: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7727: }else
1.238 brouard 7728: fprintf(ficgp,"\nreplot ");
7729: for (i=1; i<= nlstate+1 ; i ++) {
7730: k=2*i;
1.261 brouard 7731: 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 7732: for (j=1; j<= nlstate+1 ; j ++) {
7733: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7734: else fprintf(ficgp," %%*lf (%%*lf)");
7735: }
7736: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7737: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7738: 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 7739: for (j=1; j<= nlstate+1 ; j ++) {
7740: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7741: else fprintf(ficgp," %%*lf (%%*lf)");
7742: }
7743: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7744: 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 7745: for (j=1; j<= nlstate+1 ; j ++) {
7746: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7747: else fprintf(ficgp," %%*lf (%%*lf)");
7748: }
7749: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7750: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7751: } /* state */
7752: } /* vpopbased */
1.264 brouard 7753: 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 7754: } /* end nres */
7755: } /* k1 end 2 eme*/
7756:
7757:
7758: /*3eme*/
7759: for (k1=1; k1<= m ; k1 ++){
7760: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7761: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7762: continue;
7763:
7764: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7765: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7766: strcpy(gplotlabel,"(");
1.238 brouard 7767: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7768: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7769: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7770: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7771: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7772: vlv= nbcode[Tvaraff[k]][lv];
7773: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7774: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7775: }
7776: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7777: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7778: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7779: }
1.264 brouard 7780: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7781: fprintf(ficgp,"\n#\n");
7782: if(invalidvarcomb[k1]){
7783: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7784: continue;
7785: }
7786:
7787: /* k=2+nlstate*(2*cpt-2); */
7788: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7789: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7790: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7791: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7792: 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 7793: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7794: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7795: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7796: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7797: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7798: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7799:
1.238 brouard 7800: */
7801: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7802: 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 7803: /* 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 7804:
1.238 brouard 7805: }
1.261 brouard 7806: 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 7807: }
1.264 brouard 7808: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7809: } /* end nres */
7810: } /* end kl 3eme */
1.126 brouard 7811:
1.223 brouard 7812: /* 4eme */
1.201 brouard 7813: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7814: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7815: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7816: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7817: continue;
1.238 brouard 7818: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7819: strcpy(gplotlabel,"(");
1.238 brouard 7820: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7821: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7822: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7823: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7824: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7825: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7826: vlv= nbcode[Tvaraff[k]][lv];
7827: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7828: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7829: }
7830: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7831: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7832: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7833: }
1.264 brouard 7834: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7835: fprintf(ficgp,"\n#\n");
7836: if(invalidvarcomb[k1]){
7837: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7838: continue;
1.223 brouard 7839: }
1.238 brouard 7840:
1.241 brouard 7841: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7842: 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 7843: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7844: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7845: k=3;
7846: for (i=1; i<= nlstate ; i ++){
7847: if(i==1){
7848: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7849: }else{
7850: fprintf(ficgp,", '' ");
7851: }
7852: l=(nlstate+ndeath)*(i-1)+1;
7853: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7854: for (j=2; j<= nlstate+ndeath ; j ++)
7855: fprintf(ficgp,"+$%d",k+l+j-1);
7856: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7857: } /* nlstate */
1.264 brouard 7858: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7859: } /* end cpt state*/
7860: } /* end nres */
7861: } /* end covariate k1 */
7862:
1.220 brouard 7863: /* 5eme */
1.201 brouard 7864: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7865: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7866: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7867: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7868: continue;
1.238 brouard 7869: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7870: strcpy(gplotlabel,"(");
1.238 brouard 7871: 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);
7872: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7873: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7874: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7875: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7876: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7877: vlv= nbcode[Tvaraff[k]][lv];
7878: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7879: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7880: }
7881: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7882: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7883: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7884: }
1.264 brouard 7885: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7886: fprintf(ficgp,"\n#\n");
7887: if(invalidvarcomb[k1]){
7888: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7889: continue;
7890: }
1.227 brouard 7891:
1.241 brouard 7892: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7893: 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 7894: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7895: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7896: k=3;
7897: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7898: if(j==1)
7899: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7900: else
7901: fprintf(ficgp,", '' ");
7902: l=(nlstate+ndeath)*(cpt-1) +j;
7903: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7904: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7905: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7906: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7907: } /* nlstate */
7908: fprintf(ficgp,", '' ");
7909: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7910: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7911: l=(nlstate+ndeath)*(cpt-1) +j;
7912: if(j < nlstate)
7913: fprintf(ficgp,"$%d +",k+l);
7914: else
7915: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7916: }
1.264 brouard 7917: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7918: } /* end cpt state*/
7919: } /* end covariate */
7920: } /* end nres */
1.227 brouard 7921:
1.220 brouard 7922: /* 6eme */
1.202 brouard 7923: /* CV preval stable (period) for each covariate */
1.237 brouard 7924: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7925: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7926: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7927: continue;
1.255 brouard 7928: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7929: strcpy(gplotlabel,"(");
1.288 brouard 7930: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7931: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7932: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7933: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7934: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7935: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7936: vlv= nbcode[Tvaraff[k]][lv];
7937: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7938: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7939: }
1.237 brouard 7940: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7941: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7942: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7943: }
1.264 brouard 7944: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7945: fprintf(ficgp,"\n#\n");
1.223 brouard 7946: if(invalidvarcomb[k1]){
1.227 brouard 7947: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7948: continue;
1.223 brouard 7949: }
1.227 brouard 7950:
1.241 brouard 7951: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7952: 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 7953: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7954: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7955: k=3; /* Offset */
1.255 brouard 7956: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7957: if(i==1)
7958: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7959: else
7960: fprintf(ficgp,", '' ");
1.255 brouard 7961: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7962: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7963: for (j=2; j<= nlstate ; j ++)
7964: fprintf(ficgp,"+$%d",k+l+j-1);
7965: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7966: } /* nlstate */
1.264 brouard 7967: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7968: } /* end cpt state*/
7969: } /* end covariate */
1.227 brouard 7970:
7971:
1.220 brouard 7972: /* 7eme */
1.296 brouard 7973: if(prevbcast == 1){
1.288 brouard 7974: /* CV backward prevalence for each covariate */
1.237 brouard 7975: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7976: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7977: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7978: continue;
1.268 brouard 7979: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7980: strcpy(gplotlabel,"(");
1.288 brouard 7981: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7982: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7983: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7984: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7985: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7986: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7987: vlv= nbcode[Tvaraff[k]][lv];
7988: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7989: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7990: }
1.237 brouard 7991: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7992: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7993: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7994: }
1.264 brouard 7995: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7996: fprintf(ficgp,"\n#\n");
7997: if(invalidvarcomb[k1]){
7998: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7999: continue;
8000: }
8001:
1.241 brouard 8002: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8003: 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 8004: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8005: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8006: k=3; /* Offset */
1.268 brouard 8007: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8008: if(i==1)
8009: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8010: else
8011: fprintf(ficgp,", '' ");
8012: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8013: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8014: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8015: /* 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 8016: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8017: /* for (j=2; j<= nlstate ; j ++) */
8018: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8019: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8020: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8021: } /* nlstate */
1.264 brouard 8022: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8023: } /* end cpt state*/
8024: } /* end covariate */
1.296 brouard 8025: } /* End if prevbcast */
1.218 brouard 8026:
1.223 brouard 8027: /* 8eme */
1.218 brouard 8028: if(prevfcast==1){
1.288 brouard 8029: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8030:
1.237 brouard 8031: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8032: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8033: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8034: continue;
1.211 brouard 8035: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8036: strcpy(gplotlabel,"(");
1.288 brouard 8037: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8038: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8039: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8040: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8041: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8042: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8043: vlv= nbcode[Tvaraff[k]][lv];
8044: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8045: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8046: }
1.237 brouard 8047: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8048: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8049: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8050: }
1.264 brouard 8051: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8052: fprintf(ficgp,"\n#\n");
8053: if(invalidvarcomb[k1]){
8054: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8055: continue;
8056: }
8057:
8058: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8059: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8060: 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 8061: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8062: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8063:
8064: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8065: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8066: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8067: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8068: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8069: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8070: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8071: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8072: if(i==istart){
1.227 brouard 8073: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8074: }else{
8075: fprintf(ficgp,",\\\n '' ");
8076: }
8077: if(cptcoveff ==0){ /* No covariate */
8078: ioffset=2; /* Age is in 2 */
8079: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8080: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8081: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8082: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8083: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8084: if(i==nlstate+1){
1.270 brouard 8085: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8086: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8087: fprintf(ficgp,",\\\n '' ");
8088: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8089: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8090: offyear, \
1.268 brouard 8091: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8092: }else
1.227 brouard 8093: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8094: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8095: }else{ /* more than 2 covariates */
1.270 brouard 8096: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8097: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8098: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8099: iyearc=ioffset-1;
8100: iagec=ioffset;
1.227 brouard 8101: fprintf(ficgp," u %d:(",ioffset);
8102: kl=0;
8103: strcpy(gplotcondition,"(");
8104: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8105: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8106: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8107: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8108: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8109: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8110: kl++;
8111: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8112: kl++;
8113: if(k <cptcoveff && cptcoveff>1)
8114: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8115: }
8116: strcpy(gplotcondition+strlen(gplotcondition),")");
8117: /* 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 *\/ */
8118: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8119: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8120: /* '' 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*/
8121: if(i==nlstate+1){
1.270 brouard 8122: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8123: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8124: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8125: fprintf(ficgp," u %d:(",iagec);
8126: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8127: iyearc, iagec, offyear, \
8128: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8129: /* '' 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 8130: }else{
8131: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8132: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8133: }
8134: } /* end if covariate */
8135: } /* nlstate */
1.264 brouard 8136: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8137: } /* end cpt state*/
8138: } /* end covariate */
8139: } /* End if prevfcast */
1.227 brouard 8140:
1.296 brouard 8141: if(prevbcast==1){
1.268 brouard 8142: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8143:
8144: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8145: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8146: if(m != 1 && TKresult[nres]!= k1)
8147: continue;
8148: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8149: strcpy(gplotlabel,"(");
8150: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
8151: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8152: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8153: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8154: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8155: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8156: vlv= nbcode[Tvaraff[k]][lv];
8157: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8158: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8159: }
8160: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8161: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8162: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8163: }
8164: strcpy(gplotlabel+strlen(gplotlabel),")");
8165: fprintf(ficgp,"\n#\n");
8166: if(invalidvarcomb[k1]){
8167: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8168: continue;
8169: }
8170:
8171: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8172: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8173: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8174: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8175: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8176:
8177: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8178: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8179: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8180: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8181: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8182: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8183: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8184: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8185: if(i==istart){
8186: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8187: }else{
8188: fprintf(ficgp,",\\\n '' ");
8189: }
8190: if(cptcoveff ==0){ /* No covariate */
8191: ioffset=2; /* Age is in 2 */
8192: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8193: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8194: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8195: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8196: fprintf(ficgp," u %d:(", ioffset);
8197: if(i==nlstate+1){
1.270 brouard 8198: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8199: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8200: fprintf(ficgp,",\\\n '' ");
8201: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8202: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8203: offbyear, \
8204: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8205: }else
8206: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8207: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8208: }else{ /* more than 2 covariates */
1.270 brouard 8209: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8210: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8211: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8212: iyearc=ioffset-1;
8213: iagec=ioffset;
1.268 brouard 8214: fprintf(ficgp," u %d:(",ioffset);
8215: kl=0;
8216: strcpy(gplotcondition,"(");
8217: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8218: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8219: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8220: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8221: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8222: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8223: kl++;
8224: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8225: kl++;
8226: if(k <cptcoveff && cptcoveff>1)
8227: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8228: }
8229: strcpy(gplotcondition+strlen(gplotcondition),")");
8230: /* 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 *\/ */
8231: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8232: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8233: /* '' 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*/
8234: if(i==nlstate+1){
1.270 brouard 8235: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8236: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8237: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8238: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8239: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8240: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8241: iyearc,iagec,offbyear, \
8242: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8243: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8244: }else{
8245: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8246: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8247: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8248: }
8249: } /* end if covariate */
8250: } /* nlstate */
8251: fprintf(ficgp,"\nset out; unset label;\n");
8252: } /* end cpt state*/
8253: } /* end covariate */
1.296 brouard 8254: } /* End if prevbcast */
1.268 brouard 8255:
1.227 brouard 8256:
1.238 brouard 8257: /* 9eme writing MLE parameters */
8258: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8259: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8260: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8261: for(k=1; k <=(nlstate+ndeath); k++){
8262: if (k != i) {
1.227 brouard 8263: fprintf(ficgp,"# current state %d\n",k);
8264: for(j=1; j <=ncovmodel; j++){
8265: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8266: jk++;
8267: }
8268: fprintf(ficgp,"\n");
1.126 brouard 8269: }
8270: }
1.223 brouard 8271: }
1.187 brouard 8272: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8273:
1.145 brouard 8274: /*goto avoid;*/
1.238 brouard 8275: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8276: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8277: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8278: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8279: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8280: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8281: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8282: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8283: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8284: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8285: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8286: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8287: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8288: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8289: fprintf(ficgp,"#\n");
1.223 brouard 8290: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8291: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8292: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8293: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8294: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8295: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8296: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8297: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8298: continue;
1.264 brouard 8299: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8300: strcpy(gplotlabel,"(");
1.276 brouard 8301: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8302: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8303: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8304: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8305: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8306: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8307: vlv= nbcode[Tvaraff[k]][lv];
8308: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8309: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8310: }
1.237 brouard 8311: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8312: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8313: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8314: }
1.264 brouard 8315: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8316: fprintf(ficgp,"\n#\n");
1.264 brouard 8317: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8318: fprintf(ficgp,"\nset key outside ");
8319: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8320: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8321: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8322: if (ng==1){
8323: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8324: fprintf(ficgp,"\nunset log y");
8325: }else if (ng==2){
8326: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8327: fprintf(ficgp,"\nset log y");
8328: }else if (ng==3){
8329: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8330: fprintf(ficgp,"\nset log y");
8331: }else
8332: fprintf(ficgp,"\nunset title ");
8333: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8334: i=1;
8335: for(k2=1; k2<=nlstate; k2++) {
8336: k3=i;
8337: for(k=1; k<=(nlstate+ndeath); k++) {
8338: if (k != k2){
8339: switch( ng) {
8340: case 1:
8341: if(nagesqr==0)
8342: fprintf(ficgp," p%d+p%d*x",i,i+1);
8343: else /* nagesqr =1 */
8344: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8345: break;
8346: case 2: /* ng=2 */
8347: if(nagesqr==0)
8348: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8349: else /* nagesqr =1 */
8350: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8351: break;
8352: case 3:
8353: if(nagesqr==0)
8354: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8355: else /* nagesqr =1 */
8356: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8357: break;
8358: }
8359: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8360: ijp=1; /* product no age */
8361: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8362: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8363: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 8364: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
1.325 ! brouard 8365: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
1.268 brouard 8366: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
1.325 ! brouard 8367: if(DummyV[j]==0){/* Bug valgrind */
1.268 brouard 8368: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8369: }else{ /* quantitative */
8370: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8371: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8372: }
8373: ij++;
1.237 brouard 8374: }
1.268 brouard 8375: }
8376: }else if(cptcovprod >0){
8377: if(j==Tprod[ijp]) { /* */
8378: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8379: if(ijp <=cptcovprod) { /* Product */
8380: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8381: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8382: /* 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)]); */
8383: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8384: }else{ /* Vn is dummy and Vm is quanti */
8385: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8386: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8387: }
8388: }else{ /* Vn*Vm Vn is quanti */
8389: if(DummyV[Tvard[ijp][2]]==0){
8390: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8391: }else{ /* Both quanti */
8392: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8393: }
1.237 brouard 8394: }
1.268 brouard 8395: ijp++;
1.237 brouard 8396: }
1.268 brouard 8397: } /* end Tprod */
1.237 brouard 8398: } else{ /* simple covariate */
1.264 brouard 8399: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8400: if(Dummy[j]==0){
8401: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8402: }else{ /* quantitative */
8403: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8404: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8405: }
1.237 brouard 8406: } /* end simple */
8407: } /* end j */
1.223 brouard 8408: }else{
8409: i=i-ncovmodel;
8410: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8411: fprintf(ficgp," (1.");
8412: }
1.227 brouard 8413:
1.223 brouard 8414: if(ng != 1){
8415: fprintf(ficgp,")/(1");
1.227 brouard 8416:
1.264 brouard 8417: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8418: if(nagesqr==0)
1.264 brouard 8419: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8420: else /* nagesqr =1 */
1.264 brouard 8421: 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 8422:
1.223 brouard 8423: ij=1;
8424: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8425: if(cptcovage >0){
8426: if((j-2)==Tage[ij]) { /* Bug valgrind */
8427: if(ij <=cptcovage) { /* Bug valgrind */
8428: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8429: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8430: ij++;
8431: }
8432: }
8433: }else
8434: 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 8435: }
8436: fprintf(ficgp,")");
8437: }
8438: fprintf(ficgp,")");
8439: if(ng ==2)
1.276 brouard 8440: 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 8441: else /* ng= 3 */
1.276 brouard 8442: 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 8443: }else{ /* end ng <> 1 */
8444: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8445: 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 8446: }
8447: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8448: fprintf(ficgp,",");
8449: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8450: fprintf(ficgp,",");
8451: i=i+ncovmodel;
8452: } /* end k */
8453: } /* end k2 */
1.276 brouard 8454: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8455: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8456: } /* end k1 */
1.223 brouard 8457: } /* end ng */
8458: /* avoid: */
8459: fflush(ficgp);
1.126 brouard 8460: } /* end gnuplot */
8461:
8462:
8463: /*************** Moving average **************/
1.219 brouard 8464: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8465: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8466:
1.222 brouard 8467: int i, cpt, cptcod;
8468: int modcovmax =1;
8469: int mobilavrange, mob;
8470: int iage=0;
1.288 brouard 8471: int firstA1=0, firstA2=0;
1.222 brouard 8472:
1.266 brouard 8473: double sum=0., sumr=0.;
1.222 brouard 8474: double age;
1.266 brouard 8475: double *sumnewp, *sumnewm, *sumnewmr;
8476: double *agemingood, *agemaxgood;
8477: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8478:
8479:
1.278 brouard 8480: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8481: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8482:
8483: sumnewp = vector(1,ncovcombmax);
8484: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8485: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8486: agemingood = vector(1,ncovcombmax);
1.266 brouard 8487: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8488: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8489: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8490:
8491: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8492: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8493: sumnewp[cptcod]=0.;
1.266 brouard 8494: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8495: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8496: }
8497: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8498:
1.266 brouard 8499: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8500: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8501: else mobilavrange=mobilav;
8502: for (age=bage; age<=fage; age++)
8503: for (i=1; i<=nlstate;i++)
8504: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8505: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8506: /* We keep the original values on the extreme ages bage, fage and for
8507: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8508: we use a 5 terms etc. until the borders are no more concerned.
