Annotation of imach/src/imach.c, revision 1.320
1.320 ! brouard 1: /* $Id: imach.c,v 1.319 2022/06/02 04:45:11 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.320 ! brouard 4: Revision 1.319 2022/06/02 04:45:11 brouard
! 5: * imach.c (Module): Adding the Wald tests from the log to the main
! 6: htm for better display of the maximum likelihood estimators.
! 7:
1.319 brouard 8: Revision 1.318 2022/05/24 08:10:59 brouard
9: * imach.c (Module): Some attempts to find a bug of wrong estimates
10: of confidencce intervals with product in the equation modelC
11:
1.318 brouard 12: Revision 1.317 2022/05/15 15:06:23 brouard
13: * imach.c (Module): Some minor improvements
14:
1.317 brouard 15: Revision 1.316 2022/05/11 15:11:31 brouard
16: Summary: r27
17:
1.316 brouard 18: Revision 1.315 2022/05/11 15:06:32 brouard
19: *** empty log message ***
20:
1.315 brouard 21: Revision 1.314 2022/04/13 17:43:09 brouard
22: * imach.c (Module): Adding link to text data files
23:
1.314 brouard 24: Revision 1.313 2022/04/11 15:57:42 brouard
25: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
26:
1.313 brouard 27: Revision 1.312 2022/04/05 21:24:39 brouard
28: *** empty log message ***
29:
1.312 brouard 30: Revision 1.311 2022/04/05 21:03:51 brouard
31: Summary: Fixed quantitative covariates
32:
33: Fixed covariates (dummy or quantitative)
34: with missing values have never been allowed but are ERRORS and
35: program quits. Standard deviations of fixed covariates were
36: wrongly computed. Mean and standard deviations of time varying
37: covariates are still not computed.
38:
1.311 brouard 39: Revision 1.310 2022/03/17 08:45:53 brouard
40: Summary: 99r25
41:
42: Improving detection of errors: result lines should be compatible with
43: the model.
44:
1.310 brouard 45: Revision 1.309 2021/05/20 12:39:14 brouard
46: Summary: Version 0.99r24
47:
1.309 brouard 48: Revision 1.308 2021/03/31 13:11:57 brouard
49: Summary: Version 0.99r23
50:
51:
52: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
53:
1.308 brouard 54: Revision 1.307 2021/03/08 18:11:32 brouard
55: Summary: 0.99r22 fixed bug on result:
56:
1.307 brouard 57: Revision 1.306 2021/02/20 15:44:02 brouard
58: Summary: Version 0.99r21
59:
60: * imach.c (Module): Fix bug on quitting after result lines!
61: (Module): Version 0.99r21
62:
1.306 brouard 63: Revision 1.305 2021/02/20 15:28:30 brouard
64: * imach.c (Module): Fix bug on quitting after result lines!
65:
1.305 brouard 66: Revision 1.304 2021/02/12 11:34:20 brouard
67: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
68:
1.304 brouard 69: Revision 1.303 2021/02/11 19:50:15 brouard
70: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
71:
1.303 brouard 72: Revision 1.302 2020/02/22 21:00:05 brouard
73: * (Module): imach.c Update mle=-3 (for computing Life expectancy
74: and life table from the data without any state)
75:
1.302 brouard 76: Revision 1.301 2019/06/04 13:51:20 brouard
77: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
78:
1.301 brouard 79: Revision 1.300 2019/05/22 19:09:45 brouard
80: Summary: version 0.99r19 of May 2019
81:
1.300 brouard 82: Revision 1.299 2019/05/22 18:37:08 brouard
83: Summary: Cleaned 0.99r19
84:
1.299 brouard 85: Revision 1.298 2019/05/22 18:19:56 brouard
86: *** empty log message ***
87:
1.298 brouard 88: Revision 1.297 2019/05/22 17:56:10 brouard
89: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
90:
1.297 brouard 91: Revision 1.296 2019/05/20 13:03:18 brouard
92: Summary: Projection syntax simplified
93:
94:
95: We can now start projections, forward or backward, from the mean date
96: of inteviews up to or down to a number of years of projection:
97: prevforecast=1 yearsfproj=15.3 mobil_average=0
98: or
99: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
100: or
101: prevbackcast=1 yearsbproj=12.3 mobil_average=1
102: or
103: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
104:
1.296 brouard 105: Revision 1.295 2019/05/18 09:52:50 brouard
106: Summary: doxygen tex bug
107:
1.295 brouard 108: Revision 1.294 2019/05/16 14:54:33 brouard
109: Summary: There was some wrong lines added
110:
1.294 brouard 111: Revision 1.293 2019/05/09 15:17:34 brouard
112: *** empty log message ***
113:
1.293 brouard 114: Revision 1.292 2019/05/09 14:17:20 brouard
115: Summary: Some updates
116:
1.292 brouard 117: Revision 1.291 2019/05/09 13:44:18 brouard
118: Summary: Before ncovmax
119:
1.291 brouard 120: Revision 1.290 2019/05/09 13:39:37 brouard
121: Summary: 0.99r18 unlimited number of individuals
122:
123: 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.
124:
1.290 brouard 125: Revision 1.289 2018/12/13 09:16:26 brouard
126: Summary: Bug for young ages (<-30) will be in r17
127:
1.289 brouard 128: Revision 1.288 2018/05/02 20:58:27 brouard
129: Summary: Some bugs fixed
130:
1.288 brouard 131: Revision 1.287 2018/05/01 17:57:25 brouard
132: Summary: Bug fixed by providing frequencies only for non missing covariates
133:
1.287 brouard 134: Revision 1.286 2018/04/27 14:27:04 brouard
135: Summary: some minor bugs
136:
1.286 brouard 137: Revision 1.285 2018/04/21 21:02:16 brouard
138: Summary: Some bugs fixed, valgrind tested
139:
1.285 brouard 140: Revision 1.284 2018/04/20 05:22:13 brouard
141: Summary: Computing mean and stdeviation of fixed quantitative variables
142:
1.284 brouard 143: Revision 1.283 2018/04/19 14:49:16 brouard
144: Summary: Some minor bugs fixed
145:
1.283 brouard 146: Revision 1.282 2018/02/27 22:50:02 brouard
147: *** empty log message ***
148:
1.282 brouard 149: Revision 1.281 2018/02/27 19:25:23 brouard
150: Summary: Adding second argument for quitting
151:
1.281 brouard 152: Revision 1.280 2018/02/21 07:58:13 brouard
153: Summary: 0.99r15
154:
155: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
156:
1.280 brouard 157: Revision 1.279 2017/07/20 13:35:01 brouard
158: Summary: temporary working
159:
1.279 brouard 160: Revision 1.278 2017/07/19 14:09:02 brouard
161: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
162:
1.278 brouard 163: Revision 1.277 2017/07/17 08:53:49 brouard
164: Summary: BOM files can be read now
165:
1.277 brouard 166: Revision 1.276 2017/06/30 15:48:31 brouard
167: Summary: Graphs improvements
168:
1.276 brouard 169: Revision 1.275 2017/06/30 13:39:33 brouard
170: Summary: Saito's color
171:
1.275 brouard 172: Revision 1.274 2017/06/29 09:47:08 brouard
173: Summary: Version 0.99r14
174:
1.274 brouard 175: Revision 1.273 2017/06/27 11:06:02 brouard
176: Summary: More documentation on projections
177:
1.273 brouard 178: Revision 1.272 2017/06/27 10:22:40 brouard
179: Summary: Color of backprojection changed from 6 to 5(yellow)
180:
1.272 brouard 181: Revision 1.271 2017/06/27 10:17:50 brouard
182: Summary: Some bug with rint
183:
1.271 brouard 184: Revision 1.270 2017/05/24 05:45:29 brouard
185: *** empty log message ***
186:
1.270 brouard 187: Revision 1.269 2017/05/23 08:39:25 brouard
188: Summary: Code into subroutine, cleanings
189:
1.269 brouard 190: Revision 1.268 2017/05/18 20:09:32 brouard
191: Summary: backprojection and confidence intervals of backprevalence
192:
1.268 brouard 193: Revision 1.267 2017/05/13 10:25:05 brouard
194: Summary: temporary save for backprojection
195:
1.267 brouard 196: Revision 1.266 2017/05/13 07:26:12 brouard
197: Summary: Version 0.99r13 (improvements and bugs fixed)
198:
1.266 brouard 199: Revision 1.265 2017/04/26 16:22:11 brouard
200: Summary: imach 0.99r13 Some bugs fixed
201:
1.265 brouard 202: Revision 1.264 2017/04/26 06:01:29 brouard
203: Summary: Labels in graphs
204:
1.264 brouard 205: Revision 1.263 2017/04/24 15:23:15 brouard
206: Summary: to save
207:
1.263 brouard 208: Revision 1.262 2017/04/18 16:48:12 brouard
209: *** empty log message ***
210:
1.262 brouard 211: Revision 1.261 2017/04/05 10:14:09 brouard
212: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
213:
1.261 brouard 214: Revision 1.260 2017/04/04 17:46:59 brouard
215: Summary: Gnuplot indexations fixed (humm)
216:
1.260 brouard 217: Revision 1.259 2017/04/04 13:01:16 brouard
218: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
219:
1.259 brouard 220: Revision 1.258 2017/04/03 10:17:47 brouard
221: Summary: Version 0.99r12
222:
223: Some cleanings, conformed with updated documentation.
224:
1.258 brouard 225: Revision 1.257 2017/03/29 16:53:30 brouard
226: Summary: Temp
227:
1.257 brouard 228: Revision 1.256 2017/03/27 05:50:23 brouard
229: Summary: Temporary
230:
1.256 brouard 231: Revision 1.255 2017/03/08 16:02:28 brouard
232: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
233:
1.255 brouard 234: Revision 1.254 2017/03/08 07:13:00 brouard
235: Summary: Fixing data parameter line
236:
1.254 brouard 237: Revision 1.253 2016/12/15 11:59:41 brouard
238: Summary: 0.99 in progress
239:
1.253 brouard 240: Revision 1.252 2016/09/15 21:15:37 brouard
241: *** empty log message ***
242:
1.252 brouard 243: Revision 1.251 2016/09/15 15:01:13 brouard
244: Summary: not working
245:
1.251 brouard 246: Revision 1.250 2016/09/08 16:07:27 brouard
247: Summary: continue
248:
1.250 brouard 249: Revision 1.249 2016/09/07 17:14:18 brouard
250: Summary: Starting values from frequencies
251:
1.249 brouard 252: Revision 1.248 2016/09/07 14:10:18 brouard
253: *** empty log message ***
254:
1.248 brouard 255: Revision 1.247 2016/09/02 11:11:21 brouard
256: *** empty log message ***
257:
1.247 brouard 258: Revision 1.246 2016/09/02 08:49:22 brouard
259: *** empty log message ***
260:
1.246 brouard 261: Revision 1.245 2016/09/02 07:25:01 brouard
262: *** empty log message ***
263:
1.245 brouard 264: Revision 1.244 2016/09/02 07:17:34 brouard
265: *** empty log message ***
266:
1.244 brouard 267: Revision 1.243 2016/09/02 06:45:35 brouard
268: *** empty log message ***
269:
1.243 brouard 270: Revision 1.242 2016/08/30 15:01:20 brouard
271: Summary: Fixing a lots
272:
1.242 brouard 273: Revision 1.241 2016/08/29 17:17:25 brouard
274: Summary: gnuplot problem in Back projection to fix
275:
1.241 brouard 276: Revision 1.240 2016/08/29 07:53:18 brouard
277: Summary: Better
278:
1.240 brouard 279: Revision 1.239 2016/08/26 15:51:03 brouard
280: Summary: Improvement in Powell output in order to copy and paste
281:
282: Author:
283:
1.239 brouard 284: Revision 1.238 2016/08/26 14:23:35 brouard
285: Summary: Starting tests of 0.99
286:
1.238 brouard 287: Revision 1.237 2016/08/26 09:20:19 brouard
288: Summary: to valgrind
289:
1.237 brouard 290: Revision 1.236 2016/08/25 10:50:18 brouard
291: *** empty log message ***
292:
1.236 brouard 293: Revision 1.235 2016/08/25 06:59:23 brouard
294: *** empty log message ***
295:
1.235 brouard 296: Revision 1.234 2016/08/23 16:51:20 brouard
297: *** empty log message ***
298:
1.234 brouard 299: Revision 1.233 2016/08/23 07:40:50 brouard
300: Summary: not working
301:
1.233 brouard 302: Revision 1.232 2016/08/22 14:20:21 brouard
303: Summary: not working
304:
1.232 brouard 305: Revision 1.231 2016/08/22 07:17:15 brouard
306: Summary: not working
307:
1.231 brouard 308: Revision 1.230 2016/08/22 06:55:53 brouard
309: Summary: Not working
310:
1.230 brouard 311: Revision 1.229 2016/07/23 09:45:53 brouard
312: Summary: Completing for func too
313:
1.229 brouard 314: Revision 1.228 2016/07/22 17:45:30 brouard
315: Summary: Fixing some arrays, still debugging
316:
1.227 brouard 317: Revision 1.226 2016/07/12 18:42:34 brouard
318: Summary: temp
319:
1.226 brouard 320: Revision 1.225 2016/07/12 08:40:03 brouard
321: Summary: saving but not running
322:
1.225 brouard 323: Revision 1.224 2016/07/01 13:16:01 brouard
324: Summary: Fixes
325:
1.224 brouard 326: Revision 1.223 2016/02/19 09:23:35 brouard
327: Summary: temporary
328:
1.223 brouard 329: Revision 1.222 2016/02/17 08:14:50 brouard
330: Summary: Probably last 0.98 stable version 0.98r6
331:
1.222 brouard 332: Revision 1.221 2016/02/15 23:35:36 brouard
333: Summary: minor bug
334:
1.220 brouard 335: Revision 1.219 2016/02/15 00:48:12 brouard
336: *** empty log message ***
337:
1.219 brouard 338: Revision 1.218 2016/02/12 11:29:23 brouard
339: Summary: 0.99 Back projections
340:
1.218 brouard 341: Revision 1.217 2015/12/23 17:18:31 brouard
342: Summary: Experimental backcast
343:
1.217 brouard 344: Revision 1.216 2015/12/18 17:32:11 brouard
345: Summary: 0.98r4 Warning and status=-2
346:
347: Version 0.98r4 is now:
348: - displaying an error when status is -1, date of interview unknown and date of death known;
349: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
350: Older changes concerning s=-2, dating from 2005 have been supersed.
351:
1.216 brouard 352: Revision 1.215 2015/12/16 08:52:24 brouard
353: Summary: 0.98r4 working
354:
1.215 brouard 355: Revision 1.214 2015/12/16 06:57:54 brouard
356: Summary: temporary not working
357:
1.214 brouard 358: Revision 1.213 2015/12/11 18:22:17 brouard
359: Summary: 0.98r4
360:
1.213 brouard 361: Revision 1.212 2015/11/21 12:47:24 brouard
362: Summary: minor typo
363:
1.212 brouard 364: Revision 1.211 2015/11/21 12:41:11 brouard
365: Summary: 0.98r3 with some graph of projected cross-sectional
366:
367: Author: Nicolas Brouard
368:
1.211 brouard 369: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 370: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 371: Summary: Adding ftolpl parameter
372: Author: N Brouard
373:
374: We had difficulties to get smoothed confidence intervals. It was due
375: to the period prevalence which wasn't computed accurately. The inner
376: parameter ftolpl is now an outer parameter of the .imach parameter
377: file after estepm. If ftolpl is small 1.e-4 and estepm too,
378: computation are long.
379:
1.209 brouard 380: Revision 1.208 2015/11/17 14:31:57 brouard
381: Summary: temporary
382:
1.208 brouard 383: Revision 1.207 2015/10/27 17:36:57 brouard
384: *** empty log message ***
385:
1.207 brouard 386: Revision 1.206 2015/10/24 07:14:11 brouard
387: *** empty log message ***
388:
1.206 brouard 389: Revision 1.205 2015/10/23 15:50:53 brouard
390: Summary: 0.98r3 some clarification for graphs on likelihood contributions
391:
1.205 brouard 392: Revision 1.204 2015/10/01 16:20:26 brouard
393: Summary: Some new graphs of contribution to likelihood
394:
1.204 brouard 395: Revision 1.203 2015/09/30 17:45:14 brouard
396: Summary: looking at better estimation of the hessian
397:
398: Also a better criteria for convergence to the period prevalence And
399: therefore adding the number of years needed to converge. (The
400: prevalence in any alive state shold sum to one
401:
1.203 brouard 402: Revision 1.202 2015/09/22 19:45:16 brouard
403: Summary: Adding some overall graph on contribution to likelihood. Might change
404:
1.202 brouard 405: Revision 1.201 2015/09/15 17:34:58 brouard
406: Summary: 0.98r0
407:
408: - Some new graphs like suvival functions
409: - Some bugs fixed like model=1+age+V2.
410:
1.201 brouard 411: Revision 1.200 2015/09/09 16:53:55 brouard
412: Summary: Big bug thanks to Flavia
413:
414: Even model=1+age+V2. did not work anymore
415:
1.200 brouard 416: Revision 1.199 2015/09/07 14:09:23 brouard
417: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
418:
1.199 brouard 419: Revision 1.198 2015/09/03 07:14:39 brouard
420: Summary: 0.98q5 Flavia
421:
1.198 brouard 422: Revision 1.197 2015/09/01 18:24:39 brouard
423: *** empty log message ***
424:
1.197 brouard 425: Revision 1.196 2015/08/18 23:17:52 brouard
426: Summary: 0.98q5
427:
1.196 brouard 428: Revision 1.195 2015/08/18 16:28:39 brouard
429: Summary: Adding a hack for testing purpose
430:
431: After reading the title, ftol and model lines, if the comment line has
432: a q, starting with #q, the answer at the end of the run is quit. It
433: permits to run test files in batch with ctest. The former workaround was
434: $ echo q | imach foo.imach
435:
1.195 brouard 436: Revision 1.194 2015/08/18 13:32:00 brouard
437: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
438:
1.194 brouard 439: Revision 1.193 2015/08/04 07:17:42 brouard
440: Summary: 0.98q4
441:
1.193 brouard 442: Revision 1.192 2015/07/16 16:49:02 brouard
443: Summary: Fixing some outputs
444:
1.192 brouard 445: Revision 1.191 2015/07/14 10:00:33 brouard
446: Summary: Some fixes
447:
1.191 brouard 448: Revision 1.190 2015/05/05 08:51:13 brouard
449: Summary: Adding digits in output parameters (7 digits instead of 6)
450:
451: Fix 1+age+.
452:
1.190 brouard 453: Revision 1.189 2015/04/30 14:45:16 brouard
454: Summary: 0.98q2
455:
1.189 brouard 456: Revision 1.188 2015/04/30 08:27:53 brouard
457: *** empty log message ***
458:
1.188 brouard 459: Revision 1.187 2015/04/29 09:11:15 brouard
460: *** empty log message ***
461:
1.187 brouard 462: Revision 1.186 2015/04/23 12:01:52 brouard
463: Summary: V1*age is working now, version 0.98q1
464:
465: Some codes had been disabled in order to simplify and Vn*age was
466: working in the optimization phase, ie, giving correct MLE parameters,
467: but, as usual, outputs were not correct and program core dumped.
468:
1.186 brouard 469: Revision 1.185 2015/03/11 13:26:42 brouard
470: Summary: Inclusion of compile and links command line for Intel Compiler
471:
1.185 brouard 472: Revision 1.184 2015/03/11 11:52:39 brouard
473: Summary: Back from Windows 8. Intel Compiler
474:
1.184 brouard 475: Revision 1.183 2015/03/10 20:34:32 brouard
476: Summary: 0.98q0, trying with directest, mnbrak fixed
477:
478: We use directest instead of original Powell test; probably no
479: incidence on the results, but better justifications;
480: We fixed Numerical Recipes mnbrak routine which was wrong and gave
481: wrong results.
482:
1.183 brouard 483: Revision 1.182 2015/02/12 08:19:57 brouard
484: Summary: Trying to keep directest which seems simpler and more general
485: Author: Nicolas Brouard
486:
1.182 brouard 487: Revision 1.181 2015/02/11 23:22:24 brouard
488: Summary: Comments on Powell added
489:
490: Author:
491:
1.181 brouard 492: Revision 1.180 2015/02/11 17:33:45 brouard
493: Summary: Finishing move from main to function (hpijx and prevalence_limit)
494:
1.180 brouard 495: Revision 1.179 2015/01/04 09:57:06 brouard
496: Summary: back to OS/X
497:
1.179 brouard 498: Revision 1.178 2015/01/04 09:35:48 brouard
499: *** empty log message ***
500:
1.178 brouard 501: Revision 1.177 2015/01/03 18:40:56 brouard
502: Summary: Still testing ilc32 on OSX
503:
1.177 brouard 504: Revision 1.176 2015/01/03 16:45:04 brouard
505: *** empty log message ***
506:
1.176 brouard 507: Revision 1.175 2015/01/03 16:33:42 brouard
508: *** empty log message ***
509:
1.175 brouard 510: Revision 1.174 2015/01/03 16:15:49 brouard
511: Summary: Still in cross-compilation
512:
1.174 brouard 513: Revision 1.173 2015/01/03 12:06:26 brouard
514: Summary: trying to detect cross-compilation
515:
1.173 brouard 516: Revision 1.172 2014/12/27 12:07:47 brouard
517: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
518:
1.172 brouard 519: Revision 1.171 2014/12/23 13:26:59 brouard
520: Summary: Back from Visual C
521:
522: Still problem with utsname.h on Windows
523:
1.171 brouard 524: Revision 1.170 2014/12/23 11:17:12 brouard
525: Summary: Cleaning some \%% back to %%
526:
527: The escape was mandatory for a specific compiler (which one?), but too many warnings.
528:
1.170 brouard 529: Revision 1.169 2014/12/22 23:08:31 brouard
530: Summary: 0.98p
531:
532: Outputs some informations on compiler used, OS etc. Testing on different platforms.
533:
1.169 brouard 534: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 535: Summary: update
1.169 brouard 536:
1.168 brouard 537: Revision 1.167 2014/12/22 13:50:56 brouard
538: Summary: Testing uname and compiler version and if compiled 32 or 64
539:
540: Testing on Linux 64
541:
1.167 brouard 542: Revision 1.166 2014/12/22 11:40:47 brouard
543: *** empty log message ***
544:
1.166 brouard 545: Revision 1.165 2014/12/16 11:20:36 brouard
546: Summary: After compiling on Visual C
547:
548: * imach.c (Module): Merging 1.61 to 1.162
549:
1.165 brouard 550: Revision 1.164 2014/12/16 10:52:11 brouard
551: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
552:
553: * imach.c (Module): Merging 1.61 to 1.162
554:
1.164 brouard 555: Revision 1.163 2014/12/16 10:30:11 brouard
556: * imach.c (Module): Merging 1.61 to 1.162
557:
1.163 brouard 558: Revision 1.162 2014/09/25 11:43:39 brouard
559: Summary: temporary backup 0.99!
560:
1.162 brouard 561: Revision 1.1 2014/09/16 11:06:58 brouard
562: Summary: With some code (wrong) for nlopt
563:
564: Author:
565:
566: Revision 1.161 2014/09/15 20:41:41 brouard
567: Summary: Problem with macro SQR on Intel compiler
568:
1.161 brouard 569: Revision 1.160 2014/09/02 09:24:05 brouard
570: *** empty log message ***
571:
1.160 brouard 572: Revision 1.159 2014/09/01 10:34:10 brouard
573: Summary: WIN32
574: Author: Brouard
575:
1.159 brouard 576: Revision 1.158 2014/08/27 17:11:51 brouard
577: *** empty log message ***
578:
1.158 brouard 579: Revision 1.157 2014/08/27 16:26:55 brouard
580: Summary: Preparing windows Visual studio version
581: Author: Brouard
582:
583: In order to compile on Visual studio, time.h is now correct and time_t
584: and tm struct should be used. difftime should be used but sometimes I
585: just make the differences in raw time format (time(&now).
586: Trying to suppress #ifdef LINUX
587: Add xdg-open for __linux in order to open default browser.
588:
1.157 brouard 589: Revision 1.156 2014/08/25 20:10:10 brouard
590: *** empty log message ***
591:
1.156 brouard 592: Revision 1.155 2014/08/25 18:32:34 brouard
593: Summary: New compile, minor changes
594: Author: Brouard
595:
1.155 brouard 596: Revision 1.154 2014/06/20 17:32:08 brouard
597: Summary: Outputs now all graphs of convergence to period prevalence
598:
1.154 brouard 599: Revision 1.153 2014/06/20 16:45:46 brouard
600: Summary: If 3 live state, convergence to period prevalence on same graph
601: Author: Brouard
602:
1.153 brouard 603: Revision 1.152 2014/06/18 17:54:09 brouard
604: Summary: open browser, use gnuplot on same dir than imach if not found in the path
605:
1.152 brouard 606: Revision 1.151 2014/06/18 16:43:30 brouard
607: *** empty log message ***
608:
1.151 brouard 609: Revision 1.150 2014/06/18 16:42:35 brouard
610: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
611: Author: brouard
612:
1.150 brouard 613: Revision 1.149 2014/06/18 15:51:14 brouard
614: Summary: Some fixes in parameter files errors
615: Author: Nicolas Brouard
616:
1.149 brouard 617: Revision 1.148 2014/06/17 17:38:48 brouard
618: Summary: Nothing new
619: Author: Brouard
620:
621: Just a new packaging for OS/X version 0.98nS
622:
1.148 brouard 623: Revision 1.147 2014/06/16 10:33:11 brouard
624: *** empty log message ***
625:
1.147 brouard 626: Revision 1.146 2014/06/16 10:20:28 brouard
627: Summary: Merge
628: Author: Brouard
629:
630: Merge, before building revised version.