8509: */
8510: for (mob=3;mob <=mobilavrange;mob=mob+2){
8511: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8512: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8513: sumnewm[cptcod]=0.;
8514: for (i=1; i<=nlstate;i++){
1.222 brouard 8515: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8516: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8517: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8518: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8519: }
8520: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8521: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8522: } /* end i */
8523: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8524: } /* end cptcod */
1.222 brouard 8525: }/* end age */
8526: }/* end mob */
1.266 brouard 8527: }else{
8528: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8529: return -1;
1.266 brouard 8530: }
8531:
8532: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8533: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8534: if(invalidvarcomb[cptcod]){
8535: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8536: continue;
8537: }
1.219 brouard 8538:
1.266 brouard 8539: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8540: sumnewm[cptcod]=0.;
8541: sumnewmr[cptcod]=0.;
8542: for (i=1; i<=nlstate;i++){
8543: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8544: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8545: }
8546: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8547: agemingoodr[cptcod]=age;
8548: }
8549: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8550: agemingood[cptcod]=age;
8551: }
8552: } /* age */
8553: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8554: sumnewm[cptcod]=0.;
1.266 brouard 8555: sumnewmr[cptcod]=0.;
1.222 brouard 8556: for (i=1; i<=nlstate;i++){
8557: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8558: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8559: }
8560: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8561: agemaxgoodr[cptcod]=age;
1.222 brouard 8562: }
8563: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8564: agemaxgood[cptcod]=age;
8565: }
8566: } /* age */
8567: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8568: /* but they will change */
1.288 brouard 8569: firstA1=0;firstA2=0;
1.266 brouard 8570: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8571: sumnewm[cptcod]=0.;
8572: sumnewmr[cptcod]=0.;
8573: for (i=1; i<=nlstate;i++){
8574: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8575: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8576: }
8577: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8578: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8579: agemaxgoodr[cptcod]=age; /* age min */
8580: for (i=1; i<=nlstate;i++)
8581: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8582: }else{ /* bad we change the value with the values of good ages */
8583: for (i=1; i<=nlstate;i++){
8584: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8585: } /* i */
8586: } /* end bad */
8587: }else{
8588: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8589: agemaxgood[cptcod]=age;
8590: }else{ /* bad we change the value with the values of good ages */
8591: for (i=1; i<=nlstate;i++){
8592: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8593: } /* i */
8594: } /* end bad */
8595: }/* end else */
8596: sum=0.;sumr=0.;
8597: for (i=1; i<=nlstate;i++){
8598: sum+=mobaverage[(int)age][i][cptcod];
8599: sumr+=probs[(int)age][i][cptcod];
8600: }
8601: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8602: if(!firstA1){
8603: firstA1=1;
8604: 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);
8605: }
8606: 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 8607: } /* end bad */
8608: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8609: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8610: if(!firstA2){
8611: firstA2=1;
8612: 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);
8613: }
8614: 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 8615: } /* end bad */
8616: }/* age */
1.266 brouard 8617:
8618: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8619: sumnewm[cptcod]=0.;
1.266 brouard 8620: sumnewmr[cptcod]=0.;
1.222 brouard 8621: for (i=1; i<=nlstate;i++){
8622: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8623: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8624: }
8625: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8626: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8627: agemingoodr[cptcod]=age;
8628: for (i=1; i<=nlstate;i++)
8629: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8630: }else{ /* bad we change the value with the values of good ages */
8631: for (i=1; i<=nlstate;i++){
8632: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8633: } /* i */
8634: } /* end bad */
8635: }else{
8636: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8637: agemingood[cptcod]=age;
8638: }else{ /* bad */
8639: for (i=1; i<=nlstate;i++){
8640: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8641: } /* i */
8642: } /* end bad */
8643: }/* end else */
8644: sum=0.;sumr=0.;
8645: for (i=1; i<=nlstate;i++){
8646: sum+=mobaverage[(int)age][i][cptcod];
8647: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8648: }
1.266 brouard 8649: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8650: 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 8651: } /* end bad */
8652: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8653: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8654: 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 8655: } /* end bad */
8656: }/* age */
1.266 brouard 8657:
1.222 brouard 8658:
8659: for (age=bage; age<=fage; age++){
1.235 brouard 8660: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8661: sumnewp[cptcod]=0.;
8662: sumnewm[cptcod]=0.;
8663: for (i=1; i<=nlstate;i++){
8664: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8665: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8666: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8667: }
8668: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8669: }
8670: /* printf("\n"); */
8671: /* } */
1.266 brouard 8672:
1.222 brouard 8673: /* brutal averaging */
1.266 brouard 8674: /* for (i=1; i<=nlstate;i++){ */
8675: /* for (age=1; age<=bage; age++){ */
8676: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8677: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8678: /* } */
8679: /* for (age=fage; age<=AGESUP; age++){ */
8680: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8681: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8682: /* } */
8683: /* } /\* end i status *\/ */
8684: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8685: /* for (age=1; age<=AGESUP; age++){ */
8686: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8687: /* mobaverage[(int)age][i][cptcod]=0.; */
8688: /* } */
8689: /* } */
1.222 brouard 8690: }/* end cptcod */
1.266 brouard 8691: free_vector(agemaxgoodr,1, ncovcombmax);
8692: free_vector(agemaxgood,1, ncovcombmax);
8693: free_vector(agemingood,1, ncovcombmax);
8694: free_vector(agemingoodr,1, ncovcombmax);
8695: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8696: free_vector(sumnewm,1, ncovcombmax);
8697: free_vector(sumnewp,1, ncovcombmax);
8698: return 0;
8699: }/* End movingaverage */
1.218 brouard 8700:
1.126 brouard 8701:
1.296 brouard 8702:
1.126 brouard 8703: /************** Forecasting ******************/
1.296 brouard 8704: /* 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)*/
8705: 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){
8706: /* dateintemean, mean date of interviews
8707: dateprojd, year, month, day of starting projection
8708: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8709: agemin, agemax range of age
8710: dateprev1 dateprev2 range of dates during which prevalence is computed
8711: */
1.296 brouard 8712: /* double anprojd, mprojd, jprojd; */
8713: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8714: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8715: double agec; /* generic age */
1.296 brouard 8716: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8717: double *popeffectif,*popcount;
8718: double ***p3mat;
1.218 brouard 8719: /* double ***mobaverage; */
1.126 brouard 8720: char fileresf[FILENAMELENGTH];
8721:
8722: agelim=AGESUP;
1.211 brouard 8723: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8724: in each health status at the date of interview (if between dateprev1 and dateprev2).
8725: We still use firstpass and lastpass as another selection.
8726: */
1.214 brouard 8727: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8728: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8729:
1.201 brouard 8730: strcpy(fileresf,"F_");
8731: strcat(fileresf,fileresu);
1.126 brouard 8732: if((ficresf=fopen(fileresf,"w"))==NULL) {
8733: printf("Problem with forecast resultfile: %s\n", fileresf);
8734: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8735: }
1.235 brouard 8736: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8737: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8738:
1.225 brouard 8739: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8740:
8741:
8742: stepsize=(int) (stepm+YEARM-1)/YEARM;
8743: if (stepm<=12) stepsize=1;
8744: if(estepm < stepm){
8745: printf ("Problem %d lower than %d\n",estepm, stepm);
8746: }
1.270 brouard 8747: else{
8748: hstepm=estepm;
8749: }
8750: if(estepm > stepm){ /* Yes every two year */
8751: stepsize=2;
8752: }
1.296 brouard 8753: hstepm=hstepm/stepm;
1.126 brouard 8754:
1.296 brouard 8755:
8756: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8757: /* fractional in yp1 *\/ */
8758: /* aintmean=yp; */
8759: /* yp2=modf((yp1*12),&yp); */
8760: /* mintmean=yp; */
8761: /* yp1=modf((yp2*30.5),&yp); */
8762: /* jintmean=yp; */
8763: /* if(jintmean==0) jintmean=1; */
8764: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8765:
1.296 brouard 8766:
8767: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8768: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8769: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8770: i1=pow(2,cptcoveff);
1.126 brouard 8771: if (cptcovn < 1){i1=1;}
8772:
1.296 brouard 8773: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8774:
8775: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8776:
1.126 brouard 8777: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8778: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8779: for(k=1; k<=i1;k++){
1.253 brouard 8780: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8781: continue;
1.227 brouard 8782: if(invalidvarcomb[k]){
8783: printf("\nCombination (%d) projection ignored because no cases \n",k);
8784: continue;
8785: }
8786: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8787: for(j=1;j<=cptcoveff;j++) {
8788: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8789: }
1.235 brouard 8790: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8791: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8792: }
1.227 brouard 8793: fprintf(ficresf," yearproj age");
8794: for(j=1; j<=nlstate+ndeath;j++){
8795: for(i=1; i<=nlstate;i++)
8796: fprintf(ficresf," p%d%d",i,j);
8797: fprintf(ficresf," wp.%d",j);
8798: }
1.296 brouard 8799: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8800: fprintf(ficresf,"\n");
1.296 brouard 8801: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8802: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8803: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8804: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8805: nhstepm = nhstepm/hstepm;
8806: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8807: oldm=oldms;savm=savms;
1.268 brouard 8808: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8809: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8810: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8811: for (h=0; h<=nhstepm; h++){
8812: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8813: break;
8814: }
8815: }
8816: fprintf(ficresf,"\n");
8817: for(j=1;j<=cptcoveff;j++)
8818: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8819: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8820:
8821: for(j=1; j<=nlstate+ndeath;j++) {
8822: ppij=0.;
8823: for(i=1; i<=nlstate;i++) {
1.278 brouard 8824: if (mobilav>=1)
8825: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8826: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8827: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8828: }
1.268 brouard 8829: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8830: } /* end i */
8831: fprintf(ficresf," %.3f", ppij);
8832: }/* end j */
1.227 brouard 8833: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8834: } /* end agec */
1.266 brouard 8835: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8836: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8837: } /* end yearp */
8838: } /* end k */
1.219 brouard 8839:
1.126 brouard 8840: fclose(ficresf);
1.215 brouard 8841: printf("End of Computing forecasting \n");
8842: fprintf(ficlog,"End of Computing forecasting\n");
8843:
1.126 brouard 8844: }
8845:
1.269 brouard 8846: /************** Back Forecasting ******************/
1.296 brouard 8847: /* 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){ */
8848: 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){
8849: /* back1, year, month, day of starting backprojection
1.267 brouard 8850: agemin, agemax range of age
8851: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8852: anback2 year of end of backprojection (same day and month as back1).
8853: prevacurrent and prev are prevalences.
1.267 brouard 8854: */
8855: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8856: double agec; /* generic age */
1.302 brouard 8857: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 8858: double *popeffectif,*popcount;
8859: double ***p3mat;
8860: /* double ***mobaverage; */
8861: char fileresfb[FILENAMELENGTH];
8862:
1.268 brouard 8863: agelim=AGEINF;
1.267 brouard 8864: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8865: in each health status at the date of interview (if between dateprev1 and dateprev2).
8866: We still use firstpass and lastpass as another selection.
8867: */
8868: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8869: /* firstpass, lastpass, stepm, weightopt, model); */
8870:
8871: /*Do we need to compute prevalence again?*/
8872:
8873: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8874:
8875: strcpy(fileresfb,"FB_");
8876: strcat(fileresfb,fileresu);
8877: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8878: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8879: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8880: }
8881: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8882: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8883:
8884: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8885:
8886:
8887: stepsize=(int) (stepm+YEARM-1)/YEARM;
8888: if (stepm<=12) stepsize=1;
8889: if(estepm < stepm){
8890: printf ("Problem %d lower than %d\n",estepm, stepm);
8891: }
1.270 brouard 8892: else{
8893: hstepm=estepm;
8894: }
8895: if(estepm >= stepm){ /* Yes every two year */
8896: stepsize=2;
8897: }
1.267 brouard 8898:
8899: hstepm=hstepm/stepm;
1.296 brouard 8900: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8901: /* fractional in yp1 *\/ */
8902: /* aintmean=yp; */
8903: /* yp2=modf((yp1*12),&yp); */
8904: /* mintmean=yp; */
8905: /* yp1=modf((yp2*30.5),&yp); */
8906: /* jintmean=yp; */
8907: /* if(jintmean==0) jintmean=1; */
8908: /* if(mintmean==0) jintmean=1; */
1.267 brouard 8909:
8910: i1=pow(2,cptcoveff);
8911: if (cptcovn < 1){i1=1;}
8912:
1.296 brouard 8913: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
8914: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8915:
8916: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8917:
8918: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8919: for(k=1; k<=i1;k++){
8920: if(i1 != 1 && TKresult[nres]!= k)
8921: continue;
8922: if(invalidvarcomb[k]){
8923: printf("\nCombination (%d) projection ignored because no cases \n",k);
8924: continue;
8925: }
1.268 brouard 8926: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8927: for(j=1;j<=cptcoveff;j++) {
8928: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8929: }
8930: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8931: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8932: }
8933: fprintf(ficresfb," yearbproj age");
8934: for(j=1; j<=nlstate+ndeath;j++){
8935: for(i=1; i<=nlstate;i++)
1.268 brouard 8936: fprintf(ficresfb," b%d%d",i,j);
8937: fprintf(ficresfb," b.%d",j);
1.267 brouard 8938: }
1.296 brouard 8939: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 8940: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8941: fprintf(ficresfb,"\n");
1.296 brouard 8942: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 8943: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8944: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8945: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8946: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8947: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8948: nhstepm = nhstepm/hstepm;
8949: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8950: oldm=oldms;savm=savms;
1.268 brouard 8951: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8952: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8953: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8954: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8955: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8956: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8957: for (h=0; h<=nhstepm; h++){
1.268 brouard 8958: if (h*hstepm/YEARM*stepm ==-yearp) {
8959: break;
8960: }
8961: }
8962: fprintf(ficresfb,"\n");
8963: for(j=1;j<=cptcoveff;j++)
8964: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8965: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 8966: for(i=1; i<=nlstate+ndeath;i++) {
8967: ppij=0.;ppi=0.;
8968: for(j=1; j<=nlstate;j++) {
8969: /* if (mobilav==1) */
1.269 brouard 8970: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8971: ppi=ppi+prevacurrent[(int)agec][j][k];
8972: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8973: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8974: /* else { */
8975: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8976: /* } */
1.268 brouard 8977: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8978: } /* end j */
8979: if(ppi <0.99){
8980: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8981: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8982: }
8983: fprintf(ficresfb," %.3f", ppij);
8984: }/* end j */
1.267 brouard 8985: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8986: } /* end agec */
8987: } /* end yearp */
8988: } /* end k */
1.217 brouard 8989:
1.267 brouard 8990: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8991:
1.267 brouard 8992: fclose(ficresfb);
8993: printf("End of Computing Back forecasting \n");
8994: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8995:
1.267 brouard 8996: }
1.217 brouard 8997:
1.269 brouard 8998: /* Variance of prevalence limit: varprlim */
8999: 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 9000: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9001:
9002: char fileresvpl[FILENAMELENGTH];
9003: FILE *ficresvpl;
9004: double **oldm, **savm;
9005: double **varpl; /* Variances of prevalence limits by age */
9006: int i1, k, nres, j ;
9007:
9008: strcpy(fileresvpl,"VPL_");
9009: strcat(fileresvpl,fileresu);
9010: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9011: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9012: exit(0);
9013: }
1.288 brouard 9014: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9015: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9016:
9017: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9018: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9019:
9020: i1=pow(2,cptcoveff);
9021: if (cptcovn < 1){i1=1;}
9022:
9023: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9024: for(k=1; k<=i1;k++){
9025: if(i1 != 1 && TKresult[nres]!= k)
9026: continue;
9027: fprintf(ficresvpl,"\n#****** ");
9028: printf("\n#****** ");
9029: fprintf(ficlog,"\n#****** ");
9030: for(j=1;j<=cptcoveff;j++) {
9031: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9032: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9033: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9034: }
9035: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9036: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9037: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9038: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9039: }
9040: fprintf(ficresvpl,"******\n");
9041: printf("******\n");
9042: fprintf(ficlog,"******\n");
9043:
9044: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9045: oldm=oldms;savm=savms;
9046: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9047: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9048: /*}*/
9049: }
9050:
9051: fclose(ficresvpl);
1.288 brouard 9052: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9053: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9054:
9055: }
9056: /* Variance of back prevalence: varbprlim */
9057: 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){
9058: /*------- Variance of back (stable) prevalence------*/
9059:
9060: char fileresvbl[FILENAMELENGTH];
9061: FILE *ficresvbl;
9062:
9063: double **oldm, **savm;
9064: double **varbpl; /* Variances of back prevalence limits by age */
9065: int i1, k, nres, j ;
9066:
9067: strcpy(fileresvbl,"VBL_");
9068: strcat(fileresvbl,fileresu);
9069: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9070: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9071: exit(0);
9072: }
9073: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9074: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9075:
9076:
9077: i1=pow(2,cptcoveff);
9078: if (cptcovn < 1){i1=1;}
9079:
9080: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9081: for(k=1; k<=i1;k++){
9082: if(i1 != 1 && TKresult[nres]!= k)
9083: continue;
9084: fprintf(ficresvbl,"\n#****** ");
9085: printf("\n#****** ");
9086: fprintf(ficlog,"\n#****** ");
9087: for(j=1;j<=cptcoveff;j++) {
9088: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9089: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9090: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9091: }
9092: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9093: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9094: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9095: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9096: }
9097: fprintf(ficresvbl,"******\n");
9098: printf("******\n");
9099: fprintf(ficlog,"******\n");
9100:
9101: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9102: oldm=oldms;savm=savms;
9103:
9104: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9105: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9106: /*}*/
9107: }
9108:
9109: fclose(ficresvbl);
9110: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9111: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9112:
9113: } /* End of varbprlim */
9114:
1.126 brouard 9115: /************** Forecasting *****not tested NB*************/
1.227 brouard 9116: /* 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 9117:
1.227 brouard 9118: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9119: /* int *popage; */
9120: /* double calagedatem, agelim, kk1, kk2; */
9121: /* double *popeffectif,*popcount; */
9122: /* double ***p3mat,***tabpop,***tabpopprev; */
9123: /* /\* double ***mobaverage; *\/ */
9124: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9125:
1.227 brouard 9126: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9127: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9128: /* agelim=AGESUP; */
9129: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9130:
1.227 brouard 9131: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9132:
9133:
1.227 brouard 9134: /* strcpy(filerespop,"POP_"); */
9135: /* strcat(filerespop,fileresu); */
9136: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9137: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9138: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9139: /* } */
9140: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9141: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9142:
1.227 brouard 9143: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9144:
1.227 brouard 9145: /* /\* if (mobilav!=0) { *\/ */
9146: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9147: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9148: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9149: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9150: /* /\* } *\/ */
9151: /* /\* } *\/ */
1.126 brouard 9152:
1.227 brouard 9153: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9154: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9155:
1.227 brouard 9156: /* agelim=AGESUP; */
1.126 brouard 9157:
1.227 brouard 9158: /* hstepm=1; */
9159: /* hstepm=hstepm/stepm; */
1.218 brouard 9160:
1.227 brouard 9161: /* if (popforecast==1) { */
9162: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9163: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9164: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9165: /* } */
9166: /* popage=ivector(0,AGESUP); */
9167: /* popeffectif=vector(0,AGESUP); */
9168: /* popcount=vector(0,AGESUP); */
1.126 brouard 9169:
1.227 brouard 9170: /* i=1; */
9171: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9172:
1.227 brouard 9173: /* imx=i; */
9174: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9175: /* } */
1.218 brouard 9176:
1.227 brouard 9177: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9178: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9179: /* k=k+1; */
9180: /* fprintf(ficrespop,"\n#******"); */
9181: /* for(j=1;j<=cptcoveff;j++) { */
9182: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9183: /* } */
9184: /* fprintf(ficrespop,"******\n"); */
9185: /* fprintf(ficrespop,"# Age"); */
9186: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9187: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9188:
1.227 brouard 9189: /* for (cpt=0; cpt<=0;cpt++) { */
9190: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9191:
1.227 brouard 9192: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9193: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9194: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9195:
1.227 brouard 9196: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9197: /* oldm=oldms;savm=savms; */
9198: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9199:
1.227 brouard 9200: /* for (h=0; h<=nhstepm; h++){ */
9201: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9202: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9203: /* } */
9204: /* for(j=1; j<=nlstate+ndeath;j++) { */
9205: /* kk1=0.;kk2=0; */
9206: /* for(i=1; i<=nlstate;i++) { */
9207: /* if (mobilav==1) */
9208: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9209: /* else { */
9210: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9211: /* } */
9212: /* } */
9213: /* if (h==(int)(calagedatem+12*cpt)){ */
9214: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9215: /* /\*fprintf(ficrespop," %.3f", kk1); */
9216: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9217: /* } */
9218: /* } */
9219: /* for(i=1; i<=nlstate;i++){ */
9220: /* kk1=0.; */
9221: /* for(j=1; j<=nlstate;j++){ */
9222: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9223: /* } */
9224: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9225: /* } */
1.218 brouard 9226:
1.227 brouard 9227: /* if (h==(int)(calagedatem+12*cpt)) */
9228: /* for(j=1; j<=nlstate;j++) */
9229: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9230: /* } */
9231: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9232: /* } */
9233: /* } */
1.218 brouard 9234:
1.227 brouard 9235: /* /\******\/ */
1.218 brouard 9236:
1.227 brouard 9237: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9238: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9239: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9240: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9241: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9242:
1.227 brouard 9243: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9244: /* oldm=oldms;savm=savms; */
9245: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9246: /* for (h=0; h<=nhstepm; h++){ */
9247: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9248: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9249: /* } */
9250: /* for(j=1; j<=nlstate+ndeath;j++) { */
9251: /* kk1=0.;kk2=0; */