631:
1.146 brouard 632: Revision 1.145 2014/06/10 21:23:15 brouard
633: Summary: Debugging with valgrind
634: Author: Nicolas Brouard
635:
636: Lot of changes in order to output the results with some covariates
637: After the Edimburgh REVES conference 2014, it seems mandatory to
638: improve the code.
639: No more memory valgrind error but a lot has to be done in order to
640: continue the work of splitting the code into subroutines.
641: Also, decodemodel has been improved. Tricode is still not
642: optimal. nbcode should be improved. Documentation has been added in
643: the source code.
644:
1.144 brouard 645: Revision 1.143 2014/01/26 09:45:38 brouard
646: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
647:
648: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
649: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
650:
1.143 brouard 651: Revision 1.142 2014/01/26 03:57:36 brouard
652: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
653:
654: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
655:
1.142 brouard 656: Revision 1.141 2014/01/26 02:42:01 brouard
657: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
658:
1.141 brouard 659: Revision 1.140 2011/09/02 10:37:54 brouard
660: Summary: times.h is ok with mingw32 now.
661:
1.140 brouard 662: Revision 1.139 2010/06/14 07:50:17 brouard
663: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
664: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
665:
1.139 brouard 666: Revision 1.138 2010/04/30 18:19:40 brouard
667: *** empty log message ***
668:
1.138 brouard 669: Revision 1.137 2010/04/29 18:11:38 brouard
670: (Module): Checking covariates for more complex models
671: than V1+V2. A lot of change to be done. Unstable.
672:
1.137 brouard 673: Revision 1.136 2010/04/26 20:30:53 brouard
674: (Module): merging some libgsl code. Fixing computation
675: of likelione (using inter/intrapolation if mle = 0) in order to
676: get same likelihood as if mle=1.
677: Some cleaning of code and comments added.
678:
1.136 brouard 679: Revision 1.135 2009/10/29 15:33:14 brouard
680: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
681:
1.135 brouard 682: Revision 1.134 2009/10/29 13:18:53 brouard
683: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
684:
1.134 brouard 685: Revision 1.133 2009/07/06 10:21:25 brouard
686: just nforces
687:
1.133 brouard 688: Revision 1.132 2009/07/06 08:22:05 brouard
689: Many tings
690:
1.132 brouard 691: Revision 1.131 2009/06/20 16:22:47 brouard
692: Some dimensions resccaled
693:
1.131 brouard 694: Revision 1.130 2009/05/26 06:44:34 brouard
695: (Module): Max Covariate is now set to 20 instead of 8. A
696: lot of cleaning with variables initialized to 0. Trying to make
697: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
698:
1.130 brouard 699: Revision 1.129 2007/08/31 13:49:27 lievre
700: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
701:
1.129 lievre 702: Revision 1.128 2006/06/30 13:02:05 brouard
703: (Module): Clarifications on computing e.j
704:
1.128 brouard 705: Revision 1.127 2006/04/28 18:11:50 brouard
706: (Module): Yes the sum of survivors was wrong since
707: imach-114 because nhstepm was no more computed in the age
708: loop. Now we define nhstepma in the age loop.
709: (Module): In order to speed up (in case of numerous covariates) we
710: compute health expectancies (without variances) in a first step
711: and then all the health expectancies with variances or standard
712: deviation (needs data from the Hessian matrices) which slows the
713: computation.
714: In the future we should be able to stop the program is only health
715: expectancies and graph are needed without standard deviations.
716:
1.127 brouard 717: Revision 1.126 2006/04/28 17:23:28 brouard
718: (Module): Yes the sum of survivors was wrong since
719: imach-114 because nhstepm was no more computed in the age
720: loop. Now we define nhstepma in the age loop.
721: Version 0.98h
722:
1.126 brouard 723: Revision 1.125 2006/04/04 15:20:31 lievre
724: Errors in calculation of health expectancies. Age was not initialized.
725: Forecasting file added.
726:
727: Revision 1.124 2006/03/22 17:13:53 lievre
728: Parameters are printed with %lf instead of %f (more numbers after the comma).
729: The log-likelihood is printed in the log file
730:
731: Revision 1.123 2006/03/20 10:52:43 brouard
732: * imach.c (Module): <title> changed, corresponds to .htm file
733: name. <head> headers where missing.
734:
735: * imach.c (Module): Weights can have a decimal point as for
736: English (a comma might work with a correct LC_NUMERIC environment,
737: otherwise the weight is truncated).
738: Modification of warning when the covariates values are not 0 or
739: 1.
740: Version 0.98g
741:
742: Revision 1.122 2006/03/20 09:45:41 brouard
743: (Module): Weights can have a decimal point as for
744: English (a comma might work with a correct LC_NUMERIC environment,
745: otherwise the weight is truncated).
746: Modification of warning when the covariates values are not 0 or
747: 1.
748: Version 0.98g
749:
750: Revision 1.121 2006/03/16 17:45:01 lievre
751: * imach.c (Module): Comments concerning covariates added
752:
753: * imach.c (Module): refinements in the computation of lli if
754: status=-2 in order to have more reliable computation if stepm is
755: not 1 month. Version 0.98f
756:
757: Revision 1.120 2006/03/16 15:10:38 lievre
758: (Module): refinements in the computation of lli if
759: status=-2 in order to have more reliable computation if stepm is
760: not 1 month. Version 0.98f
761:
762: Revision 1.119 2006/03/15 17:42:26 brouard
763: (Module): Bug if status = -2, the loglikelihood was
764: computed as likelihood omitting the logarithm. Version O.98e
765:
766: Revision 1.118 2006/03/14 18:20:07 brouard
767: (Module): varevsij Comments added explaining the second
768: table of variances if popbased=1 .
769: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
770: (Module): Function pstamp added
771: (Module): Version 0.98d
772:
773: Revision 1.117 2006/03/14 17:16:22 brouard
774: (Module): varevsij Comments added explaining the second
775: table of variances if popbased=1 .
776: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
777: (Module): Function pstamp added
778: (Module): Version 0.98d
779:
780: Revision 1.116 2006/03/06 10:29:27 brouard
781: (Module): Variance-covariance wrong links and
782: varian-covariance of ej. is needed (Saito).
783:
784: Revision 1.115 2006/02/27 12:17:45 brouard
785: (Module): One freematrix added in mlikeli! 0.98c
786:
787: Revision 1.114 2006/02/26 12:57:58 brouard
788: (Module): Some improvements in processing parameter
789: filename with strsep.
790:
791: Revision 1.113 2006/02/24 14:20:24 brouard
792: (Module): Memory leaks checks with valgrind and:
793: datafile was not closed, some imatrix were not freed and on matrix
794: allocation too.
795:
796: Revision 1.112 2006/01/30 09:55:26 brouard
797: (Module): Back to gnuplot.exe instead of wgnuplot.exe
798:
799: Revision 1.111 2006/01/25 20:38:18 brouard
800: (Module): Lots of cleaning and bugs added (Gompertz)
801: (Module): Comments can be added in data file. Missing date values
802: can be a simple dot '.'.
803:
804: Revision 1.110 2006/01/25 00:51:50 brouard
805: (Module): Lots of cleaning and bugs added (Gompertz)
806:
807: Revision 1.109 2006/01/24 19:37:15 brouard
808: (Module): Comments (lines starting with a #) are allowed in data.
809:
810: Revision 1.108 2006/01/19 18:05:42 lievre
811: Gnuplot problem appeared...
812: To be fixed
813:
814: Revision 1.107 2006/01/19 16:20:37 brouard
815: Test existence of gnuplot in imach path
816:
817: Revision 1.106 2006/01/19 13:24:36 brouard
818: Some cleaning and links added in html output
819:
820: Revision 1.105 2006/01/05 20:23:19 lievre
821: *** empty log message ***
822:
823: Revision 1.104 2005/09/30 16:11:43 lievre
824: (Module): sump fixed, loop imx fixed, and simplifications.
825: (Module): If the status is missing at the last wave but we know
826: that the person is alive, then we can code his/her status as -2
827: (instead of missing=-1 in earlier versions) and his/her
828: contributions to the likelihood is 1 - Prob of dying from last
829: health status (= 1-p13= p11+p12 in the easiest case of somebody in
830: the healthy state at last known wave). Version is 0.98
831:
832: Revision 1.103 2005/09/30 15:54:49 lievre
833: (Module): sump fixed, loop imx fixed, and simplifications.
834:
835: Revision 1.102 2004/09/15 17:31:30 brouard
836: Add the possibility to read data file including tab characters.
837:
838: Revision 1.101 2004/09/15 10:38:38 brouard
839: Fix on curr_time
840:
841: Revision 1.100 2004/07/12 18:29:06 brouard
842: Add version for Mac OS X. Just define UNIX in Makefile
843:
844: Revision 1.99 2004/06/05 08:57:40 brouard
845: *** empty log message ***
846:
847: Revision 1.98 2004/05/16 15:05:56 brouard
848: New version 0.97 . First attempt to estimate force of mortality
849: directly from the data i.e. without the need of knowing the health
850: state at each age, but using a Gompertz model: log u =a + b*age .
851: This is the basic analysis of mortality and should be done before any
852: other analysis, in order to test if the mortality estimated from the
853: cross-longitudinal survey is different from the mortality estimated
854: from other sources like vital statistic data.
855:
856: The same imach parameter file can be used but the option for mle should be -3.
857:
1.133 brouard 858: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 859: former routines in order to include the new code within the former code.
860:
861: The output is very simple: only an estimate of the intercept and of
862: the slope with 95% confident intervals.
863:
864: Current limitations:
865: A) Even if you enter covariates, i.e. with the
866: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
867: B) There is no computation of Life Expectancy nor Life Table.
868:
869: Revision 1.97 2004/02/20 13:25:42 lievre
870: Version 0.96d. Population forecasting command line is (temporarily)
871: suppressed.
872:
873: Revision 1.96 2003/07/15 15:38:55 brouard
874: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
875: rewritten within the same printf. Workaround: many printfs.
876:
877: Revision 1.95 2003/07/08 07:54:34 brouard
878: * imach.c (Repository):
879: (Repository): Using imachwizard code to output a more meaningful covariance
880: matrix (cov(a12,c31) instead of numbers.
881:
882: Revision 1.94 2003/06/27 13:00:02 brouard
883: Just cleaning
884:
885: Revision 1.93 2003/06/25 16:33:55 brouard
886: (Module): On windows (cygwin) function asctime_r doesn't
887: exist so I changed back to asctime which exists.
888: (Module): Version 0.96b
889:
890: Revision 1.92 2003/06/25 16:30:45 brouard
891: (Module): On windows (cygwin) function asctime_r doesn't
892: exist so I changed back to asctime which exists.
893:
894: Revision 1.91 2003/06/25 15:30:29 brouard
895: * imach.c (Repository): Duplicated warning errors corrected.
896: (Repository): Elapsed time after each iteration is now output. It
897: helps to forecast when convergence will be reached. Elapsed time
898: is stamped in powell. We created a new html file for the graphs
899: concerning matrix of covariance. It has extension -cov.htm.
900:
901: Revision 1.90 2003/06/24 12:34:15 brouard
902: (Module): Some bugs corrected for windows. Also, when
903: mle=-1 a template is output in file "or"mypar.txt with the design
904: of the covariance matrix to be input.
905:
906: Revision 1.89 2003/06/24 12:30:52 brouard
907: (Module): Some bugs corrected for windows. Also, when
908: mle=-1 a template is output in file "or"mypar.txt with the design
909: of the covariance matrix to be input.
910:
911: Revision 1.88 2003/06/23 17:54:56 brouard
912: * 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.
913:
914: Revision 1.87 2003/06/18 12:26:01 brouard
915: Version 0.96
916:
917: Revision 1.86 2003/06/17 20:04:08 brouard
918: (Module): Change position of html and gnuplot routines and added
919: routine fileappend.
920:
921: Revision 1.85 2003/06/17 13:12:43 brouard
922: * imach.c (Repository): Check when date of death was earlier that
923: current date of interview. It may happen when the death was just
924: prior to the death. In this case, dh was negative and likelihood
925: was wrong (infinity). We still send an "Error" but patch by
926: assuming that the date of death was just one stepm after the
927: interview.
928: (Repository): Because some people have very long ID (first column)
929: we changed int to long in num[] and we added a new lvector for
930: memory allocation. But we also truncated to 8 characters (left
931: truncation)
932: (Repository): No more line truncation errors.
933:
934: Revision 1.84 2003/06/13 21:44:43 brouard
935: * imach.c (Repository): Replace "freqsummary" at a correct
936: place. It differs from routine "prevalence" which may be called
937: many times. Probs is memory consuming and must be used with
938: parcimony.
939: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
940:
941: Revision 1.83 2003/06/10 13:39:11 lievre
942: *** empty log message ***
943:
944: Revision 1.82 2003/06/05 15:57:20 brouard
945: Add log in imach.c and fullversion number is now printed.
946:
947: */
948: /*
949: Interpolated Markov Chain
950:
951: Short summary of the programme:
952:
1.227 brouard 953: This program computes Healthy Life Expectancies or State-specific
954: (if states aren't health statuses) Expectancies from
955: cross-longitudinal data. Cross-longitudinal data consist in:
956:
957: -1- a first survey ("cross") where individuals from different ages
958: are interviewed on their health status or degree of disability (in
959: the case of a health survey which is our main interest)
960:
961: -2- at least a second wave of interviews ("longitudinal") which
962: measure each change (if any) in individual health status. Health
963: expectancies are computed from the time spent in each health state
964: according to a model. More health states you consider, more time is
965: necessary to reach the Maximum Likelihood of the parameters involved
966: in the model. The simplest model is the multinomial logistic model
967: where pij is the probability to be observed in state j at the second
968: wave conditional to be observed in state i at the first
969: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
970: etc , where 'age' is age and 'sex' is a covariate. If you want to
971: have a more complex model than "constant and age", you should modify
972: the program where the markup *Covariates have to be included here
973: again* invites you to do it. More covariates you add, slower the
1.126 brouard 974: convergence.
975:
976: The advantage of this computer programme, compared to a simple
977: multinomial logistic model, is clear when the delay between waves is not
978: identical for each individual. Also, if a individual missed an
979: intermediate interview, the information is lost, but taken into
980: account using an interpolation or extrapolation.
981:
982: hPijx is the probability to be observed in state i at age x+h
983: conditional to the observed state i at age x. The delay 'h' can be
984: split into an exact number (nh*stepm) of unobserved intermediate
985: states. This elementary transition (by month, quarter,
986: semester or year) is modelled as a multinomial logistic. The hPx
987: matrix is simply the matrix product of nh*stepm elementary matrices
988: and the contribution of each individual to the likelihood is simply
989: hPijx.
990:
991: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 992: of the life expectancies. It also computes the period (stable) prevalence.
993:
994: Back prevalence and projections:
1.227 brouard 995:
996: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
997: double agemaxpar, double ftolpl, int *ncvyearp, double
998: dateprev1,double dateprev2, int firstpass, int lastpass, int
999: mobilavproj)
1000:
1001: Computes the back prevalence limit for any combination of
1002: covariate values k at any age between ageminpar and agemaxpar and
1003: returns it in **bprlim. In the loops,
1004:
1005: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1006: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1007:
1008: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1009: Computes for any combination of covariates k and any age between bage and fage
1010: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1011: oldm=oldms;savm=savms;
1.227 brouard 1012:
1.267 brouard 1013: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1014: Computes the transition matrix starting at age 'age' over
1015: 'nhstepm*hstepm*stepm' months (i.e. until
1016: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1017: nhstepm*hstepm matrices.
1018:
1019: Returns p3mat[i][j][h] after calling
1020: p3mat[i][j][h]=matprod2(newm,
1021: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1022: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1023: oldm);
1.226 brouard 1024:
1025: Important routines
1026:
1027: - func (or funcone), computes logit (pij) distinguishing
1028: o fixed variables (single or product dummies or quantitative);
1029: o varying variables by:
1030: (1) wave (single, product dummies, quantitative),
1031: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1032: % fixed dummy (treated) or quantitative (not done because time-consuming);
1033: % varying dummy (not done) or quantitative (not done);
1034: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1035: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1036: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1037: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1038: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1039:
1.226 brouard 1040:
1041:
1.133 brouard 1042: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1043: Institut national d'études démographiques, Paris.
1.126 brouard 1044: This software have been partly granted by Euro-REVES, a concerted action
1045: from the European Union.
1046: It is copyrighted identically to a GNU software product, ie programme and
1047: software can be distributed freely for non commercial use. Latest version
1048: can be accessed at http://euroreves.ined.fr/imach .
1049:
1050: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1051: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1052:
1053: **********************************************************************/
1054: /*
1055: main
1056: read parameterfile
1057: read datafile
1058: concatwav
1059: freqsummary
1060: if (mle >= 1)
1061: mlikeli
1062: print results files
1063: if mle==1
1064: computes hessian
1065: read end of parameter file: agemin, agemax, bage, fage, estepm
1066: begin-prev-date,...
1067: open gnuplot file
1068: open html file
1.145 brouard 1069: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1070: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1071: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1072: freexexit2 possible for memory heap.
1073:
1074: h Pij x | pij_nom ficrestpij
1075: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1076: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1077: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1078:
1079: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1080: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1081: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1082: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1083: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1084:
1.126 brouard 1085: forecasting if prevfcast==1 prevforecast call prevalence()
1086: health expectancies
1087: Variance-covariance of DFLE
1088: prevalence()
1089: movingaverage()
1090: varevsij()
1091: if popbased==1 varevsij(,popbased)
1092: total life expectancies
1093: Variance of period (stable) prevalence
1094: end
1095: */
1096:
1.187 brouard 1097: /* #define DEBUG */
1098: /* #define DEBUGBRENT */
1.203 brouard 1099: /* #define DEBUGLINMIN */
1100: /* #define DEBUGHESS */
1101: #define DEBUGHESSIJ
1.224 brouard 1102: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1103: #define POWELL /* Instead of NLOPT */
1.224 brouard 1104: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1105: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1106: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1107: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1108:
1109: #include <math.h>
1110: #include <stdio.h>
1111: #include <stdlib.h>
1112: #include <string.h>
1.226 brouard 1113: #include <ctype.h>
1.159 brouard 1114:
1115: #ifdef _WIN32
1116: #include <io.h>
1.172 brouard 1117: #include <windows.h>
1118: #include <tchar.h>
1.159 brouard 1119: #else
1.126 brouard 1120: #include <unistd.h>
1.159 brouard 1121: #endif
1.126 brouard 1122:
1123: #include <limits.h>
1124: #include <sys/types.h>
1.171 brouard 1125:
1126: #if defined(__GNUC__)
1127: #include <sys/utsname.h> /* Doesn't work on Windows */
1128: #endif
1129:
1.126 brouard 1130: #include <sys/stat.h>
1131: #include <errno.h>
1.159 brouard 1132: /* extern int errno; */
1.126 brouard 1133:
1.157 brouard 1134: /* #ifdef LINUX */
1135: /* #include <time.h> */
1136: /* #include "timeval.h" */
1137: /* #else */
1138: /* #include <sys/time.h> */
1139: /* #endif */
1140:
1.126 brouard 1141: #include <time.h>
1142:
1.136 brouard 1143: #ifdef GSL
1144: #include <gsl/gsl_errno.h>
1145: #include <gsl/gsl_multimin.h>
1146: #endif
1147:
1.167 brouard 1148:
1.162 brouard 1149: #ifdef NLOPT
1150: #include <nlopt.h>
1151: typedef struct {
1152: double (* function)(double [] );
1153: } myfunc_data ;
1154: #endif
1155:
1.126 brouard 1156: /* #include <libintl.h> */
1157: /* #define _(String) gettext (String) */
1158:
1.251 brouard 1159: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1160:
1161: #define GNUPLOTPROGRAM "gnuplot"
1162: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1163: #define FILENAMELENGTH 132
1164:
1165: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1166: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1167:
1.144 brouard 1168: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1169: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1170:
1171: #define NINTERVMAX 8
1.144 brouard 1172: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1173: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.318 brouard 1174: #define NCOVMAX 30 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1175: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1176: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1177: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1178: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1179: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1180: /* #define AGESUP 130 */
1.288 brouard 1181: /* #define AGESUP 150 */
1182: #define AGESUP 200
1.268 brouard 1183: #define AGEINF 0
1.218 brouard 1184: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1185: #define AGEBASE 40
1.194 brouard 1186: #define AGEOVERFLOW 1.e20
1.164 brouard 1187: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1188: #ifdef _WIN32
1189: #define DIRSEPARATOR '\\'
1190: #define CHARSEPARATOR "\\"
1191: #define ODIRSEPARATOR '/'
1192: #else
1.126 brouard 1193: #define DIRSEPARATOR '/'
1194: #define CHARSEPARATOR "/"
1195: #define ODIRSEPARATOR '\\'
1196: #endif
1197:
1.320 ! brouard 1198: /* $Id: imach.c,v 1.319 2022/06/02 04:45:11 brouard Exp $ */
1.126 brouard 1199: /* $State: Exp $ */
1.196 brouard 1200: #include "version.h"
1201: char version[]=__IMACH_VERSION__;
1.316 brouard 1202: char copyright[]="May 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";
1.320 ! brouard 1203: char fullversion[]="$Revision: 1.319 $ $Date: 2022/06/02 04:45:11 $";
1.126 brouard 1204: char strstart[80];
1205: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1206: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1207: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1208: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1209: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1210: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1211: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1212: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1213: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1214: int cptcovprodnoage=0; /**< Number of covariate products without age */
1215: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1216: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1217: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1218: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1219: int nsd=0; /**< Total number of single dummy variables (output) */
1220: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1221: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1222: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1223: int ntveff=0; /**< ntveff number of effective time varying variables */
1224: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1225: int cptcov=0; /* Working variable */
1.290 brouard 1226: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1227: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1228: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1229: int nlstate=2; /* Number of live states */
1230: int ndeath=1; /* Number of dead states */
1.130 brouard 1231: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1232: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1233: int popbased=0;
1234:
1235: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1236: int maxwav=0; /* Maxim number of waves */
1237: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1238: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1239: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1240: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1241: int mle=1, weightopt=0;
1.126 brouard 1242: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1243: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1244: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1245: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1246: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1247: int selected(int kvar); /* Is covariate kvar selected for printing results */
1248:
1.130 brouard 1249: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1250: double **matprod2(); /* test */
1.126 brouard 1251: double **oldm, **newm, **savm; /* Working pointers to matrices */
1252: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1253: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1254:
1.136 brouard 1255: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1256: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1257: FILE *ficlog, *ficrespow;
1.130 brouard 1258: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1259: double fretone; /* Only one call to likelihood */