9252: /* for(i=1; i<=nlstate;i++) { */
9253: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9254: /* } */
9255: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9256: /* } */
9257: /* } */
9258: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9259: /* } */
9260: /* } */
9261: /* } */
9262: /* } */
1.218 brouard 9263:
1.227 brouard 9264: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9265:
1.227 brouard 9266: /* if (popforecast==1) { */
9267: /* free_ivector(popage,0,AGESUP); */
9268: /* free_vector(popeffectif,0,AGESUP); */
9269: /* free_vector(popcount,0,AGESUP); */
9270: /* } */
9271: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9272: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9273: /* fclose(ficrespop); */
9274: /* } /\* End of popforecast *\/ */
1.218 brouard 9275:
1.126 brouard 9276: int fileappend(FILE *fichier, char *optionfich)
9277: {
9278: if((fichier=fopen(optionfich,"a"))==NULL) {
9279: printf("Problem with file: %s\n", optionfich);
9280: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9281: return (0);
9282: }
9283: fflush(fichier);
9284: return (1);
9285: }
9286:
9287:
9288: /**************** function prwizard **********************/
9289: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9290: {
9291:
9292: /* Wizard to print covariance matrix template */
9293:
1.164 brouard 9294: char ca[32], cb[32];
9295: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9296: int numlinepar;
9297:
9298: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9299: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9300: for(i=1; i <=nlstate; i++){
9301: jj=0;
9302: for(j=1; j <=nlstate+ndeath; j++){
9303: if(j==i) continue;
9304: jj++;
9305: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9306: printf("%1d%1d",i,j);
9307: fprintf(ficparo,"%1d%1d",i,j);
9308: for(k=1; k<=ncovmodel;k++){
9309: /* printf(" %lf",param[i][j][k]); */
9310: /* fprintf(ficparo," %lf",param[i][j][k]); */
9311: printf(" 0.");
9312: fprintf(ficparo," 0.");
9313: }
9314: printf("\n");
9315: fprintf(ficparo,"\n");
9316: }
9317: }
9318: printf("# Scales (for hessian or gradient estimation)\n");
9319: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9320: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9321: for(i=1; i <=nlstate; i++){
9322: jj=0;
9323: for(j=1; j <=nlstate+ndeath; j++){
9324: if(j==i) continue;
9325: jj++;
9326: fprintf(ficparo,"%1d%1d",i,j);
9327: printf("%1d%1d",i,j);
9328: fflush(stdout);
9329: for(k=1; k<=ncovmodel;k++){
9330: /* printf(" %le",delti3[i][j][k]); */
9331: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9332: printf(" 0.");
9333: fprintf(ficparo," 0.");
9334: }
9335: numlinepar++;
9336: printf("\n");
9337: fprintf(ficparo,"\n");
9338: }
9339: }
9340: printf("# Covariance matrix\n");
9341: /* # 121 Var(a12)\n\ */
9342: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9343: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9344: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9345: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9346: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9347: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9348: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9349: fflush(stdout);
9350: fprintf(ficparo,"# Covariance matrix\n");
9351: /* # 121 Var(a12)\n\ */
9352: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9353: /* # ...\n\ */
9354: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9355:
9356: for(itimes=1;itimes<=2;itimes++){
9357: jj=0;
9358: for(i=1; i <=nlstate; i++){
9359: for(j=1; j <=nlstate+ndeath; j++){
9360: if(j==i) continue;
9361: for(k=1; k<=ncovmodel;k++){
9362: jj++;
9363: ca[0]= k+'a'-1;ca[1]='\0';
9364: if(itimes==1){
9365: printf("#%1d%1d%d",i,j,k);
9366: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9367: }else{
9368: printf("%1d%1d%d",i,j,k);
9369: fprintf(ficparo,"%1d%1d%d",i,j,k);
9370: /* printf(" %.5le",matcov[i][j]); */
9371: }
9372: ll=0;
9373: for(li=1;li <=nlstate; li++){
9374: for(lj=1;lj <=nlstate+ndeath; lj++){
9375: if(lj==li) continue;
9376: for(lk=1;lk<=ncovmodel;lk++){
9377: ll++;
9378: if(ll<=jj){
9379: cb[0]= lk +'a'-1;cb[1]='\0';
9380: if(ll<jj){
9381: if(itimes==1){
9382: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9383: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9384: }else{
9385: printf(" 0.");
9386: fprintf(ficparo," 0.");
9387: }
9388: }else{
9389: if(itimes==1){
9390: printf(" Var(%s%1d%1d)",ca,i,j);
9391: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9392: }else{
9393: printf(" 0.");
9394: fprintf(ficparo," 0.");
9395: }
9396: }
9397: }
9398: } /* end lk */
9399: } /* end lj */
9400: } /* end li */
9401: printf("\n");
9402: fprintf(ficparo,"\n");
9403: numlinepar++;
9404: } /* end k*/
9405: } /*end j */
9406: } /* end i */
9407: } /* end itimes */
9408:
9409: } /* end of prwizard */
9410: /******************* Gompertz Likelihood ******************************/
9411: double gompertz(double x[])
9412: {
1.302 brouard 9413: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9414: int i,n=0; /* n is the size of the sample */
9415:
1.220 brouard 9416: for (i=1;i<=imx ; i++) {
1.126 brouard 9417: sump=sump+weight[i];
9418: /* sump=sump+1;*/
9419: num=num+1;
9420: }
1.302 brouard 9421: L=0.0;
9422: /* agegomp=AGEGOMP; */
1.126 brouard 9423: /* for (i=0; i<=imx; i++)
9424: 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]);*/
9425:
1.302 brouard 9426: for (i=1;i<=imx ; i++) {
9427: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9428: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9429: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9430: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9431: * +
9432: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9433: */
9434: if (wav[i] > 1 || agedc[i] < AGESUP) {
9435: if (cens[i] == 1){
9436: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9437: } else if (cens[i] == 0){
1.126 brouard 9438: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9439: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9440: } else
9441: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9442: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9443: L=L+A*weight[i];
1.126 brouard 9444: /* 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 9445: }
9446: }
1.126 brouard 9447:
1.302 brouard 9448: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9449:
9450: return -2*L*num/sump;
9451: }
9452:
1.136 brouard 9453: #ifdef GSL
9454: /******************* Gompertz_f Likelihood ******************************/
9455: double gompertz_f(const gsl_vector *v, void *params)
9456: {
1.302 brouard 9457: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9458: double *x= (double *) v->data;
9459: int i,n=0; /* n is the size of the sample */
9460:
9461: for (i=0;i<=imx-1 ; i++) {
9462: sump=sump+weight[i];
9463: /* sump=sump+1;*/
9464: num=num+1;
9465: }
9466:
9467:
9468: /* for (i=0; i<=imx; i++)
9469: 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]);*/
9470: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9471: for (i=1;i<=imx ; i++)
9472: {
9473: if (cens[i] == 1 && wav[i]>1)
9474: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9475:
9476: if (cens[i] == 0 && wav[i]>1)
9477: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9478: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9479:
9480: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9481: if (wav[i] > 1 ) { /* ??? */
9482: LL=LL+A*weight[i];
9483: /* 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]);*/
9484: }
9485: }
9486:
9487: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9488: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9489:
9490: return -2*LL*num/sump;
9491: }
9492: #endif
9493:
1.126 brouard 9494: /******************* Printing html file ***********/
1.201 brouard 9495: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9496: int lastpass, int stepm, int weightopt, char model[],\
9497: int imx, double p[],double **matcov,double agemortsup){
9498: int i,k;
9499:
9500: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9501: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9502: for (i=1;i<=2;i++)
9503: 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 9504: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9505: fprintf(fichtm,"</ul>");
9506:
9507: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9508:
9509: 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>");
9510:
9511: for (k=agegomp;k<(agemortsup-2);k++)
9512: 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]);
9513:
9514:
9515: fflush(fichtm);
9516: }
9517:
9518: /******************* Gnuplot file **************/
1.201 brouard 9519: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9520:
9521: char dirfileres[132],optfileres[132];
1.164 brouard 9522:
1.126 brouard 9523: int ng;
9524:
9525:
9526: /*#ifdef windows */
9527: fprintf(ficgp,"cd \"%s\" \n",pathc);
9528: /*#endif */
9529:
9530:
9531: strcpy(dirfileres,optionfilefiname);
9532: strcpy(optfileres,"vpl");
1.199 brouard 9533: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9534: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9535: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9536: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9537: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9538:
9539: }
9540:
1.136 brouard 9541: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9542: {
1.126 brouard 9543:
1.136 brouard 9544: /*-------- data file ----------*/
9545: FILE *fic;
9546: char dummy[]=" ";
1.240 brouard 9547: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9548: int lstra;
1.136 brouard 9549: int linei, month, year,iout;
1.302 brouard 9550: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9551: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9552: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9553: char *stratrunc;
1.223 brouard 9554:
1.240 brouard 9555: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9556: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9557:
1.240 brouard 9558: for(v=1; v <=ncovcol;v++){
9559: DummyV[v]=0;
9560: FixedV[v]=0;
9561: }
9562: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9563: DummyV[v]=1;
9564: FixedV[v]=0;
9565: }
9566: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9567: DummyV[v]=0;
9568: FixedV[v]=1;
9569: }
9570: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9571: DummyV[v]=1;
9572: FixedV[v]=1;
9573: }
9574: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9575: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9576: 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]);
9577: }
1.126 brouard 9578:
1.136 brouard 9579: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9580: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9581: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9582: }
1.126 brouard 9583:
1.302 brouard 9584: /* Is it a BOM UTF-8 Windows file? */
9585: /* First data line */
9586: linei=0;
9587: while(fgets(line, MAXLINE, fic)) {
9588: noffset=0;
9589: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9590: {
9591: noffset=noffset+3;
9592: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9593: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9594: fflush(ficlog); return 1;
9595: }
9596: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9597: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9598: {
9599: noffset=noffset+2;
1.304 brouard 9600: 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);
9601: 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 9602: fflush(ficlog); return 1;
9603: }
9604: else if( line[0] == 0 && line[1] == 0)
9605: {
9606: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9607: noffset=noffset+4;
1.304 brouard 9608: 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);
9609: 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 9610: fflush(ficlog); return 1;
9611: }
9612: } else{
9613: ;/*printf(" Not a BOM file\n");*/
9614: }
9615: /* If line starts with a # it is a comment */
9616: if (line[noffset] == '#') {
9617: linei=linei+1;
9618: break;
9619: }else{
9620: break;
9621: }
9622: }
9623: fclose(fic);
9624: if((fic=fopen(datafile,"r"))==NULL) {
9625: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9626: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9627: }
9628: /* Not a Bom file */
9629:
1.136 brouard 9630: i=1;
9631: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9632: linei=linei+1;
9633: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9634: if(line[j] == '\t')
9635: line[j] = ' ';
9636: }
9637: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9638: ;
9639: };
9640: line[j+1]=0; /* Trims blanks at end of line */
9641: if(line[0]=='#'){
9642: fprintf(ficlog,"Comment line\n%s\n",line);
9643: printf("Comment line\n%s\n",line);
9644: continue;
9645: }
9646: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9647: strcpy(line, linetmp);
1.223 brouard 9648:
9649: /* Loops on waves */
9650: for (j=maxwav;j>=1;j--){
9651: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9652: cutv(stra, strb, line, ' ');
9653: if(strb[0]=='.') { /* Missing value */
9654: lval=-1;
9655: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9656: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9657: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9658: 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);
9659: 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);
9660: return 1;
9661: }
9662: }else{
9663: errno=0;
9664: /* what_kind_of_number(strb); */
9665: dval=strtod(strb,&endptr);
9666: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9667: /* if(strb != endptr && *endptr == '\0') */
9668: /* dval=dlval; */
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 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);
9672: 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);
9673: return 1;
9674: }
9675: cotqvar[j][iv][i]=dval;
9676: cotvar[j][ntv+iv][i]=dval;
9677: }
9678: strcpy(line,stra);
1.223 brouard 9679: }/* end loop ntqv */
1.225 brouard 9680:
1.223 brouard 9681: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9682: cutv(stra, strb, line, ' ');
9683: if(strb[0]=='.') { /* Missing value */
9684: lval=-1;
9685: }else{
9686: errno=0;
9687: lval=strtol(strb,&endptr,10);
9688: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9689: if( strb[0]=='\0' || (*endptr != '\0')){
9690: 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);
9691: 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);
9692: return 1;
9693: }
9694: }
9695: if(lval <-1 || lval >1){
9696: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9697: 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 9698: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9699: For example, for multinomial values like 1, 2 and 3,\n \
9700: build V1=0 V2=0 for the reference value (1),\n \
9701: V1=1 V2=0 for (2) \n \
1.223 brouard 9702: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9703: output of IMaCh is often meaningless.\n \
1.319 brouard 9704: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 9705: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9706: 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 9707: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9708: For example, for multinomial values like 1, 2 and 3,\n \
9709: build V1=0 V2=0 for the reference value (1),\n \
9710: V1=1 V2=0 for (2) \n \
1.223 brouard 9711: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9712: output of IMaCh is often meaningless.\n \
1.319 brouard 9713: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 9714: return 1;
9715: }
9716: cotvar[j][iv][i]=(double)(lval);
9717: strcpy(line,stra);
1.223 brouard 9718: }/* end loop ntv */
1.225 brouard 9719:
1.223 brouard 9720: /* Statuses at wave */
1.137 brouard 9721: cutv(stra, strb, line, ' ');
1.223 brouard 9722: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9723: lval=-1;
1.136 brouard 9724: }else{
1.238 brouard 9725: errno=0;
9726: lval=strtol(strb,&endptr,10);
9727: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9728: if( strb[0]=='\0' || (*endptr != '\0')){
9729: 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);
9730: 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);
9731: return 1;
9732: }
1.136 brouard 9733: }
1.225 brouard 9734:
1.136 brouard 9735: s[j][i]=lval;
1.225 brouard 9736:
1.223 brouard 9737: /* Date of Interview */
1.136 brouard 9738: strcpy(line,stra);
9739: cutv(stra, strb,line,' ');
1.169 brouard 9740: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9741: }
1.169 brouard 9742: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9743: month=99;
9744: year=9999;
1.136 brouard 9745: }else{
1.225 brouard 9746: 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);
9747: 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);
9748: return 1;
1.136 brouard 9749: }
9750: anint[j][i]= (double) year;
1.302 brouard 9751: mint[j][i]= (double)month;
9752: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
9753: /* 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]); */
9754: /* 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]); */
9755: /* } */
1.136 brouard 9756: strcpy(line,stra);
1.223 brouard 9757: } /* End loop on waves */
1.225 brouard 9758:
1.223 brouard 9759: /* Date of death */
1.136 brouard 9760: cutv(stra, strb,line,' ');
1.169 brouard 9761: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9762: }
1.169 brouard 9763: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9764: month=99;
9765: year=9999;
9766: }else{
1.141 brouard 9767: 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 9768: 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);
9769: return 1;
1.136 brouard 9770: }
9771: andc[i]=(double) year;
9772: moisdc[i]=(double) month;
9773: strcpy(line,stra);
9774:
1.223 brouard 9775: /* Date of birth */
1.136 brouard 9776: cutv(stra, strb,line,' ');
1.169 brouard 9777: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9778: }
1.169 brouard 9779: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9780: month=99;
9781: year=9999;
9782: }else{
1.141 brouard 9783: 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);
9784: 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 9785: return 1;
1.136 brouard 9786: }
9787: if (year==9999) {
1.141 brouard 9788: 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);
9789: 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 9790: return 1;
9791:
1.136 brouard 9792: }
9793: annais[i]=(double)(year);
1.302 brouard 9794: moisnais[i]=(double)(month);
9795: for (j=1;j<=maxwav;j++){
9796: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
9797: 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]);
9798: 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]);
9799: }
9800: }
9801:
1.136 brouard 9802: strcpy(line,stra);
1.225 brouard 9803:
1.223 brouard 9804: /* Sample weight */
1.136 brouard 9805: cutv(stra, strb,line,' ');
9806: errno=0;
9807: dval=strtod(strb,&endptr);
9808: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9809: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9810: 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 9811: fflush(ficlog);
9812: return 1;
9813: }
9814: weight[i]=dval;
9815: strcpy(line,stra);
1.225 brouard 9816:
1.223 brouard 9817: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9818: cutv(stra, strb, line, ' ');
9819: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9820: lval=-1;
1.311 brouard 9821: coqvar[iv][i]=NAN;
9822: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 9823: }else{
1.225 brouard 9824: errno=0;
9825: /* what_kind_of_number(strb); */
9826: dval=strtod(strb,&endptr);
9827: /* if(strb != endptr && *endptr == '\0') */
9828: /* dval=dlval; */
9829: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9830: if( strb[0]=='\0' || (*endptr != '\0')){
9831: 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);
9832: 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);
9833: return 1;
9834: }
9835: coqvar[iv][i]=dval;
1.226 brouard 9836: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9837: }
9838: strcpy(line,stra);
9839: }/* end loop nqv */
1.136 brouard 9840:
1.223 brouard 9841: /* Covariate values */
1.136 brouard 9842: for (j=ncovcol;j>=1;j--){
9843: cutv(stra, strb,line,' ');
1.223 brouard 9844: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9845: lval=-1;
1.136 brouard 9846: }else{
1.225 brouard 9847: errno=0;
9848: lval=strtol(strb,&endptr,10);
9849: if( strb[0]=='\0' || (*endptr != '\0')){
9850: 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);
9851: 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);
9852: return 1;
9853: }
1.136 brouard 9854: }
9855: if(lval <-1 || lval >1){
1.225 brouard 9856: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9857: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9858: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9859: For example, for multinomial values like 1, 2 and 3,\n \
9860: build V1=0 V2=0 for the reference value (1),\n \
9861: V1=1 V2=0 for (2) \n \
1.136 brouard 9862: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9863: output of IMaCh is often meaningless.\n \
1.136 brouard 9864: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9865: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9866: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9867: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9868: For example, for multinomial values like 1, 2 and 3,\n \
9869: build V1=0 V2=0 for the reference value (1),\n \
9870: V1=1 V2=0 for (2) \n \
1.136 brouard 9871: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9872: output of IMaCh is often meaningless.\n \
1.136 brouard 9873: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9874: return 1;
1.136 brouard 9875: }
9876: covar[j][i]=(double)(lval);
9877: strcpy(line,stra);
9878: }
9879: lstra=strlen(stra);
1.225 brouard 9880:
1.136 brouard 9881: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9882: stratrunc = &(stra[lstra-9]);
9883: num[i]=atol(stratrunc);
9884: }
9885: else
9886: num[i]=atol(stra);
9887: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9888: 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;}*/
9889:
9890: i=i+1;
9891: } /* End loop reading data */
1.225 brouard 9892:
1.136 brouard 9893: *imax=i-1; /* Number of individuals */
9894: fclose(fic);
1.225 brouard 9895:
1.136 brouard 9896: return (0);
1.164 brouard 9897: /* endread: */
1.225 brouard 9898: printf("Exiting readdata: ");
9899: fclose(fic);
9900: return (1);
1.223 brouard 9901: }
1.126 brouard 9902:
1.234 brouard 9903: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9904: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9905: while (*p2 == ' ')
1.234 brouard 9906: p2++;
9907: /* while ((*p1++ = *p2++) !=0) */
9908: /* ; */
9909: /* do */
9910: /* while (*p2 == ' ') */
9911: /* p2++; */
9912: /* while (*p1++ == *p2++); */
9913: *stri=p2;
1.145 brouard 9914: }
9915:
1.235 brouard 9916: int decoderesult ( char resultline[], int nres)
1.230 brouard 9917: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9918: {
1.235 brouard 9919: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9920: char resultsav[MAXLINE];
1.234 brouard 9921: int resultmodel[MAXLINE];
9922: int modelresult[MAXLINE];
1.230 brouard 9923: char stra[80], strb[80], strc[80], strd[80],stre[80];
9924:
1.234 brouard 9925: removefirstspace(&resultline);
1.230 brouard 9926:
9927: if (strstr(resultline,"v") !=0){
9928: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9929: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9930: return 1;
9931: }
9932: trimbb(resultsav, resultline);
9933: if (strlen(resultsav) >1){
9934: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9935: }
1.253 brouard 9936: if(j == 0){ /* Resultline but no = */
9937: TKresult[nres]=0; /* Combination for the nresult and the model */
9938: return (0);
9939: }
1.234 brouard 9940: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.318 brouard 9941: 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 9942: 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 9943: }
9944: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9945: if(nbocc(resultsav,'=') >1){
1.318 brouard 9946: 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" */
9947: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.234 brouard 9948: }else
9949: cutl(strc,strd,resultsav,'=');
1.318 brouard 9950: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 9951:
1.230 brouard 9952: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 9953: 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 9954: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9955: /* cptcovsel++; */
9956: if (nbocc(stra,'=') >0)
9957: strcpy(resultsav,stra); /* and analyzes it */
9958: }
1.235 brouard 9959: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 9960: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on model. model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9961: 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 9962: match=0;
1.318 brouard 9963: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9964: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9965: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 9966: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 9967: break;
9968: }
9969: }
9970: if(match == 0){
1.310 brouard 9971: printf("Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9972: fprintf(ficlog,"Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9973: return 1;
1.234 brouard 9974: }
9975: }
9976: }
1.235 brouard 9977: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 9978: 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 9979: match=0;
1.318 brouard 9980: 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 9981: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9982: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.318 brouard 9983: 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 9984: ++match;
9985: }
9986: }
9987: }
9988: if(match == 0){
9989: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
1.310 brouard 9990: fprintf(ficlog,"Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9991: return 1;
1.234 brouard 9992: }else if(match > 1){
9993: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 9994: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9995: return 1;
1.234 brouard 9996: }
9997: }
1.235 brouard 9998:
1.234 brouard 9999: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10000: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10001: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10002: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
10003: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10004: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10005: /* 1 0 0 0 */
10006: /* 2 1 0 0 */
10007: /* 3 0 1 0 */
10008: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
10009: /* 5 0 0 1 */
10010: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
10011: /* 7 0 1 1 */
10012: /* 8 1 1 1 */
1.237 brouard 10013: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10014: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10015: /* V5*age V5 known which value for nres? */
10016: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.318 brouard 10017: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* loop on model line */
1.235 brouard 10018: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 10019: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 10020: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
10021: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 10022: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
10023: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
10024: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 10025: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
10026: k4++;;
10027: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
1.318 brouard 10028: k3q= resultmodel[k1]; /* resultmodel[1(V5)] = 25.1=k3q */
10029: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.237 brouard 10030: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10031: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
10032: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 10033: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
10034: k4q++;;
10035: }
10036: }
1.234 brouard 10037:
1.235 brouard 10038: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 10039: return (0);
10040: }
1.235 brouard 10041:
1.230 brouard 10042: int decodemodel( char model[], int lastobs)
10043: /**< This routine decodes the model and returns:
1.224 brouard 10044: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10045: * - nagesqr = 1 if age*age in the model, otherwise 0.