1.130 brouard 1260: long ipmx=0; /* Number of contributions */
1.126 brouard 1261: double sw; /* Sum of weights */
1262: char filerespow[FILENAMELENGTH];
1263: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1264: FILE *ficresilk;
1265: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1266: FILE *ficresprobmorprev;
1267: FILE *fichtm, *fichtmcov; /* Html File */
1268: FILE *ficreseij;
1269: char filerese[FILENAMELENGTH];
1270: FILE *ficresstdeij;
1271: char fileresstde[FILENAMELENGTH];
1272: FILE *ficrescveij;
1273: char filerescve[FILENAMELENGTH];
1274: FILE *ficresvij;
1275: char fileresv[FILENAMELENGTH];
1.269 brouard 1276:
1.126 brouard 1277: char title[MAXLINE];
1.234 brouard 1278: char model[MAXLINE]; /**< The model line */
1.217 brouard 1279: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1280: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1281: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1282: char command[FILENAMELENGTH];
1283: int outcmd=0;
1284:
1.217 brouard 1285: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1286: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1287: char filelog[FILENAMELENGTH]; /* Log file */
1288: char filerest[FILENAMELENGTH];
1289: char fileregp[FILENAMELENGTH];
1290: char popfile[FILENAMELENGTH];
1291:
1292: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1293:
1.157 brouard 1294: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1295: /* struct timezone tzp; */
1296: /* extern int gettimeofday(); */
1297: struct tm tml, *gmtime(), *localtime();
1298:
1299: extern time_t time();
1300:
1301: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1302: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1303: struct tm tm;
1304:
1.126 brouard 1305: char strcurr[80], strfor[80];
1306:
1307: char *endptr;
1308: long lval;
1309: double dval;
1310:
1311: #define NR_END 1
1312: #define FREE_ARG char*
1313: #define FTOL 1.0e-10
1314:
1315: #define NRANSI
1.240 brouard 1316: #define ITMAX 200
1317: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1318:
1319: #define TOL 2.0e-4
1320:
1321: #define CGOLD 0.3819660
1322: #define ZEPS 1.0e-10
1323: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1324:
1325: #define GOLD 1.618034
1326: #define GLIMIT 100.0
1327: #define TINY 1.0e-20
1328:
1329: static double maxarg1,maxarg2;
1330: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1331: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1332:
1333: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1334: #define rint(a) floor(a+0.5)
1.166 brouard 1335: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1336: #define mytinydouble 1.0e-16
1.166 brouard 1337: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1338: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1339: /* static double dsqrarg; */
1340: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1341: static double sqrarg;
1342: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1343: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1344: int agegomp= AGEGOMP;
1345:
1346: int imx;
1347: int stepm=1;
1348: /* Stepm, step in month: minimum step interpolation*/
1349:
1350: int estepm;
1351: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1352:
1353: int m,nb;
1354: long *num;
1.197 brouard 1355: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1356: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1357: covariate for which somebody answered excluding
1358: undefined. Usually 2: 0 and 1. */
1359: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1360: covariate for which somebody answered including
1361: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1362: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1363: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1364: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1365: double *ageexmed,*agecens;
1366: double dateintmean=0;
1.296 brouard 1367: double anprojd, mprojd, jprojd; /* For eventual projections */
1368: double anprojf, mprojf, jprojf;
1.126 brouard 1369:
1.296 brouard 1370: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1371: double anbackf, mbackf, jbackf;
1372: double jintmean,mintmean,aintmean;
1.126 brouard 1373: double *weight;
1374: int **s; /* Status */
1.141 brouard 1375: double *agedc;
1.145 brouard 1376: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1377: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1378: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1379: double **coqvar; /* Fixed quantitative covariate nqv */
1380: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1381: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1382: double idx;
1383: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1384: /* Some documentation */
1385: /* Design original data
1386: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1387: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1388: * ntv=3 nqtv=1
1389: * cptcovn number of covariates (not including constant and age) = # of + plus 1 = 10+1=11
1390: * For time varying covariate, quanti or dummies
1391: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1392: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1393: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1394: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1395: * covar[k,i], value of kth fixed covariate dummy or quanti :
1396: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1397: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1398: * k= 1 2 3 4 5 6 7 8 9 10 11
1399: */
1400: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1401: /* 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
1402: # States 1=Coresidence, 2 Living alone, 3 Institution
1403: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1404: */
1.319 brouard 1405: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1406: /* k 1 2 3 4 5 6 7 8 9 */
1407: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1408: /* fixed or varying), 1 for age product, 2 for*/
1409: /* product */
1410: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1411: /*(single or product without age), 2 dummy*/
1412: /* with age product, 3 quant with age product*/
1413: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1414: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1415: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1416: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1417: /* nsq 1 2 */ /* Counting single quantit tv */
1418: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1419: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1420: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1421: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1422: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1423: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1424: /* 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 1425: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1426: /* Type */
1427: /* V 1 2 3 4 5 */
1428: /* F F V V V */
1429: /* D Q D D Q */
1430: /* */
1431: int *TvarsD;
1432: int *TvarsDind;
1433: int *TvarsQ;
1434: int *TvarsQind;
1435:
1.318 brouard 1436: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1437: int nresult=0;
1.258 brouard 1438: int parameterline=0; /* # of the parameter (type) line */
1.318 brouard 1439: int TKresult[MAXRESULTLINESPONE];
1440: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1441: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1442: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */
1443: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1444: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1445: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , variable # (output) */
1446:
1447: /* 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
1448: # States 1=Coresidence, 2 Living alone, 3 Institution
1449: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1450: */
1.234 brouard 1451: /* 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 1452: 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 */
1453: 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 */
1454: 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 */
1455: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1456: 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 */
1457: 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 1458: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1459: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1460: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1461: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1462: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1463: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1464: 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 */
1465: 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 */
1466:
1.230 brouard 1467: int *Tvarsel; /**< Selected covariates for output */
1468: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1469: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1470: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1471: 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 1472: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1473: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1474: int *Tage;
1.227 brouard 1475: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1476: 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 1477: 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*/
1478: 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 1479: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1480: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1481: int **Tvard;
1482: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1483: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1484: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1485: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1486: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1487: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1488: double *lsurv, *lpop, *tpop;
1489:
1.231 brouard 1490: #define FD 1; /* Fixed dummy covariate */
1491: #define FQ 2; /* Fixed quantitative covariate */
1492: #define FP 3; /* Fixed product covariate */
1493: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1494: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1495: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1496: #define VD 10; /* Varying dummy covariate */
1497: #define VQ 11; /* Varying quantitative covariate */
1498: #define VP 12; /* Varying product covariate */
1499: #define VPDD 13; /* Varying product dummy*dummy covariate */
1500: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1501: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1502: #define APFD 16; /* Age product * fixed dummy covariate */
1503: #define APFQ 17; /* Age product * fixed quantitative covariate */
1504: #define APVD 18; /* Age product * varying dummy covariate */
1505: #define APVQ 19; /* Age product * varying quantitative covariate */
1506:
1507: #define FTYPE 1; /* Fixed covariate */
1508: #define VTYPE 2; /* Varying covariate (loop in wave) */
1509: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1510:
1511: struct kmodel{
1512: int maintype; /* main type */
1513: int subtype; /* subtype */
1514: };
1515: struct kmodel modell[NCOVMAX];
1516:
1.143 brouard 1517: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1518: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1519:
1520: /**************** split *************************/
1521: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1522: {
1523: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1524: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1525: */
1526: char *ss; /* pointer */
1.186 brouard 1527: int l1=0, l2=0; /* length counters */
1.126 brouard 1528:
1529: l1 = strlen(path ); /* length of path */
1530: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1531: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1532: if ( ss == NULL ) { /* no directory, so determine current directory */
1533: strcpy( name, path ); /* we got the fullname name because no directory */
1534: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1535: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1536: /* get current working directory */
1537: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1538: #ifdef WIN32
1539: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1540: #else
1541: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1542: #endif
1.126 brouard 1543: return( GLOCK_ERROR_GETCWD );
1544: }
1545: /* got dirc from getcwd*/
1546: printf(" DIRC = %s \n",dirc);
1.205 brouard 1547: } else { /* strip directory from path */
1.126 brouard 1548: ss++; /* after this, the filename */
1549: l2 = strlen( ss ); /* length of filename */
1550: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1551: strcpy( name, ss ); /* save file name */
1552: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1553: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1554: printf(" DIRC2 = %s \n",dirc);
1555: }
1556: /* We add a separator at the end of dirc if not exists */
1557: l1 = strlen( dirc ); /* length of directory */
1558: if( dirc[l1-1] != DIRSEPARATOR ){
1559: dirc[l1] = DIRSEPARATOR;
1560: dirc[l1+1] = 0;
1561: printf(" DIRC3 = %s \n",dirc);
1562: }
1563: ss = strrchr( name, '.' ); /* find last / */
1564: if (ss >0){
1565: ss++;
1566: strcpy(ext,ss); /* save extension */
1567: l1= strlen( name);
1568: l2= strlen(ss)+1;
1569: strncpy( finame, name, l1-l2);
1570: finame[l1-l2]= 0;
1571: }
1572:
1573: return( 0 ); /* we're done */
1574: }
1575:
1576:
1577: /******************************************/
1578:
1579: void replace_back_to_slash(char *s, char*t)
1580: {
1581: int i;
1582: int lg=0;
1583: i=0;
1584: lg=strlen(t);
1585: for(i=0; i<= lg; i++) {
1586: (s[i] = t[i]);
1587: if (t[i]== '\\') s[i]='/';
1588: }
1589: }
1590:
1.132 brouard 1591: char *trimbb(char *out, char *in)
1.137 brouard 1592: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1593: char *s;
1594: s=out;
1595: while (*in != '\0'){
1.137 brouard 1596: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1597: in++;
1598: }
1599: *out++ = *in++;
1600: }
1601: *out='\0';
1602: return s;
1603: }
1604:
1.187 brouard 1605: /* char *substrchaine(char *out, char *in, char *chain) */
1606: /* { */
1607: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1608: /* char *s, *t; */
1609: /* t=in;s=out; */
1610: /* while ((*in != *chain) && (*in != '\0')){ */
1611: /* *out++ = *in++; */
1612: /* } */
1613:
1614: /* /\* *in matches *chain *\/ */
1615: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1616: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1617: /* } */
1618: /* in--; chain--; */
1619: /* while ( (*in != '\0')){ */
1620: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1621: /* *out++ = *in++; */
1622: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1623: /* } */
1624: /* *out='\0'; */
1625: /* out=s; */
1626: /* return out; */
1627: /* } */
1628: char *substrchaine(char *out, char *in, char *chain)
1629: {
1630: /* Substract chain 'chain' from 'in', return and output 'out' */
1631: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1632:
1633: char *strloc;
1634:
1635: strcpy (out, in);
1636: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1637: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1638: if(strloc != NULL){
1639: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1640: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1641: /* strcpy (strloc, strloc +strlen(chain));*/
1642: }
1643: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1644: return out;
1645: }
1646:
1647:
1.145 brouard 1648: char *cutl(char *blocc, char *alocc, char *in, char occ)
1649: {
1.187 brouard 1650: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1651: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1652: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1653: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1654: */
1.160 brouard 1655: char *s, *t;
1.145 brouard 1656: t=in;s=in;
1657: while ((*in != occ) && (*in != '\0')){
1658: *alocc++ = *in++;
1659: }
1660: if( *in == occ){
1661: *(alocc)='\0';
1662: s=++in;
1663: }
1664:
1665: if (s == t) {/* occ not found */
1666: *(alocc-(in-s))='\0';
1667: in=s;
1668: }
1669: while ( *in != '\0'){
1670: *blocc++ = *in++;
1671: }
1672:
1673: *blocc='\0';
1674: return t;
1675: }
1.137 brouard 1676: char *cutv(char *blocc, char *alocc, char *in, char occ)
1677: {
1.187 brouard 1678: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1679: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1680: gives blocc="abcdef2ghi" and alocc="j".
1681: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1682: */
1683: char *s, *t;
1684: t=in;s=in;
1685: while (*in != '\0'){
1686: while( *in == occ){
1687: *blocc++ = *in++;
1688: s=in;
1689: }
1690: *blocc++ = *in++;
1691: }
1692: if (s == t) /* occ not found */
1693: *(blocc-(in-s))='\0';
1694: else
1695: *(blocc-(in-s)-1)='\0';
1696: in=s;
1697: while ( *in != '\0'){
1698: *alocc++ = *in++;
1699: }
1700:
1701: *alocc='\0';
1702: return s;
1703: }
1704:
1.126 brouard 1705: int nbocc(char *s, char occ)
1706: {
1707: int i,j=0;
1708: int lg=20;
1709: i=0;
1710: lg=strlen(s);
1711: for(i=0; i<= lg; i++) {
1.234 brouard 1712: if (s[i] == occ ) j++;
1.126 brouard 1713: }
1714: return j;
1715: }
1716:
1.137 brouard 1717: /* void cutv(char *u,char *v, char*t, char occ) */
1718: /* { */
1719: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1720: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1721: /* gives u="abcdef2ghi" and v="j" *\/ */
1722: /* int i,lg,j,p=0; */
1723: /* i=0; */
1724: /* lg=strlen(t); */
1725: /* for(j=0; j<=lg-1; j++) { */
1726: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1727: /* } */
1.126 brouard 1728:
1.137 brouard 1729: /* for(j=0; j<p; j++) { */
1730: /* (u[j] = t[j]); */
1731: /* } */
1732: /* u[p]='\0'; */
1.126 brouard 1733:
1.137 brouard 1734: /* for(j=0; j<= lg; j++) { */
1735: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1736: /* } */
1737: /* } */
1.126 brouard 1738:
1.160 brouard 1739: #ifdef _WIN32
1740: char * strsep(char **pp, const char *delim)
1741: {
1742: char *p, *q;
1743:
1744: if ((p = *pp) == NULL)
1745: return 0;
1746: if ((q = strpbrk (p, delim)) != NULL)
1747: {
1748: *pp = q + 1;
1749: *q = '\0';
1750: }
1751: else
1752: *pp = 0;
1753: return p;
1754: }
1755: #endif
1756:
1.126 brouard 1757: /********************** nrerror ********************/
1758:
1759: void nrerror(char error_text[])
1760: {
1761: fprintf(stderr,"ERREUR ...\n");
1762: fprintf(stderr,"%s\n",error_text);
1763: exit(EXIT_FAILURE);
1764: }
1765: /*********************** vector *******************/
1766: double *vector(int nl, int nh)
1767: {
1768: double *v;
1769: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1770: if (!v) nrerror("allocation failure in vector");
1771: return v-nl+NR_END;
1772: }
1773:
1774: /************************ free vector ******************/
1775: void free_vector(double*v, int nl, int nh)
1776: {
1777: free((FREE_ARG)(v+nl-NR_END));
1778: }
1779:
1780: /************************ivector *******************************/
1781: int *ivector(long nl,long nh)
1782: {
1783: int *v;
1784: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1785: if (!v) nrerror("allocation failure in ivector");
1786: return v-nl+NR_END;
1787: }
1788:
1789: /******************free ivector **************************/
1790: void free_ivector(int *v, long nl, long nh)
1791: {
1792: free((FREE_ARG)(v+nl-NR_END));
1793: }
1794:
1795: /************************lvector *******************************/
1796: long *lvector(long nl,long nh)
1797: {
1798: long *v;
1799: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1800: if (!v) nrerror("allocation failure in ivector");
1801: return v-nl+NR_END;
1802: }
1803:
1804: /******************free lvector **************************/
1805: void free_lvector(long *v, long nl, long nh)
1806: {
1807: free((FREE_ARG)(v+nl-NR_END));
1808: }
1809:
1810: /******************* imatrix *******************************/
1811: int **imatrix(long nrl, long nrh, long ncl, long nch)
1812: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1813: {
1814: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1815: int **m;
1816:
1817: /* allocate pointers to rows */
1818: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1819: if (!m) nrerror("allocation failure 1 in matrix()");
1820: m += NR_END;
1821: m -= nrl;
1822:
1823:
1824: /* allocate rows and set pointers to them */
1825: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1826: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1827: m[nrl] += NR_END;
1828: m[nrl] -= ncl;
1829:
1830: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1831:
1832: /* return pointer to array of pointers to rows */
1833: return m;
1834: }
1835:
1836: /****************** free_imatrix *************************/
1837: void free_imatrix(m,nrl,nrh,ncl,nch)
1838: int **m;
1839: long nch,ncl,nrh,nrl;
1840: /* free an int matrix allocated by imatrix() */
1841: {
1842: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1843: free((FREE_ARG) (m+nrl-NR_END));
1844: }
1845:
1846: /******************* matrix *******************************/
1847: double **matrix(long nrl, long nrh, long ncl, long nch)
1848: {
1849: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1850: double **m;
1851:
1852: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1853: if (!m) nrerror("allocation failure 1 in matrix()");
1854: m += NR_END;
1855: m -= nrl;
1856:
1857: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1858: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1859: m[nrl] += NR_END;
1860: m[nrl] -= ncl;
1861:
1862: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1863: return m;
1.145 brouard 1864: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1865: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1866: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1867: */
1868: }
1869:
1870: /*************************free matrix ************************/
1871: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1872: {
1873: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1874: free((FREE_ARG)(m+nrl-NR_END));
1875: }
1876:
1877: /******************* ma3x *******************************/
1878: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1879: {
1880: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1881: double ***m;
1882:
1883: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1884: if (!m) nrerror("allocation failure 1 in matrix()");
1885: m += NR_END;
1886: m -= nrl;
1887:
1888: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1889: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1890: m[nrl] += NR_END;
1891: m[nrl] -= ncl;
1892:
1893: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1894:
1895: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1896: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1897: m[nrl][ncl] += NR_END;
1898: m[nrl][ncl] -= nll;
1899: for (j=ncl+1; j<=nch; j++)
1900: m[nrl][j]=m[nrl][j-1]+nlay;
1901:
1902: for (i=nrl+1; i<=nrh; i++) {
1903: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1904: for (j=ncl+1; j<=nch; j++)
1905: m[i][j]=m[i][j-1]+nlay;
1906: }
1907: return m;
1908: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1909: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1910: */
1911: }
1912:
1913: /*************************free ma3x ************************/
1914: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1915: {
1916: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1917: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1918: free((FREE_ARG)(m+nrl-NR_END));
1919: }
1920:
1921: /*************** function subdirf ***********/
1922: char *subdirf(char fileres[])
1923: {
1924: /* Caution optionfilefiname is hidden */
1925: strcpy(tmpout,optionfilefiname);
1926: strcat(tmpout,"/"); /* Add to the right */
1927: strcat(tmpout,fileres);
1928: return tmpout;
1929: }
1930:
1931: /*************** function subdirf2 ***********/
1932: char *subdirf2(char fileres[], char *preop)
1933: {
1.314 brouard 1934: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
1935: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 1936: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 1937: /* Caution optionfilefiname is hidden */
1938: strcpy(tmpout,optionfilefiname);
1939: strcat(tmpout,"/");
1940: strcat(tmpout,preop);
1941: strcat(tmpout,fileres);
1942: return tmpout;
1943: }
1944:
1945: /*************** function subdirf3 ***********/
1946: char *subdirf3(char fileres[], char *preop, char *preop2)
1947: {
1948:
1949: /* Caution optionfilefiname is hidden */
1950: strcpy(tmpout,optionfilefiname);
1951: strcat(tmpout,"/");
1952: strcat(tmpout,preop);
1953: strcat(tmpout,preop2);
1954: strcat(tmpout,fileres);
1955: return tmpout;
1956: }
1.213 brouard 1957:
1958: /*************** function subdirfext ***********/
1959: char *subdirfext(char fileres[], char *preop, char *postop)
1960: {
1961:
1962: strcpy(tmpout,preop);
1963: strcat(tmpout,fileres);
1964: strcat(tmpout,postop);
1965: return tmpout;
1966: }
1.126 brouard 1967:
1.213 brouard 1968: /*************** function subdirfext3 ***********/
1969: char *subdirfext3(char fileres[], char *preop, char *postop)
1970: {
1971:
1972: /* Caution optionfilefiname is hidden */
1973: strcpy(tmpout,optionfilefiname);
1974: strcat(tmpout,"/");
1975: strcat(tmpout,preop);
1976: strcat(tmpout,fileres);
1977: strcat(tmpout,postop);
1978: return tmpout;
1979: }
1980:
1.162 brouard 1981: char *asc_diff_time(long time_sec, char ascdiff[])
1982: {
1983: long sec_left, days, hours, minutes;
1984: days = (time_sec) / (60*60*24);
1985: sec_left = (time_sec) % (60*60*24);
1986: hours = (sec_left) / (60*60) ;
1987: sec_left = (sec_left) %(60*60);
1988: minutes = (sec_left) /60;
1989: sec_left = (sec_left) % (60);
1990: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1991: return ascdiff;
1992: }
1993:
1.126 brouard 1994: /***************** f1dim *************************/
1995: extern int ncom;
1996: extern double *pcom,*xicom;
1997: extern double (*nrfunc)(double []);
1998:
1999: double f1dim(double x)
2000: {
2001: int j;
2002: double f;
2003: double *xt;
2004:
2005: xt=vector(1,ncom);
2006: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2007: f=(*nrfunc)(xt);
2008: free_vector(xt,1,ncom);
2009: return f;
2010: }
2011:
2012: /*****************brent *************************/
2013: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2014: {
2015: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2016: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2017: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2018: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2019: * returned function value.