10046: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10047: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10048: * - cptcovage number of covariates with age*products =2
10049: * - cptcovs number of simple covariates
10050: * - 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
10051: * which is a new column after the 9 (ncovcol) variables.
1.319 brouard 10052: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10053: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10054: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10055: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10056: */
1.319 brouard 10057: /* 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 10058: {
1.238 brouard 10059: int i, j, k, ks, v;
1.227 brouard 10060: int j1, k1, k2, k3, k4;
1.136 brouard 10061: char modelsav[80];
1.145 brouard 10062: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10063: char *strpt;
1.136 brouard 10064:
1.145 brouard 10065: /*removespace(model);*/
1.136 brouard 10066: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10067: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10068: if (strstr(model,"AGE") !=0){
1.192 brouard 10069: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10070: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10071: return 1;
10072: }
1.141 brouard 10073: if (strstr(model,"v") !=0){
10074: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
10075: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
10076: return 1;
10077: }
1.187 brouard 10078: strcpy(modelsav,model);
10079: if ((strpt=strstr(model,"age*age")) !=0){
10080: printf(" strpt=%s, model=%s\n",strpt, model);
10081: if(strpt != model){
1.234 brouard 10082: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10083: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10084: corresponding column of parameters.\n",model);
1.234 brouard 10085: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10086: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10087: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10088: return 1;
1.225 brouard 10089: }
1.187 brouard 10090: nagesqr=1;
10091: if (strstr(model,"+age*age") !=0)
1.234 brouard 10092: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10093: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10094: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10095: else
1.234 brouard 10096: substrchaine(modelsav, model, "age*age");
1.187 brouard 10097: }else
10098: nagesqr=0;
10099: if (strlen(modelsav) >1){
10100: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10101: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10102: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10103: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10104: * cst, age and age*age
10105: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10106: /* including age products which are counted in cptcovage.
10107: * but the covariates which are products must be treated
10108: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10109: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10110: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10111:
10112:
1.187 brouard 10113: /* Design
10114: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10115: * < ncovcol=8 >
10116: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10117: * k= 1 2 3 4 5 6 7 8
10118: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10119: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10120: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10121: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10122: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10123: * Tage[++cptcovage]=k
10124: * if products, new covar are created after ncovcol with k1
10125: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10126: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10127: * 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
10128: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10129: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10130: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10131: * < ncovcol=8 >
10132: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10133: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10134: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10135: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10136: * p Tprod[1]@2={ 6, 5}
10137: *p Tvard[1][1]@4= {7, 8, 5, 6}
10138: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10139: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10140: *How to reorganize? Tvars(orted)
1.187 brouard 10141: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10142: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10143: * {2, 1, 4, 8, 5, 6, 3, 7}
10144: * Struct []
10145: */
1.225 brouard 10146:
1.187 brouard 10147: /* This loop fills the array Tvar from the string 'model'.*/
10148: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10149: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10150: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10151: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10152: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10153: /* k=1 Tvar[1]=2 (from V2) */
10154: /* k=5 Tvar[5] */
10155: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10156: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10157: /* } */
1.198 brouard 10158: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10159: /*
10160: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10161: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10162: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10163: }
1.187 brouard 10164: cptcovage=0;
1.319 brouard 10165: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10166: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10167: 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" */
10168: if (nbocc(modelsav,'+')==0)
10169: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10170: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10171: /*scanf("%d",i);*/
1.319 brouard 10172: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10173: 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 10174: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10175: /* covar is not filled and then is empty */
10176: cptcovprod--;
10177: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10178: 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 10179: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10180: cptcovage++; /* Counts the number of covariates which include age as a product */
10181: 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 10182: /*printf("stre=%s ", stre);*/
10183: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10184: cptcovprod--;
10185: cutl(stre,strb,strc,'V');
10186: Tvar[k]=atoi(stre);
10187: Typevar[k]=1; /* 1 for age product */
10188: cptcovage++;
10189: Tage[cptcovage]=k;
10190: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10191: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10192: cptcovn++;
10193: cptcovprodnoage++;k1++;
10194: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10195: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10196: because this model-covariate is a construction we invent a new column
10197: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.319 brouard 10198: If already ncovcol=4 and model=V2 + V1 +V1*V4 +age*V3 +V3*V2
10199: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
10200: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */
1.234 brouard 10201: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10202: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10203: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10204: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10205: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
10206: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
10207: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10208: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10209: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10210: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10211: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10212: for (i=1; i<=lastobs;i++){
10213: /* Computes the new covariate which is a product of
10214: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10215: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10216: }
10217: } /* End age is not in the model */
10218: } /* End if model includes a product */
1.319 brouard 10219: else { /* not a product */
1.234 brouard 10220: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10221: /* scanf("%d",i);*/
10222: cutl(strd,strc,strb,'V');
10223: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10224: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10225: Tvar[k]=atoi(strd);
10226: Typevar[k]=0; /* 0 for simple covariates */
10227: }
10228: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10229: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10230: scanf("%d",i);*/
1.187 brouard 10231: } /* end of loop + on total covariates */
10232: } /* end if strlen(modelsave == 0) age*age might exist */
10233: } /* end if strlen(model == 0) */
1.136 brouard 10234:
10235: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10236: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10237:
1.136 brouard 10238: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10239: printf("cptcovprod=%d ", cptcovprod);
10240: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10241: scanf("%d ",i);*/
10242:
10243:
1.230 brouard 10244: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10245: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10246: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10247: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10248: k = 1 2 3 4 5 6 7 8 9
10249: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 10250: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 10251: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10252: Dummy[k] 1 0 0 0 3 1 1 2 3
10253: Tmodelind[combination of covar]=k;
1.225 brouard 10254: */
10255: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10256: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10257: /* 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 10258: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 10259: printf("Model=1+age+%s\n\
1.227 brouard 10260: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10261: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10262: 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 10263: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10264: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10265: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10266: 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 10267: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10268: 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 */
10269: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10270: Fixed[k]= 0;
10271: Dummy[k]= 0;
1.225 brouard 10272: ncoveff++;
1.232 brouard 10273: ncovf++;
1.234 brouard 10274: nsd++;
10275: modell[k].maintype= FTYPE;
10276: TvarsD[nsd]=Tvar[k];
10277: TvarsDind[nsd]=k;
10278: TvarF[ncovf]=Tvar[k];
10279: TvarFind[ncovf]=k;
10280: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10281: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10282: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10283: Fixed[k]= 0;
10284: Dummy[k]= 0;
10285: ncoveff++;
10286: ncovf++;
10287: modell[k].maintype= FTYPE;
10288: TvarF[ncovf]=Tvar[k];
10289: TvarFind[ncovf]=k;
1.230 brouard 10290: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10291: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10292: }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 10293: Fixed[k]= 0;
10294: Dummy[k]= 1;
1.230 brouard 10295: nqfveff++;
1.234 brouard 10296: modell[k].maintype= FTYPE;
10297: modell[k].subtype= FQ;
10298: nsq++;
10299: TvarsQ[nsq]=Tvar[k];
10300: TvarsQind[nsq]=k;
1.232 brouard 10301: ncovf++;
1.234 brouard 10302: TvarF[ncovf]=Tvar[k];
10303: TvarFind[ncovf]=k;
1.231 brouard 10304: 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 10305: 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 10306: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10307: Fixed[k]= 1;
10308: Dummy[k]= 0;
1.225 brouard 10309: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10310: modell[k].maintype= VTYPE;
10311: modell[k].subtype= VD;
10312: nsd++;
10313: TvarsD[nsd]=Tvar[k];
10314: TvarsDind[nsd]=k;
10315: ncovv++; /* Only simple time varying variables */
10316: TvarV[ncovv]=Tvar[k];
1.242 brouard 10317: 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 10318: 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 */
10319: 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 10320: 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);
10321: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10322: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10323: Fixed[k]= 1;
10324: Dummy[k]= 1;
10325: nqtveff++;
10326: modell[k].maintype= VTYPE;
10327: modell[k].subtype= VQ;
10328: ncovv++; /* Only simple time varying variables */
10329: nsq++;
1.319 brouard 10330: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */
1.234 brouard 10331: TvarsQind[nsq]=k;
10332: TvarV[ncovv]=Tvar[k];
1.242 brouard 10333: 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 10334: 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 */
10335: 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 10336: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10337: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10338: 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 10339: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10340: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10341: ncova++;
10342: TvarA[ncova]=Tvar[k];
10343: TvarAind[ncova]=k;
1.231 brouard 10344: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10345: Fixed[k]= 2;
10346: Dummy[k]= 2;
10347: modell[k].maintype= ATYPE;
10348: modell[k].subtype= APFD;
10349: /* ncoveff++; */
1.227 brouard 10350: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10351: Fixed[k]= 2;
10352: Dummy[k]= 3;
10353: modell[k].maintype= ATYPE;
10354: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10355: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10356: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10357: Fixed[k]= 3;
10358: Dummy[k]= 2;
10359: modell[k].maintype= ATYPE;
10360: modell[k].subtype= APVD; /* Product age * varying dummy */
10361: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10362: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10363: Fixed[k]= 3;
10364: Dummy[k]= 3;
10365: modell[k].maintype= ATYPE;
10366: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10367: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10368: }
10369: }else if (Typevar[k] == 2) { /* product without age */
10370: k1=Tposprod[k];
10371: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10372: if(Tvard[k1][2] <=ncovcol){
10373: Fixed[k]= 1;
10374: Dummy[k]= 0;
10375: modell[k].maintype= FTYPE;
10376: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10377: ncovf++; /* Fixed variables without age */
10378: TvarF[ncovf]=Tvar[k];
10379: TvarFind[ncovf]=k;
10380: }else if(Tvard[k1][2] <=ncovcol+nqv){
10381: Fixed[k]= 0; /* or 2 ?*/
10382: Dummy[k]= 1;
10383: modell[k].maintype= FTYPE;
10384: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10385: ncovf++; /* Varying variables without age */
10386: TvarF[ncovf]=Tvar[k];
10387: TvarFind[ncovf]=k;
10388: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10389: Fixed[k]= 1;
10390: Dummy[k]= 0;
10391: modell[k].maintype= VTYPE;
10392: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10393: ncovv++; /* Varying variables without age */
10394: TvarV[ncovv]=Tvar[k];
10395: TvarVind[ncovv]=k;
10396: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10397: Fixed[k]= 1;
10398: Dummy[k]= 1;
10399: modell[k].maintype= VTYPE;
10400: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10401: ncovv++; /* Varying variables without age */
10402: TvarV[ncovv]=Tvar[k];
10403: TvarVind[ncovv]=k;
10404: }
1.227 brouard 10405: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10406: if(Tvard[k1][2] <=ncovcol){
10407: Fixed[k]= 0; /* or 2 ?*/
10408: Dummy[k]= 1;
10409: modell[k].maintype= FTYPE;
10410: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10411: ncovf++; /* Fixed variables without age */
10412: TvarF[ncovf]=Tvar[k];
10413: TvarFind[ncovf]=k;
10414: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10415: Fixed[k]= 1;
10416: Dummy[k]= 1;
10417: modell[k].maintype= VTYPE;
10418: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10419: ncovv++; /* Varying variables without age */
10420: TvarV[ncovv]=Tvar[k];
10421: TvarVind[ncovv]=k;
10422: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10423: Fixed[k]= 1;
10424: Dummy[k]= 1;
10425: modell[k].maintype= VTYPE;
10426: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10427: ncovv++; /* Varying variables without age */
10428: TvarV[ncovv]=Tvar[k];
10429: TvarVind[ncovv]=k;
10430: ncovv++; /* Varying variables without age */
10431: TvarV[ncovv]=Tvar[k];
10432: TvarVind[ncovv]=k;
10433: }
1.227 brouard 10434: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10435: if(Tvard[k1][2] <=ncovcol){
10436: Fixed[k]= 1;
10437: Dummy[k]= 1;
10438: modell[k].maintype= VTYPE;
10439: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10440: ncovv++; /* Varying variables without age */
10441: TvarV[ncovv]=Tvar[k];
10442: TvarVind[ncovv]=k;
10443: }else if(Tvard[k1][2] <=ncovcol+nqv){
10444: Fixed[k]= 1;
10445: Dummy[k]= 1;
10446: modell[k].maintype= VTYPE;
10447: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10448: ncovv++; /* Varying variables without age */
10449: TvarV[ncovv]=Tvar[k];
10450: TvarVind[ncovv]=k;
10451: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10452: Fixed[k]= 1;
10453: Dummy[k]= 0;
10454: modell[k].maintype= VTYPE;
10455: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10456: ncovv++; /* Varying variables without age */
10457: TvarV[ncovv]=Tvar[k];
10458: TvarVind[ncovv]=k;
10459: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10460: Fixed[k]= 1;
10461: Dummy[k]= 1;
10462: modell[k].maintype= VTYPE;
10463: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10464: ncovv++; /* Varying variables without age */
10465: TvarV[ncovv]=Tvar[k];
10466: TvarVind[ncovv]=k;
10467: }
1.227 brouard 10468: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10469: if(Tvard[k1][2] <=ncovcol){
10470: Fixed[k]= 1;
10471: Dummy[k]= 1;
10472: modell[k].maintype= VTYPE;
10473: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10474: ncovv++; /* Varying variables without age */
10475: TvarV[ncovv]=Tvar[k];
10476: TvarVind[ncovv]=k;
10477: }else if(Tvard[k1][2] <=ncovcol+nqv){
10478: Fixed[k]= 1;
10479: Dummy[k]= 1;
10480: modell[k].maintype= VTYPE;
10481: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10482: ncovv++; /* Varying variables without age */
10483: TvarV[ncovv]=Tvar[k];
10484: TvarVind[ncovv]=k;
10485: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10486: Fixed[k]= 1;
10487: Dummy[k]= 1;
10488: modell[k].maintype= VTYPE;
10489: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10490: ncovv++; /* Varying variables without age */
10491: TvarV[ncovv]=Tvar[k];
10492: TvarVind[ncovv]=k;
10493: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10494: Fixed[k]= 1;
10495: Dummy[k]= 1;
10496: modell[k].maintype= VTYPE;
10497: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10498: ncovv++; /* Varying variables without age */
10499: TvarV[ncovv]=Tvar[k];
10500: TvarVind[ncovv]=k;
10501: }
1.227 brouard 10502: }else{
1.240 brouard 10503: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10504: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10505: } /*end k1*/
1.225 brouard 10506: }else{
1.226 brouard 10507: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10508: 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 10509: }
1.227 brouard 10510: 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 10511: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10512: 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]);
10513: }
10514: /* Searching for doublons in the model */
10515: for(k1=1; k1<= cptcovt;k1++){
10516: for(k2=1; k2 <k1;k2++){
1.285 brouard 10517: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10518: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10519: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10520: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10521: 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]);
10522: 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 10523: return(1);
10524: }
10525: }else if (Typevar[k1] ==2){
10526: k3=Tposprod[k1];
10527: k4=Tposprod[k2];
10528: 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])) ){
10529: 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]]);
10530: 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);
10531: return(1);
10532: }
10533: }
1.227 brouard 10534: }
10535: }
1.225 brouard 10536: }
10537: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10538: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10539: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10540: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10541: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10542: /*endread:*/
1.225 brouard 10543: printf("Exiting decodemodel: ");
10544: return (1);
1.136 brouard 10545: }
10546:
1.169 brouard 10547: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10548: {/* Check ages at death */
1.136 brouard 10549: int i, m;
1.218 brouard 10550: int firstone=0;
10551:
1.136 brouard 10552: for (i=1; i<=imx; i++) {
10553: for(m=2; (m<= maxwav); m++) {
10554: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10555: anint[m][i]=9999;
1.216 brouard 10556: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10557: s[m][i]=-1;
1.136 brouard 10558: }
10559: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10560: *nberr = *nberr + 1;
1.218 brouard 10561: if(firstone == 0){
10562: firstone=1;
1.260 brouard 10563: 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 10564: }
1.262 brouard 10565: 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 10566: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10567: }
10568: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10569: (*nberr)++;
1.259 brouard 10570: 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 10571: 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 10572: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10573: }
10574: }
10575: }
10576:
10577: for (i=1; i<=imx; i++) {
10578: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10579: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10580: 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 10581: if (s[m][i] >= nlstate+1) {
1.169 brouard 10582: if(agedc[i]>0){
10583: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10584: agev[m][i]=agedc[i];
1.214 brouard 10585: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10586: }else {
1.136 brouard 10587: if ((int)andc[i]!=9999){
10588: nbwarn++;
10589: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10590: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10591: agev[m][i]=-1;
10592: }
10593: }
1.169 brouard 10594: } /* agedc > 0 */
1.214 brouard 10595: } /* end if */
1.136 brouard 10596: else if(s[m][i] !=9){ /* Standard case, age in fractional
10597: years but with the precision of a month */
10598: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10599: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10600: agev[m][i]=1;
10601: else if(agev[m][i] < *agemin){
10602: *agemin=agev[m][i];
10603: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10604: }
10605: else if(agev[m][i] >*agemax){
10606: *agemax=agev[m][i];
1.156 brouard 10607: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10608: }
10609: /*agev[m][i]=anint[m][i]-annais[i];*/
10610: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10611: } /* en if 9*/
1.136 brouard 10612: else { /* =9 */
1.214 brouard 10613: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10614: agev[m][i]=1;
10615: s[m][i]=-1;
10616: }
10617: }
1.214 brouard 10618: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10619: agev[m][i]=1;
1.214 brouard 10620: else{
10621: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10622: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10623: agev[m][i]=0;
10624: }
10625: } /* End for lastpass */
10626: }
1.136 brouard 10627:
10628: for (i=1; i<=imx; i++) {
10629: for(m=firstpass; (m<=lastpass); m++){
10630: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10631: (*nberr)++;
1.136 brouard 10632: 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);
10633: 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);
10634: return 1;
10635: }
10636: }
10637: }
10638:
10639: /*for (i=1; i<=imx; i++){
10640: for (m=firstpass; (m<lastpass); m++){
10641: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10642: }
10643:
10644: }*/
10645:
10646:
1.139 brouard 10647: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10648: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10649:
10650: return (0);
1.164 brouard 10651: /* endread:*/
1.136 brouard 10652: printf("Exiting calandcheckages: ");
10653: return (1);
10654: }
10655:
1.172 brouard 10656: #if defined(_MSC_VER)
10657: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10658: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10659: //#include "stdafx.h"
10660: //#include <stdio.h>
10661: //#include <tchar.h>
10662: //#include <windows.h>
10663: //#include <iostream>
10664: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10665:
10666: LPFN_ISWOW64PROCESS fnIsWow64Process;
10667:
10668: BOOL IsWow64()
10669: {
10670: BOOL bIsWow64 = FALSE;
10671:
10672: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10673: // (HANDLE, PBOOL);
10674:
10675: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10676:
10677: HMODULE module = GetModuleHandle(_T("kernel32"));
10678: const char funcName[] = "IsWow64Process";
10679: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10680: GetProcAddress(module, funcName);
10681:
10682: if (NULL != fnIsWow64Process)
10683: {
10684: if (!fnIsWow64Process(GetCurrentProcess(),
10685: &bIsWow64))
10686: //throw std::exception("Unknown error");
10687: printf("Unknown error\n");
10688: }
10689: return bIsWow64 != FALSE;
10690: }
10691: #endif
1.177 brouard 10692:
1.191 brouard 10693: void syscompilerinfo(int logged)
1.292 brouard 10694: {
10695: #include <stdint.h>
10696:
10697: /* #include "syscompilerinfo.h"*/
1.185 brouard 10698: /* command line Intel compiler 32bit windows, XP compatible:*/
10699: /* /GS /W3 /Gy
10700: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10701: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10702: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10703: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10704: */
10705: /* 64 bits */
1.185 brouard 10706: /*
10707: /GS /W3 /Gy
10708: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10709: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10710: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10711: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10712: /* Optimization are useless and O3 is slower than O2 */
10713: /*
10714: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10715: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10716: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10717: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10718: */