2020: */
1.126 brouard 2021: int iter;
2022: double a,b,d,etemp;
1.159 brouard 2023: double fu=0,fv,fw,fx;
1.164 brouard 2024: double ftemp=0.;
1.126 brouard 2025: double p,q,r,tol1,tol2,u,v,w,x,xm;
2026: double e=0.0;
2027:
2028: a=(ax < cx ? ax : cx);
2029: b=(ax > cx ? ax : cx);
2030: x=w=v=bx;
2031: fw=fv=fx=(*f)(x);
2032: for (iter=1;iter<=ITMAX;iter++) {
2033: xm=0.5*(a+b);
2034: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2035: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2036: printf(".");fflush(stdout);
2037: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2038: #ifdef DEBUGBRENT
1.126 brouard 2039: 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);
2040: 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);
2041: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2042: #endif
2043: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2044: *xmin=x;
2045: return fx;
2046: }
2047: ftemp=fu;
2048: if (fabs(e) > tol1) {
2049: r=(x-w)*(fx-fv);
2050: q=(x-v)*(fx-fw);
2051: p=(x-v)*q-(x-w)*r;
2052: q=2.0*(q-r);
2053: if (q > 0.0) p = -p;
2054: q=fabs(q);
2055: etemp=e;
2056: e=d;
2057: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2058: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2059: else {
1.224 brouard 2060: d=p/q;
2061: u=x+d;
2062: if (u-a < tol2 || b-u < tol2)
2063: d=SIGN(tol1,xm-x);
1.126 brouard 2064: }
2065: } else {
2066: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2067: }
2068: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2069: fu=(*f)(u);
2070: if (fu <= fx) {
2071: if (u >= x) a=x; else b=x;
2072: SHFT(v,w,x,u)
1.183 brouard 2073: SHFT(fv,fw,fx,fu)
2074: } else {
2075: if (u < x) a=u; else b=u;
2076: if (fu <= fw || w == x) {
1.224 brouard 2077: v=w;
2078: w=u;
2079: fv=fw;
2080: fw=fu;
1.183 brouard 2081: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2082: v=u;
2083: fv=fu;
1.183 brouard 2084: }
2085: }
1.126 brouard 2086: }
2087: nrerror("Too many iterations in brent");
2088: *xmin=x;
2089: return fx;
2090: }
2091:
2092: /****************** mnbrak ***********************/
2093:
2094: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2095: double (*func)(double))
1.183 brouard 2096: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2097: the downhill direction (defined by the function as evaluated at the initial points) and returns
2098: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2099: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2100: */
1.126 brouard 2101: double ulim,u,r,q, dum;
2102: double fu;
1.187 brouard 2103:
2104: double scale=10.;
2105: int iterscale=0;
2106:
2107: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2108: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2109:
2110:
2111: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2112: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2113: /* *bx = *ax - (*ax - *bx)/scale; */
2114: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2115: /* } */
2116:
1.126 brouard 2117: if (*fb > *fa) {
2118: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2119: SHFT(dum,*fb,*fa,dum)
2120: }
1.126 brouard 2121: *cx=(*bx)+GOLD*(*bx-*ax);
2122: *fc=(*func)(*cx);
1.183 brouard 2123: #ifdef DEBUG
1.224 brouard 2124: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2125: 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 2126: #endif
1.224 brouard 2127: 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 2128: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2129: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2130: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2131: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2132: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2133: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2134: fu=(*func)(u);
1.163 brouard 2135: #ifdef DEBUG
2136: /* f(x)=A(x-u)**2+f(u) */
2137: double A, fparabu;
2138: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2139: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2140: 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);
2141: 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 2142: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2143: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2144: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2145: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2146: #endif
1.184 brouard 2147: #ifdef MNBRAKORIGINAL
1.183 brouard 2148: #else
1.191 brouard 2149: /* if (fu > *fc) { */
2150: /* #ifdef DEBUG */
2151: /* printf("mnbrak4 fu > fc \n"); */
2152: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2153: /* #endif */
2154: /* /\* 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 *\\/ *\/ */
2155: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2156: /* dum=u; /\* Shifting c and u *\/ */
2157: /* u = *cx; */
2158: /* *cx = dum; */
2159: /* dum = fu; */
2160: /* fu = *fc; */
2161: /* *fc =dum; */
2162: /* } else { /\* end *\/ */
2163: /* #ifdef DEBUG */
2164: /* printf("mnbrak3 fu < fc \n"); */
2165: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2166: /* #endif */
2167: /* dum=u; /\* Shifting c and u *\/ */
2168: /* u = *cx; */
2169: /* *cx = dum; */
2170: /* dum = fu; */
2171: /* fu = *fc; */
2172: /* *fc =dum; */
2173: /* } */
1.224 brouard 2174: #ifdef DEBUGMNBRAK
2175: double A, fparabu;
2176: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2177: fparabu= *fa - A*(*ax-u)*(*ax-u);
2178: 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);
2179: 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 2180: #endif
1.191 brouard 2181: dum=u; /* Shifting c and u */
2182: u = *cx;
2183: *cx = dum;
2184: dum = fu;
2185: fu = *fc;
2186: *fc =dum;
1.183 brouard 2187: #endif
1.162 brouard 2188: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2189: #ifdef DEBUG
1.224 brouard 2190: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2191: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2192: #endif
1.126 brouard 2193: fu=(*func)(u);
2194: if (fu < *fc) {
1.183 brouard 2195: #ifdef DEBUG
1.224 brouard 2196: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2197: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2198: #endif
2199: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2200: SHFT(*fb,*fc,fu,(*func)(u))
2201: #ifdef DEBUG
2202: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2203: #endif
2204: }
1.162 brouard 2205: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2206: #ifdef DEBUG
1.224 brouard 2207: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2208: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2209: #endif
1.126 brouard 2210: u=ulim;
2211: fu=(*func)(u);
1.183 brouard 2212: } else { /* u could be left to b (if r > q parabola has a maximum) */
2213: #ifdef DEBUG
1.224 brouard 2214: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2215: 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 2216: #endif
1.126 brouard 2217: u=(*cx)+GOLD*(*cx-*bx);
2218: fu=(*func)(u);
1.224 brouard 2219: #ifdef DEBUG
2220: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2221: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2222: #endif
1.183 brouard 2223: } /* end tests */
1.126 brouard 2224: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2225: SHFT(*fa,*fb,*fc,fu)
2226: #ifdef DEBUG
1.224 brouard 2227: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2228: 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 2229: #endif
2230: } /* 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 2231: }
2232:
2233: /*************** linmin ************************/
1.162 brouard 2234: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2235: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2236: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2237: the value of func at the returned location p . This is actually all accomplished by calling the
2238: routines mnbrak and brent .*/
1.126 brouard 2239: int ncom;
2240: double *pcom,*xicom;
2241: double (*nrfunc)(double []);
2242:
1.224 brouard 2243: #ifdef LINMINORIGINAL
1.126 brouard 2244: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2245: #else
2246: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2247: #endif
1.126 brouard 2248: {
2249: double brent(double ax, double bx, double cx,
2250: double (*f)(double), double tol, double *xmin);
2251: double f1dim(double x);
2252: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2253: double *fc, double (*func)(double));
2254: int j;
2255: double xx,xmin,bx,ax;
2256: double fx,fb,fa;
1.187 brouard 2257:
1.203 brouard 2258: #ifdef LINMINORIGINAL
2259: #else
2260: double scale=10., axs, xxs; /* Scale added for infinity */
2261: #endif
2262:
1.126 brouard 2263: ncom=n;
2264: pcom=vector(1,n);
2265: xicom=vector(1,n);
2266: nrfunc=func;
2267: for (j=1;j<=n;j++) {
2268: pcom[j]=p[j];
1.202 brouard 2269: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2270: }
1.187 brouard 2271:
1.203 brouard 2272: #ifdef LINMINORIGINAL
2273: xx=1.;
2274: #else
2275: axs=0.0;
2276: xxs=1.;
2277: do{
2278: xx= xxs;
2279: #endif
1.187 brouard 2280: ax=0.;
2281: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2282: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2283: /* 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)) */
2284: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2285: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2286: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2287: /* 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 2288: #ifdef LINMINORIGINAL
2289: #else
2290: if (fx != fx){
1.224 brouard 2291: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2292: printf("|");
2293: fprintf(ficlog,"|");
1.203 brouard 2294: #ifdef DEBUGLINMIN
1.224 brouard 2295: 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 2296: #endif
2297: }
1.224 brouard 2298: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2299: #endif
2300:
1.191 brouard 2301: #ifdef DEBUGLINMIN
2302: 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 2303: 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 2304: #endif
1.224 brouard 2305: #ifdef LINMINORIGINAL
2306: #else
1.317 brouard 2307: if(fb == fx){ /* Flat function in the direction */
2308: xmin=xx;
1.224 brouard 2309: *flat=1;
1.317 brouard 2310: }else{
1.224 brouard 2311: *flat=0;
2312: #endif
2313: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2314: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2315: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2316: /* fmin = f(p[j] + xmin * xi[j]) */
2317: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2318: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2319: #ifdef DEBUG
1.224 brouard 2320: 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);
2321: 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);
2322: #endif
2323: #ifdef LINMINORIGINAL
2324: #else
2325: }
1.126 brouard 2326: #endif
1.191 brouard 2327: #ifdef DEBUGLINMIN
2328: printf("linmin end ");
1.202 brouard 2329: fprintf(ficlog,"linmin end ");
1.191 brouard 2330: #endif
1.126 brouard 2331: for (j=1;j<=n;j++) {
1.203 brouard 2332: #ifdef LINMINORIGINAL
2333: xi[j] *= xmin;
2334: #else
2335: #ifdef DEBUGLINMIN
2336: if(xxs <1.0)
2337: printf(" before xi[%d]=%12.8f", j,xi[j]);
2338: #endif
2339: 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) */
2340: #ifdef DEBUGLINMIN
2341: if(xxs <1.0)
2342: 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 );
2343: #endif
2344: #endif
1.187 brouard 2345: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2346: }
1.191 brouard 2347: #ifdef DEBUGLINMIN
1.203 brouard 2348: printf("\n");
1.191 brouard 2349: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2350: 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 2351: for (j=1;j<=n;j++) {
1.202 brouard 2352: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2353: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2354: if(j % ncovmodel == 0){
1.191 brouard 2355: printf("\n");
1.202 brouard 2356: fprintf(ficlog,"\n");
2357: }
1.191 brouard 2358: }
1.203 brouard 2359: #else
1.191 brouard 2360: #endif
1.126 brouard 2361: free_vector(xicom,1,n);
2362: free_vector(pcom,1,n);
2363: }
2364:
2365:
2366: /*************** powell ************************/
1.162 brouard 2367: /*
1.317 brouard 2368: Minimization of a function func of n variables. Input consists in an initial starting point
2369: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2370: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2371: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2372: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2373: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2374: */
1.224 brouard 2375: #ifdef LINMINORIGINAL
2376: #else
2377: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2378: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2379: #endif
1.126 brouard 2380: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2381: double (*func)(double []))
2382: {
1.224 brouard 2383: #ifdef LINMINORIGINAL
2384: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2385: double (*func)(double []));
1.224 brouard 2386: #else
1.241 brouard 2387: void linmin(double p[], double xi[], int n, double *fret,
2388: double (*func)(double []),int *flat);
1.224 brouard 2389: #endif
1.239 brouard 2390: int i,ibig,j,jk,k;
1.126 brouard 2391: double del,t,*pt,*ptt,*xit;
1.181 brouard 2392: double directest;
1.126 brouard 2393: double fp,fptt;
2394: double *xits;
2395: int niterf, itmp;
2396:
2397: pt=vector(1,n);
2398: ptt=vector(1,n);
2399: xit=vector(1,n);
2400: xits=vector(1,n);
2401: *fret=(*func)(p);
2402: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2403: rcurr_time = time(NULL);
1.126 brouard 2404: for (*iter=1;;++(*iter)) {
1.187 brouard 2405: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2406: ibig=0;
2407: del=0.0;
1.157 brouard 2408: rlast_time=rcurr_time;
2409: /* (void) gettimeofday(&curr_time,&tzp); */
2410: rcurr_time = time(NULL);
2411: curr_time = *localtime(&rcurr_time);
2412: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2413: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2414: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2415: for (i=1;i<=n;i++) {
1.126 brouard 2416: fprintf(ficrespow," %.12lf", p[i]);
2417: }
1.239 brouard 2418: fprintf(ficrespow,"\n");fflush(ficrespow);
2419: printf("\n#model= 1 + age ");
2420: fprintf(ficlog,"\n#model= 1 + age ");
2421: if(nagesqr==1){
1.241 brouard 2422: printf(" + age*age ");
2423: fprintf(ficlog," + age*age ");
1.239 brouard 2424: }
2425: for(j=1;j <=ncovmodel-2;j++){
2426: if(Typevar[j]==0) {
2427: printf(" + V%d ",Tvar[j]);
2428: fprintf(ficlog," + V%d ",Tvar[j]);
2429: }else if(Typevar[j]==1) {
2430: printf(" + V%d*age ",Tvar[j]);
2431: fprintf(ficlog," + V%d*age ",Tvar[j]);
2432: }else if(Typevar[j]==2) {
2433: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2434: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2435: }
2436: }
1.126 brouard 2437: printf("\n");
1.239 brouard 2438: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2439: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2440: fprintf(ficlog,"\n");
1.239 brouard 2441: for(i=1,jk=1; i <=nlstate; i++){
2442: for(k=1; k <=(nlstate+ndeath); k++){
2443: if (k != i) {
2444: printf("%d%d ",i,k);
2445: fprintf(ficlog,"%d%d ",i,k);
2446: for(j=1; j <=ncovmodel; j++){
2447: printf("%12.7f ",p[jk]);
2448: fprintf(ficlog,"%12.7f ",p[jk]);
2449: jk++;
2450: }
2451: printf("\n");
2452: fprintf(ficlog,"\n");
2453: }
2454: }
2455: }
1.241 brouard 2456: if(*iter <=3 && *iter >1){
1.157 brouard 2457: tml = *localtime(&rcurr_time);
2458: strcpy(strcurr,asctime(&tml));
2459: rforecast_time=rcurr_time;
1.126 brouard 2460: itmp = strlen(strcurr);
2461: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2462: strcurr[itmp-1]='\0';
1.162 brouard 2463: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2464: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2465: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2466: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2467: forecast_time = *localtime(&rforecast_time);
2468: strcpy(strfor,asctime(&forecast_time));
2469: itmp = strlen(strfor);
2470: if(strfor[itmp-1]=='\n')
2471: strfor[itmp-1]='\0';
2472: 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);
2473: 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 2474: }
2475: }
1.187 brouard 2476: for (i=1;i<=n;i++) { /* For each direction i */
2477: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2478: fptt=(*fret);
2479: #ifdef DEBUG
1.203 brouard 2480: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2481: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2482: #endif
1.203 brouard 2483: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2484: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2485: #ifdef LINMINORIGINAL
1.188 brouard 2486: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2487: #else
2488: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2489: flatdir[i]=flat; /* Function is vanishing in that direction i */
2490: #endif
2491: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2492: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2493: /* because that direction will be replaced unless the gain del is small */
2494: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2495: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2496: /* with the new direction. */
2497: del=fabs(fptt-(*fret));
2498: ibig=i;
1.126 brouard 2499: }
2500: #ifdef DEBUG
2501: printf("%d %.12e",i,(*fret));
2502: fprintf(ficlog,"%d %.12e",i,(*fret));
2503: for (j=1;j<=n;j++) {
1.224 brouard 2504: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2505: printf(" x(%d)=%.12e",j,xit[j]);
2506: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2507: }
2508: for(j=1;j<=n;j++) {
1.225 brouard 2509: printf(" p(%d)=%.12e",j,p[j]);
2510: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2511: }
2512: printf("\n");
2513: fprintf(ficlog,"\n");
2514: #endif
1.187 brouard 2515: } /* end loop on each direction i */
2516: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2517: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2518: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2519: for(j=1;j<=n;j++) {
2520: if(flatdir[j] >0){
2521: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2522: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2523: }
1.319 brouard 2524: /* printf("\n"); */
2525: /* fprintf(ficlog,"\n"); */
2526: }
1.243 brouard 2527: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2528: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2529: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2530: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2531: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2532: /* decreased of more than 3.84 */
2533: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2534: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2535: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2536:
1.188 brouard 2537: /* Starting the program with initial values given by a former maximization will simply change */
2538: /* the scales of the directions and the directions, because the are reset to canonical directions */
2539: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2540: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2541: #ifdef DEBUG
2542: int k[2],l;
2543: k[0]=1;
2544: k[1]=-1;
2545: printf("Max: %.12e",(*func)(p));
2546: fprintf(ficlog,"Max: %.12e",(*func)(p));
2547: for (j=1;j<=n;j++) {
2548: printf(" %.12e",p[j]);
2549: fprintf(ficlog," %.12e",p[j]);
2550: }
2551: printf("\n");
2552: fprintf(ficlog,"\n");
2553: for(l=0;l<=1;l++) {
2554: for (j=1;j<=n;j++) {
2555: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2556: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2557: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2558: }
2559: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2560: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2561: }
2562: #endif
2563:
2564: free_vector(xit,1,n);
2565: free_vector(xits,1,n);
2566: free_vector(ptt,1,n);
2567: free_vector(pt,1,n);
2568: return;
1.192 brouard 2569: } /* enough precision */
1.240 brouard 2570: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2571: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2572: ptt[j]=2.0*p[j]-pt[j];
2573: xit[j]=p[j]-pt[j];
2574: pt[j]=p[j];
2575: }
1.181 brouard 2576: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2577: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2578: if (*iter <=4) {
1.225 brouard 2579: #else
2580: #endif
1.224 brouard 2581: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2582: #else
1.161 brouard 2583: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2584: #endif
1.162 brouard 2585: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2586: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2587: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2588: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2589: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2590: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2591: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2592: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2593: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2594: /* Even if f3 <f1, directest can be negative and t >0 */
2595: /* mu² and del² are equal when f3=f1 */
2596: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2597: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2598: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2599: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2600: #ifdef NRCORIGINAL
2601: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2602: #else
2603: 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 2604: t= t- del*SQR(fp-fptt);
1.183 brouard 2605: #endif
1.202 brouard 2606: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2607: #ifdef DEBUG
1.181 brouard 2608: 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);
2609: 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 2610: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2611: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2612: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2613: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2614: 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);
2615: 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);
2616: #endif
1.183 brouard 2617: #ifdef POWELLORIGINAL
2618: if (t < 0.0) { /* Then we use it for new direction */
2619: #else
1.182 brouard 2620: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2621: 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 2622: 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 2623: 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 2624: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2625: }
1.181 brouard 2626: if (directest < 0.0) { /* Then we use it for new direction */
2627: #endif
1.191 brouard 2628: #ifdef DEBUGLINMIN
1.234 brouard 2629: printf("Before linmin in direction P%d-P0\n",n);
2630: for (j=1;j<=n;j++) {
2631: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2632: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2633: if(j % ncovmodel == 0){
2634: printf("\n");
2635: fprintf(ficlog,"\n");
2636: }
2637: }
1.224 brouard 2638: #endif
2639: #ifdef LINMINORIGINAL
1.234 brouard 2640: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2641: #else
1.234 brouard 2642: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2643: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2644: #endif
1.234 brouard 2645:
1.191 brouard 2646: #ifdef DEBUGLINMIN
1.234 brouard 2647: for (j=1;j<=n;j++) {
2648: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2649: fprintf(ficlog,"After 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
1.234 brouard 2656: for (j=1;j<=n;j++) {
2657: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2658: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2659: }
1.224 brouard 2660: #ifdef LINMINORIGINAL
2661: #else
1.234 brouard 2662: for (j=1, flatd=0;j<=n;j++) {
2663: if(flatdir[j]>0)
2664: flatd++;
2665: }
2666: if(flatd >0){
1.255 brouard 2667: printf("%d flat directions: ",flatd);
2668: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2669: for (j=1;j<=n;j++) {
2670: if(flatdir[j]>0){
2671: printf("%d ",j);
2672: fprintf(ficlog,"%d ",j);
2673: }
2674: }
2675: printf("\n");
2676: fprintf(ficlog,"\n");
1.319 brouard 2677: #ifdef FLATSUP
2678: free_vector(xit,1,n);
2679: free_vector(xits,1,n);
2680: free_vector(ptt,1,n);
2681: free_vector(pt,1,n);
2682: return;
2683: #endif
1.234 brouard 2684: }
1.191 brouard 2685: #endif
1.234 brouard 2686: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2687: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2688:
1.126 brouard 2689: #ifdef DEBUG
1.234 brouard 2690: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2691: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2692: for(j=1;j<=n;j++){
2693: printf(" %lf",xit[j]);
2694: fprintf(ficlog," %lf",xit[j]);
2695: }
2696: printf("\n");
2697: fprintf(ficlog,"\n");
1.126 brouard 2698: #endif
1.192 brouard 2699: } /* end of t or directest negative */
1.224 brouard 2700: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2701: #else
1.234 brouard 2702: } /* end if (fptt < fp) */
1.192 brouard 2703: #endif
1.225 brouard 2704: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2705: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2706: #else
1.224 brouard 2707: #endif
1.234 brouard 2708: } /* loop iteration */
1.126 brouard 2709: }
1.234 brouard 2710:
1.126 brouard 2711: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2712:
1.235 brouard 2713: 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 2714: {
1.279 brouard 2715: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2716: * (and selected quantitative values in nres)
2717: * by left multiplying the unit
2718: * matrix by transitions matrix until convergence is reached with precision ftolpl
2719: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2720: * Wx is row vector: population in state 1, population in state 2, population dead
2721: * or prevalence in state 1, prevalence in state 2, 0
2722: * newm is the matrix after multiplications, its rows are identical at a factor.
2723: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2724: * Output is prlim.
2725: * Initial matrix pimij
2726: */
1.206 brouard 2727: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2728: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2729: /* 0, 0 , 1} */
2730: /*
2731: * and after some iteration: */
2732: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2733: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2734: /* 0, 0 , 1} */
2735: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2736: /* {0.51571254859325999, 0.4842874514067399, */
2737: /* 0.51326036147820708, 0.48673963852179264} */
2738: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2739:
1.126 brouard 2740: int i, ii,j,k;
1.209 brouard 2741: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2742: /* double **matprod2(); */ /* test */
1.218 brouard 2743: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2744: double **newm;
1.209 brouard 2745: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2746: int ncvloop=0;
1.288 brouard 2747: int first=0;
1.169 brouard 2748:
1.209 brouard 2749: min=vector(1,nlstate);
2750: max=vector(1,nlstate);
2751: meandiff=vector(1,nlstate);
2752:
1.218 brouard 2753: /* Starting with matrix unity */
1.126 brouard 2754: for (ii=1;ii<=nlstate+ndeath;ii++)
2755: for (j=1;j<=nlstate+ndeath;j++){
2756: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2757: }
1.169 brouard 2758:
2759: cov[1]=1.;
2760:
2761: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2762: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2763: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2764: ncvloop++;
1.126 brouard 2765: newm=savm;
2766: /* Covariates have to be included here again */
1.138 brouard 2767: cov[2]=agefin;
1.319 brouard 2768: if(nagesqr==1){
2769: cov[3]= agefin*agefin;
2770: }
1.234 brouard 2771: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2772: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2773: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.319 brouard 2774: /* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; */
1.235 brouard 2775: /* 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 2776: }
2777: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2778: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 2779: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2780: /* cov[++k1]=Tqresult[nres][k]; */
1.235 brouard 2781: /* 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 2782: }
1.237 brouard 2783: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2784: if(Dummy[Tage[k]]==2){ /* dummy with age */
1.234 brouard 2785: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2786: /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
2787: } else if(Dummy[Tage[k]]==3){ /* quantitative with age */
2788: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2789: /* cov[++k1]=Tqresult[nres][k]; */
1.234 brouard 2790: }
1.235 brouard 2791: /* 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 2792: }
1.237 brouard 2793: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2794: /* 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 2795: if(Dummy[Tvard[k][1]==0]){
2796: if(Dummy[Tvard[k][2]==0]){
2797: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
1.319 brouard 2798: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.237 brouard 2799: }else{
2800: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
1.319 brouard 2801: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */
1.237 brouard 2802: }
2803: }else{
2804: if(Dummy[Tvard[k][2]==0]){
2805: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
1.319 brouard 2806: /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */
1.237 brouard 2807: }else{
2808: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
1.319 brouard 2809: /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
1.237 brouard 2810: }
2811: }
1.234 brouard 2812: }
1.138 brouard 2813: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2814: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2815: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2816: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2817: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2818: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2819: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2820:
1.126 brouard 2821: savm=oldm;
2822: oldm=newm;
1.209 brouard 2823:
2824: for(j=1; j<=nlstate; j++){
2825: max[j]=0.;
2826: min[j]=1.;
2827: }
2828: for(i=1;i<=nlstate;i++){
2829: sumnew=0;
2830: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2831: for(j=1; j<=nlstate; j++){
2832: prlim[i][j]= newm[i][j]/(1-sumnew);
2833: max[j]=FMAX(max[j],prlim[i][j]);
2834: min[j]=FMIN(min[j],prlim[i][j]);
2835: }
2836: }
2837:
1.126 brouard 2838: maxmax=0.;
1.209 brouard 2839: for(j=1; j<=nlstate; j++){
2840: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2841: maxmax=FMAX(maxmax,meandiff[j]);
2842: /* 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 2843: } /* j loop */
1.203 brouard 2844: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2845: /* 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 2846: if(maxmax < ftolpl){
1.209 brouard 2847: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2848: free_vector(min,1,nlstate);
2849: free_vector(max,1,nlstate);
2850: free_vector(meandiff,1,nlstate);
1.126 brouard 2851: return prlim;
2852: }
1.288 brouard 2853: } /* agefin loop */
1.208 brouard 2854: /* After some age loop it doesn't converge */
1.288 brouard 2855: if(!first){
2856: first=1;
2857: 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 2858: 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);
2859: }else if (first >=1 && first <10){
2860: 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);
2861: first++;
2862: }else if (first ==10){
2863: 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);
2864: 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");
2865: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
2866: first++;
1.288 brouard 2867: }
2868:
1.209 brouard 2869: /* 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); */
2870: free_vector(min,1,nlstate);
2871: free_vector(max,1,nlstate);
2872: free_vector(meandiff,1,nlstate);
1.208 brouard 2873:
1.169 brouard 2874: return prlim; /* should not reach here */
1.126 brouard 2875: }
2876:
1.217 brouard 2877:
2878: /**** Back Prevalence limit (stable or period prevalence) ****************/
2879:
1.218 brouard 2880: /* 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) */
2881: /* 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 2882: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2883: {
1.264 brouard 2884: /* 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 2885: matrix by transitions matrix until convergence is reached with precision ftolpl */
2886: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2887: /* Wx is row vector: population in state 1, population in state 2, population dead */
2888: /* or prevalence in state 1, prevalence in state 2, 0 */
2889: /* newm is the matrix after multiplications, its rows are identical at a factor */
2890: /* Initial matrix pimij */
2891: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2892: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2893: /* 0, 0 , 1} */
2894: /*
2895: * and after some iteration: */
2896: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2897: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2898: /* 0, 0 , 1} */
2899: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2900: /* {0.51571254859325999, 0.4842874514067399, */
2901: /* 0.51326036147820708, 0.48673963852179264} */
2902: /* If we start from prlim again, prlim tends to a constant matrix */
2903:
2904: int i, ii,j,k;
1.247 brouard 2905: int first=0;
1.217 brouard 2906: double *min, *max, *meandiff, maxmax,sumnew=0.;
2907: /* double **matprod2(); */ /* test */
2908: double **out, cov[NCOVMAX+1], **bmij();
2909: double **newm;
1.218 brouard 2910: double **dnewm, **doldm, **dsavm; /* for use */
2911: double **oldm, **savm; /* for use */
2912:
1.217 brouard 2913: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2914: int ncvloop=0;
2915:
2916: min=vector(1,nlstate);
2917: max=vector(1,nlstate);
2918: meandiff=vector(1,nlstate);
2919:
1.266 brouard 2920: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2921: oldm=oldms; savm=savms;
2922:
2923: /* Starting with matrix unity */
2924: for (ii=1;ii<=nlstate+ndeath;ii++)
2925: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2926: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2927: }
2928:
2929: cov[1]=1.;
2930:
2931: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2932: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2933: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2934: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2935: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2936: ncvloop++;
1.218 brouard 2937: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2938: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2939: /* Covariates have to be included here again */
2940: cov[2]=agefin;
1.319 brouard 2941: if(nagesqr==1){
1.217 brouard 2942: cov[3]= agefin*agefin;;
1.319 brouard 2943: }
1.242 brouard 2944: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2945: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2946: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2947: /* 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 2948: }
2949: /* for (k=1; k<=cptcovn;k++) { */
2950: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2951: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2952: /* /\* 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])]); *\/ */
2953: /* } */
2954: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2955: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2956: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2957: /* 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]); */
2958: }
2959: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2960: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2961: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2962: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2963: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2964: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ ERROR ???*/
2965: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.242 brouard 2966: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2967: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
2968: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.242 brouard 2969: }
2970: /* 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]); */
2971: }
2972: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2973: /* 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]); */
2974: if(Dummy[Tvard[k][1]==0]){
2975: if(Dummy[Tvard[k][2]==0]){
2976: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2977: }else{
2978: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2979: }
2980: }else{
2981: if(Dummy[Tvard[k][2]==0]){
2982: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2983: }else{
2984: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2985: }
2986: }
1.217 brouard 2987: }
2988:
2989: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2990: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2991: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2992: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2993: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2994: /* ij should be linked to the correct index of cov */
2995: /* age and covariate values ij are in 'cov', but we need to pass
2996: * ij for the observed prevalence at age and status and covariate
2997: * number: prevacurrent[(int)agefin][ii][ij]
2998: */
2999: /* 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 *\/ */
3000: /* 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 *\/ */
3001: 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 3002: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3003: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3004: /* for(i=1; i<=nlstate+ndeath; i++) { */
3005: /* printf("%d newm= ",i); */
3006: /* for(j=1;j<=nlstate+ndeath;j++) { */
3007: /* printf("%f ",newm[i][j]); */
3008: /* } */
3009: /* printf("oldm * "); */
3010: /* for(j=1;j<=nlstate+ndeath;j++) { */
3011: /* printf("%f ",oldm[i][j]); */
3012: /* } */
1.268 brouard 3013: /* printf(" bmmij "); */
1.266 brouard 3014: /* for(j=1;j<=nlstate+ndeath;j++) { */
3015: /* printf("%f ",pmmij[i][j]); */
3016: /* } */
3017: /* printf("\n"); */
3018: /* } */
3019: /* } */
1.217 brouard 3020: savm=oldm;
3021: oldm=newm;
1.266 brouard 3022:
1.217 brouard 3023: for(j=1; j<=nlstate; j++){
3024: max[j]=0.;
3025: min[j]=1.;
3026: }
3027: for(j=1; j<=nlstate; j++){
3028: for(i=1;i<=nlstate;i++){
1.234 brouard 3029: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3030: bprlim[i][j]= newm[i][j];
3031: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3032: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3033: }
3034: }
1.218 brouard 3035:
1.217 brouard 3036: maxmax=0.;
3037: for(i=1; i<=nlstate; i++){
1.318 brouard 3038: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3039: maxmax=FMAX(maxmax,meandiff[i]);
3040: /* 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 3041: } /* i loop */
1.217 brouard 3042: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3043: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3044: if(maxmax < ftolpl){
1.220 brouard 3045: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3046: free_vector(min,1,nlstate);
3047: free_vector(max,1,nlstate);
3048: free_vector(meandiff,1,nlstate);
3049: return bprlim;
3050: }
1.288 brouard 3051: } /* agefin loop */
1.217 brouard 3052: /* After some age loop it doesn't converge */
1.288 brouard 3053: if(!first){
1.247 brouard 3054: first=1;
3055: 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\
3056: 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);
3057: }
3058: 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 3059: 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);
3060: /* 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); */
3061: free_vector(min,1,nlstate);
3062: free_vector(max,1,nlstate);
3063: free_vector(meandiff,1,nlstate);
3064:
3065: return bprlim; /* should not reach here */
3066: }
3067:
1.126 brouard 3068: /*************** transition probabilities ***************/
3069:
3070: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3071: {
1.138 brouard 3072: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3073: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3074: model to the ncovmodel covariates (including constant and age).