1.186 brouard 10719: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10720: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10721: /PDB:"visual studio
10722: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10723: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10724: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10725: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10726: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10727: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10728: uiAccess='false'"
10729: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10730: /NOLOGO /TLBID:1
10731: */
1.292 brouard 10732:
10733:
1.177 brouard 10734: #if defined __INTEL_COMPILER
1.178 brouard 10735: #if defined(__GNUC__)
10736: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10737: #endif
1.177 brouard 10738: #elif defined(__GNUC__)
1.179 brouard 10739: #ifndef __APPLE__
1.174 brouard 10740: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10741: #endif
1.177 brouard 10742: struct utsname sysInfo;
1.178 brouard 10743: int cross = CROSS;
10744: if (cross){
10745: printf("Cross-");
1.191 brouard 10746: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10747: }
1.174 brouard 10748: #endif
10749:
1.191 brouard 10750: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10751: #if defined(__clang__)
1.191 brouard 10752: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10753: #endif
10754: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10755: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10756: #endif
10757: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10758: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10759: #endif
10760: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10761: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10762: #endif
10763: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10764: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10765: #endif
10766: #if defined(_MSC_VER)
1.191 brouard 10767: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10768: #endif
10769: #if defined(__PGI)
1.191 brouard 10770: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10771: #endif
10772: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10773: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10774: #endif
1.191 brouard 10775: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10776:
1.167 brouard 10777: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10778: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10779: // Windows (x64 and x86)
1.191 brouard 10780: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10781: #elif __unix__ // all unices, not all compilers
10782: // Unix
1.191 brouard 10783: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10784: #elif __linux__
10785: // linux
1.191 brouard 10786: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10787: #elif __APPLE__
1.174 brouard 10788: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10789: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10790: #endif
10791:
10792: /* __MINGW32__ */
10793: /* __CYGWIN__ */
10794: /* __MINGW64__ */
10795: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10796: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10797: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10798: /* _WIN64 // Defined for applications for Win64. */
10799: /* _M_X64 // Defined for compilations that target x64 processors. */
10800: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10801:
1.167 brouard 10802: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10803: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10804: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10805: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10806: #else
1.191 brouard 10807: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10808: #endif
10809:
1.169 brouard 10810: #if defined(__GNUC__)
10811: # if defined(__GNUC_PATCHLEVEL__)
10812: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10813: + __GNUC_MINOR__ * 100 \
10814: + __GNUC_PATCHLEVEL__)
10815: # else
10816: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10817: + __GNUC_MINOR__ * 100)
10818: # endif
1.174 brouard 10819: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10820: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10821:
10822: if (uname(&sysInfo) != -1) {
10823: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10824: 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 10825: }
10826: else
10827: perror("uname() error");
1.179 brouard 10828: //#ifndef __INTEL_COMPILER
10829: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10830: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10831: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10832: #endif
1.169 brouard 10833: #endif
1.172 brouard 10834:
1.286 brouard 10835: // void main ()
1.172 brouard 10836: // {
1.169 brouard 10837: #if defined(_MSC_VER)
1.174 brouard 10838: if (IsWow64()){
1.191 brouard 10839: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10840: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10841: }
10842: else{
1.191 brouard 10843: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10844: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10845: }
1.172 brouard 10846: // printf("\nPress Enter to continue...");
10847: // getchar();
10848: // }
10849:
1.169 brouard 10850: #endif
10851:
1.167 brouard 10852:
1.219 brouard 10853: }
1.136 brouard 10854:
1.219 brouard 10855: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10856: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10857: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10858: /* double ftolpl = 1.e-10; */
1.180 brouard 10859: double age, agebase, agelim;
1.203 brouard 10860: double tot;
1.180 brouard 10861:
1.202 brouard 10862: strcpy(filerespl,"PL_");
10863: strcat(filerespl,fileresu);
10864: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10865: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10866: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10867: }
1.288 brouard 10868: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10869: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10870: pstamp(ficrespl);
1.288 brouard 10871: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10872: fprintf(ficrespl,"#Age ");
10873: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10874: fprintf(ficrespl,"\n");
1.180 brouard 10875:
1.219 brouard 10876: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10877:
1.219 brouard 10878: agebase=ageminpar;
10879: agelim=agemaxpar;
1.180 brouard 10880:
1.227 brouard 10881: /* i1=pow(2,ncoveff); */
1.234 brouard 10882: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10883: if (cptcovn < 1){i1=1;}
1.180 brouard 10884:
1.238 brouard 10885: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10886: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10887: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10888: continue;
1.235 brouard 10889:
1.238 brouard 10890: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10891: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10892: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10893: /* k=k+1; */
10894: /* to clean */
10895: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10896: fprintf(ficrespl,"#******");
10897: printf("#******");
10898: fprintf(ficlog,"#******");
10899: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10900: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10901: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10902: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10903: }
10904: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10905: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10906: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10907: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10908: }
10909: fprintf(ficrespl,"******\n");
10910: printf("******\n");
10911: fprintf(ficlog,"******\n");
10912: if(invalidvarcomb[k]){
10913: printf("\nCombination (%d) ignored because no case \n",k);
10914: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10915: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10916: continue;
10917: }
1.219 brouard 10918:
1.238 brouard 10919: fprintf(ficrespl,"#Age ");
10920: for(j=1;j<=cptcoveff;j++) {
10921: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10922: }
10923: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10924: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10925:
1.238 brouard 10926: for (age=agebase; age<=agelim; age++){
10927: /* for (age=agebase; age<=agebase; age++){ */
10928: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10929: fprintf(ficrespl,"%.0f ",age );
10930: for(j=1;j<=cptcoveff;j++)
10931: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10932: tot=0.;
10933: for(i=1; i<=nlstate;i++){
10934: tot += prlim[i][i];
10935: fprintf(ficrespl," %.5f", prlim[i][i]);
10936: }
10937: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10938: } /* Age */
10939: /* was end of cptcod */
10940: } /* cptcov */
10941: } /* nres */
1.219 brouard 10942: return 0;
1.180 brouard 10943: }
10944:
1.218 brouard 10945: 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 10946: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10947:
10948: /* Computes the back prevalence limit for any combination of covariate values
10949: * at any age between ageminpar and agemaxpar
10950: */
1.235 brouard 10951: int i, j, k, i1, nres=0 ;
1.217 brouard 10952: /* double ftolpl = 1.e-10; */
10953: double age, agebase, agelim;
10954: double tot;
1.218 brouard 10955: /* double ***mobaverage; */
10956: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10957:
10958: strcpy(fileresplb,"PLB_");
10959: strcat(fileresplb,fileresu);
10960: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10961: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10962: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10963: }
1.288 brouard 10964: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10965: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10966: pstamp(ficresplb);
1.288 brouard 10967: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10968: fprintf(ficresplb,"#Age ");
10969: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10970: fprintf(ficresplb,"\n");
10971:
1.218 brouard 10972:
10973: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10974:
10975: agebase=ageminpar;
10976: agelim=agemaxpar;
10977:
10978:
1.227 brouard 10979: i1=pow(2,cptcoveff);
1.218 brouard 10980: if (cptcovn < 1){i1=1;}
1.227 brouard 10981:
1.238 brouard 10982: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10983: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10984: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10985: continue;
10986: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10987: fprintf(ficresplb,"#******");
10988: printf("#******");
10989: fprintf(ficlog,"#******");
10990: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10991: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10992: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10993: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10994: }
10995: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10996: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10997: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10998: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10999: }
11000: fprintf(ficresplb,"******\n");
11001: printf("******\n");
11002: fprintf(ficlog,"******\n");
11003: if(invalidvarcomb[k]){
11004: printf("\nCombination (%d) ignored because no cases \n",k);
11005: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
11006: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
11007: continue;
11008: }
1.218 brouard 11009:
1.238 brouard 11010: fprintf(ficresplb,"#Age ");
11011: for(j=1;j<=cptcoveff;j++) {
11012: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11013: }
11014: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
11015: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 11016:
11017:
1.238 brouard 11018: for (age=agebase; age<=agelim; age++){
11019: /* for (age=agebase; age<=agebase; age++){ */
11020: if(mobilavproj > 0){
11021: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11022: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11023: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11024: }else if (mobilavproj == 0){
11025: 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);
11026: 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);
11027: exit(1);
11028: }else{
11029: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11030: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11031: /* printf("TOTOT\n"); */
11032: /* exit(1); */
1.238 brouard 11033: }
11034: fprintf(ficresplb,"%.0f ",age );
11035: for(j=1;j<=cptcoveff;j++)
11036: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11037: tot=0.;
11038: for(i=1; i<=nlstate;i++){
11039: tot += bprlim[i][i];
11040: fprintf(ficresplb," %.5f", bprlim[i][i]);
11041: }
11042: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11043: } /* Age */
11044: /* was end of cptcod */
1.255 brouard 11045: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 11046: } /* end of any combination */
11047: } /* end of nres */
1.218 brouard 11048: /* hBijx(p, bage, fage); */
11049: /* fclose(ficrespijb); */
11050:
11051: return 0;
1.217 brouard 11052: }
1.218 brouard 11053:
1.180 brouard 11054: int hPijx(double *p, int bage, int fage){
11055: /*------------- h Pij x at various ages ------------*/
11056:
11057: int stepsize;
11058: int agelim;
11059: int hstepm;
11060: int nhstepm;
1.235 brouard 11061: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11062:
11063: double agedeb;
11064: double ***p3mat;
11065:
1.201 brouard 11066: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 11067: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11068: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11069: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11070: }
11071: printf("Computing pij: result on file '%s' \n", filerespij);
11072: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11073:
11074: stepsize=(int) (stepm+YEARM-1)/YEARM;
11075: /*if (stepm<=24) stepsize=2;*/
11076:
11077: agelim=AGESUP;
11078: hstepm=stepsize*YEARM; /* Every year of age */
11079: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 11080:
1.180 brouard 11081: /* hstepm=1; aff par mois*/
11082: pstamp(ficrespij);
11083: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 11084: i1= pow(2,cptcoveff);
1.218 brouard 11085: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11086: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11087: /* k=k+1; */
1.235 brouard 11088: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11089: for(k=1; k<=i1;k++){
1.253 brouard 11090: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11091: continue;
1.183 brouard 11092: fprintf(ficrespij,"\n#****** ");
1.227 brouard 11093: for(j=1;j<=cptcoveff;j++)
1.198 brouard 11094: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11095: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11096: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11097: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11098: }
1.183 brouard 11099: fprintf(ficrespij,"******\n");
11100:
11101: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11102: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11103: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11104:
11105: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 11106:
1.183 brouard 11107: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11108: oldm=oldms;savm=savms;
1.235 brouard 11109: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 11110: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11111: for(i=1; i<=nlstate;i++)
11112: for(j=1; j<=nlstate+ndeath;j++)
11113: fprintf(ficrespij," %1d-%1d",i,j);
11114: fprintf(ficrespij,"\n");
11115: for (h=0; h<=nhstepm; h++){
11116: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11117: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 11118: for(i=1; i<=nlstate;i++)
11119: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 11120: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 11121: fprintf(ficrespij,"\n");
11122: }
1.183 brouard 11123: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11124: fprintf(ficrespij,"\n");
11125: }
1.180 brouard 11126: /*}*/
11127: }
1.218 brouard 11128: return 0;
1.180 brouard 11129: }
1.218 brouard 11130:
11131: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11132: /*------------- h Bij x at various ages ------------*/
11133:
11134: int stepsize;
1.218 brouard 11135: /* int agelim; */
11136: int ageminl;
1.217 brouard 11137: int hstepm;
11138: int nhstepm;
1.238 brouard 11139: int h, i, i1, j, k, nres;
1.218 brouard 11140:
1.217 brouard 11141: double agedeb;
11142: double ***p3mat;
1.218 brouard 11143:
11144: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11145: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11146: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11147: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11148: }
11149: printf("Computing pij back: result on file '%s' \n", filerespijb);
11150: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11151:
11152: stepsize=(int) (stepm+YEARM-1)/YEARM;
11153: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11154:
1.218 brouard 11155: /* agelim=AGESUP; */
1.289 brouard 11156: ageminl=AGEINF; /* was 30 */
1.218 brouard 11157: hstepm=stepsize*YEARM; /* Every year of age */
11158: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11159:
11160: /* hstepm=1; aff par mois*/
11161: pstamp(ficrespijb);
1.255 brouard 11162: 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 11163: i1= pow(2,cptcoveff);
1.218 brouard 11164: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11165: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11166: /* k=k+1; */
1.238 brouard 11167: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11168: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11169: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11170: continue;
11171: fprintf(ficrespijb,"\n#****** ");
11172: for(j=1;j<=cptcoveff;j++)
11173: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11174: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11175: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11176: }
11177: fprintf(ficrespijb,"******\n");
1.264 brouard 11178: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 11179: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
11180: continue;
11181: }
11182:
11183: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11184: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11185: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 11186: 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 */
11187: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 11188:
11189: /* nhstepm=nhstepm*YEARM; aff par mois*/
11190:
1.266 brouard 11191: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11192: /* and memory limitations if stepm is small */
11193:
1.238 brouard 11194: /* oldm=oldms;savm=savms; */
11195: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.325 ! brouard 11196: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
1.238 brouard 11197: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 11198: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 11199: for(i=1; i<=nlstate;i++)
11200: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 11201: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 11202: fprintf(ficrespijb,"\n");
1.238 brouard 11203: for (h=0; h<=nhstepm; h++){
11204: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11205: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11206: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
11207: for(i=1; i<=nlstate;i++)
11208: for(j=1; j<=nlstate+ndeath;j++)
1.325 ! brouard 11209: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.238 brouard 11210: fprintf(ficrespijb,"\n");
11211: }
11212: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11213: fprintf(ficrespijb,"\n");
11214: } /* end age deb */
11215: } /* end combination */
11216: } /* end nres */
1.218 brouard 11217: return 0;
11218: } /* hBijx */
1.217 brouard 11219:
1.180 brouard 11220:
1.136 brouard 11221: /***********************************************/
11222: /**************** Main Program *****************/
11223: /***********************************************/
11224:
11225: int main(int argc, char *argv[])
11226: {
11227: #ifdef GSL
11228: const gsl_multimin_fminimizer_type *T;
11229: size_t iteri = 0, it;
11230: int rval = GSL_CONTINUE;
11231: int status = GSL_SUCCESS;
11232: double ssval;
11233: #endif
11234: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11235: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11236: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11237: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11238: int jj, ll, li, lj, lk;
1.136 brouard 11239: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11240: int num_filled;
1.136 brouard 11241: int itimes;
11242: int NDIM=2;
11243: int vpopbased=0;
1.235 brouard 11244: int nres=0;
1.258 brouard 11245: int endishere=0;
1.277 brouard 11246: int noffset=0;
1.274 brouard 11247: int ncurrv=0; /* Temporary variable */
11248:
1.164 brouard 11249: char ca[32], cb[32];
1.136 brouard 11250: /* FILE *fichtm; *//* Html File */
11251: /* FILE *ficgp;*/ /*Gnuplot File */
11252: struct stat info;
1.191 brouard 11253: double agedeb=0.;
1.194 brouard 11254:
11255: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11256: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11257:
1.165 brouard 11258: double fret;
1.191 brouard 11259: double dum=0.; /* Dummy variable */
1.136 brouard 11260: double ***p3mat;
1.218 brouard 11261: /* double ***mobaverage; */
1.319 brouard 11262: double wald;
1.164 brouard 11263:
11264: char line[MAXLINE];
1.197 brouard 11265: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11266:
1.234 brouard 11267: char modeltemp[MAXLINE];
1.230 brouard 11268: char resultline[MAXLINE];
11269:
1.136 brouard 11270: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11271: char *tok, *val; /* pathtot */
1.290 brouard 11272: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 11273: int c, h , cpt, c2;
1.191 brouard 11274: int jl=0;
11275: int i1, j1, jk, stepsize=0;
1.194 brouard 11276: int count=0;
11277:
1.164 brouard 11278: int *tab;
1.136 brouard 11279: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11280: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11281: /* double anprojf, mprojf, jprojf; */
11282: /* double jintmean,mintmean,aintmean; */
11283: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11284: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11285: double yrfproj= 10.0; /* Number of years of forward projections */
11286: double yrbproj= 10.0; /* Number of years of backward projections */
11287: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11288: int mobilav=0,popforecast=0;
1.191 brouard 11289: int hstepm=0, nhstepm=0;
1.136 brouard 11290: int agemortsup;
11291: float sumlpop=0.;
11292: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11293: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11294:
1.191 brouard 11295: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11296: double ftolpl=FTOL;
11297: double **prlim;
1.217 brouard 11298: double **bprlim;
1.317 brouard 11299: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
11300: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 11301: double ***paramstart; /* Matrix of starting parameter values */
11302: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11303: double **matcov; /* Matrix of covariance */
1.203 brouard 11304: double **hess; /* Hessian matrix */
1.136 brouard 11305: double ***delti3; /* Scale */
11306: double *delti; /* Scale */
11307: double ***eij, ***vareij;
11308: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11309:
1.136 brouard 11310: double *epj, vepp;
1.164 brouard 11311:
1.273 brouard 11312: double dateprev1, dateprev2;
1.296 brouard 11313: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11314: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11315:
1.217 brouard 11316:
1.136 brouard 11317: double **ximort;
1.145 brouard 11318: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11319: int *dcwave;
11320:
1.164 brouard 11321: char z[1]="c";
1.136 brouard 11322:
11323: /*char *strt;*/
11324: char strtend[80];
1.126 brouard 11325:
1.164 brouard 11326:
1.126 brouard 11327: /* setlocale (LC_ALL, ""); */
11328: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11329: /* textdomain (PACKAGE); */
11330: /* setlocale (LC_CTYPE, ""); */
11331: /* setlocale (LC_MESSAGES, ""); */
11332:
11333: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11334: rstart_time = time(NULL);
11335: /* (void) gettimeofday(&start_time,&tzp);*/
11336: start_time = *localtime(&rstart_time);
1.126 brouard 11337: curr_time=start_time;
1.157 brouard 11338: /*tml = *localtime(&start_time.tm_sec);*/
11339: /* strcpy(strstart,asctime(&tml)); */
11340: strcpy(strstart,asctime(&start_time));
1.126 brouard 11341:
11342: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11343: /* tp.tm_sec = tp.tm_sec +86400; */
11344: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11345: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11346: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11347: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11348: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11349: /* strt=asctime(&tmg); */
11350: /* printf("Time(after) =%s",strstart); */
11351: /* (void) time (&time_value);
11352: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11353: * tm = *localtime(&time_value);
11354: * strstart=asctime(&tm);
11355: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11356: */
11357:
11358: nberr=0; /* Number of errors and warnings */
11359: nbwarn=0;
1.184 brouard 11360: #ifdef WIN32
11361: _getcwd(pathcd, size);
11362: #else
1.126 brouard 11363: getcwd(pathcd, size);
1.184 brouard 11364: #endif
1.191 brouard 11365: syscompilerinfo(0);
1.196 brouard 11366: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11367: if(argc <=1){
11368: printf("\nEnter the parameter file name: ");
1.205 brouard 11369: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11370: printf("ERROR Empty parameter file name\n");
11371: goto end;
11372: }
1.126 brouard 11373: i=strlen(pathr);
11374: if(pathr[i-1]=='\n')
11375: pathr[i-1]='\0';
1.156 brouard 11376: i=strlen(pathr);
1.205 brouard 11377: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11378: pathr[i-1]='\0';
1.205 brouard 11379: }
11380: i=strlen(pathr);
11381: if( i==0 ){
11382: printf("ERROR Empty parameter file name\n");
11383: goto end;
11384: }
11385: for (tok = pathr; tok != NULL; ){
1.126 brouard 11386: printf("Pathr |%s|\n",pathr);
11387: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11388: printf("val= |%s| pathr=%s\n",val,pathr);
11389: strcpy (pathtot, val);
11390: if(pathr[0] == '\0') break; /* Dirty */
11391: }
11392: }
1.281 brouard 11393: else if (argc<=2){
11394: strcpy(pathtot,argv[1]);
11395: }
1.126 brouard 11396: else{
11397: strcpy(pathtot,argv[1]);
1.281 brouard 11398: strcpy(z,argv[2]);
11399: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11400: }
11401: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11402: /*cygwin_split_path(pathtot,path,optionfile);
11403: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11404: /* cutv(path,optionfile,pathtot,'\\');*/
11405:
11406: /* Split argv[0], imach program to get pathimach */
11407: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11408: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11409: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11410: /* strcpy(pathimach,argv[0]); */
11411: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11412: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11413: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11414: #ifdef WIN32
11415: _chdir(path); /* Can be a relative path */
11416: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11417: #else
1.126 brouard 11418: chdir(path); /* Can be a relative path */
1.184 brouard 11419: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11420: #endif
11421: printf("Current directory %s!\n",pathcd);
1.126 brouard 11422: strcpy(command,"mkdir ");
11423: strcat(command,optionfilefiname);
11424: if((outcmd=system(command)) != 0){
1.169 brouard 11425: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11426: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11427: /* fclose(ficlog); */
11428: /* exit(1); */
11429: }
11430: /* if((imk=mkdir(optionfilefiname))<0){ */
11431: /* perror("mkdir"); */
11432: /* } */
11433:
11434: /*-------- arguments in the command line --------*/
11435:
1.186 brouard 11436: /* Main Log file */
1.126 brouard 11437: strcat(filelog, optionfilefiname);
11438: strcat(filelog,".log"); /* */
11439: if((ficlog=fopen(filelog,"w"))==NULL) {
11440: printf("Problem with logfile %s\n",filelog);
11441: goto end;
11442: }
11443: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11444: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11445: fprintf(ficlog,"\nEnter the parameter file name: \n");
11446: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11447: path=%s \n\
11448: optionfile=%s\n\
11449: optionfilext=%s\n\
1.156 brouard 11450: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11451:
1.197 brouard 11452: syscompilerinfo(1);
1.167 brouard 11453:
1.126 brouard 11454: printf("Local time (at start):%s",strstart);
11455: fprintf(ficlog,"Local time (at start): %s",strstart);
11456: fflush(ficlog);
11457: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11458: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11459:
11460: /* */
11461: strcpy(fileres,"r");
11462: strcat(fileres, optionfilefiname);
1.201 brouard 11463: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11464: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11465: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11466:
1.186 brouard 11467: /* Main ---------arguments file --------*/
1.126 brouard 11468:
11469: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11470: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11471: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11472: fflush(ficlog);
1.149 brouard 11473: /* goto end; */
11474: exit(70);
1.126 brouard 11475: }
11476:
11477: strcpy(filereso,"o");
1.201 brouard 11478: strcat(filereso,fileresu);
1.126 brouard 11479: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11480: printf("Problem with Output resultfile: %s\n", filereso);
11481: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11482: fflush(ficlog);
11483: goto end;
11484: }
1.278 brouard 11485: /*-------- Rewriting parameter file ----------*/
11486: strcpy(rfileres,"r"); /* "Rparameterfile */
11487: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11488: strcat(rfileres,"."); /* */
11489: strcat(rfileres,optionfilext); /* Other files have txt extension */
11490: if((ficres =fopen(rfileres,"w"))==NULL) {
11491: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11492: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11493: fflush(ficlog);
11494: goto end;
11495: }
11496: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11497:
1.278 brouard 11498:
1.126 brouard 11499: /* Reads comments: lines beginning with '#' */
11500: numlinepar=0;
1.277 brouard 11501: /* Is it a BOM UTF-8 Windows file? */
11502: /* First parameter line */
1.197 brouard 11503: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11504: noffset=0;
11505: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11506: {
11507: noffset=noffset+3;
11508: printf("# File is an UTF8 Bom.\n"); // 0xBF
11509: }
1.302 brouard 11510: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11511: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11512: {
11513: noffset=noffset+2;
11514: printf("# File is an UTF16BE BOM file\n");
11515: }
11516: else if( line[0] == 0 && line[1] == 0)
11517: {
11518: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11519: noffset=noffset+4;
11520: printf("# File is an UTF16BE BOM file\n");
11521: }
11522: } else{
11523: ;/*printf(" Not a BOM file\n");*/
11524: }
11525:
1.197 brouard 11526: /* If line starts with a # it is a comment */
1.277 brouard 11527: if (line[noffset] == '#') {
1.197 brouard 11528: numlinepar++;
11529: fputs(line,stdout);
11530: fputs(line,ficparo);
1.278 brouard 11531: fputs(line,ficres);
1.197 brouard 11532: fputs(line,ficlog);
11533: continue;
11534: }else
11535: break;
11536: }
11537: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11538: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11539: if (num_filled != 5) {
11540: printf("Should be 5 parameters\n");
1.283 brouard 11541: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11542: }
1.126 brouard 11543: numlinepar++;
1.197 brouard 11544: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11545: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11546: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11547: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11548: }
11549: /* Second parameter line */
11550: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11551: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11552: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11553: if (line[0] == '#') {
11554: numlinepar++;
1.283 brouard 11555: printf("%s",line);
11556: fprintf(ficres,"%s",line);
11557: fprintf(ficparo,"%s",line);
11558: fprintf(ficlog,"%s",line);
1.197 brouard 11559: continue;
11560: }else
11561: break;
11562: }
1.223 brouard 11563: 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", \
11564: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11565: if (num_filled != 11) {
11566: 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 11567: printf("but line=%s\n",line);
1.283 brouard 11568: 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");
11569: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11570: }
1.286 brouard 11571: if( lastpass > maxwav){
11572: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11573: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11574: fflush(ficlog);
11575: goto end;
11576: }
11577: 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 11578: 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 11579: 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 11580: 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 11581: }
1.203 brouard 11582: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11583: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11584: /* Third parameter line */
11585: while(fgets(line, MAXLINE, ficpar)) {
11586: /* If line starts with a # it is a comment */
11587: if (line[0] == '#') {
11588: numlinepar++;
1.283 brouard 11589: printf("%s",line);
11590: fprintf(ficres,"%s",line);
11591: fprintf(ficparo,"%s",line);
11592: fprintf(ficlog,"%s",line);
1.197 brouard 11593: continue;
11594: }else
11595: break;
11596: }
1.201 brouard 11597: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11598: if (num_filled != 1){
1.302 brouard 11599: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
11600: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 11601: model[0]='\0';
11602: goto end;
11603: }
11604: else{
11605: if (model[0]=='+'){
11606: for(i=1; i<=strlen(model);i++)
11607: modeltemp[i-1]=model[i];
1.201 brouard 11608: strcpy(model,modeltemp);
1.197 brouard 11609: }
11610: }
1.199 brouard 11611: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11612: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11613: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11614: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11615: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11616: }
11617: /* 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); */
11618: /* numlinepar=numlinepar+3; /\* In general *\/ */
11619: /* 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 11620: /* 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); */
11621: /* 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 11622: fflush(ficlog);
1.190 brouard 11623: /* if(model[0]=='#'|| model[0]== '\0'){ */
11624: if(model[0]=='#'){
1.279 brouard 11625: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11626: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11627: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11628: if(mle != -1){
1.279 brouard 11629: 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 11630: exit(1);
11631: }
11632: }
1.126 brouard 11633: while((c=getc(ficpar))=='#' && c!= EOF){
11634: ungetc(c,ficpar);
11635: fgets(line, MAXLINE, ficpar);
11636: numlinepar++;
1.195 brouard 11637: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11638: z[0]=line[1];
11639: }
11640: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11641: fputs(line, stdout);
11642: //puts(line);
1.126 brouard 11643: fputs(line,ficparo);
11644: fputs(line,ficlog);
11645: }
11646: ungetc(c,ficpar);
11647:
11648:
1.290 brouard 11649: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11650: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11651: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11652: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11653: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11654: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11655: v1+v2*age+v2*v3 makes cptcovn = 3
11656: */
11657: if (strlen(model)>1)
1.187 brouard 11658: 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 11659: else
1.187 brouard 11660: ncovmodel=2; /* Constant and age */
1.133 brouard 11661: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11662: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11663: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11664: 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);
11665: 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);
11666: fflush(stdout);
11667: fclose (ficlog);
11668: goto end;
11669: }
1.126 brouard 11670: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11671: delti=delti3[1][1];
11672: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11673: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11674: /* We could also provide initial parameters values giving by simple logistic regression
11675: * only one way, that is without matrix product. We will have nlstate maximizations */
11676: /* for(i=1;i<nlstate;i++){ */
11677: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11678: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11679: /* } */
1.126 brouard 11680: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11681: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11682: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11683: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11684: fclose (ficparo);
11685: fclose (ficlog);
11686: goto end;
11687: exit(0);
1.220 brouard 11688: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11689: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11690: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11691: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11692: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11693: matcov=matrix(1,npar,1,npar);
1.203 brouard 11694: hess=matrix(1,npar,1,npar);
1.220 brouard 11695: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11696: /* Read guessed parameters */
1.126 brouard 11697: /* Reads comments: lines beginning with '#' */
11698: while((c=getc(ficpar))=='#' && c!= EOF){
11699: ungetc(c,ficpar);
11700: fgets(line, MAXLINE, ficpar);
11701: numlinepar++;
1.141 brouard 11702: fputs(line,stdout);
1.126 brouard 11703: fputs(line,ficparo);
11704: fputs(line,ficlog);
11705: }
11706: ungetc(c,ficpar);
11707:
11708: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11709: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11710: for(i=1; i <=nlstate; i++){
1.234 brouard 11711: j=0;
1.126 brouard 11712: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11713: if(jj==i) continue;
11714: j++;
1.292 brouard 11715: while((c=getc(ficpar))=='#' && c!= EOF){
11716: ungetc(c,ficpar);
11717: fgets(line, MAXLINE, ficpar);
11718: numlinepar++;
11719: fputs(line,stdout);
11720: fputs(line,ficparo);
11721: fputs(line,ficlog);
11722: }
11723: ungetc(c,ficpar);
1.234 brouard 11724: fscanf(ficpar,"%1d%1d",&i1,&j1);
11725: if ((i1 != i) || (j1 != jj)){
11726: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11727: It might be a problem of design; if ncovcol and the model are correct\n \
11728: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11729: exit(1);
11730: }
11731: fprintf(ficparo,"%1d%1d",i1,j1);
11732: if(mle==1)
11733: printf("%1d%1d",i,jj);
11734: fprintf(ficlog,"%1d%1d",i,jj);
11735: for(k=1; k<=ncovmodel;k++){
11736: fscanf(ficpar," %lf",¶m[i][j][k]);
11737: if(mle==1){
11738: printf(" %lf",param[i][j][k]);
11739: fprintf(ficlog," %lf",param[i][j][k]);
11740: }
11741: else
11742: fprintf(ficlog," %lf",param[i][j][k]);
11743: fprintf(ficparo," %lf",param[i][j][k]);
11744: }
11745: fscanf(ficpar,"\n");
11746: numlinepar++;
11747: if(mle==1)
11748: printf("\n");
11749: fprintf(ficlog,"\n");
11750: fprintf(ficparo,"\n");
1.126 brouard 11751: }
11752: }
11753: fflush(ficlog);
1.234 brouard 11754:
1.251 brouard 11755: /* Reads parameters values */
1.126 brouard 11756: p=param[1][1];
1.251 brouard 11757: pstart=paramstart[1][1];
1.126 brouard 11758:
11759: /* Reads comments: lines beginning with '#' */
11760: while((c=getc(ficpar))=='#' && c!= EOF){
11761: ungetc(c,ficpar);
11762: fgets(line, MAXLINE, ficpar);
11763: numlinepar++;
1.141 brouard 11764: fputs(line,stdout);
1.126 brouard 11765: fputs(line,ficparo);
11766: fputs(line,ficlog);
11767: }
11768: ungetc(c,ficpar);
11769:
11770: for(i=1; i <=nlstate; i++){
11771: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11772: fscanf(ficpar,"%1d%1d",&i1,&j1);
11773: if ( (i1-i) * (j1-j) != 0){
11774: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11775: exit(1);
11776: }
11777: printf("%1d%1d",i,j);
11778: fprintf(ficparo,"%1d%1d",i1,j1);
11779: fprintf(ficlog,"%1d%1d",i1,j1);
11780: for(k=1; k<=ncovmodel;k++){
11781: fscanf(ficpar,"%le",&delti3[i][j][k]);
11782: printf(" %le",delti3[i][j][k]);
11783: fprintf(ficparo," %le",delti3[i][j][k]);
11784: fprintf(ficlog," %le",delti3[i][j][k]);
11785: }
11786: fscanf(ficpar,"\n");
11787: numlinepar++;
11788: printf("\n");
11789: fprintf(ficparo,"\n");
11790: fprintf(ficlog,"\n");
1.126 brouard 11791: }
11792: }
11793: fflush(ficlog);
1.234 brouard 11794:
1.145 brouard 11795: /* Reads covariance matrix */
1.126 brouard 11796: delti=delti3[1][1];
1.220 brouard 11797:
11798:
1.126 brouard 11799: /* 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 11800:
1.126 brouard 11801: /* Reads comments: lines beginning with '#' */
11802: while((c=getc(ficpar))=='#' && c!= EOF){
11803: ungetc(c,ficpar);
11804: fgets(line, MAXLINE, ficpar);
11805: numlinepar++;
1.141 brouard 11806: fputs(line,stdout);
1.126 brouard 11807: fputs(line,ficparo);
11808: fputs(line,ficlog);
11809: }
11810: ungetc(c,ficpar);
1.220 brouard 11811:
1.126 brouard 11812: matcov=matrix(1,npar,1,npar);
1.203 brouard 11813: hess=matrix(1,npar,1,npar);
1.131 brouard 11814: for(i=1; i <=npar; i++)
11815: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11816:
1.194 brouard 11817: /* Scans npar lines */
1.126 brouard 11818: for(i=1; i <=npar; i++){
1.226 brouard 11819: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11820: if(count != 3){
1.226 brouard 11821: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11822: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11823: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11824: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11825: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11826: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11827: exit(1);
1.220 brouard 11828: }else{
1.226 brouard 11829: if(mle==1)
11830: printf("%1d%1d%d",i1,j1,jk);
11831: }
11832: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11833: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11834: for(j=1; j <=i; j++){
1.226 brouard 11835: fscanf(ficpar," %le",&matcov[i][j]);
11836: if(mle==1){
11837: printf(" %.5le",matcov[i][j]);
11838: }
11839: fprintf(ficlog," %.5le",matcov[i][j]);
11840: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11841: }
11842: fscanf(ficpar,"\n");
11843: numlinepar++;
11844: if(mle==1)
1.220 brouard 11845: printf("\n");
1.126 brouard 11846: fprintf(ficlog,"\n");
11847: fprintf(ficparo,"\n");
11848: }
1.194 brouard 11849: /* End of read covariance matrix npar lines */
1.126 brouard 11850: for(i=1; i <=npar; i++)
11851: for(j=i+1;j<=npar;j++)
1.226 brouard 11852: matcov[i][j]=matcov[j][i];
1.126 brouard 11853:
11854: if(mle==1)
11855: printf("\n");
11856: fprintf(ficlog,"\n");
11857:
11858: fflush(ficlog);
11859:
11860: } /* End of mle != -3 */
1.218 brouard 11861:
1.186 brouard 11862: /* Main data
11863: */
1.290 brouard 11864: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11865: /* num=lvector(1,n); */
11866: /* moisnais=vector(1,n); */
11867: /* annais=vector(1,n); */
11868: /* moisdc=vector(1,n); */
11869: /* andc=vector(1,n); */
11870: /* weight=vector(1,n); */
11871: /* agedc=vector(1,n); */
11872: /* cod=ivector(1,n); */
11873: /* for(i=1;i<=n;i++){ */
11874: num=lvector(firstobs,lastobs);
11875: moisnais=vector(firstobs,lastobs);
11876: annais=vector(firstobs,lastobs);
11877: moisdc=vector(firstobs,lastobs);
11878: andc=vector(firstobs,lastobs);
11879: weight=vector(firstobs,lastobs);
11880: agedc=vector(firstobs,lastobs);
11881: cod=ivector(firstobs,lastobs);
11882: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11883: num[i]=0;
11884: moisnais[i]=0;
11885: annais[i]=0;
11886: moisdc[i]=0;
11887: andc[i]=0;
11888: agedc[i]=0;
11889: cod[i]=0;
11890: weight[i]=1.0; /* Equal weights, 1 by default */
11891: }
1.290 brouard 11892: mint=matrix(1,maxwav,firstobs,lastobs);
11893: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 ! brouard 11894: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
! 11895: printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel));
1.126 brouard 11896: tab=ivector(1,NCOVMAX);
1.144 brouard 11897: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11898: 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 11899:
1.136 brouard 11900: /* Reads data from file datafile */
11901: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11902: goto end;
11903:
11904: /* Calculation of the number of parameters from char model */
1.234 brouard 11905: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11906: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11907: k=3 V4 Tvar[k=3]= 4 (from V4)
11908: k=2 V1 Tvar[k=2]= 1 (from V1)
11909: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11910: */
11911:
11912: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11913: TvarsDind=ivector(1,NCOVMAX); /* */
11914: TvarsD=ivector(1,NCOVMAX); /* */
11915: TvarsQind=ivector(1,NCOVMAX); /* */
11916: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11917: TvarF=ivector(1,NCOVMAX); /* */
11918: TvarFind=ivector(1,NCOVMAX); /* */
11919: TvarV=ivector(1,NCOVMAX); /* */
11920: TvarVind=ivector(1,NCOVMAX); /* */
11921: TvarA=ivector(1,NCOVMAX); /* */
11922: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11923: TvarFD=ivector(1,NCOVMAX); /* */
11924: TvarFDind=ivector(1,NCOVMAX); /* */
11925: TvarFQ=ivector(1,NCOVMAX); /* */
11926: TvarFQind=ivector(1,NCOVMAX); /* */
11927: TvarVD=ivector(1,NCOVMAX); /* */
11928: TvarVDind=ivector(1,NCOVMAX); /* */
11929: TvarVQ=ivector(1,NCOVMAX); /* */
11930: TvarVQind=ivector(1,NCOVMAX); /* */
11931:
1.230 brouard 11932: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11933: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11934: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11935: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11936: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11937: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11938: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11939: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11940: */
11941: /* For model-covariate k tells which data-covariate to use but
11942: because this model-covariate is a construction we invent a new column
11943: ncovcol + k1
11944: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11945: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11946: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11947: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11948: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11949: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11950: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11951: */
1.145 brouard 11952: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11953: 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 11954: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11955: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11956: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11957: 4 covariates (3 plus signs)
11958: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11959: */
1.230 brouard 11960: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11961: * individual dummy, fixed or varying:
11962: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11963: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11964: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11965: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11966: * Tmodelind[1]@9={9,0,3,2,}*/
11967: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11968: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11969: * individual quantitative, fixed or varying:
11970: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11971: * 3, 1, 0, 0, 0, 0, 0, 0},
11972: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11973: /* Main decodemodel */
11974:
1.187 brouard 11975:
1.223 brouard 11976: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11977: goto end;
11978:
1.137 brouard 11979: if((double)(lastobs-imx)/(double)imx > 1.10){
11980: nbwarn++;
11981: 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);
11982: 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);
11983: }
1.136 brouard 11984: /* if(mle==1){*/
1.137 brouard 11985: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11986: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11987: }
11988:
11989: /*-calculation of age at interview from date of interview and age at death -*/
11990: agev=matrix(1,maxwav,1,imx);
11991:
11992: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11993: goto end;
11994:
1.126 brouard 11995:
1.136 brouard 11996: agegomp=(int)agemin;
1.290 brouard 11997: free_vector(moisnais,firstobs,lastobs);
11998: free_vector(annais,firstobs,lastobs);
1.126 brouard 11999: /* free_matrix(mint,1,maxwav,1,n);
12000: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 12001: /* free_vector(moisdc,1,n); */
12002: /* free_vector(andc,1,n); */
1.145 brouard 12003: /* */
12004:
1.126 brouard 12005: wav=ivector(1,imx);
1.214 brouard 12006: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
12007: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
12008: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
12009: 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.*/
12010: bh=imatrix(1,lastpass-firstpass+2,1,imx);
12011: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 12012:
12013: /* Concatenates waves */
1.214 brouard 12014: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
12015: Death is a valid wave (if date is known).
12016: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
12017: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
12018: and mw[mi+1][i]. dh depends on stepm.
12019: */
12020:
1.126 brouard 12021: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12022: /* Concatenates waves */
1.145 brouard 12023:
1.290 brouard 12024: free_vector(moisdc,firstobs,lastobs);
12025: free_vector(andc,firstobs,lastobs);
1.215 brouard 12026:
1.126 brouard 12027: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12028: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12029: ncodemax[1]=1;
1.145 brouard 12030: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12031: cptcoveff=0;
1.220 brouard 12032: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
12033: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 12034: }
12035:
12036: ncovcombmax=pow(2,cptcoveff);
12037: invalidvarcomb=ivector(1, ncovcombmax);
12038: for(i=1;i<ncovcombmax;i++)
12039: invalidvarcomb[i]=0;
12040:
1.211 brouard 12041: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12042: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12043: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12044:
1.200 brouard 12045: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12046: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12047: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12048: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12049: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12050: * (currently 0 or 1) in the data.
12051: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12052: * corresponding modality (h,j).
12053: */
12054:
1.145 brouard 12055: h=0;
12056: /*if (cptcovn > 0) */
1.126 brouard 12057: m=pow(2,cptcoveff);
12058:
1.144 brouard 12059: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12060: * For k=4 covariates, h goes from 1 to m=2**k
12061: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12062: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 12063: * h\k 1 2 3 4
1.143 brouard 12064: *______________________________
12065: * 1 i=1 1 i=1 1 i=1 1 i=1 1
12066: * 2 2 1 1 1
12067: * 3 i=2 1 2 1 1
12068: * 4 2 2 1 1
12069: * 5 i=3 1 i=2 1 2 1
12070: * 6 2 1 2 1
12071: * 7 i=4 1 2 2 1
12072: * 8 2 2 2 1
1.197 brouard 12073: * 9 i=5 1 i=3 1 i=2 1 2
12074: * 10 2 1 1 2
12075: * 11 i=6 1 2 1 2
12076: * 12 2 2 1 2
12077: * 13 i=7 1 i=4 1 2 2
12078: * 14 2 1 2 2
12079: * 15 i=8 1 2 2 2
12080: * 16 2 2 2 2
1.143 brouard 12081: */
1.212 brouard 12082: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12083: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12084: * and the value of each covariate?
12085: * V1=1, V2=1, V3=2, V4=1 ?
12086: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12087: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12088: * In order to get the real value in the data, we use nbcode
12089: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12090: * We are keeping this crazy system in order to be able (in the future?)
12091: * to have more than 2 values (0 or 1) for a covariate.
12092: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12093: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12094: * bbbbbbbb
12095: * 76543210
12096: * h-1 00000101 (6-1=5)
1.219 brouard 12097: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12098: * &
12099: * 1 00000001 (1)
1.219 brouard 12100: * 00000000 = 1 & ((h-1) >> (k-1))
12101: * +1= 00000001 =1
1.211 brouard 12102: *
12103: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12104: * h' 1101 =2^3+2^2+0x2^1+2^0
12105: * >>k' 11
12106: * & 00000001
12107: * = 00000001
12108: * +1 = 00000010=2 = codtabm(14,3)
12109: * Reverse h=6 and m=16?