3075: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3076: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3077: ncth covariate in the global vector x is given by the formula:
3078: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3079: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3080: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3081: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3082: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3083: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3084: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3085: */
3086: double s1, lnpijopii;
1.126 brouard 3087: /*double t34;*/
1.164 brouard 3088: int i,j, nc, ii, jj;
1.126 brouard 3089:
1.223 brouard 3090: for(i=1; i<= nlstate; i++){
3091: for(j=1; j<i;j++){
3092: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3093: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3094: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3095: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3096: }
3097: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3098: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3099: }
3100: for(j=i+1; j<=nlstate+ndeath;j++){
3101: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3102: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3103: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3104: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3105: }
3106: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3107: }
3108: }
1.218 brouard 3109:
1.223 brouard 3110: for(i=1; i<= nlstate; i++){
3111: s1=0;
3112: for(j=1; j<i; j++){
3113: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3114: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3115: }
3116: for(j=i+1; j<=nlstate+ndeath; j++){
3117: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3118: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3119: }
3120: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3121: ps[i][i]=1./(s1+1.);
3122: /* Computing other pijs */
3123: for(j=1; j<i; j++)
3124: ps[i][j]= exp(ps[i][j])*ps[i][i];
3125: for(j=i+1; j<=nlstate+ndeath; j++)
3126: ps[i][j]= exp(ps[i][j])*ps[i][i];
3127: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3128: } /* end i */
1.218 brouard 3129:
1.223 brouard 3130: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3131: for(jj=1; jj<= nlstate+ndeath; jj++){
3132: ps[ii][jj]=0;
3133: ps[ii][ii]=1;
3134: }
3135: }
1.294 brouard 3136:
3137:
1.223 brouard 3138: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3139: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3140: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3141: /* } */
3142: /* printf("\n "); */
3143: /* } */
3144: /* printf("\n ");printf("%lf ",cov[2]);*/
3145: /*
3146: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3147: goto end;*/
1.266 brouard 3148: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3149: }
3150:
1.218 brouard 3151: /*************** backward transition probabilities ***************/
3152:
3153: /* 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 ) */
3154: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3155: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3156: {
1.302 brouard 3157: /* 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 3158: * 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 3159: */
1.218 brouard 3160: int i, ii, j,k;
1.222 brouard 3161:
3162: double **out, **pmij();
3163: double sumnew=0.;
1.218 brouard 3164: double agefin;
1.292 brouard 3165: 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 3166: double **dnewm, **dsavm, **doldm;
3167: double **bbmij;
3168:
1.218 brouard 3169: doldm=ddoldms; /* global pointers */
1.222 brouard 3170: dnewm=ddnewms;
3171: dsavm=ddsavms;
1.318 brouard 3172:
3173: /* Debug */
3174: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3175: agefin=cov[2];
1.268 brouard 3176: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3177: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3178: the observed prevalence (with this covariate ij) at beginning of transition */
3179: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3180:
3181: /* P_x */
1.266 brouard 3182: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3183: /* outputs pmmij which is a stochastic matrix in row */
3184:
3185: /* Diag(w_x) */
1.292 brouard 3186: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3187: sumnew=0.;
1.269 brouard 3188: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3189: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3190: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3191: sumnew+=prevacurrent[(int)agefin][ii][ij];
3192: }
3193: if(sumnew >0.01){ /* At least some value in the prevalence */
3194: for (ii=1;ii<=nlstate+ndeath;ii++){
3195: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3196: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3197: }
3198: }else{
3199: for (ii=1;ii<=nlstate+ndeath;ii++){
3200: for (j=1;j<=nlstate+ndeath;j++)
3201: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3202: }
3203: /* if(sumnew <0.9){ */
3204: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3205: /* } */
3206: }
3207: k3=0.0; /* We put the last diagonal to 0 */
3208: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3209: doldm[ii][ii]= k3;
3210: }
3211: /* End doldm, At the end doldm is diag[(w_i)] */
3212:
1.292 brouard 3213: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3214: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3215:
1.292 brouard 3216: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3217: /* 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 3218: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3219: sumnew=0.;
1.222 brouard 3220: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3221: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3222: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3223: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3224: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3225: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3226: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3227: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3228: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3229: /* }else */
1.268 brouard 3230: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3231: } /*End ii */
3232: } /* 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 */
3233:
1.292 brouard 3234: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3235: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3236: /* end bmij */
1.266 brouard 3237: return ps; /*pointer is unchanged */
1.218 brouard 3238: }
1.217 brouard 3239: /*************** transition probabilities ***************/
3240:
1.218 brouard 3241: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3242: {
3243: /* According to parameters values stored in x and the covariate's values stored in cov,
3244: computes the probability to be observed in state j being in state i by appying the
3245: model to the ncovmodel covariates (including constant and age).
3246: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3247: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3248: ncth covariate in the global vector x is given by the formula:
3249: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3250: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3251: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3252: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3253: Outputs ps[i][j] the probability to be observed in j being in j according to
3254: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3255: */
3256: double s1, lnpijopii;
3257: /*double t34;*/
3258: int i,j, nc, ii, jj;
3259:
1.234 brouard 3260: for(i=1; i<= nlstate; i++){
3261: for(j=1; j<i;j++){
3262: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3263: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3264: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3265: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3266: }
3267: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3268: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3269: }
3270: for(j=i+1; j<=nlstate+ndeath;j++){
3271: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3272: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3273: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3274: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3275: }
3276: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3277: }
3278: }
3279:
3280: for(i=1; i<= nlstate; i++){
3281: s1=0;
3282: for(j=1; j<i; j++){
3283: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3284: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3285: }
3286: for(j=i+1; j<=nlstate+ndeath; j++){
3287: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3288: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3289: }
3290: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3291: ps[i][i]=1./(s1+1.);
3292: /* Computing other pijs */
3293: for(j=1; j<i; j++)
3294: ps[i][j]= exp(ps[i][j])*ps[i][i];
3295: for(j=i+1; j<=nlstate+ndeath; j++)
3296: ps[i][j]= exp(ps[i][j])*ps[i][i];
3297: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3298: } /* end i */
3299:
3300: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3301: for(jj=1; jj<= nlstate+ndeath; jj++){
3302: ps[ii][jj]=0;
3303: ps[ii][ii]=1;
3304: }
3305: }
1.296 brouard 3306: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3307: for(jj=1; jj<= nlstate+ndeath; jj++){
3308: s1=0.;
3309: for(ii=1; ii<= nlstate+ndeath; ii++){
3310: s1+=ps[ii][jj];
3311: }
3312: for(ii=1; ii<= nlstate; ii++){
3313: ps[ii][jj]=ps[ii][jj]/s1;
3314: }
3315: }
3316: /* Transposition */
3317: for(jj=1; jj<= nlstate+ndeath; jj++){
3318: for(ii=jj; ii<= nlstate+ndeath; ii++){
3319: s1=ps[ii][jj];
3320: ps[ii][jj]=ps[jj][ii];
3321: ps[jj][ii]=s1;
3322: }
3323: }
3324: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3325: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3326: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3327: /* } */
3328: /* printf("\n "); */
3329: /* } */
3330: /* printf("\n ");printf("%lf ",cov[2]);*/
3331: /*
3332: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3333: goto end;*/
3334: return ps;
1.217 brouard 3335: }
3336:
3337:
1.126 brouard 3338: /**************** Product of 2 matrices ******************/
3339:
1.145 brouard 3340: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3341: {
3342: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3343: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3344: /* in, b, out are matrice of pointers which should have been initialized
3345: before: only the contents of out is modified. The function returns
3346: a pointer to pointers identical to out */
1.145 brouard 3347: int i, j, k;
1.126 brouard 3348: for(i=nrl; i<= nrh; i++)
1.145 brouard 3349: for(k=ncolol; k<=ncoloh; k++){
3350: out[i][k]=0.;
3351: for(j=ncl; j<=nch; j++)
3352: out[i][k] +=in[i][j]*b[j][k];
3353: }
1.126 brouard 3354: return out;
3355: }
3356:
3357:
3358: /************* Higher Matrix Product ***************/
3359:
1.235 brouard 3360: 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 3361: {
1.218 brouard 3362: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3363: 'nhstepm*hstepm*stepm' months (i.e. until
3364: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3365: nhstepm*hstepm matrices.
3366: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3367: (typically every 2 years instead of every month which is too big
3368: for the memory).
3369: Model is determined by parameters x and covariates have to be
3370: included manually here.
3371:
3372: */
3373:
3374: int i, j, d, h, k;
1.131 brouard 3375: double **out, cov[NCOVMAX+1];
1.126 brouard 3376: double **newm;
1.187 brouard 3377: double agexact;
1.214 brouard 3378: double agebegin, ageend;
1.126 brouard 3379:
3380: /* Hstepm could be zero and should return the unit matrix */
3381: for (i=1;i<=nlstate+ndeath;i++)
3382: for (j=1;j<=nlstate+ndeath;j++){
3383: oldm[i][j]=(i==j ? 1.0 : 0.0);
3384: po[i][j][0]=(i==j ? 1.0 : 0.0);
3385: }
3386: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3387: for(h=1; h <=nhstepm; h++){
3388: for(d=1; d <=hstepm; d++){
3389: newm=savm;
3390: /* Covariates have to be included here again */
3391: cov[1]=1.;
1.214 brouard 3392: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3393: cov[2]=agexact;
1.319 brouard 3394: if(nagesqr==1){
1.227 brouard 3395: cov[3]= agexact*agexact;
1.319 brouard 3396: }
1.235 brouard 3397: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
1.319 brouard 3398: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3399: /* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 */
3400: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3401: /* k 1 2 3 4 5 6 7 8 9 */
3402: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
3403: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
3404: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
3405: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1.235 brouard 3406: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3407: /* 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)); */
3408: }
3409: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3410: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 3411: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
1.235 brouard 3412: /* 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]); */
3413: }
1.319 brouard 3414: for (k=1; k<=cptcovage;k++){ /* For product with age V1+V1*age +V4 +age*V3 */
3415: /* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*/
3416: /* */
3417: if(Dummy[Tage[k]]== 2){ /* dummy with age */
3418: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ */
1.235 brouard 3419: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3420: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
3421: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.235 brouard 3422: }
3423: /* 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]); */
3424: }
1.319 brouard 3425: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 3426: /* 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 3427: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
3428: if(Dummy[Tvard[k][1]==0]){
3429: if(Dummy[Tvard[k][2]==0]){
3430: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3431: }else{
3432: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
3433: }
3434: }else{
3435: if(Dummy[Tvard[k][2]==0]){
3436: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
3437: }else{
3438: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3439: }
3440: }
1.235 brouard 3441: }
3442: /* for (k=1; k<=cptcovn;k++) */
3443: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3444: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3445: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3446: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3447: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3448:
3449:
1.126 brouard 3450: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3451: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3452: /* right multiplication of oldm by the current matrix */
1.126 brouard 3453: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3454: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3455: /* if((int)age == 70){ */
3456: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3457: /* for(i=1; i<=nlstate+ndeath; i++) { */
3458: /* printf("%d pmmij ",i); */
3459: /* for(j=1;j<=nlstate+ndeath;j++) { */
3460: /* printf("%f ",pmmij[i][j]); */
3461: /* } */
3462: /* printf(" oldm "); */
3463: /* for(j=1;j<=nlstate+ndeath;j++) { */
3464: /* printf("%f ",oldm[i][j]); */
3465: /* } */
3466: /* printf("\n"); */
3467: /* } */
3468: /* } */
1.126 brouard 3469: savm=oldm;
3470: oldm=newm;
3471: }
3472: for(i=1; i<=nlstate+ndeath; i++)
3473: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3474: po[i][j][h]=newm[i][j];
3475: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3476: }
1.128 brouard 3477: /*printf("h=%d ",h);*/
1.126 brouard 3478: } /* end h */
1.267 brouard 3479: /* printf("\n H=%d \n",h); */
1.126 brouard 3480: return po;
3481: }
3482:
1.217 brouard 3483: /************* Higher Back Matrix Product ***************/
1.218 brouard 3484: /* 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 3485: 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 3486: {
1.266 brouard 3487: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3488: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3489: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3490: nhstepm*hstepm matrices.
3491: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3492: (typically every 2 years instead of every month which is too big
1.217 brouard 3493: for the memory).
1.218 brouard 3494: Model is determined by parameters x and covariates have to be
1.266 brouard 3495: included manually here. Then we use a call to bmij(x and cov)
3496: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3497: */
1.217 brouard 3498:
3499: int i, j, d, h, k;
1.266 brouard 3500: double **out, cov[NCOVMAX+1], **bmij();
3501: double **newm, ***newmm;
1.217 brouard 3502: double agexact;
3503: double agebegin, ageend;
1.222 brouard 3504: double **oldm, **savm;
1.217 brouard 3505:
1.266 brouard 3506: newmm=po; /* To be saved */
3507: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3508: /* Hstepm could be zero and should return the unit matrix */
3509: for (i=1;i<=nlstate+ndeath;i++)
3510: for (j=1;j<=nlstate+ndeath;j++){
3511: oldm[i][j]=(i==j ? 1.0 : 0.0);
3512: po[i][j][0]=(i==j ? 1.0 : 0.0);
3513: }
3514: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3515: for(h=1; h <=nhstepm; h++){
3516: for(d=1; d <=hstepm; d++){
3517: newm=savm;
3518: /* Covariates have to be included here again */
3519: cov[1]=1.;
1.271 brouard 3520: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3521: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3522: /* Debug */
3523: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3524: cov[2]=agexact;
3525: if(nagesqr==1)
1.222 brouard 3526: cov[3]= agexact*agexact;
1.266 brouard 3527: for (k=1; k<=cptcovn;k++){
3528: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3529: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3530: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3531: /* 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)); */
3532: }
1.267 brouard 3533: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3534: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3535: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3536: /* 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]); */
3537: }
1.319 brouard 3538: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 *//* For product with age */
3539: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age error!!!*\/ */
3540: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.267 brouard 3541: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3542: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
1.267 brouard 3543: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3544: }
3545: /* 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]); */
3546: }
3547: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3548: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3549: }
1.217 brouard 3550: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3551: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3552:
1.218 brouard 3553: /* Careful transposed matrix */
1.266 brouard 3554: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3555: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3556: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3557: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3558: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3559: /* if((int)age == 70){ */
3560: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3561: /* for(i=1; i<=nlstate+ndeath; i++) { */
3562: /* printf("%d pmmij ",i); */
3563: /* for(j=1;j<=nlstate+ndeath;j++) { */
3564: /* printf("%f ",pmmij[i][j]); */
3565: /* } */
3566: /* printf(" oldm "); */
3567: /* for(j=1;j<=nlstate+ndeath;j++) { */
3568: /* printf("%f ",oldm[i][j]); */
3569: /* } */
3570: /* printf("\n"); */
3571: /* } */
3572: /* } */
3573: savm=oldm;
3574: oldm=newm;
3575: }
3576: for(i=1; i<=nlstate+ndeath; i++)
3577: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3578: po[i][j][h]=newm[i][j];
1.268 brouard 3579: /* if(h==nhstepm) */
3580: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3581: }
1.268 brouard 3582: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3583: } /* end h */
1.268 brouard 3584: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3585: return po;
3586: }
3587:
3588:
1.162 brouard 3589: #ifdef NLOPT
3590: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3591: double fret;
3592: double *xt;
3593: int j;
3594: myfunc_data *d2 = (myfunc_data *) pd;
3595: /* xt = (p1-1); */
3596: xt=vector(1,n);
3597: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3598:
3599: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3600: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3601: printf("Function = %.12lf ",fret);
3602: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3603: printf("\n");
3604: free_vector(xt,1,n);
3605: return fret;
3606: }
3607: #endif
1.126 brouard 3608:
3609: /*************** log-likelihood *************/
3610: double func( double *x)
3611: {
1.226 brouard 3612: int i, ii, j, k, mi, d, kk;
3613: int ioffset=0;
3614: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3615: double **out;
3616: double lli; /* Individual log likelihood */
3617: int s1, s2;
1.228 brouard 3618: 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 3619: double bbh, survp;
3620: long ipmx;
3621: double agexact;
3622: /*extern weight */
3623: /* We are differentiating ll according to initial status */
3624: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3625: /*for(i=1;i<imx;i++)
3626: printf(" %d\n",s[4][i]);
3627: */
1.162 brouard 3628:
1.226 brouard 3629: ++countcallfunc;
1.162 brouard 3630:
1.226 brouard 3631: cov[1]=1.;
1.126 brouard 3632:
1.226 brouard 3633: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3634: ioffset=0;
1.226 brouard 3635: if(mle==1){
3636: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3637: /* Computes the values of the ncovmodel covariates of the model
3638: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3639: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3640: to be observed in j being in i according to the model.
3641: */
1.243 brouard 3642: ioffset=2+nagesqr ;
1.233 brouard 3643: /* Fixed */
1.319 brouard 3644: for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */
3645: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3646: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3647: /* 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 3648: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.319 brouard 3649: 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)*/
3650: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3651: }
1.226 brouard 3652: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3653: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3654: has been calculated etc */
3655: /* For an individual i, wav[i] gives the number of effective waves */
3656: /* We compute the contribution to Likelihood of each effective transition
3657: mw[mi][i] is real wave of the mi th effectve wave */
3658: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3659: s2=s[mw[mi+1][i]][i];
3660: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3661: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3662: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3663: */
3664: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3665: 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*/
3666: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */
1.242 brouard 3667: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3668: }
3669: for (ii=1;ii<=nlstate+ndeath;ii++)
3670: for (j=1;j<=nlstate+ndeath;j++){
3671: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3672: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3673: }
3674: for(d=0; d<dh[mi][i]; d++){
3675: newm=savm;
3676: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3677: cov[2]=agexact;
3678: if(nagesqr==1)
3679: cov[3]= agexact*agexact; /* Should be changed here */
3680: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3681: if(!FixedV[Tvar[Tage[kk]]])
3682: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3683: else
3684: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3685: }
3686: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3687: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3688: savm=oldm;
3689: oldm=newm;
3690: } /* end mult */
3691:
3692: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3693: /* But now since version 0.9 we anticipate for bias at large stepm.
3694: * If stepm is larger than one month (smallest stepm) and if the exact delay
3695: * (in months) between two waves is not a multiple of stepm, we rounded to
3696: * the nearest (and in case of equal distance, to the lowest) interval but now
3697: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3698: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3699: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3700: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3701: * -stepm/2 to stepm/2 .
3702: * For stepm=1 the results are the same as for previous versions of Imach.
3703: * For stepm > 1 the results are less biased than in previous versions.
3704: */
1.234 brouard 3705: s1=s[mw[mi][i]][i];
3706: s2=s[mw[mi+1][i]][i];
3707: bbh=(double)bh[mi][i]/(double)stepm;
3708: /* bias bh is positive if real duration
3709: * is higher than the multiple of stepm and negative otherwise.
3710: */
3711: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3712: if( s2 > nlstate){
3713: /* i.e. if s2 is a death state and if the date of death is known
3714: then the contribution to the likelihood is the probability to
3715: die between last step unit time and current step unit time,
3716: which is also equal to probability to die before dh
3717: minus probability to die before dh-stepm .
3718: In version up to 0.92 likelihood was computed
3719: as if date of death was unknown. Death was treated as any other
3720: health state: the date of the interview describes the actual state
3721: and not the date of a change in health state. The former idea was
3722: to consider that at each interview the state was recorded
3723: (healthy, disable or death) and IMaCh was corrected; but when we
3724: introduced the exact date of death then we should have modified
3725: the contribution of an exact death to the likelihood. This new
3726: contribution is smaller and very dependent of the step unit
3727: stepm. It is no more the probability to die between last interview
3728: and month of death but the probability to survive from last
3729: interview up to one month before death multiplied by the
3730: probability to die within a month. Thanks to Chris
3731: Jackson for correcting this bug. Former versions increased
3732: mortality artificially. The bad side is that we add another loop
3733: which slows down the processing. The difference can be up to 10%
3734: lower mortality.
3735: */
3736: /* If, at the beginning of the maximization mostly, the
3737: cumulative probability or probability to be dead is
3738: constant (ie = 1) over time d, the difference is equal to
3739: 0. out[s1][3] = savm[s1][3]: probability, being at state
3740: s1 at precedent wave, to be dead a month before current
3741: wave is equal to probability, being at state s1 at
3742: precedent wave, to be dead at mont of the current
3743: wave. Then the observed probability (that this person died)
3744: is null according to current estimated parameter. In fact,
3745: it should be very low but not zero otherwise the log go to
3746: infinity.