12110: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12111: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12112: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12113: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12114: * V3=decodtabm(14,3,2**4)=2
12115: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12116: *(h-1) >> (j-1) 0011 =13 >> 2
12117: * &1 000000001
12118: * = 000000001
12119: * +1= 000000010 =2
12120: * 2211
12121: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12122: * V3=2
1.220 brouard 12123: * codtabm and decodtabm are identical
1.211 brouard 12124: */
12125:
1.145 brouard 12126:
12127: free_ivector(Ndum,-1,NCOVMAX);
12128:
12129:
1.126 brouard 12130:
1.186 brouard 12131: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12132: strcpy(optionfilegnuplot,optionfilefiname);
12133: if(mle==-3)
1.201 brouard 12134: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12135: strcat(optionfilegnuplot,".gp");
12136:
12137: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12138: printf("Problem with file %s",optionfilegnuplot);
12139: }
12140: else{
1.204 brouard 12141: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12142: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12143: //fprintf(ficgp,"set missing 'NaNq'\n");
12144: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12145: }
12146: /* fclose(ficgp);*/
1.186 brouard 12147:
12148:
12149: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12150:
12151: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12152: if(mle==-3)
1.201 brouard 12153: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12154: strcat(optionfilehtm,".htm");
12155: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12156: printf("Problem with %s \n",optionfilehtm);
12157: exit(0);
1.126 brouard 12158: }
12159:
12160: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
12161: strcat(optionfilehtmcov,"-cov.htm");
12162: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
12163: printf("Problem with %s \n",optionfilehtmcov), exit(0);
12164: }
12165: else{
12166: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
12167: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12168: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 12169: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
12170: }
12171:
1.324 brouard 12172: 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 日本学術振興会 (<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 12173: <hr size=\"2\" color=\"#EC5E5E\"> \n\
12174: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 12175: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12176: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 12177: \n\
12178: <hr size=\"2\" color=\"#EC5E5E\">\
12179: <ul><li><h4>Parameter files</h4>\n\
12180: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
12181: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
12182: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12183: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12184: - Date and time at start: %s</ul>\n",\
12185: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
12186: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12187: fileres,fileres,\
12188: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12189: fflush(fichtm);
12190:
12191: strcpy(pathr,path);
12192: strcat(pathr,optionfilefiname);
1.184 brouard 12193: #ifdef WIN32
12194: _chdir(optionfilefiname); /* Move to directory named optionfile */
12195: #else
1.126 brouard 12196: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12197: #endif
12198:
1.126 brouard 12199:
1.220 brouard 12200: /* Calculates basic frequencies. Computes observed prevalence at single age
12201: and for any valid combination of covariates
1.126 brouard 12202: and prints on file fileres'p'. */
1.251 brouard 12203: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12204: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12205:
12206: fprintf(fichtm,"\n");
1.286 brouard 12207: 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 12208: ftol, stepm);
12209: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12210: ncurrv=1;
12211: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12212: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12213: ncurrv=i;
12214: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12215: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12216: ncurrv=i;
12217: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12218: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12219: ncurrv=i;
12220: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12221: 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", \
12222: nlstate, ndeath, maxwav, mle, weightopt);
12223:
12224: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12225: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12226:
12227:
1.317 brouard 12228: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12229: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12230: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12231: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12232: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12233: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12234: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12235: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12236: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12237:
1.126 brouard 12238: /* For Powell, parameters are in a vector p[] starting at p[1]
12239: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12240: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12241:
12242: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12243: /* For mortality only */
1.126 brouard 12244: if (mle==-3){
1.136 brouard 12245: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12246: for(i=1;i<=NDIM;i++)
12247: for(j=1;j<=NDIM;j++)
12248: ximort[i][j]=0.;
1.186 brouard 12249: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12250: cens=ivector(firstobs,lastobs);
12251: ageexmed=vector(firstobs,lastobs);
12252: agecens=vector(firstobs,lastobs);
12253: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12254:
1.126 brouard 12255: for (i=1; i<=imx; i++){
12256: dcwave[i]=-1;
12257: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12258: if (s[m][i]>nlstate) {
12259: dcwave[i]=m;
12260: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12261: break;
12262: }
1.126 brouard 12263: }
1.226 brouard 12264:
1.126 brouard 12265: for (i=1; i<=imx; i++) {
12266: if (wav[i]>0){
1.226 brouard 12267: ageexmed[i]=agev[mw[1][i]][i];
12268: j=wav[i];
12269: agecens[i]=1.;
12270:
12271: if (ageexmed[i]> 1 && wav[i] > 0){
12272: agecens[i]=agev[mw[j][i]][i];
12273: cens[i]= 1;
12274: }else if (ageexmed[i]< 1)
12275: cens[i]= -1;
12276: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12277: cens[i]=0 ;
1.126 brouard 12278: }
12279: else cens[i]=-1;
12280: }
12281:
12282: for (i=1;i<=NDIM;i++) {
12283: for (j=1;j<=NDIM;j++)
1.226 brouard 12284: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12285: }
12286:
1.302 brouard 12287: p[1]=0.0268; p[NDIM]=0.083;
12288: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12289:
12290:
1.136 brouard 12291: #ifdef GSL
12292: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12293: #else
1.126 brouard 12294: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12295: #endif
1.201 brouard 12296: strcpy(filerespow,"POW-MORT_");
12297: strcat(filerespow,fileresu);
1.126 brouard 12298: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12299: printf("Problem with resultfile: %s\n", filerespow);
12300: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12301: }
1.136 brouard 12302: #ifdef GSL
12303: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12304: #else
1.126 brouard 12305: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12306: #endif
1.126 brouard 12307: /* for (i=1;i<=nlstate;i++)
12308: for(j=1;j<=nlstate+ndeath;j++)
12309: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12310: */
12311: fprintf(ficrespow,"\n");
1.136 brouard 12312: #ifdef GSL
12313: /* gsl starts here */
12314: T = gsl_multimin_fminimizer_nmsimplex;
12315: gsl_multimin_fminimizer *sfm = NULL;
12316: gsl_vector *ss, *x;
12317: gsl_multimin_function minex_func;
12318:
12319: /* Initial vertex size vector */
12320: ss = gsl_vector_alloc (NDIM);
12321:
12322: if (ss == NULL){
12323: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12324: }
12325: /* Set all step sizes to 1 */
12326: gsl_vector_set_all (ss, 0.001);
12327:
12328: /* Starting point */
1.126 brouard 12329:
1.136 brouard 12330: x = gsl_vector_alloc (NDIM);
12331:
12332: if (x == NULL){
12333: gsl_vector_free(ss);
12334: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12335: }
12336:
12337: /* Initialize method and iterate */
12338: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12339: /* gsl_vector_set(x, 0, 0.0268); */
12340: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12341: gsl_vector_set(x, 0, p[1]);
12342: gsl_vector_set(x, 1, p[2]);
12343:
12344: minex_func.f = &gompertz_f;
12345: minex_func.n = NDIM;
12346: minex_func.params = (void *)&p; /* ??? */
12347:
12348: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12349: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12350:
12351: printf("Iterations beginning .....\n\n");
12352: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12353:
12354: iteri=0;
12355: while (rval == GSL_CONTINUE){
12356: iteri++;
12357: status = gsl_multimin_fminimizer_iterate(sfm);
12358:
12359: if (status) printf("error: %s\n", gsl_strerror (status));
12360: fflush(0);
12361:
12362: if (status)
12363: break;
12364:
12365: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12366: ssval = gsl_multimin_fminimizer_size (sfm);
12367:
12368: if (rval == GSL_SUCCESS)
12369: printf ("converged to a local maximum at\n");
12370:
12371: printf("%5d ", iteri);
12372: for (it = 0; it < NDIM; it++){
12373: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12374: }
12375: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12376: }
12377:
12378: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12379:
12380: gsl_vector_free(x); /* initial values */
12381: gsl_vector_free(ss); /* inital step size */
12382: for (it=0; it<NDIM; it++){
12383: p[it+1]=gsl_vector_get(sfm->x,it);
12384: fprintf(ficrespow," %.12lf", p[it]);
12385: }
12386: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12387: #endif
12388: #ifdef POWELL
12389: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12390: #endif
1.126 brouard 12391: fclose(ficrespow);
12392:
1.203 brouard 12393: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12394:
12395: for(i=1; i <=NDIM; i++)
12396: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12397: matcov[i][j]=matcov[j][i];
1.126 brouard 12398:
12399: printf("\nCovariance matrix\n ");
1.203 brouard 12400: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12401: for(i=1; i <=NDIM; i++) {
12402: for(j=1;j<=NDIM;j++){
1.220 brouard 12403: printf("%f ",matcov[i][j]);
12404: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12405: }
1.203 brouard 12406: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12407: }
12408:
12409: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12410: for (i=1;i<=NDIM;i++) {
1.126 brouard 12411: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12412: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12413: }
1.302 brouard 12414: lsurv=vector(agegomp,AGESUP);
12415: lpop=vector(agegomp,AGESUP);
12416: tpop=vector(agegomp,AGESUP);
1.126 brouard 12417: lsurv[agegomp]=100000;
12418:
12419: for (k=agegomp;k<=AGESUP;k++) {
12420: agemortsup=k;
12421: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12422: }
12423:
12424: for (k=agegomp;k<agemortsup;k++)
12425: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12426:
12427: for (k=agegomp;k<agemortsup;k++){
12428: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12429: sumlpop=sumlpop+lpop[k];
12430: }
12431:
12432: tpop[agegomp]=sumlpop;
12433: for (k=agegomp;k<(agemortsup-3);k++){
12434: /* tpop[k+1]=2;*/
12435: tpop[k+1]=tpop[k]-lpop[k];
12436: }
12437:
12438:
12439: printf("\nAge lx qx dx Lx Tx e(x)\n");
12440: for (k=agegomp;k<(agemortsup-2);k++)
12441: 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]);
12442:
12443:
12444: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12445: ageminpar=50;
12446: agemaxpar=100;
1.194 brouard 12447: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12448: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12449: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12450: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12451: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12452: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12453: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12454: }else{
12455: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12456: 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 12457: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12458: }
1.201 brouard 12459: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12460: stepm, weightopt,\
12461: model,imx,p,matcov,agemortsup);
12462:
1.302 brouard 12463: free_vector(lsurv,agegomp,AGESUP);
12464: free_vector(lpop,agegomp,AGESUP);
12465: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12466: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12467: free_ivector(dcwave,firstobs,lastobs);
12468: free_vector(agecens,firstobs,lastobs);
12469: free_vector(ageexmed,firstobs,lastobs);
12470: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12471: #ifdef GSL
1.136 brouard 12472: #endif
1.186 brouard 12473: } /* Endof if mle==-3 mortality only */
1.205 brouard 12474: /* Standard */
12475: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12476: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12477: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12478: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12479: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12480: for (k=1; k<=npar;k++)
12481: printf(" %d %8.5f",k,p[k]);
12482: printf("\n");
1.205 brouard 12483: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12484: /* mlikeli uses func not funcone */
1.247 brouard 12485: /* for(i=1;i<nlstate;i++){ */
12486: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12487: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12488: /* } */
1.205 brouard 12489: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12490: }
12491: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12492: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12493: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12494: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12495: }
12496: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12497: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12498: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12499: for (k=1; k<=npar;k++)
12500: printf(" %d %8.5f",k,p[k]);
12501: printf("\n");
12502:
12503: /*--------- results files --------------*/
1.283 brouard 12504: /* 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 12505:
12506:
12507: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12508: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 12509: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12510:
12511: printf("#model= 1 + age ");
12512: fprintf(ficres,"#model= 1 + age ");
12513: fprintf(ficlog,"#model= 1 + age ");
12514: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
12515: </ul>", model);
12516:
12517: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
12518: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
12519: if(nagesqr==1){
12520: printf(" + age*age ");
12521: fprintf(ficres," + age*age ");
12522: fprintf(ficlog," + age*age ");
12523: fprintf(fichtm, "<th>+ age*age</th>");
12524: }
12525: for(j=1;j <=ncovmodel-2;j++){
12526: if(Typevar[j]==0) {
12527: printf(" + V%d ",Tvar[j]);
12528: fprintf(ficres," + V%d ",Tvar[j]);
12529: fprintf(ficlog," + V%d ",Tvar[j]);
12530: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12531: }else if(Typevar[j]==1) {
12532: printf(" + V%d*age ",Tvar[j]);
12533: fprintf(ficres," + V%d*age ",Tvar[j]);
12534: fprintf(ficlog," + V%d*age ",Tvar[j]);
12535: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12536: }else if(Typevar[j]==2) {
12537: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12538: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12539: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12540: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12541: }
12542: }
12543: printf("\n");
12544: fprintf(ficres,"\n");
12545: fprintf(ficlog,"\n");
12546: fprintf(fichtm, "</tr>");
12547: fprintf(fichtm, "\n");
12548:
12549:
1.126 brouard 12550: for(i=1,jk=1; i <=nlstate; i++){
12551: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12552: if (k != i) {
1.319 brouard 12553: fprintf(fichtm, "<tr>");
1.225 brouard 12554: printf("%d%d ",i,k);
12555: fprintf(ficlog,"%d%d ",i,k);
12556: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 12557: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12558: for(j=1; j <=ncovmodel; j++){
12559: printf("%12.7f ",p[jk]);
12560: fprintf(ficlog,"%12.7f ",p[jk]);
12561: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 12562: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 12563: jk++;
12564: }
12565: printf("\n");
12566: fprintf(ficlog,"\n");
12567: fprintf(ficres,"\n");
1.319 brouard 12568: fprintf(fichtm, "</tr>\n");
1.225 brouard 12569: }
1.126 brouard 12570: }
12571: }
1.319 brouard 12572: /* fprintf(fichtm,"</tr>\n"); */
12573: fprintf(fichtm,"</table>\n");
12574: fprintf(fichtm, "\n");
12575:
1.203 brouard 12576: if(mle != 0){
12577: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12578: ftolhess=ftol; /* Usually correct */
1.203 brouard 12579: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12580: 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");
12581: 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 12582: 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 12583: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
12584: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
12585: if(nagesqr==1){
12586: printf(" + age*age ");
12587: fprintf(ficres," + age*age ");
12588: fprintf(ficlog," + age*age ");
12589: fprintf(fichtm, "<th>+ age*age</th>");
12590: }
12591: for(j=1;j <=ncovmodel-2;j++){
12592: if(Typevar[j]==0) {
12593: printf(" + V%d ",Tvar[j]);
12594: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12595: }else if(Typevar[j]==1) {
12596: printf(" + V%d*age ",Tvar[j]);
12597: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12598: }else if(Typevar[j]==2) {
12599: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12600: }
12601: }
12602: fprintf(fichtm, "</tr>\n");
12603:
1.203 brouard 12604: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12605: for(k=1; k <=(nlstate+ndeath); k++){
12606: if (k != i) {
1.319 brouard 12607: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 12608: printf("%d%d ",i,k);
12609: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 12610: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12611: for(j=1; j <=ncovmodel; j++){
1.319 brouard 12612: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 12613: printf("%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
12614: fprintf(ficlog,"%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.319 brouard 12615: if(fabs(wald) > 1.96){
1.321 brouard 12616: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 12617: }else{
12618: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
12619: }
1.324 brouard 12620: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 12621: 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 12622: jk++;
12623: }
12624: printf("\n");
12625: fprintf(ficlog,"\n");
1.319 brouard 12626: fprintf(fichtm, "</tr>\n");
1.225 brouard 12627: }
12628: }
1.193 brouard 12629: }
1.203 brouard 12630: } /* end of hesscov and Wald tests */
1.319 brouard 12631: fprintf(fichtm,"</table>\n");
1.225 brouard 12632:
1.203 brouard 12633: /* */
1.126 brouard 12634: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12635: printf("# Scales (for hessian or gradient estimation)\n");
12636: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12637: for(i=1,jk=1; i <=nlstate; i++){
12638: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12639: if (j!=i) {
12640: fprintf(ficres,"%1d%1d",i,j);
12641: printf("%1d%1d",i,j);
12642: fprintf(ficlog,"%1d%1d",i,j);
12643: for(k=1; k<=ncovmodel;k++){
12644: printf(" %.5e",delti[jk]);
12645: fprintf(ficlog," %.5e",delti[jk]);
12646: fprintf(ficres," %.5e",delti[jk]);
12647: jk++;
12648: }
12649: printf("\n");
12650: fprintf(ficlog,"\n");
12651: fprintf(ficres,"\n");
12652: }
1.126 brouard 12653: }
12654: }
12655:
12656: 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 12657: if(mle >= 1) /* To big for the screen */
1.126 brouard 12658: 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");
12659: 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");
12660: /* # 121 Var(a12)\n\ */
12661: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12662: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12663: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12664: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12665: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12666: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12667: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12668:
12669:
12670: /* Just to have a covariance matrix which will be more understandable
12671: even is we still don't want to manage dictionary of variables
12672: */
12673: for(itimes=1;itimes<=2;itimes++){
12674: jj=0;
12675: for(i=1; i <=nlstate; i++){
1.225 brouard 12676: for(j=1; j <=nlstate+ndeath; j++){
12677: if(j==i) continue;
12678: for(k=1; k<=ncovmodel;k++){
12679: jj++;
12680: ca[0]= k+'a'-1;ca[1]='\0';
12681: if(itimes==1){
12682: if(mle>=1)
12683: printf("#%1d%1d%d",i,j,k);
12684: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12685: fprintf(ficres,"#%1d%1d%d",i,j,k);
12686: }else{
12687: if(mle>=1)
12688: printf("%1d%1d%d",i,j,k);
12689: fprintf(ficlog,"%1d%1d%d",i,j,k);
12690: fprintf(ficres,"%1d%1d%d",i,j,k);
12691: }
12692: ll=0;
12693: for(li=1;li <=nlstate; li++){
12694: for(lj=1;lj <=nlstate+ndeath; lj++){
12695: if(lj==li) continue;
12696: for(lk=1;lk<=ncovmodel;lk++){
12697: ll++;
12698: if(ll<=jj){
12699: cb[0]= lk +'a'-1;cb[1]='\0';
12700: if(ll<jj){
12701: if(itimes==1){
12702: if(mle>=1)
12703: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12704: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12705: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12706: }else{
12707: if(mle>=1)
12708: printf(" %.5e",matcov[jj][ll]);
12709: fprintf(ficlog," %.5e",matcov[jj][ll]);
12710: fprintf(ficres," %.5e",matcov[jj][ll]);
12711: }
12712: }else{
12713: if(itimes==1){
12714: if(mle>=1)
12715: printf(" Var(%s%1d%1d)",ca,i,j);
12716: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12717: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12718: }else{
12719: if(mle>=1)
12720: printf(" %.7e",matcov[jj][ll]);
12721: fprintf(ficlog," %.7e",matcov[jj][ll]);
12722: fprintf(ficres," %.7e",matcov[jj][ll]);
12723: }
12724: }
12725: }
12726: } /* end lk */
12727: } /* end lj */
12728: } /* end li */
12729: if(mle>=1)
12730: printf("\n");
12731: fprintf(ficlog,"\n");
12732: fprintf(ficres,"\n");
12733: numlinepar++;
12734: } /* end k*/
12735: } /*end j */
1.126 brouard 12736: } /* end i */
12737: } /* end itimes */
12738:
12739: fflush(ficlog);
12740: fflush(ficres);
1.225 brouard 12741: while(fgets(line, MAXLINE, ficpar)) {
12742: /* If line starts with a # it is a comment */
12743: if (line[0] == '#') {
12744: numlinepar++;
12745: fputs(line,stdout);
12746: fputs(line,ficparo);
12747: fputs(line,ficlog);
1.299 brouard 12748: fputs(line,ficres);
1.225 brouard 12749: continue;
12750: }else
12751: break;
12752: }
12753:
1.209 brouard 12754: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12755: /* ungetc(c,ficpar); */
12756: /* fgets(line, MAXLINE, ficpar); */
12757: /* fputs(line,stdout); */
12758: /* fputs(line,ficparo); */
12759: /* } */
12760: /* ungetc(c,ficpar); */
1.126 brouard 12761:
12762: estepm=0;
1.209 brouard 12763: 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 12764:
12765: if (num_filled != 6) {
12766: 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);
12767: 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);
12768: goto end;
12769: }
12770: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12771: }
12772: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12773: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12774:
1.209 brouard 12775: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12776: if (estepm==0 || estepm < stepm) estepm=stepm;
12777: if (fage <= 2) {
12778: bage = ageminpar;
12779: fage = agemaxpar;
12780: }
12781:
12782: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12783: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12784: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12785:
1.186 brouard 12786: /* Other stuffs, more or less useful */
1.254 brouard 12787: while(fgets(line, MAXLINE, ficpar)) {
12788: /* If line starts with a # it is a comment */
12789: if (line[0] == '#') {
12790: numlinepar++;
12791: fputs(line,stdout);
12792: fputs(line,ficparo);
12793: fputs(line,ficlog);
1.299 brouard 12794: fputs(line,ficres);
1.254 brouard 12795: continue;
12796: }else
12797: break;
12798: }
12799:
12800: 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){
12801:
12802: if (num_filled != 7) {
12803: 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);
12804: 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);
12805: goto end;
12806: }
12807: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12808: 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);
12809: 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);
12810: 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 12811: }
1.254 brouard 12812:
12813: while(fgets(line, MAXLINE, ficpar)) {
12814: /* If line starts with a # it is a comment */
12815: if (line[0] == '#') {
12816: numlinepar++;
12817: fputs(line,stdout);
12818: fputs(line,ficparo);
12819: fputs(line,ficlog);
1.299 brouard 12820: fputs(line,ficres);
1.254 brouard 12821: continue;
12822: }else
12823: break;
1.126 brouard 12824: }
12825:
12826:
12827: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12828: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12829:
1.254 brouard 12830: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12831: if (num_filled != 1) {
12832: 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);
12833: 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);
12834: goto end;
12835: }
12836: printf("pop_based=%d\n",popbased);
12837: fprintf(ficlog,"pop_based=%d\n",popbased);
12838: fprintf(ficparo,"pop_based=%d\n",popbased);
12839: fprintf(ficres,"pop_based=%d\n",popbased);
12840: }
12841:
1.258 brouard 12842: /* Results */
1.307 brouard 12843: endishere=0;
1.258 brouard 12844: nresult=0;
1.308 brouard 12845: parameterline=0;
1.258 brouard 12846: do{
12847: if(!fgets(line, MAXLINE, ficpar)){
12848: endishere=1;
1.308 brouard 12849: parameterline=15;
1.258 brouard 12850: }else if (line[0] == '#') {
12851: /* If line starts with a # it is a comment */
1.254 brouard 12852: numlinepar++;
12853: fputs(line,stdout);
12854: fputs(line,ficparo);
12855: fputs(line,ficlog);
1.299 brouard 12856: fputs(line,ficres);
1.254 brouard 12857: continue;
1.258 brouard 12858: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12859: parameterline=11;
1.296 brouard 12860: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12861: parameterline=12;
1.307 brouard 12862: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 12863: parameterline=13;
1.307 brouard 12864: }
1.258 brouard 12865: else{
12866: parameterline=14;
1.254 brouard 12867: }
1.308 brouard 12868: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 12869: case 11:
1.296 brouard 12870: 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)){
12871: 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 12872: 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);