3747: */
1.183 brouard 3748: /* #ifdef INFINITYORIGINAL */
3749: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3750: /* #else */
3751: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3752: /* lli=log(mytinydouble); */
3753: /* else */
3754: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3755: /* #endif */
1.226 brouard 3756: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3757:
1.226 brouard 3758: } else if ( s2==-1 ) { /* alive */
3759: for (j=1,survp=0. ; j<=nlstate; j++)
3760: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3761: /*survp += out[s1][j]; */
3762: lli= log(survp);
3763: }
3764: else if (s2==-4) {
3765: for (j=3,survp=0. ; j<=nlstate; j++)
3766: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3767: lli= log(survp);
3768: }
3769: else if (s2==-5) {
3770: for (j=1,survp=0. ; j<=2; j++)
3771: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3772: lli= log(survp);
3773: }
3774: else{
3775: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3776: /* 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 */
3777: }
3778: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3779: /*if(lli ==000.0)*/
3780: /*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); */
3781: ipmx +=1;
3782: sw += weight[i];
3783: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3784: /* if (lli < log(mytinydouble)){ */
3785: /* 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); */
3786: /* 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]); */
3787: /* } */
3788: } /* end of wave */
3789: } /* end of individual */
3790: } else if(mle==2){
3791: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 3792: ioffset=2+nagesqr ;
3793: for (k=1; k<=ncovf;k++)
3794: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 3795: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3796: for(k=1; k <= ncovv ; k++){
3797: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3798: }
1.226 brouard 3799: for (ii=1;ii<=nlstate+ndeath;ii++)
3800: for (j=1;j<=nlstate+ndeath;j++){
3801: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3802: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3803: }
3804: for(d=0; d<=dh[mi][i]; d++){
3805: newm=savm;
3806: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3807: cov[2]=agexact;
3808: if(nagesqr==1)
3809: cov[3]= agexact*agexact;
3810: for (kk=1; kk<=cptcovage;kk++) {
3811: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3812: }
3813: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3814: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3815: savm=oldm;
3816: oldm=newm;
3817: } /* end mult */
3818:
3819: s1=s[mw[mi][i]][i];
3820: s2=s[mw[mi+1][i]][i];
3821: bbh=(double)bh[mi][i]/(double)stepm;
3822: 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 */
3823: ipmx +=1;
3824: sw += weight[i];
3825: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3826: } /* end of wave */
3827: } /* end of individual */
3828: } else if(mle==3){ /* exponential inter-extrapolation */
3829: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3830: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3831: for(mi=1; mi<= wav[i]-1; mi++){
3832: for (ii=1;ii<=nlstate+ndeath;ii++)
3833: for (j=1;j<=nlstate+ndeath;j++){
3834: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3835: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3836: }
3837: for(d=0; d<dh[mi][i]; d++){
3838: newm=savm;
3839: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3840: cov[2]=agexact;
3841: if(nagesqr==1)
3842: cov[3]= agexact*agexact;
3843: for (kk=1; kk<=cptcovage;kk++) {
3844: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3845: }
3846: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3847: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3848: savm=oldm;
3849: oldm=newm;
3850: } /* end mult */
3851:
3852: s1=s[mw[mi][i]][i];
3853: s2=s[mw[mi+1][i]][i];
3854: bbh=(double)bh[mi][i]/(double)stepm;
3855: 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 */
3856: ipmx +=1;
3857: sw += weight[i];
3858: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3859: } /* end of wave */
3860: } /* end of individual */
3861: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3862: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3863: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3864: for(mi=1; mi<= wav[i]-1; mi++){
3865: for (ii=1;ii<=nlstate+ndeath;ii++)
3866: for (j=1;j<=nlstate+ndeath;j++){
3867: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3868: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3869: }
3870: for(d=0; d<dh[mi][i]; d++){
3871: newm=savm;
3872: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3873: cov[2]=agexact;
3874: if(nagesqr==1)
3875: cov[3]= agexact*agexact;
3876: for (kk=1; kk<=cptcovage;kk++) {
3877: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3878: }
1.126 brouard 3879:
1.226 brouard 3880: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3881: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3882: savm=oldm;
3883: oldm=newm;
3884: } /* end mult */
3885:
3886: s1=s[mw[mi][i]][i];
3887: s2=s[mw[mi+1][i]][i];
3888: if( s2 > nlstate){
3889: lli=log(out[s1][s2] - savm[s1][s2]);
3890: } else if ( s2==-1 ) { /* alive */
3891: for (j=1,survp=0. ; j<=nlstate; j++)
3892: survp += out[s1][j];
3893: lli= log(survp);
3894: }else{
3895: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3896: }
3897: ipmx +=1;
3898: sw += weight[i];
3899: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3900: /* 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 3901: } /* end of wave */
3902: } /* end of individual */
3903: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3904: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3905: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3906: for(mi=1; mi<= wav[i]-1; mi++){
3907: for (ii=1;ii<=nlstate+ndeath;ii++)
3908: for (j=1;j<=nlstate+ndeath;j++){
3909: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3910: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3911: }
3912: for(d=0; d<dh[mi][i]; d++){
3913: newm=savm;
3914: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3915: cov[2]=agexact;
3916: if(nagesqr==1)
3917: cov[3]= agexact*agexact;
3918: for (kk=1; kk<=cptcovage;kk++) {
3919: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3920: }
1.126 brouard 3921:
1.226 brouard 3922: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3923: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3924: savm=oldm;
3925: oldm=newm;
3926: } /* end mult */
3927:
3928: s1=s[mw[mi][i]][i];
3929: s2=s[mw[mi+1][i]][i];
3930: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3931: ipmx +=1;
3932: sw += weight[i];
3933: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3934: /*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]);*/
3935: } /* end of wave */
3936: } /* end of individual */
3937: } /* End of if */
3938: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3939: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3940: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3941: return -l;
1.126 brouard 3942: }
3943:
3944: /*************** log-likelihood *************/
3945: double funcone( double *x)
3946: {
1.228 brouard 3947: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3948: int i, ii, j, k, mi, d, kk;
1.228 brouard 3949: int ioffset=0;
1.131 brouard 3950: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3951: double **out;
3952: double lli; /* Individual log likelihood */
3953: double llt;
3954: int s1, s2;
1.228 brouard 3955: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3956:
1.126 brouard 3957: double bbh, survp;
1.187 brouard 3958: double agexact;
1.214 brouard 3959: double agebegin, ageend;
1.126 brouard 3960: /*extern weight */
3961: /* We are differentiating ll according to initial status */
3962: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3963: /*for(i=1;i<imx;i++)
3964: printf(" %d\n",s[4][i]);
3965: */
3966: cov[1]=1.;
3967:
3968: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3969: ioffset=0;
3970: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3971: /* ioffset=2+nagesqr+cptcovage; */
3972: ioffset=2+nagesqr;
1.232 brouard 3973: /* Fixed */
1.224 brouard 3974: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3975: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 3976: 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 3977: 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)*/
3978: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3979: /* cov[2+6]=covar[Tvar[6]][i]; */
3980: /* cov[2+6]=covar[2][i]; V2 */
3981: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3982: /* cov[2+7]=covar[Tvar[7]][i]; */
3983: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3984: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3985: /* cov[2+9]=covar[Tvar[9]][i]; */
3986: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3987: }
1.232 brouard 3988: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3989: /* 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?)*\/ */
3990: /* } */
1.231 brouard 3991: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3992: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3993: /* } */
1.225 brouard 3994:
1.233 brouard 3995:
3996: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3997: /* Wave varying (but not age varying) */
3998: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3999: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
4000: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4001: }
1.232 brouard 4002: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 4003: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4004: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4005: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4006: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4007: /* 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 4008: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4009: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4010: /* /\* 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]); *\/ */
4011: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4012: /* } */
1.126 brouard 4013: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4014: for (j=1;j<=nlstate+ndeath;j++){
4015: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4016: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4017: }
1.214 brouard 4018:
4019: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4020: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4021: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4022: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4023: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4024: and mw[mi+1][i]. dh depends on stepm.*/
4025: newm=savm;
1.247 brouard 4026: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4027: cov[2]=agexact;
4028: if(nagesqr==1)
4029: cov[3]= agexact*agexact;
4030: for (kk=1; kk<=cptcovage;kk++) {
4031: if(!FixedV[Tvar[Tage[kk]]])
4032: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4033: else
4034: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
4035: }
4036: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4037: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4038: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4039: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4040: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4041: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4042: savm=oldm;
4043: oldm=newm;
1.126 brouard 4044: } /* end mult */
4045:
4046: s1=s[mw[mi][i]][i];
4047: s2=s[mw[mi+1][i]][i];
1.217 brouard 4048: /* if(s2==-1){ */
1.268 brouard 4049: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4050: /* /\* exit(1); *\/ */
4051: /* } */
1.126 brouard 4052: bbh=(double)bh[mi][i]/(double)stepm;
4053: /* bias is positive if real duration
4054: * is higher than the multiple of stepm and negative otherwise.
4055: */
4056: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4057: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4058: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4059: for (j=1,survp=0. ; j<=nlstate; j++)
4060: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4061: lli= log(survp);
1.126 brouard 4062: }else if (mle==1){
1.242 brouard 4063: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4064: } else if(mle==2){
1.242 brouard 4065: 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 4066: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4067: 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 4068: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4069: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4070: } else{ /* mle=0 back to 1 */
1.242 brouard 4071: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4072: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4073: } /* End of if */
4074: ipmx +=1;
4075: sw += weight[i];
4076: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 4077: /*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 4078: if(globpr){
1.246 brouard 4079: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4080: %11.6f %11.6f %11.6f ", \
1.242 brouard 4081: 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 4082: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 4083: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4084: llt +=ll[k]*gipmx/gsw;
4085: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
4086: }
4087: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 4088: }
1.232 brouard 4089: } /* end of wave */
4090: } /* end of individual */
4091: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4092: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4093: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4094: if(globpr==0){ /* First time we count the contributions and weights */
4095: gipmx=ipmx;
4096: gsw=sw;
4097: }
4098: return -l;
1.126 brouard 4099: }
4100:
4101:
4102: /*************** function likelione ***********/
1.292 brouard 4103: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4104: {
4105: /* This routine should help understanding what is done with
4106: the selection of individuals/waves and
4107: to check the exact contribution to the likelihood.
4108: Plotting could be done.
4109: */
4110: int k;
4111:
4112: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4113: strcpy(fileresilk,"ILK_");
1.202 brouard 4114: strcat(fileresilk,fileresu);
1.126 brouard 4115: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4116: printf("Problem with resultfile: %s\n", fileresilk);
4117: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4118: }
1.214 brouard 4119: 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");
4120: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4121: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4122: for(k=1; k<=nlstate; k++)
4123: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4124: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4125: }
4126:
1.292 brouard 4127: *fretone=(*func)(p);
1.126 brouard 4128: if(*globpri !=0){
4129: fclose(ficresilk);
1.205 brouard 4130: if (mle ==0)
4131: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4132: else if(mle >=1)
4133: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4134: 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 4135: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4136:
4137: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4138: 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 4139: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4140: }
1.207 brouard 4141: 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 4142: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4143: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4144: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4145: fflush(fichtm);
1.205 brouard 4146: }
1.126 brouard 4147: return;
4148: }
4149:
4150:
4151: /*********** Maximum Likelihood Estimation ***************/
4152:
4153: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4154: {
1.319 brouard 4155: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4156: double **xi;
4157: double fret;
4158: double fretone; /* Only one call to likelihood */
4159: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4160:
4161: #ifdef NLOPT
4162: int creturn;
4163: nlopt_opt opt;
4164: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4165: double *lb;
4166: double minf; /* the minimum objective value, upon return */
4167: double * p1; /* Shifted parameters from 0 instead of 1 */
4168: myfunc_data dinst, *d = &dinst;
4169: #endif
4170:
4171:
1.126 brouard 4172: xi=matrix(1,npar,1,npar);
4173: for (i=1;i<=npar;i++)
4174: for (j=1;j<=npar;j++)
4175: xi[i][j]=(i==j ? 1.0 : 0.0);
4176: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4177: strcpy(filerespow,"POW_");
1.126 brouard 4178: strcat(filerespow,fileres);
4179: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4180: printf("Problem with resultfile: %s\n", filerespow);
4181: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4182: }
4183: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4184: for (i=1;i<=nlstate;i++)
4185: for(j=1;j<=nlstate+ndeath;j++)
4186: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4187: fprintf(ficrespow,"\n");
1.162 brouard 4188: #ifdef POWELL
1.319 brouard 4189: #ifdef LINMINORIGINAL
4190: #else /* LINMINORIGINAL */
4191:
4192: flatdir=ivector(1,npar);
4193: for (j=1;j<=npar;j++) flatdir[j]=0;
4194: #endif /*LINMINORIGINAL */
4195:
4196: #ifdef FLATSUP
4197: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4198: /* reorganizing p by suppressing flat directions */
4199: for(i=1, jk=1; i <=nlstate; i++){
4200: for(k=1; k <=(nlstate+ndeath); k++){
4201: if (k != i) {
4202: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4203: if(flatdir[jk]==1){
4204: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4205: }
4206: for(j=1; j <=ncovmodel; j++){
4207: printf("%12.7f ",p[jk]);
4208: jk++;
4209: }
4210: printf("\n");
4211: }
4212: }
4213: }
4214: /* skipping */
4215: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4216: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4217: for(k=1; k <=(nlstate+ndeath); k++){
4218: if (k != i) {
4219: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4220: if(flatdir[jk]==1){
4221: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4222: for(j=1; j <=ncovmodel; jk++,j++){
4223: printf(" p[%d]=%12.7f",jk, p[jk]);
4224: /*q[jjk]=p[jk];*/
4225: }
4226: }else{
4227: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4228: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4229: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4230: /*q[jjk]=p[jk];*/
4231: }
4232: }
4233: printf("\n");
4234: }
4235: fflush(stdout);
4236: }
4237: }
4238: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4239: #else /* FLATSUP */
1.126 brouard 4240: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4241: #endif /* FLATSUP */
4242:
4243: #ifdef LINMINORIGINAL
4244: #else
4245: free_ivector(flatdir,1,npar);
4246: #endif /* LINMINORIGINAL*/
4247: #endif /* POWELL */
1.126 brouard 4248:
1.162 brouard 4249: #ifdef NLOPT
4250: #ifdef NEWUOA
4251: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4252: #else
4253: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4254: #endif
4255: lb=vector(0,npar-1);
4256: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4257: nlopt_set_lower_bounds(opt, lb);
4258: nlopt_set_initial_step1(opt, 0.1);
4259:
4260: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4261: d->function = func;
4262: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4263: nlopt_set_min_objective(opt, myfunc, d);
4264: nlopt_set_xtol_rel(opt, ftol);
4265: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4266: printf("nlopt failed! %d\n",creturn);
4267: }
4268: else {
4269: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4270: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4271: iter=1; /* not equal */
4272: }
4273: nlopt_destroy(opt);
4274: #endif
1.319 brouard 4275: #ifdef FLATSUP
4276: /* npared = npar -flatd/ncovmodel; */
4277: /* xired= matrix(1,npared,1,npared); */
4278: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4279: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4280: /* free_matrix(xire,1,npared,1,npared); */
4281: #else /* FLATSUP */
4282: #endif /* FLATSUP */
1.126 brouard 4283: free_matrix(xi,1,npar,1,npar);
4284: fclose(ficrespow);
1.203 brouard 4285: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4286: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4287: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4288:
4289: }
4290:
4291: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4292: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4293: {
4294: double **a,**y,*x,pd;
1.203 brouard 4295: /* double **hess; */
1.164 brouard 4296: int i, j;
1.126 brouard 4297: int *indx;
4298:
4299: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4300: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4301: void lubksb(double **a, int npar, int *indx, double b[]) ;
4302: void ludcmp(double **a, int npar, int *indx, double *d) ;
4303: double gompertz(double p[]);
1.203 brouard 4304: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4305:
4306: printf("\nCalculation of the hessian matrix. Wait...\n");
4307: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4308: for (i=1;i<=npar;i++){
1.203 brouard 4309: printf("%d-",i);fflush(stdout);
4310: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4311:
4312: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4313:
4314: /* printf(" %f ",p[i]);
4315: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4316: }
4317:
4318: for (i=1;i<=npar;i++) {
4319: for (j=1;j<=npar;j++) {
4320: if (j>i) {
1.203 brouard 4321: printf(".%d-%d",i,j);fflush(stdout);
4322: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4323: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4324:
4325: hess[j][i]=hess[i][j];
4326: /*printf(" %lf ",hess[i][j]);*/
4327: }
4328: }
4329: }
4330: printf("\n");
4331: fprintf(ficlog,"\n");
4332:
4333: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4334: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4335:
4336: a=matrix(1,npar,1,npar);
4337: y=matrix(1,npar,1,npar);
4338: x=vector(1,npar);
4339: indx=ivector(1,npar);
4340: for (i=1;i<=npar;i++)
4341: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4342: ludcmp(a,npar,indx,&pd);
4343:
4344: for (j=1;j<=npar;j++) {
4345: for (i=1;i<=npar;i++) x[i]=0;
4346: x[j]=1;
4347: lubksb(a,npar,indx,x);
4348: for (i=1;i<=npar;i++){
4349: matcov[i][j]=x[i];
4350: }
4351: }
4352:
4353: printf("\n#Hessian matrix#\n");
4354: fprintf(ficlog,"\n#Hessian matrix#\n");
4355: for (i=1;i<=npar;i++) {
4356: for (j=1;j<=npar;j++) {
1.203 brouard 4357: printf("%.6e ",hess[i][j]);
4358: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4359: }
4360: printf("\n");
4361: fprintf(ficlog,"\n");
4362: }
4363:
1.203 brouard 4364: /* printf("\n#Covariance matrix#\n"); */
4365: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4366: /* for (i=1;i<=npar;i++) { */
4367: /* for (j=1;j<=npar;j++) { */
4368: /* printf("%.6e ",matcov[i][j]); */
4369: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4370: /* } */
4371: /* printf("\n"); */
4372: /* fprintf(ficlog,"\n"); */
4373: /* } */
4374:
1.126 brouard 4375: /* Recompute Inverse */
1.203 brouard 4376: /* for (i=1;i<=npar;i++) */
4377: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4378: /* ludcmp(a,npar,indx,&pd); */
4379:
4380: /* printf("\n#Hessian matrix recomputed#\n"); */
4381:
4382: /* for (j=1;j<=npar;j++) { */
4383: /* for (i=1;i<=npar;i++) x[i]=0; */
4384: /* x[j]=1; */
4385: /* lubksb(a,npar,indx,x); */
4386: /* for (i=1;i<=npar;i++){ */
4387: /* y[i][j]=x[i]; */
4388: /* printf("%.3e ",y[i][j]); */
4389: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4390: /* } */
4391: /* printf("\n"); */
4392: /* fprintf(ficlog,"\n"); */
4393: /* } */
4394:
4395: /* Verifying the inverse matrix */
4396: #ifdef DEBUGHESS
4397: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4398:
1.203 brouard 4399: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4400: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4401:
4402: for (j=1;j<=npar;j++) {
4403: for (i=1;i<=npar;i++){
1.203 brouard 4404: printf("%.2f ",y[i][j]);
4405: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4406: }
4407: printf("\n");
4408: fprintf(ficlog,"\n");
4409: }
1.203 brouard 4410: #endif
1.126 brouard 4411:
4412: free_matrix(a,1,npar,1,npar);
4413: free_matrix(y,1,npar,1,npar);
4414: free_vector(x,1,npar);
4415: free_ivector(indx,1,npar);
1.203 brouard 4416: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4417:
4418:
4419: }
4420:
4421: /*************** hessian matrix ****************/
4422: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4423: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4424: int i;
4425: int l=1, lmax=20;
1.203 brouard 4426: double k1,k2, res, fx;
1.132 brouard 4427: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4428: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4429: int k=0,kmax=10;
4430: double l1;
4431:
4432: fx=func(x);
4433: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4434: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4435: l1=pow(10,l);
4436: delts=delt;
4437: for(k=1 ; k <kmax; k=k+1){
4438: delt = delta*(l1*k);
4439: p2[theta]=x[theta] +delt;
1.145 brouard 4440: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4441: p2[theta]=x[theta]-delt;
4442: k2=func(p2)-fx;
4443: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4444: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4445:
1.203 brouard 4446: #ifdef DEBUGHESSII
1.126 brouard 4447: 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);
4448: 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);
4449: #endif
4450: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4451: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4452: k=kmax;
4453: }
4454: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4455: k=kmax; l=lmax*10;
1.126 brouard 4456: }
4457: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4458: delts=delt;
4459: }
1.203 brouard 4460: } /* End loop k */
1.126 brouard 4461: }
4462: delti[theta]=delts;
4463: return res;
4464:
4465: }
4466:
1.203 brouard 4467: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4468: {
4469: int i;
1.164 brouard 4470: int l=1, lmax=20;
1.126 brouard 4471: double k1,k2,k3,k4,res,fx;
1.132 brouard 4472: double p2[MAXPARM+1];
1.203 brouard 4473: int k, kmax=1;
4474: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4475:
4476: int firstime=0;
1.203 brouard 4477:
1.126 brouard 4478: fx=func(x);
1.203 brouard 4479: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4480: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4481: p2[thetai]=x[thetai]+delti[thetai]*k;
4482: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4483: k1=func(p2)-fx;
4484:
1.203 brouard 4485: p2[thetai]=x[thetai]+delti[thetai]*k;
4486: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4487: k2=func(p2)-fx;
4488:
1.203 brouard 4489: p2[thetai]=x[thetai]-delti[thetai]*k;
4490: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4491: k3=func(p2)-fx;
4492:
1.203 brouard 4493: p2[thetai]=x[thetai]-delti[thetai]*k;
4494: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4495: k4=func(p2)-fx;
1.203 brouard 4496: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4497: if(k1*k2*k3*k4 <0.){
1.208 brouard 4498: firstime=1;
1.203 brouard 4499: kmax=kmax+10;
1.208 brouard 4500: }
4501: if(kmax >=10 || firstime ==1){
1.246 brouard 4502: 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);
4503: 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 4504: 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);
4505: 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);
4506: }
4507: #ifdef DEBUGHESSIJ
4508: v1=hess[thetai][thetai];
4509: v2=hess[thetaj][thetaj];
4510: cv12=res;
4511: /* Computing eigen value of Hessian matrix */
4512: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4513: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4514: if ((lc2 <0) || (lc1 <0) ){
4515: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4516: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4517: 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);
4518: 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);
4519: }
1.126 brouard 4520: #endif
4521: }
4522: return res;
4523: }
4524:
1.203 brouard 4525: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4526: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4527: /* { */
4528: /* int i; */
4529: /* int l=1, lmax=20; */
4530: /* double k1,k2,k3,k4,res,fx; */
4531: /* double p2[MAXPARM+1]; */
4532: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4533: /* int k=0,kmax=10; */
4534: /* double l1; */
4535:
4536: /* fx=func(x); */
4537: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4538: /* l1=pow(10,l); */
4539: /* delts=delt; */
4540: /* for(k=1 ; k <kmax; k=k+1){ */
4541: /* delt = delti*(l1*k); */
4542: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4543: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4544: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4545: /* k1=func(p2)-fx; */
4546:
4547: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4548: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4549: /* k2=func(p2)-fx; */
4550:
4551: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4552: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4553: /* k3=func(p2)-fx; */
4554:
4555: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4556: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4557: /* k4=func(p2)-fx; */
4558: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4559: /* #ifdef DEBUGHESSIJ */
4560: /* 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); */
4561: /* 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); */
4562: /* #endif */
4563: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4564: /* k=kmax; */
4565: /* } */
4566: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4567: /* k=kmax; l=lmax*10; */
4568: /* } */
4569: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4570: /* delts=delt; */
4571: /* } */
4572: /* } /\* End loop k *\/ */
4573: /* } */
4574: /* delti[theta]=delts; */
4575: /* return res; */
4576: /* } */
4577:
4578:
1.126 brouard 4579: /************** Inverse of matrix **************/
4580: void ludcmp(double **a, int n, int *indx, double *d)
4581: {
4582: int i,imax,j,k;
4583: double big,dum,sum,temp;
4584: double *vv;
4585:
4586: vv=vector(1,n);
4587: *d=1.0;
4588: for (i=1;i<=n;i++) {
4589: big=0.0;
4590: for (j=1;j<=n;j++)
4591: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4592: if (big == 0.0){
4593: printf(" Singular Hessian matrix at row %d:\n",i);
4594: for (j=1;j<=n;j++) {
4595: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4596: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4597: }
4598: fflush(ficlog);
4599: fclose(ficlog);
4600: nrerror("Singular matrix in routine ludcmp");
4601: }
1.126 brouard 4602: vv[i]=1.0/big;
4603: }
4604: for (j=1;j<=n;j++) {
4605: for (i=1;i<j;i++) {
4606: sum=a[i][j];
4607: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4608: a[i][j]=sum;
4609: }
4610: big=0.0;
4611: for (i=j;i<=n;i++) {
4612: sum=a[i][j];
4613: for (k=1;k<j;k++)
4614: sum -= a[i][k]*a[k][j];
4615: a[i][j]=sum;
4616: if ( (dum=vv[i]*fabs(sum)) >= big) {
4617: big=dum;
4618: imax=i;
4619: }
4620: }
4621: if (j != imax) {
4622: for (k=1;k<=n;k++) {
4623: dum=a[imax][k];
4624: a[imax][k]=a[j][k];
4625: a[j][k]=dum;
4626: }
4627: *d = -(*d);
4628: vv[imax]=vv[j];
4629: }
4630: indx[j]=imax;
4631: if (a[j][j] == 0.0) a[j][j]=TINY;
4632: if (j != n) {
4633: dum=1.0/(a[j][j]);
4634: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4635: }
4636: }
4637: free_vector(vv,1,n); /* Doesn't work */
4638: ;
4639: }
4640:
4641: void lubksb(double **a, int n, int *indx, double b[])
4642: {
4643: int i,ii=0,ip,j;
4644: double sum;
4645:
4646: for (i=1;i<=n;i++) {
4647: ip=indx[i];
4648: sum=b[ip];
4649: b[ip]=b[i];
4650: if (ii)
4651: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4652: else if (sum) ii=i;
4653: b[i]=sum;
4654: }
4655: for (i=n;i>=1;i--) {
4656: sum=b[i];
4657: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4658: b[i]=sum/a[i][i];
4659: }
4660: }
4661:
4662: void pstamp(FILE *fichier)
4663: {
1.196 brouard 4664: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4665: }
4666:
1.297 brouard 4667: void date2dmy(double date,double *day, double *month, double *year){
4668: double yp=0., yp1=0., yp2=0.;
4669:
4670: yp1=modf(date,&yp);/* extracts integral of date in yp and
4671: fractional in yp1 */
4672: *year=yp;
4673: yp2=modf((yp1*12),&yp);
4674: *month=yp;
4675: yp1=modf((yp2*30.5),&yp);
4676: *day=yp;
4677: if(*day==0) *day=1;
4678: if(*month==0) *month=1;
4679: }
4680:
1.253 brouard 4681:
4682:
1.126 brouard 4683: /************ Frequencies ********************/
1.251 brouard 4684: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4685: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4686: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4687: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4688:
1.265 brouard 4689: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4690: int iind=0, iage=0;
4691: int mi; /* Effective wave */
4692: int first;
4693: double ***freq; /* Frequencies */
1.268 brouard 4694: 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 */
4695: 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 4696: double *meanq, *stdq, *idq;
1.226 brouard 4697: double **meanqt;
4698: double *pp, **prop, *posprop, *pospropt;
4699: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4700: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4701: double agebegin, ageend;
4702:
4703: pp=vector(1,nlstate);
1.251 brouard 4704: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4705: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4706: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4707: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4708: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4709: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4710: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4711: meanqt=matrix(1,lastpass,1,nqtveff);
4712: strcpy(fileresp,"P_");
4713: strcat(fileresp,fileresu);
4714: /*strcat(fileresphtm,fileresu);*/
4715: if((ficresp=fopen(fileresp,"w"))==NULL) {
4716: printf("Problem with prevalence resultfile: %s\n", fileresp);
4717: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4718: exit(0);
4719: }
1.240 brouard 4720:
1.226 brouard 4721: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4722: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4723: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4724: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4725: fflush(ficlog);
4726: exit(70);
4727: }
4728: else{
4729: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4730: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4731: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4732: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4733: }
1.319 brouard 4734: 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 4735:
1.226 brouard 4736: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4737: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4738: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4739: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4740: fflush(ficlog);
4741: exit(70);
1.240 brouard 4742: } else{
1.226 brouard 4743: 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 4744: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4745: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4746: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4747: }
1.319 brouard 4748: 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 4749:
1.253 brouard 4750: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4751: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4752: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4753: j1=0;
1.126 brouard 4754:
1.227 brouard 4755: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4756: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4757: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4758:
4759:
1.226 brouard 4760: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4761: reference=low_education V1=0,V2=0
4762: med_educ V1=1 V2=0,
4763: high_educ V1=0 V2=1
4764: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4765: */
1.249 brouard 4766: dateintsum=0;
4767: k2cpt=0;
4768:
1.253 brouard 4769: if(cptcoveff == 0 )
1.265 brouard 4770: nl=1; /* Constant and age model only */
1.253 brouard 4771: else
4772: nl=2;
1.265 brouard 4773:
4774: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4775: /* Loop on nj=1 or 2 if dummy covariates j!=0
4776: * Loop on j1(1 to 2**cptcoveff) covariate combination
4777: * freq[s1][s2][iage] =0.
4778: * Loop on iind
4779: * ++freq[s1][s2][iage] weighted
4780: * end iind
4781: * if covariate and j!0
4782: * headers Variable on one line
4783: * endif cov j!=0
4784: * header of frequency table by age
4785: * Loop on age
4786: * pp[s1]+=freq[s1][s2][iage] weighted
4787: * pos+=freq[s1][s2][iage] weighted
4788: * Loop on s1 initial state
4789: * fprintf(ficresp
4790: * end s1
4791: * end age
4792: * if j!=0 computes starting values
4793: * end compute starting values
4794: * end j1
4795: * end nl
4796: */
1.253 brouard 4797: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4798: if(nj==1)
4799: j=0; /* First pass for the constant */
1.265 brouard 4800: else{
1.253 brouard 4801: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4802: }
1.251 brouard 4803: first=1;
1.265 brouard 4804: 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 4805: posproptt=0.;
4806: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4807: scanf("%d", i);*/
4808: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4809: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4810: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4811: freq[i][s2][m]=0;
1.251 brouard 4812:
4813: for (i=1; i<=nlstate; i++) {
1.240 brouard 4814: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4815: prop[i][m]=0;
4816: posprop[i]=0;
4817: pospropt[i]=0;
4818: }
1.283 brouard 4819: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4820: idq[z1]=0.;
4821: meanq[z1]=0.;
4822: stdq[z1]=0.;
1.283 brouard 4823: }
4824: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4825: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4826: /* meanqt[m][z1]=0.; */
4827: /* } */
4828: /* } */
1.251 brouard 4829: /* dateintsum=0; */
4830: /* k2cpt=0; */
4831:
1.265 brouard 4832: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4833: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4834: bool=1;
4835: if(j !=0){
4836: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4837: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4838: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4839: /* if(Tvaraff[z1] ==-20){ */
4840: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4841: /* }else if(Tvaraff[z1] ==-10){ */
4842: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4843: /* }else */
4844: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4845: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4846: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4847: /* 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",
4848: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4849: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4850: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4851: } /* Onlyf fixed */
4852: } /* end z1 */
4853: } /* cptcovn > 0 */
4854: } /* end any */
4855: }/* end j==0 */
1.265 brouard 4856: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4857: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4858: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4859: m=mw[mi][iind];
4860: if(j!=0){
4861: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4862: for (z1=1; z1<=cptcoveff; z1++) {
4863: if( Fixed[Tmodelind[z1]]==1){
4864: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4865: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4866: value is -1, we don't select. It differs from the
4867: constant and age model which counts them. */
4868: bool=0; /* not selected */
4869: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4870: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4871: bool=0;
4872: }
4873: }
4874: }
4875: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4876: } /* end j==0 */
4877: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4878: if(bool==1){ /*Selected */
1.251 brouard 4879: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4880: and mw[mi+1][iind]. dh depends on stepm. */
4881: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4882: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4883: if(m >=firstpass && m <=lastpass){
4884: k2=anint[m][iind]+(mint[m][iind]/12.);
4885: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4886: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4887: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4888: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4889: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4890: if (m<lastpass) {
4891: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4892: /* 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]); */
4893: if(s[m][iind]==-1)
4894: 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.));
4895: 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 4896: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
4897: if(!isnan(covar[ncovcol+z1][iind])){
4898: idq[z1]=idq[z1]+weight[iind];
4899: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4900: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
4901: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4902: }
1.284 brouard 4903: }
1.251 brouard 4904: /* if((int)agev[m][iind] == 55) */
4905: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4906: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4907: 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 4908: }
1.251 brouard 4909: } /* end if between passes */
4910: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4911: dateintsum=dateintsum+k2; /* on all covariates ?*/
4912: k2cpt++;
4913: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4914: }
1.251 brouard 4915: }else{
4916: bool=1;
4917: }/* end bool 2 */
4918: } /* end m */
1.284 brouard 4919: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4920: /* idq[z1]=idq[z1]+weight[iind]; */
4921: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4922: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4923: /* } */
1.251 brouard 4924: } /* end bool */
4925: } /* end iind = 1 to imx */
1.319 brouard 4926: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 4927: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4928:
4929:
4930: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4931: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4932: pstamp(ficresp);
1.251 brouard 4933: if (cptcoveff>0 && j!=0){
1.265 brouard 4934: pstamp(ficresp);
1.251 brouard 4935: printf( "\n#********** Variable ");
4936: fprintf(ficresp, "\n#********** Variable ");
4937: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4938: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4939: fprintf(ficlog, "\n#********** Variable ");
4940: for (z1=1; z1<=cptcoveff; z1++){
4941: if(!FixedV[Tvaraff[z1]]){
4942: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4943: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4944: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4945: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4946: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4947: }else{
1.251 brouard 4948: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4949: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4950: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4951: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4952: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4953: }
4954: }
4955: printf( "**********\n#");
4956: fprintf(ficresp, "**********\n#");
4957: fprintf(ficresphtm, "**********</h3>\n");
4958: fprintf(ficresphtmfr, "**********</h3>\n");
4959: fprintf(ficlog, "**********\n");
4960: }
1.284 brouard 4961: /*
4962: Printing means of quantitative variables if any
4963: */
4964: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 4965: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 4966: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 4967: if(weightopt==1){
4968: printf(" Weighted mean and standard deviation of");
4969: fprintf(ficlog," Weighted mean and standard deviation of");
4970: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4971: }
1.311 brouard 4972: /* mu = \frac{w x}{\sum w}
4973: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
4974: */
4975: 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]));
4976: 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]));
4977: 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 4978: }
4979: /* for (z1=1; z1<= nqtveff; z1++) { */
4980: /* for(m=1;m<=lastpass;m++){ */
4981: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4982: /* } */
4983: /* } */
1.283 brouard 4984:
1.251 brouard 4985: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4986: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4987: fprintf(ficresp, " Age");
4988: 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 4989: for(i=1; i<=nlstate;i++) {
1.265 brouard 4990: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4991: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4992: }
1.265 brouard 4993: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4994: fprintf(ficresphtm, "\n");
4995:
4996: /* Header of frequency table by age */
4997: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4998: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4999: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5000: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5001: if(s2!=0 && m!=0)
5002: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5003: }
1.226 brouard 5004: }
1.251 brouard 5005: fprintf(ficresphtmfr, "\n");
5006:
5007: /* For each age */
5008: for(iage=iagemin; iage <= iagemax+3; iage++){
5009: fprintf(ficresphtm,"<tr>");
5010: if(iage==iagemax+1){
5011: fprintf(ficlog,"1");
5012: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5013: }else if(iage==iagemax+2){
5014: fprintf(ficlog,"0");
5015: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5016: }else if(iage==iagemax+3){
5017: fprintf(ficlog,"Total");
5018: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5019: }else{
1.240 brouard 5020: if(first==1){
1.251 brouard 5021: first=0;
5022: printf("See log file for details...\n");
5023: }
5024: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5025: fprintf(ficlog,"Age %d", iage);
5026: }
1.265 brouard 5027: for(s1=1; s1 <=nlstate ; s1++){
5028: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5029: pp[s1] += freq[s1][m][iage];
1.251 brouard 5030: }
1.265 brouard 5031: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5032: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5033: pos += freq[s1][m][iage];
5034: if(pp[s1]>=1.e-10){
1.251 brouard 5035: if(first==1){
1.265 brouard 5036: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5037: }
1.265 brouard 5038: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5039: }else{
5040: if(first==1)
1.265 brouard 5041: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5042: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5043: }
5044: }
5045:
1.265 brouard 5046: for(s1=1; s1 <=nlstate ; s1++){
5047: /* posprop[s1]=0; */
5048: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5049: pp[s1] += freq[s1][m][iage];
5050: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5051:
5052: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5053: pos += pp[s1]; /* pos is the total number of transitions until this age */
5054: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5055: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5056: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5057: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5058: }
5059:
5060: /* Writing ficresp */
5061: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5062: if( iage <= iagemax){
5063: fprintf(ficresp," %d",iage);
5064: }
5065: }else if( nj==2){
5066: if( iage <= iagemax){
5067: fprintf(ficresp," %d",iage);
5068: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
5069: }
1.240 brouard 5070: }
1.265 brouard 5071: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5072: if(pos>=1.e-5){
1.251 brouard 5073: if(first==1)
1.265 brouard 5074: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5075: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5076: }else{
5077: if(first==1)
1.265 brouard 5078: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5079: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5080: }
5081: if( iage <= iagemax){
5082: if(pos>=1.e-5){
1.265 brouard 5083: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5084: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5085: }else if( nj==2){
5086: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5087: }
5088: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5089: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5090: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5091: } else{
5092: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
5093: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5094: }
1.240 brouard 5095: }
1.265 brouard 5096: pospropt[s1] +=posprop[s1];
5097: } /* end loop s1 */
1.251 brouard 5098: /* pospropt=0.; */
1.265 brouard 5099: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5100: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5101: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5102: if(first==1){
1.265 brouard 5103: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5104: }
1.265 brouard 5105: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5106: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5107: }
1.265 brouard 5108: if(s1!=0 && m!=0)
5109: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5110: }
1.265 brouard 5111: } /* end loop s1 */
1.251 brouard 5112: posproptt=0.;
1.265 brouard 5113: for(s1=1; s1 <=nlstate; s1++){
5114: posproptt += pospropt[s1];
1.251 brouard 5115: }
5116: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5117: fprintf(ficresphtm,"</tr>\n");
5118: if((cptcoveff==0 && nj==1)|| nj==2 ) {
5119: if(iage <= iagemax)
5120: fprintf(ficresp,"\n");
1.240 brouard 5121: }
1.251 brouard 5122: if(first==1)
5123: printf("Others in log...\n");
5124: fprintf(ficlog,"\n");
5125: } /* end loop age iage */
1.265 brouard 5126:
1.251 brouard 5127: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5128: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5129: if(posproptt < 1.e-5){
1.265 brouard 5130: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5131: }else{
1.265 brouard 5132: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5133: }
1.226 brouard 5134: }
1.251 brouard 5135: fprintf(ficresphtm,"</tr>\n");
5136: fprintf(ficresphtm,"</table>\n");
5137: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5138: if(posproptt < 1.e-5){
1.251 brouard 5139: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5140: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5141: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5142: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5143: invalidvarcomb[j1]=1;
1.226 brouard 5144: }else{
1.251 brouard 5145: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
5146: invalidvarcomb[j1]=0;
1.226 brouard 5147: }
1.251 brouard 5148: fprintf(ficresphtmfr,"</table>\n");
5149: fprintf(ficlog,"\n");
5150: if(j!=0){
5151: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5152: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5153: for(k=1; k <=(nlstate+ndeath); k++){
5154: if (k != i) {
1.265 brouard 5155: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5156: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5157: if(j1==1){ /* All dummy covariates to zero */
5158: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5159: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5160: printf("%d%d ",i,k);
5161: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5162: 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]));
5163: 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]));
5164: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5165: }
1.253 brouard 5166: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5167: for(iage=iagemin; iage <= iagemax+3; iage++){
5168: x[iage]= (double)iage;
5169: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5170: /* 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 5171: }
1.268 brouard 5172: /* Some are not finite, but linreg will ignore these ages */
5173: no=0;
1.253 brouard 5174: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5175: pstart[s1]=b;
5176: pstart[s1-1]=a;
1.252 brouard 5177: }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 */
5178: 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]);
5179: 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 5180: 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 5181: printf("%d%d ",i,k);
5182: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5183: 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 5184: }else{ /* Other cases, like quantitative fixed or varying covariates */
5185: ;
5186: }
5187: /* printf("%12.7f )", param[i][jj][k]); */
5188: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5189: s1++;
1.251 brouard 5190: } /* end jj */
5191: } /* end k!= i */
5192: } /* end k */
1.265 brouard 5193: } /* end i, s1 */
1.251 brouard 5194: } /* end j !=0 */
5195: } /* end selected combination of covariate j1 */
5196: if(j==0){ /* We can estimate starting values from the occurences in each case */
5197: printf("#Freqsummary: Starting values for the constants:\n");
5198: fprintf(ficlog,"\n");
1.265 brouard 5199: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5200: for(k=1; k <=(nlstate+ndeath); k++){
5201: if (k != i) {
5202: printf("%d%d ",i,k);
5203: fprintf(ficlog,"%d%d ",i,k);
5204: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5205: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5206: if(jj==1){ /* Age has to be done */
1.265 brouard 5207: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5208: 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]));
5209: 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 5210: }
5211: /* printf("%12.7f )", param[i][jj][k]); */
5212: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5213: s1++;
1.250 brouard 5214: }
1.251 brouard 5215: printf("\n");
5216: fprintf(ficlog,"\n");
1.250 brouard 5217: }
5218: }
1.284 brouard 5219: } /* end of state i */
1.251 brouard 5220: printf("#Freqsummary\n");
5221: fprintf(ficlog,"\n");
1.265 brouard 5222: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5223: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5224: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5225: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5226: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5227: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5228: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5229: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5230: /* } */
5231: }
1.265 brouard 5232: } /* end loop s1 */
1.251 brouard 5233:
5234: printf("\n");
5235: fprintf(ficlog,"\n");
5236: } /* end j=0 */
1.249 brouard 5237: } /* end j */
1.252 brouard 5238:
1.253 brouard 5239: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5240: for(i=1, jk=1; i <=nlstate; i++){
5241: for(j=1; j <=nlstate+ndeath; j++){
5242: if(j!=i){
5243: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5244: printf("%1d%1d",i,j);
5245: fprintf(ficparo,"%1d%1d",i,j);
5246: for(k=1; k<=ncovmodel;k++){
5247: /* printf(" %lf",param[i][j][k]); */
5248: /* fprintf(ficparo," %lf",param[i][j][k]); */
5249: p[jk]=pstart[jk];
5250: printf(" %f ",pstart[jk]);
5251: fprintf(ficparo," %f ",pstart[jk]);
5252: jk++;
5253: }
5254: printf("\n");
5255: fprintf(ficparo,"\n");
5256: }
5257: }
5258: }
5259: } /* end mle=-2 */
1.226 brouard 5260: dateintmean=dateintsum/k2cpt;
1.296 brouard 5261: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5262:
1.226 brouard 5263: fclose(ficresp);
5264: fclose(ficresphtm);
5265: fclose(ficresphtmfr);
1.283 brouard 5266: free_vector(idq,1,nqfveff);
1.226 brouard 5267: free_vector(meanq,1,nqfveff);
1.284 brouard 5268: free_vector(stdq,1,nqfveff);
1.226 brouard 5269: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5270: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5271: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5272: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5273: free_vector(pospropt,1,nlstate);
5274: free_vector(posprop,1,nlstate);
1.251 brouard 5275: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5276: free_vector(pp,1,nlstate);
5277: /* End of freqsummary */
5278: }
1.126 brouard 5279:
1.268 brouard 5280: /* Simple linear regression */
5281: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5282:
5283: /* y=a+bx regression */
5284: double sumx = 0.0; /* sum of x */
5285: double sumx2 = 0.0; /* sum of x**2 */
5286: double sumxy = 0.0; /* sum of x * y */
5287: double sumy = 0.0; /* sum of y */
5288: double sumy2 = 0.0; /* sum of y**2 */
5289: double sume2 = 0.0; /* sum of square or residuals */
5290: double yhat;
5291:
5292: double denom=0;
5293: int i;
5294: int ne=*no;
5295:
5296: for ( i=ifi, ne=0;i<=ila;i++) {
5297: if(!isfinite(x[i]) || !isfinite(y[i])){
5298: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5299: continue;
5300: }
5301: ne=ne+1;
5302: sumx += x[i];
5303: sumx2 += x[i]*x[i];
5304: sumxy += x[i] * y[i];
5305: sumy += y[i];
5306: sumy2 += y[i]*y[i];
5307: denom = (ne * sumx2 - sumx*sumx);
5308: /* 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); */
5309: }
5310:
5311: denom = (ne * sumx2 - sumx*sumx);
5312: if (denom == 0) {
5313: // vertical, slope m is infinity
5314: *b = INFINITY;
5315: *a = 0;
5316: if (r) *r = 0;
5317: return 1;
5318: }
5319:
5320: *b = (ne * sumxy - sumx * sumy) / denom;
5321: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5322: if (r!=NULL) {
5323: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5324: sqrt((sumx2 - sumx*sumx/ne) *
5325: (sumy2 - sumy*sumy/ne));
5326: }
5327: *no=ne;
5328: for ( i=ifi, ne=0;i<=ila;i++) {
5329: if(!isfinite(x[i]) || !isfinite(y[i])){
5330: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5331: continue;
5332: }
5333: ne=ne+1;
5334: yhat = y[i] - *a -*b* x[i];
5335: sume2 += yhat * yhat ;
5336:
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: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5341: *sa= *sb * sqrt(sumx2/ne);
5342:
5343: return 0;
5344: }
5345:
1.126 brouard 5346: /************ Prevalence ********************/
1.227 brouard 5347: 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)
5348: {
5349: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5350: in each health status at the date of interview (if between dateprev1 and dateprev2).
5351: We still use firstpass and lastpass as another selection.
5352: */
1.126 brouard 5353:
1.227 brouard 5354: int i, m, jk, j1, bool, z1,j, iv;
5355: int mi; /* Effective wave */
5356: int iage;
5357: double agebegin, ageend;
5358:
5359: double **prop;
5360: double posprop;
5361: double y2; /* in fractional years */
5362: int iagemin, iagemax;
5363: int first; /** to stop verbosity which is redirected to log file */
5364:
5365: iagemin= (int) agemin;
5366: iagemax= (int) agemax;
5367: /*pp=vector(1,nlstate);*/
1.251 brouard 5368: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5369: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5370: j1=0;
1.222 brouard 5371:
1.227 brouard 5372: /*j=cptcoveff;*/
5373: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5374:
1.288 brouard 5375: first=0;
1.227 brouard 5376: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5377: for (i=1; i<=nlstate; i++)
1.251 brouard 5378: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5379: prop[i][iage]=0.0;
5380: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5381: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5382: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5383:
5384: for (i=1; i<=imx; i++) { /* Each individual */
5385: bool=1;
5386: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5387: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5388: m=mw[mi][i];
5389: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5390: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5391: for (z1=1; z1<=cptcoveff; z1++){
5392: if( Fixed[Tmodelind[z1]]==1){
5393: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5394: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5395: bool=0;
5396: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5397: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5398: bool=0;
5399: }
5400: }
5401: if(bool==1){ /* Otherwise we skip that wave/person */
5402: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5403: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5404: if(m >=firstpass && m <=lastpass){
5405: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5406: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5407: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5408: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5409: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5410: 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);
5411: exit(1);
5412: }
5413: if (s[m][i]>0 && s[m][i]<=nlstate) {
5414: /*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]]);*/
5415: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5416: prop[s[m][i]][iagemax+3] += weight[i];
5417: } /* end valid statuses */
5418: } /* end selection of dates */
5419: } /* end selection of waves */
5420: } /* end bool */
5421: } /* end wave */
5422: } /* end individual */
5423: for(i=iagemin; i <= iagemax+3; i++){
5424: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5425: posprop += prop[jk][i];
5426: }
5427:
5428: for(jk=1; jk <=nlstate ; jk++){
5429: if( i <= iagemax){
5430: if(posprop>=1.e-5){
5431: probs[i][jk][j1]= prop[jk][i]/posprop;
5432: } else{
1.288 brouard 5433: if(!first){
5434: first=1;
1.266 brouard 5435: 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]);
5436: }else{
1.288 brouard 5437: 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 5438: }
5439: }
5440: }
5441: }/* end jk */
5442: }/* end i */
1.222 brouard 5443: /*} *//* end i1 */
1.227 brouard 5444: } /* end j1 */
1.222 brouard 5445:
1.227 brouard 5446: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5447: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5448: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5449: } /* End of prevalence */
1.126 brouard 5450:
5451: /************* Waves Concatenation ***************/
5452:
5453: 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)
5454: {
1.298 brouard 5455: /* 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 5456: Death is a valid wave (if date is known).
5457: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5458: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5459: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5460: */
1.126 brouard 5461:
1.224 brouard 5462: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5463: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5464: double sum=0., jmean=0.;*/
1.224 brouard 5465: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5466: int j, k=0,jk, ju, jl;
5467: double sum=0.;
5468: first=0;
1.214 brouard 5469: firstwo=0;
1.217 brouard 5470: firsthree=0;
1.218 brouard 5471: firstfour=0;
1.164 brouard 5472: jmin=100000;
1.126 brouard 5473: jmax=-1;
5474: jmean=0.;
1.224 brouard 5475:
5476: /* Treating live states */
1.214 brouard 5477: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5478: mi=0; /* First valid wave */
1.227 brouard 5479: mli=0; /* Last valid wave */
1.309 brouard 5480: m=firstpass; /* Loop on waves */
5481: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5482: 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 */
5483: mli=m-1;/* mw[++mi][i]=m-1; */
5484: }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 5485: 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 5486: mli=m;
1.224 brouard 5487: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5488: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5489: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5490: }
1.309 brouard 5491: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5492: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5493: break;
1.224 brouard 5494: #else
1.317 brouard 5495: 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 5496: if(firsthree == 0){
1.302 brouard 5497: 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 5498: firsthree=1;
1.317 brouard 5499: }else if(firsthree >=1 && firsthree < 10){
5500: 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);
5501: firsthree++;
5502: }else if(firsthree == 10){
5503: printf("Information, too many Information flags: no more reported to log either\n");
5504: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5505: firsthree++;
5506: }else{
5507: firsthree++;
1.227 brouard 5508: }
1.309 brouard 5509: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5510: mli=m;
5511: }
5512: if(s[m][i]==-2){ /* Vital status is really unknown */
5513: nbwarn++;
1.309 brouard 5514: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5515: 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);
5516: 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);
5517: }
5518: break;
5519: }
5520: break;
1.224 brouard 5521: #endif
1.227 brouard 5522: }/* End m >= lastpass */
1.126 brouard 5523: }/* end while */
1.224 brouard 5524:
1.227 brouard 5525: /* 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 5526: /* After last pass */
1.224 brouard 5527: /* Treating death states */
1.214 brouard 5528: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5529: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5530: /* } */
1.126 brouard 5531: mi++; /* Death is another wave */
5532: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5533: /* Only death is a correct wave */
1.126 brouard 5534: mw[mi][i]=m;
1.257 brouard 5535: } /* else not in a death state */
1.224 brouard 5536: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5537: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5538: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5539: 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 5540: nbwarn++;
5541: if(firstfiv==0){
1.309 brouard 5542: 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 5543: firstfiv=1;
5544: }else{
1.309 brouard 5545: 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 5546: }
1.309 brouard 5547: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5548: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5549: nberr++;
5550: if(firstwo==0){
1.309 brouard 5551: 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 5552: firstwo=1;
5553: }
1.309 brouard 5554: 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 5555: }
1.257 brouard 5556: }else{ /* if date of interview is unknown */
1.227 brouard 5557: /* death is known but not confirmed by death status at any wave */
5558: if(firstfour==0){
1.309 brouard 5559: 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 5560: firstfour=1;
5561: }
1.309 brouard 5562: 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 5563: }
1.224 brouard 5564: } /* end if date of death is known */
5565: #endif
1.309 brouard 5566: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5567: /* wav[i]=mw[mi][i]; */
1.126 brouard 5568: if(mi==0){
5569: nbwarn++;
5570: if(first==0){
1.227 brouard 5571: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5572: first=1;
1.126 brouard 5573: }
5574: if(first==1){
1.227 brouard 5575: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5576: }
5577: } /* end mi==0 */
5578: } /* End individuals */
1.214 brouard 5579: /* wav and mw are no more changed */
1.223 brouard 5580:
1.317 brouard 5581: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5582: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5583:
5584:
1.126 brouard 5585: for(i=1; i<=imx; i++){
5586: for(mi=1; mi<wav[i];mi++){
5587: if (stepm <=0)
1.227 brouard 5588: dh[mi][i]=1;
1.126 brouard 5589: else{
1.260 brouard 5590: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5591: if (agedc[i] < 2*AGESUP) {
5592: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5593: if(j==0) j=1; /* Survives at least one month after exam */
5594: else if(j<0){
5595: nberr++;
5596: 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]);
5597: j=1; /* Temporary Dangerous patch */
5598: 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);
5599: 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]);
5600: 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);
5601: }
5602: k=k+1;
5603: if (j >= jmax){
5604: jmax=j;
5605: ijmax=i;
5606: }
5607: if (j <= jmin){
5608: jmin=j;
5609: ijmin=i;
5610: }
5611: sum=sum+j;
5612: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5613: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5614: }
5615: }
5616: else{
5617: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5618: /* 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 5619:
1.227 brouard 5620: k=k+1;
5621: if (j >= jmax) {
5622: jmax=j;
5623: ijmax=i;
5624: }
5625: else if (j <= jmin){
5626: jmin=j;
5627: ijmin=i;
5628: }
5629: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5630: /*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]);*/
5631: if(j<0){
5632: nberr++;
5633: 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]);
5634: 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]);
5635: }
5636: sum=sum+j;
5637: }
5638: jk= j/stepm;
5639: jl= j -jk*stepm;
5640: ju= j -(jk+1)*stepm;
5641: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5642: if(jl==0){
5643: dh[mi][i]=jk;
5644: bh[mi][i]=0;
5645: }else{ /* We want a negative bias in order to only have interpolation ie
5646: * to avoid the price of an extra matrix product in likelihood */
5647: dh[mi][i]=jk+1;
5648: bh[mi][i]=ju;
5649: }
5650: }else{
5651: if(jl <= -ju){
5652: dh[mi][i]=jk;
5653: bh[mi][i]=jl; /* bias is positive if real duration
5654: * is higher than the multiple of stepm and negative otherwise.