12873: 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);
12874: 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);
12875: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12876: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12877: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 12878: prvforecast = 1;
12879: }
12880: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 12881: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12882: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12883: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 12884: prvforecast = 2;
12885: }
12886: else {
12887: 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);
12888: 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);
12889: goto end;
1.258 brouard 12890: }
1.254 brouard 12891: break;
1.258 brouard 12892: case 12:
1.296 brouard 12893: 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)){
12894: 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);
12895: 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);
12896: 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);
12897: 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);
12898: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 12899: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12900: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 12901: prvbackcast = 1;
12902: }
12903: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 12904: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12905: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12906: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 12907: prvbackcast = 2;
12908: }
12909: else {
12910: 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);
12911: 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);
12912: goto end;
1.258 brouard 12913: }
1.230 brouard 12914: break;
1.258 brouard 12915: case 13:
1.307 brouard 12916: num_filled=sscanf(line,"result:%[^\n]\n",resultline);
12917: nresult++; /* Sum of resultlines */
12918: printf("Result %d: result:%s\n",nresult, resultline);
1.318 brouard 12919: if(nresult > MAXRESULTLINESPONE-1){
12920: 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);
12921: 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 12922: goto end;
12923: }
1.310 brouard 12924: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 12925: fprintf(ficparo,"result: %s\n",resultline);
12926: fprintf(ficres,"result: %s\n",resultline);
12927: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 12928: } else
12929: goto end;
1.307 brouard 12930: break;
12931: case 14:
12932: printf("Error: Unknown command '%s'\n",line);
12933: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 12934: if(line[0] == ' ' || line[0] == '\n'){
12935: printf("It should not be an empty line '%s'\n",line);
12936: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
12937: }
1.307 brouard 12938: if(ncovmodel >=2 && nresult==0 ){
12939: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
12940: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12941: }
1.307 brouard 12942: /* goto end; */
12943: break;
1.308 brouard 12944: case 15:
12945: printf("End of resultlines.\n");
12946: fprintf(ficlog,"End of resultlines.\n");
12947: break;
12948: default: /* parameterline =0 */
1.307 brouard 12949: nresult=1;
12950: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 12951: } /* End switch parameterline */
12952: }while(endishere==0); /* End do */
1.126 brouard 12953:
1.230 brouard 12954: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12955: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12956:
12957: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12958: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12959: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12960: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12961: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12962: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12963: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12964: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12965: }else{
1.270 brouard 12966: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 12967: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
12968: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
12969: if(prvforecast==1){
12970: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
12971: jprojd=jproj1;
12972: mprojd=mproj1;
12973: anprojd=anproj1;
12974: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
12975: jprojf=jproj2;
12976: mprojf=mproj2;
12977: anprojf=anproj2;
12978: } else if(prvforecast == 2){
12979: dateprojd=dateintmean;
12980: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
12981: dateprojf=dateintmean+yrfproj;
12982: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
12983: }
12984: if(prvbackcast==1){
12985: datebackd=(jback1+12*mback1+365*anback1)/365;
12986: jbackd=jback1;
12987: mbackd=mback1;
12988: anbackd=anback1;
12989: datebackf=(jback2+12*mback2+365*anback2)/365;
12990: jbackf=jback2;
12991: mbackf=mback2;
12992: anbackf=anback2;
12993: } else if(prvbackcast == 2){
12994: datebackd=dateintmean;
12995: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
12996: datebackf=dateintmean-yrbproj;
12997: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
12998: }
12999:
13000: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 13001: }
13002: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 13003: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
13004: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 13005:
1.225 brouard 13006: /*------------ free_vector -------------*/
13007: /* chdir(path); */
1.220 brouard 13008:
1.215 brouard 13009: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
13010: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
13011: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
13012: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 13013: free_lvector(num,firstobs,lastobs);
13014: free_vector(agedc,firstobs,lastobs);
1.126 brouard 13015: /*free_matrix(covar,0,NCOVMAX,1,n);*/
13016: /*free_matrix(covar,1,NCOVMAX,1,n);*/
13017: fclose(ficparo);
13018: fclose(ficres);
1.220 brouard 13019:
13020:
1.186 brouard 13021: /* Other results (useful)*/
1.220 brouard 13022:
13023:
1.126 brouard 13024: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13025: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13026: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 13027: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13028: fclose(ficrespl);
13029:
13030: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13031: /*#include "hpijx.h"*/
13032: hPijx(p, bage, fage);
1.145 brouard 13033: fclose(ficrespij);
1.227 brouard 13034:
1.220 brouard 13035: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 13036: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 13037: k=1;
1.126 brouard 13038: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13039:
1.269 brouard 13040: /* Prevalence for each covariate combination in probs[age][status][cov] */
13041: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13042: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13043: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13044: for(k=1;k<=ncovcombmax;k++)
13045: probs[i][j][k]=0.;
1.269 brouard 13046: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13047: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13048: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13049: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13050: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13051: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13052: for(k=1;k<=ncovcombmax;k++)
13053: mobaverages[i][j][k]=0.;
1.219 brouard 13054: mobaverage=mobaverages;
13055: if (mobilav!=0) {
1.235 brouard 13056: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13057: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13058: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13059: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13060: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13061: }
1.269 brouard 13062: } else if (mobilavproj !=0) {
1.235 brouard 13063: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13064: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13065: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13066: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13067: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13068: }
1.269 brouard 13069: }else{
13070: printf("Internal error moving average\n");
13071: fflush(stdout);
13072: exit(1);
1.219 brouard 13073: }
13074: }/* end if moving average */
1.227 brouard 13075:
1.126 brouard 13076: /*---------- Forecasting ------------------*/
1.296 brouard 13077: if(prevfcast==1){
13078: /* /\* if(stepm ==1){*\/ */
13079: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13080: /*This done previously after freqsummary.*/
13081: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13082: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13083:
13084: /* } else if (prvforecast==2){ */
13085: /* /\* if(stepm ==1){*\/ */
13086: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13087: /* } */
13088: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13089: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13090: }
1.269 brouard 13091:
1.296 brouard 13092: /* Prevbcasting */
13093: if(prevbcast==1){
1.219 brouard 13094: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13095: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13096: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13097:
13098: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13099:
13100: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13101:
1.219 brouard 13102: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13103: fclose(ficresplb);
13104:
1.222 brouard 13105: hBijx(p, bage, fage, mobaverage);
13106: fclose(ficrespijb);
1.219 brouard 13107:
1.296 brouard 13108: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13109: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13110: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13111: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13112: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13113: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13114:
13115:
1.269 brouard 13116: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13117:
13118:
1.269 brouard 13119: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13120: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13121: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13122: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13123: } /* end Prevbcasting */
1.268 brouard 13124:
1.186 brouard 13125:
13126: /* ------ Other prevalence ratios------------ */
1.126 brouard 13127:
1.215 brouard 13128: free_ivector(wav,1,imx);
13129: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13130: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13131: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13132:
13133:
1.127 brouard 13134: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 13135:
1.201 brouard 13136: strcpy(filerese,"E_");
13137: strcat(filerese,fileresu);
1.126 brouard 13138: if((ficreseij=fopen(filerese,"w"))==NULL) {
13139: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13140: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13141: }
1.208 brouard 13142: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
13143: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 13144:
13145: pstamp(ficreseij);
1.219 brouard 13146:
1.235 brouard 13147: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13148: if (cptcovn < 1){i1=1;}
13149:
13150: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13151: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13152: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13153: continue;
1.219 brouard 13154: fprintf(ficreseij,"\n#****** ");
1.235 brouard 13155: printf("\n#****** ");
1.225 brouard 13156: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13157: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13158: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13159: }
13160: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13161: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13162: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 13163: }
13164: fprintf(ficreseij,"******\n");
1.235 brouard 13165: printf("******\n");
1.219 brouard 13166:
13167: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13168: oldm=oldms;savm=savms;
1.235 brouard 13169: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 13170:
1.219 brouard 13171: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 13172: }
13173: fclose(ficreseij);
1.208 brouard 13174: printf("done evsij\n");fflush(stdout);
13175: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 13176:
1.218 brouard 13177:
1.227 brouard 13178: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 13179:
1.201 brouard 13180: strcpy(filerest,"T_");
13181: strcat(filerest,fileresu);
1.127 brouard 13182: if((ficrest=fopen(filerest,"w"))==NULL) {
13183: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
13184: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
13185: }
1.208 brouard 13186: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
13187: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 13188: strcpy(fileresstde,"STDE_");
13189: strcat(fileresstde,fileresu);
1.126 brouard 13190: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 13191: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
13192: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 13193: }
1.227 brouard 13194: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
13195: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 13196:
1.201 brouard 13197: strcpy(filerescve,"CVE_");
13198: strcat(filerescve,fileresu);
1.126 brouard 13199: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 13200: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
13201: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 13202: }
1.227 brouard 13203: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
13204: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 13205:
1.201 brouard 13206: strcpy(fileresv,"V_");
13207: strcat(fileresv,fileresu);
1.126 brouard 13208: if((ficresvij=fopen(fileresv,"w"))==NULL) {
13209: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
13210: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
13211: }
1.227 brouard 13212: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
13213: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 13214:
1.235 brouard 13215: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13216: if (cptcovn < 1){i1=1;}
13217:
13218: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13219: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13220: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13221: continue;
1.321 brouard 13222: printf("\n# model %s \n#****** Result for:", model);
13223: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
13224: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.227 brouard 13225: for(j=1;j<=cptcoveff;j++){
13226: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13227: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13228: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13229: }
1.235 brouard 13230: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13231: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13232: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13233: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13234: }
1.208 brouard 13235: fprintf(ficrest,"******\n");
1.227 brouard 13236: fprintf(ficlog,"******\n");
13237: printf("******\n");
1.208 brouard 13238:
13239: fprintf(ficresstdeij,"\n#****** ");
13240: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 13241: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13242: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13243: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 13244: }
1.235 brouard 13245: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13246: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13247: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13248: }
1.208 brouard 13249: fprintf(ficresstdeij,"******\n");
13250: fprintf(ficrescveij,"******\n");
13251:
13252: fprintf(ficresvij,"\n#****** ");
1.238 brouard 13253: /* pstamp(ficresvij); */
1.225 brouard 13254: for(j=1;j<=cptcoveff;j++)
1.227 brouard 13255: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13256: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13257: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13258: }
1.208 brouard 13259: fprintf(ficresvij,"******\n");
13260:
13261: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13262: oldm=oldms;savm=savms;
1.235 brouard 13263: printf(" cvevsij ");
13264: fprintf(ficlog, " cvevsij ");
13265: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 13266: printf(" end cvevsij \n ");
13267: fprintf(ficlog, " end cvevsij \n ");
13268:
13269: /*
13270: */
13271: /* goto endfree; */
13272:
13273: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13274: pstamp(ficrest);
13275:
1.269 brouard 13276: epj=vector(1,nlstate+1);
1.208 brouard 13277: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 13278: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
13279: cptcod= 0; /* To be deleted */
13280: printf("varevsij vpopbased=%d \n",vpopbased);
13281: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 13282: 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 13283: 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 ");
13284: if(vpopbased==1)
13285: 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);
13286: else
1.288 brouard 13287: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13288: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
13289: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
13290: fprintf(ficrest,"\n");
13291: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 13292: printf("Computing age specific forward period (stable) prevalences in each health state \n");
13293: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13294: for(age=bage; age <=fage ;age++){
1.235 brouard 13295: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 13296: if (vpopbased==1) {
13297: if(mobilav ==0){
13298: for(i=1; i<=nlstate;i++)
13299: prlim[i][i]=probs[(int)age][i][k];
13300: }else{ /* mobilav */
13301: for(i=1; i<=nlstate;i++)
13302: prlim[i][i]=mobaverage[(int)age][i][k];
13303: }
13304: }
1.219 brouard 13305:
1.227 brouard 13306: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
13307: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
13308: /* printf(" age %4.0f ",age); */
13309: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
13310: for(i=1, epj[j]=0.;i <=nlstate;i++) {
13311: epj[j] += prlim[i][i]*eij[i][j][(int)age];
13312: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
13313: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
13314: }
13315: epj[nlstate+1] +=epj[j];
13316: }
13317: /* printf(" age %4.0f \n",age); */
1.219 brouard 13318:
1.227 brouard 13319: for(i=1, vepp=0.;i <=nlstate;i++)
13320: for(j=1;j <=nlstate;j++)
13321: vepp += vareij[i][j][(int)age];
13322: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
13323: for(j=1;j <=nlstate;j++){
13324: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
13325: }
13326: fprintf(ficrest,"\n");
13327: }
1.208 brouard 13328: } /* End vpopbased */
1.269 brouard 13329: free_vector(epj,1,nlstate+1);
1.208 brouard 13330: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
13331: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 13332: printf("done selection\n");fflush(stdout);
13333: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 13334:
1.235 brouard 13335: } /* End k selection */
1.227 brouard 13336:
13337: printf("done State-specific expectancies\n");fflush(stdout);
13338: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
13339:
1.288 brouard 13340: /* variance-covariance of forward period prevalence*/
1.269 brouard 13341: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13342:
1.227 brouard 13343:
1.290 brouard 13344: free_vector(weight,firstobs,lastobs);
1.227 brouard 13345: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 13346: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
13347: free_matrix(anint,1,maxwav,firstobs,lastobs);
13348: free_matrix(mint,1,maxwav,firstobs,lastobs);
13349: free_ivector(cod,firstobs,lastobs);
1.227 brouard 13350: free_ivector(tab,1,NCOVMAX);
13351: fclose(ficresstdeij);
13352: fclose(ficrescveij);
13353: fclose(ficresvij);
13354: fclose(ficrest);
13355: fclose(ficpar);
13356:
13357:
1.126 brouard 13358: /*---------- End : free ----------------*/
1.219 brouard 13359: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 13360: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
13361: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 13362: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
13363: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 13364: } /* mle==-3 arrives here for freeing */
1.227 brouard 13365: /* endfree:*/
13366: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
13367: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
13368: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 13369: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13370: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13371: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13372: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13373: free_matrix(matcov,1,npar,1,npar);
13374: free_matrix(hess,1,npar,1,npar);
13375: /*free_vector(delti,1,npar);*/
13376: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13377: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13378: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13379: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13380:
13381: free_ivector(ncodemax,1,NCOVMAX);
13382: free_ivector(ncodemaxwundef,1,NCOVMAX);
13383: free_ivector(Dummy,-1,NCOVMAX);
13384: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13385: free_ivector(DummyV,1,NCOVMAX);
13386: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13387: free_ivector(Typevar,-1,NCOVMAX);
13388: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13389: free_ivector(TvarsQ,1,NCOVMAX);
13390: free_ivector(TvarsQind,1,NCOVMAX);
13391: free_ivector(TvarsD,1,NCOVMAX);
13392: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13393: free_ivector(TvarFD,1,NCOVMAX);
13394: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13395: free_ivector(TvarF,1,NCOVMAX);
13396: free_ivector(TvarFind,1,NCOVMAX);
13397: free_ivector(TvarV,1,NCOVMAX);
13398: free_ivector(TvarVind,1,NCOVMAX);
13399: free_ivector(TvarA,1,NCOVMAX);
13400: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13401: free_ivector(TvarFQ,1,NCOVMAX);
13402: free_ivector(TvarFQind,1,NCOVMAX);
13403: free_ivector(TvarVD,1,NCOVMAX);
13404: free_ivector(TvarVDind,1,NCOVMAX);
13405: free_ivector(TvarVQ,1,NCOVMAX);
13406: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13407: free_ivector(Tvarsel,1,NCOVMAX);
13408: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13409: free_ivector(Tposprod,1,NCOVMAX);
13410: free_ivector(Tprod,1,NCOVMAX);
13411: free_ivector(Tvaraff,1,NCOVMAX);
13412: free_ivector(invalidvarcomb,1,ncovcombmax);
13413: free_ivector(Tage,1,NCOVMAX);
13414: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 13415: free_ivector(TmodelInvind,1,NCOVMAX);
13416: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 13417:
13418: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
13419: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 13420: fflush(fichtm);
13421: fflush(ficgp);
13422:
1.227 brouard 13423:
1.126 brouard 13424: if((nberr >0) || (nbwarn>0)){
1.216 brouard 13425: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
13426: 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 13427: }else{
13428: printf("End of Imach\n");
13429: fprintf(ficlog,"End of Imach\n");
13430: }
13431: printf("See log file on %s\n",filelog);
13432: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 13433: /*(void) gettimeofday(&end_time,&tzp);*/
13434: rend_time = time(NULL);
13435: end_time = *localtime(&rend_time);
13436: /* tml = *localtime(&end_time.tm_sec); */
13437: strcpy(strtend,asctime(&end_time));
1.126 brouard 13438: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13439: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13440: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13441:
1.157 brouard 13442: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13443: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13444: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13445: /* printf("Total time was %d uSec.\n", total_usecs);*/
13446: /* if(fileappend(fichtm,optionfilehtm)){ */
13447: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13448: fclose(fichtm);
13449: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13450: fclose(fichtmcov);
13451: fclose(ficgp);
13452: fclose(ficlog);
13453: /*------ End -----------*/
1.227 brouard 13454:
1.281 brouard 13455:
13456: /* Executes gnuplot */
1.227 brouard 13457:
13458: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13459: #ifdef WIN32
1.227 brouard 13460: if (_chdir(pathcd) != 0)
13461: printf("Can't move to directory %s!\n",path);
13462: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13463: #else
1.227 brouard 13464: if(chdir(pathcd) != 0)
13465: printf("Can't move to directory %s!\n", path);
13466: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13467: #endif
1.126 brouard 13468: printf("Current directory %s!\n",pathcd);
13469: /*strcat(plotcmd,CHARSEPARATOR);*/
13470: sprintf(plotcmd,"gnuplot");
1.157 brouard 13471: #ifdef _WIN32
1.126 brouard 13472: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13473: #endif
13474: if(!stat(plotcmd,&info)){
1.158 brouard 13475: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13476: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13477: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13478: }else
13479: strcpy(pplotcmd,plotcmd);
1.157 brouard 13480: #ifdef __unix
1.126 brouard 13481: strcpy(plotcmd,GNUPLOTPROGRAM);
13482: if(!stat(plotcmd,&info)){
1.158 brouard 13483: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13484: }else
13485: strcpy(pplotcmd,plotcmd);
13486: #endif
13487: }else
13488: strcpy(pplotcmd,plotcmd);
13489:
13490: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13491: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13492: strcpy(pplotcmd,plotcmd);
1.227 brouard 13493:
1.126 brouard 13494: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13495: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13496: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13497: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13498: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13499: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13500: strcpy(plotcmd,pplotcmd);
13501: }
1.126 brouard 13502: }
1.158 brouard 13503: printf(" Successful, please wait...");
1.126 brouard 13504: while (z[0] != 'q') {
13505: /* chdir(path); */
1.154 brouard 13506: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13507: scanf("%s",z);
13508: /* if (z[0] == 'c') system("./imach"); */
13509: if (z[0] == 'e') {
1.158 brouard 13510: #ifdef __APPLE__
1.152 brouard 13511: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13512: #elif __linux
13513: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13514: #else
1.152 brouard 13515: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13516: #endif
13517: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13518: system(pplotcmd);
1.126 brouard 13519: }
13520: else if (z[0] == 'g') system(plotcmd);
13521: else if (z[0] == 'q') exit(0);
13522: }
1.227 brouard 13523: end:
1.126 brouard 13524: while (z[0] != 'q') {
1.195 brouard 13525: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13526: scanf("%s",z);
13527: }
1.283 brouard 13528: printf("End\n");
1.282 brouard 13529: exit(0);
1.126 brouard 13530: }
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