5655: */
5656: }
5657: else{
5658: dh[mi][i]=jk+1;
5659: bh[mi][i]=ju;
5660: }
5661: if(dh[mi][i]==0){
5662: dh[mi][i]=1; /* At least one step */
5663: bh[mi][i]=ju; /* At least one step */
5664: /* 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);*/
5665: }
5666: } /* end if mle */
1.126 brouard 5667: }
5668: } /* end wave */
5669: }
5670: jmean=sum/k;
5671: 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 5672: 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 5673: }
1.126 brouard 5674:
5675: /*********** Tricode ****************************/
1.220 brouard 5676: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5677: {
5678: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5679: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5680: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5681: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5682: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5683: */
1.130 brouard 5684:
1.242 brouard 5685: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5686: int modmaxcovj=0; /* Modality max of covariates j */
5687: int cptcode=0; /* Modality max of covariates j */
5688: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5689:
5690:
1.242 brouard 5691: /* cptcoveff=0; */
5692: /* *cptcov=0; */
1.126 brouard 5693:
1.242 brouard 5694: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5695: for (k=1; k <= maxncov; k++)
5696: for(j=1; j<=2; j++)
5697: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5698:
1.242 brouard 5699: /* Loop on covariates without age and products and no quantitative variable */
5700: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5701: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5702: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5703: switch(Fixed[k]) {
5704: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5705: modmaxcovj=0;
5706: modmincovj=0;
1.242 brouard 5707: 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*/
5708: ij=(int)(covar[Tvar[k]][i]);
5709: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5710: * If product of Vn*Vm, still boolean *:
5711: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5712: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5713: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5714: modality of the nth covariate of individual i. */
5715: if (ij > modmaxcovj)
5716: modmaxcovj=ij;
5717: else if (ij < modmincovj)
5718: modmincovj=ij;
1.287 brouard 5719: if (ij <0 || ij >1 ){
1.311 brouard 5720: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5721: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5722: fflush(ficlog);
5723: exit(1);
1.287 brouard 5724: }
5725: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5726: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5727: exit(1);
5728: }else
5729: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5730: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5731: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5732: /* getting the maximum value of the modality of the covariate
5733: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5734: female ies 1, then modmaxcovj=1.
5735: */
5736: } /* end for loop on individuals i */
5737: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5738: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5739: cptcode=modmaxcovj;
5740: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5741: /*for (i=0; i<=cptcode; i++) {*/
5742: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5743: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5744: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5745: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5746: if( j != -1){
5747: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5748: covariate for which somebody answered excluding
5749: undefined. Usually 2: 0 and 1. */
5750: }
5751: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5752: covariate for which somebody answered including
5753: undefined. Usually 3: -1, 0 and 1. */
5754: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5755: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5756: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5757:
1.242 brouard 5758: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5759: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5760: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5761: /* modmincovj=3; modmaxcovj = 7; */
5762: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5763: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5764: /* defining two dummy variables: variables V1_1 and V1_2.*/
5765: /* nbcode[Tvar[j]][ij]=k; */
5766: /* nbcode[Tvar[j]][1]=0; */
5767: /* nbcode[Tvar[j]][2]=1; */
5768: /* nbcode[Tvar[j]][3]=2; */
5769: /* To be continued (not working yet). */
5770: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5771:
5772: /* 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*/
5773: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5774: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5775: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5776: /*, could be restored in the future */
5777: 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 5778: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5779: break;
5780: }
5781: ij++;
1.287 brouard 5782: 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 5783: cptcode = ij; /* New max modality for covar j */
5784: } /* end of loop on modality i=-1 to 1 or more */
5785: break;
5786: case 1: /* Testing on varying covariate, could be simple and
5787: * should look at waves or product of fixed *
5788: * varying. No time to test -1, assuming 0 and 1 only */
5789: ij=0;
5790: for(i=0; i<=1;i++){
5791: nbcode[Tvar[k]][++ij]=i;
5792: }
5793: break;
5794: default:
5795: break;
5796: } /* end switch */
5797: } /* end dummy test */
1.311 brouard 5798: if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5799: 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*/
5800: if(isnan(covar[Tvar[k]][i])){
5801: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5802: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5803: fflush(ficlog);
5804: exit(1);
5805: }
5806: }
5807: }
1.287 brouard 5808: } /* 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 5809:
5810: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5811: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5812: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5813: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5814: 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 */
5815: 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 */
5816: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5817: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5818:
5819: ij=0;
5820: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5821: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5822: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5823: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5824: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5825: /* If product not in single variable we don't print results */
5826: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5827: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5828: 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*/
5829: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5830: 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 */
5831: if(Fixed[k]!=0)
5832: anyvaryingduminmodel=1;
5833: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5834: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5835: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5836: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5837: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5838: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5839: }
5840: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5841: /* ij--; */
5842: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5843: *cptcov=ij; /*Number of total real effective covariates: effective
5844: * because they can be excluded from the model and real
5845: * if in the model but excluded because missing values, but how to get k from ij?*/
5846: for(j=ij+1; j<= cptcovt; j++){
5847: Tvaraff[j]=0;
5848: Tmodelind[j]=0;
5849: }
5850: for(j=ntveff+1; j<= cptcovt; j++){
5851: TmodelInvind[j]=0;
5852: }
5853: /* To be sorted */
5854: ;
5855: }
1.126 brouard 5856:
1.145 brouard 5857:
1.126 brouard 5858: /*********** Health Expectancies ****************/
5859:
1.235 brouard 5860: 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 5861:
5862: {
5863: /* Health expectancies, no variances */
1.164 brouard 5864: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5865: int nhstepma, nstepma; /* Decreasing with age */
5866: double age, agelim, hf;
5867: double ***p3mat;
5868: double eip;
5869:
1.238 brouard 5870: /* pstamp(ficreseij); */
1.126 brouard 5871: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5872: fprintf(ficreseij,"# Age");
5873: for(i=1; i<=nlstate;i++){
5874: for(j=1; j<=nlstate;j++){
5875: fprintf(ficreseij," e%1d%1d ",i,j);
5876: }
5877: fprintf(ficreseij," e%1d. ",i);
5878: }
5879: fprintf(ficreseij,"\n");
5880:
5881:
5882: if(estepm < stepm){
5883: printf ("Problem %d lower than %d\n",estepm, stepm);
5884: }
5885: else hstepm=estepm;
5886: /* We compute the life expectancy from trapezoids spaced every estepm months
5887: * This is mainly to measure the difference between two models: for example
5888: * if stepm=24 months pijx are given only every 2 years and by summing them
5889: * we are calculating an estimate of the Life Expectancy assuming a linear
5890: * progression in between and thus overestimating or underestimating according
5891: * to the curvature of the survival function. If, for the same date, we
5892: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5893: * to compare the new estimate of Life expectancy with the same linear
5894: * hypothesis. A more precise result, taking into account a more precise
5895: * curvature will be obtained if estepm is as small as stepm. */
5896:
5897: /* For example we decided to compute the life expectancy with the smallest unit */
5898: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5899: nhstepm is the number of hstepm from age to agelim
5900: nstepm is the number of stepm from age to agelin.
1.270 brouard 5901: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5902: and note for a fixed period like estepm months */
5903: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5904: survival function given by stepm (the optimization length). Unfortunately it
5905: means that if the survival funtion is printed only each two years of age and if
5906: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5907: results. So we changed our mind and took the option of the best precision.
5908: */
5909: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5910:
5911: agelim=AGESUP;
5912: /* If stepm=6 months */
5913: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5914: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5915:
5916: /* nhstepm age range expressed in number of stepm */
5917: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5918: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5919: /* if (stepm >= YEARM) hstepm=1;*/
5920: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5921: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5922:
5923: for (age=bage; age<=fage; age ++){
5924: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5925: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5926: /* if (stepm >= YEARM) hstepm=1;*/
5927: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5928:
5929: /* If stepm=6 months */
5930: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5931: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5932:
1.235 brouard 5933: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5934:
5935: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5936:
5937: printf("%d|",(int)age);fflush(stdout);
5938: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5939:
5940: /* Computing expectancies */
5941: for(i=1; i<=nlstate;i++)
5942: for(j=1; j<=nlstate;j++)
5943: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5944: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5945:
5946: /* 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]);*/
5947:
5948: }
5949:
5950: fprintf(ficreseij,"%3.0f",age );
5951: for(i=1; i<=nlstate;i++){
5952: eip=0;
5953: for(j=1; j<=nlstate;j++){
5954: eip +=eij[i][j][(int)age];
5955: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5956: }
5957: fprintf(ficreseij,"%9.4f", eip );
5958: }
5959: fprintf(ficreseij,"\n");
5960:
5961: }
5962: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5963: printf("\n");
5964: fprintf(ficlog,"\n");
5965:
5966: }
5967:
1.235 brouard 5968: 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 5969:
5970: {
5971: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5972: to initial status i, ei. .
1.126 brouard 5973: */
5974: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5975: int nhstepma, nstepma; /* Decreasing with age */
5976: double age, agelim, hf;
5977: double ***p3matp, ***p3matm, ***varhe;
5978: double **dnewm,**doldm;
5979: double *xp, *xm;
5980: double **gp, **gm;
5981: double ***gradg, ***trgradg;
5982: int theta;
5983:
5984: double eip, vip;
5985:
5986: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5987: xp=vector(1,npar);
5988: xm=vector(1,npar);
5989: dnewm=matrix(1,nlstate*nlstate,1,npar);
5990: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5991:
5992: pstamp(ficresstdeij);
5993: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5994: fprintf(ficresstdeij,"# Age");
5995: for(i=1; i<=nlstate;i++){
5996: for(j=1; j<=nlstate;j++)
5997: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5998: fprintf(ficresstdeij," e%1d. ",i);
5999: }
6000: fprintf(ficresstdeij,"\n");
6001:
6002: pstamp(ficrescveij);
6003: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6004: fprintf(ficrescveij,"# Age");
6005: for(i=1; i<=nlstate;i++)
6006: for(j=1; j<=nlstate;j++){
6007: cptj= (j-1)*nlstate+i;
6008: for(i2=1; i2<=nlstate;i2++)
6009: for(j2=1; j2<=nlstate;j2++){
6010: cptj2= (j2-1)*nlstate+i2;
6011: if(cptj2 <= cptj)
6012: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6013: }
6014: }
6015: fprintf(ficrescveij,"\n");
6016:
6017: if(estepm < stepm){
6018: printf ("Problem %d lower than %d\n",estepm, stepm);
6019: }
6020: else hstepm=estepm;
6021: /* We compute the life expectancy from trapezoids spaced every estepm months
6022: * This is mainly to measure the difference between two models: for example
6023: * if stepm=24 months pijx are given only every 2 years and by summing them
6024: * we are calculating an estimate of the Life Expectancy assuming a linear
6025: * progression in between and thus overestimating or underestimating according
6026: * to the curvature of the survival function. If, for the same date, we
6027: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6028: * to compare the new estimate of Life expectancy with the same linear
6029: * hypothesis. A more precise result, taking into account a more precise
6030: * curvature will be obtained if estepm is as small as stepm. */
6031:
6032: /* For example we decided to compute the life expectancy with the smallest unit */
6033: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6034: nhstepm is the number of hstepm from age to agelim
6035: nstepm is the number of stepm from age to agelin.
6036: Look at hpijx to understand the reason of that which relies in memory size
6037: and note for a fixed period like estepm months */
6038: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6039: survival function given by stepm (the optimization length). Unfortunately it
6040: means that if the survival funtion is printed only each two years of age and if
6041: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6042: results. So we changed our mind and took the option of the best precision.
6043: */
6044: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6045:
6046: /* If stepm=6 months */
6047: /* nhstepm age range expressed in number of stepm */
6048: agelim=AGESUP;
6049: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6050: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6051: /* if (stepm >= YEARM) hstepm=1;*/
6052: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6053:
6054: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6055: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6056: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6057: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6058: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6059: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6060:
6061: for (age=bage; age<=fage; age ++){
6062: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6063: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6064: /* if (stepm >= YEARM) hstepm=1;*/
6065: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6066:
1.126 brouard 6067: /* If stepm=6 months */
6068: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6069: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6070:
6071: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6072:
1.126 brouard 6073: /* Computing Variances of health expectancies */
6074: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6075: decrease memory allocation */
6076: for(theta=1; theta <=npar; theta++){
6077: for(i=1; i<=npar; i++){
1.222 brouard 6078: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6079: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6080: }
1.235 brouard 6081: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6082: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6083:
1.126 brouard 6084: for(j=1; j<= nlstate; j++){
1.222 brouard 6085: for(i=1; i<=nlstate; i++){
6086: for(h=0; h<=nhstepm-1; h++){
6087: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6088: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6089: }
6090: }
1.126 brouard 6091: }
1.218 brouard 6092:
1.126 brouard 6093: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6094: for(h=0; h<=nhstepm-1; h++){
6095: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6096: }
1.126 brouard 6097: }/* End theta */
6098:
6099:
6100: for(h=0; h<=nhstepm-1; h++)
6101: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6102: for(theta=1; theta <=npar; theta++)
6103: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6104:
1.218 brouard 6105:
1.222 brouard 6106: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6107: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6108: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6109:
1.222 brouard 6110: printf("%d|",(int)age);fflush(stdout);
6111: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6112: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6113: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6114: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6115: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6116: for(ij=1;ij<=nlstate*nlstate;ij++)
6117: for(ji=1;ji<=nlstate*nlstate;ji++)
6118: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6119: }
6120: }
1.320 ! brouard 6121: /* if((int)age ==50){ */
! 6122: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
! 6123: /* } */
1.126 brouard 6124: /* Computing expectancies */
1.235 brouard 6125: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6126: for(i=1; i<=nlstate;i++)
6127: for(j=1; j<=nlstate;j++)
1.222 brouard 6128: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6129: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6130:
1.222 brouard 6131: /* 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 6132:
1.222 brouard 6133: }
1.269 brouard 6134:
6135: /* Standard deviation of expectancies ij */
1.126 brouard 6136: fprintf(ficresstdeij,"%3.0f",age );
6137: for(i=1; i<=nlstate;i++){
6138: eip=0.;
6139: vip=0.;
6140: for(j=1; j<=nlstate;j++){
1.222 brouard 6141: eip += eij[i][j][(int)age];
6142: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6143: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6144: 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 6145: }
6146: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6147: }
6148: fprintf(ficresstdeij,"\n");
1.218 brouard 6149:
1.269 brouard 6150: /* Variance of expectancies ij */
1.126 brouard 6151: fprintf(ficrescveij,"%3.0f",age );
6152: for(i=1; i<=nlstate;i++)
6153: for(j=1; j<=nlstate;j++){
1.222 brouard 6154: cptj= (j-1)*nlstate+i;
6155: for(i2=1; i2<=nlstate;i2++)
6156: for(j2=1; j2<=nlstate;j2++){
6157: cptj2= (j2-1)*nlstate+i2;
6158: if(cptj2 <= cptj)
6159: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6160: }
1.126 brouard 6161: }
6162: fprintf(ficrescveij,"\n");
1.218 brouard 6163:
1.126 brouard 6164: }
6165: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6166: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6167: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6168: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6169: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6170: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6171: printf("\n");
6172: fprintf(ficlog,"\n");
1.218 brouard 6173:
1.126 brouard 6174: free_vector(xm,1,npar);
6175: free_vector(xp,1,npar);
6176: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6177: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6178: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6179: }
1.218 brouard 6180:
1.126 brouard 6181: /************ Variance ******************/
1.235 brouard 6182: 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 6183: {
1.279 brouard 6184: /** Variance of health expectancies
6185: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6186: * double **newm;
6187: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6188: */
1.218 brouard 6189:
6190: /* int movingaverage(); */
6191: double **dnewm,**doldm;
6192: double **dnewmp,**doldmp;
6193: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6194: int first=0;
1.218 brouard 6195: int k;
6196: double *xp;
1.279 brouard 6197: double **gp, **gm; /**< for var eij */
6198: double ***gradg, ***trgradg; /**< for var eij */
6199: double **gradgp, **trgradgp; /**< for var p point j */
6200: double *gpp, *gmp; /**< for var p point j */
6201: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6202: double ***p3mat;
6203: double age,agelim, hf;
6204: /* double ***mobaverage; */
6205: int theta;
6206: char digit[4];
6207: char digitp[25];
6208:
6209: char fileresprobmorprev[FILENAMELENGTH];
6210:
6211: if(popbased==1){
6212: if(mobilav!=0)
6213: strcpy(digitp,"-POPULBASED-MOBILAV_");
6214: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6215: }
6216: else
6217: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6218:
1.218 brouard 6219: /* if (mobilav!=0) { */
6220: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6221: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6222: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6223: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6224: /* } */
6225: /* } */
6226:
6227: strcpy(fileresprobmorprev,"PRMORPREV-");
6228: sprintf(digit,"%-d",ij);
6229: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6230: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6231: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6232: strcat(fileresprobmorprev,fileresu);
6233: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6234: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6235: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6236: }
6237: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6238: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6239: pstamp(ficresprobmorprev);
6240: 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 6241: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
6242: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
6243: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
6244: }
6245: for(j=1;j<=cptcoveff;j++)
6246: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
6247: fprintf(ficresprobmorprev,"\n");
6248:
1.218 brouard 6249: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6250: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6251: fprintf(ficresprobmorprev," p.%-d SE",j);
6252: for(i=1; i<=nlstate;i++)
6253: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6254: }
6255: fprintf(ficresprobmorprev,"\n");
6256:
6257: fprintf(ficgp,"\n# Routine varevsij");
6258: fprintf(ficgp,"\nunset title \n");
6259: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6260: 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");
6261: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6262:
1.218 brouard 6263: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6264: pstamp(ficresvij);
6265: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6266: if(popbased==1)
6267: 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);
6268: else
6269: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6270: fprintf(ficresvij,"# Age");
6271: for(i=1; i<=nlstate;i++)
6272: for(j=1; j<=nlstate;j++)
6273: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6274: fprintf(ficresvij,"\n");
6275:
6276: xp=vector(1,npar);
6277: dnewm=matrix(1,nlstate,1,npar);
6278: doldm=matrix(1,nlstate,1,nlstate);
6279: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6280: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6281:
6282: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6283: gpp=vector(nlstate+1,nlstate+ndeath);
6284: gmp=vector(nlstate+1,nlstate+ndeath);
6285: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6286:
1.218 brouard 6287: if(estepm < stepm){
6288: printf ("Problem %d lower than %d\n",estepm, stepm);
6289: }
6290: else hstepm=estepm;
6291: /* For example we decided to compute the life expectancy with the smallest unit */
6292: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6293: nhstepm is the number of hstepm from age to agelim
6294: nstepm is the number of stepm from age to agelim.
6295: Look at function hpijx to understand why because of memory size limitations,
6296: we decided (b) to get a life expectancy respecting the most precise curvature of the
6297: survival function given by stepm (the optimization length). Unfortunately it
6298: means that if the survival funtion is printed every two years of age and if
6299: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6300: results. So we changed our mind and took the option of the best precision.
6301: */
6302: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6303: agelim = AGESUP;
6304: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6305: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6306: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6307: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6308: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6309: gp=matrix(0,nhstepm,1,nlstate);
6310: gm=matrix(0,nhstepm,1,nlstate);
6311:
6312:
6313: for(theta=1; theta <=npar; theta++){
6314: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6315: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6316: }
1.279 brouard 6317: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6318: * returns into prlim .
1.288 brouard 6319: */
1.242 brouard 6320: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6321:
6322: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6323: if (popbased==1) {
6324: if(mobilav ==0){
6325: for(i=1; i<=nlstate;i++)
6326: prlim[i][i]=probs[(int)age][i][ij];
6327: }else{ /* mobilav */
6328: for(i=1; i<=nlstate;i++)
6329: prlim[i][i]=mobaverage[(int)age][i][ij];
6330: }
6331: }
1.295 brouard 6332: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6333: */
6334: 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 6335: /**< 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 6336: * at horizon h in state j including mortality.
6337: */
1.218 brouard 6338: for(j=1; j<= nlstate; j++){
6339: for(h=0; h<=nhstepm; h++){
6340: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6341: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6342: }
6343: }
1.279 brouard 6344: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6345: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6346: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6347: */
6348: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6349: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6350: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6351: }
6352:
6353: /* Again with minus shift */
1.218 brouard 6354:
6355: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6356: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6357:
1.242 brouard 6358: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6359:
6360: if (popbased==1) {
6361: if(mobilav ==0){
6362: for(i=1; i<=nlstate;i++)
6363: prlim[i][i]=probs[(int)age][i][ij];
6364: }else{ /* mobilav */
6365: for(i=1; i<=nlstate;i++)
6366: prlim[i][i]=mobaverage[(int)age][i][ij];
6367: }
6368: }
6369:
1.235 brouard 6370: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6371:
6372: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6373: for(h=0; h<=nhstepm; h++){
6374: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6375: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6376: }
6377: }
6378: /* This for computing probability of death (h=1 means
6379: computed over hstepm matrices product = hstepm*stepm months)
6380: as a weighted average of prlim.
6381: */
6382: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6383: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6384: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6385: }
1.279 brouard 6386: /* end shifting computations */
6387:
6388: /**< Computing gradient matrix at horizon h
6389: */
1.218 brouard 6390: for(j=1; j<= nlstate; j++) /* vareij */
6391: for(h=0; h<=nhstepm; h++){
6392: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6393: }
1.279 brouard 6394: /**< Gradient of overall mortality p.3 (or p.j)
6395: */
6396: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6397: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6398: }
6399:
6400: } /* End theta */
1.279 brouard 6401:
6402: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6403: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6404:
6405: for(h=0; h<=nhstepm; h++) /* veij */
6406: for(j=1; j<=nlstate;j++)
6407: for(theta=1; theta <=npar; theta++)
6408: trgradg[h][j][theta]=gradg[h][theta][j];
6409:
6410: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6411: for(theta=1; theta <=npar; theta++)
6412: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6413: /**< as well as its transposed matrix
6414: */
1.218 brouard 6415:
6416: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6417: for(i=1;i<=nlstate;i++)
6418: for(j=1;j<=nlstate;j++)
6419: vareij[i][j][(int)age] =0.;
1.279 brouard 6420:
6421: /* Computing trgradg by matcov by gradg at age and summing over h
6422: * and k (nhstepm) formula 15 of article
6423: * Lievre-Brouard-Heathcote
6424: */
6425:
1.218 brouard 6426: for(h=0;h<=nhstepm;h++){
6427: for(k=0;k<=nhstepm;k++){
6428: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6429: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6430: for(i=1;i<=nlstate;i++)
6431: for(j=1;j<=nlstate;j++)
6432: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6433: }
6434: }
6435:
1.279 brouard 6436: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6437: * p.j overall mortality formula 49 but computed directly because
6438: * we compute the grad (wix pijx) instead of grad (pijx),even if
6439: * wix is independent of theta.
6440: */
1.218 brouard 6441: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6442: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6443: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6444: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6445: varppt[j][i]=doldmp[j][i];
6446: /* end ppptj */
6447: /* x centered again */
6448:
1.242 brouard 6449: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6450:
6451: if (popbased==1) {
6452: if(mobilav ==0){
6453: for(i=1; i<=nlstate;i++)
6454: prlim[i][i]=probs[(int)age][i][ij];
6455: }else{ /* mobilav */
6456: for(i=1; i<=nlstate;i++)
6457: prlim[i][i]=mobaverage[(int)age][i][ij];
6458: }
6459: }
6460:
6461: /* This for computing probability of death (h=1 means
6462: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6463: as a weighted average of prlim.
6464: */
1.235 brouard 6465: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6466: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6467: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6468: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6469: }
6470: /* end probability of death */
6471:
6472: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6473: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6474: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6475: for(i=1; i<=nlstate;i++){
6476: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6477: }
6478: }
6479: fprintf(ficresprobmorprev,"\n");
6480:
6481: fprintf(ficresvij,"%.0f ",age );
6482: for(i=1; i<=nlstate;i++)
6483: for(j=1; j<=nlstate;j++){
6484: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6485: }
6486: fprintf(ficresvij,"\n");
6487: free_matrix(gp,0,nhstepm,1,nlstate);
6488: free_matrix(gm,0,nhstepm,1,nlstate);
6489: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6490: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6491: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6492: } /* End age */
6493: free_vector(gpp,nlstate+1,nlstate+ndeath);
6494: free_vector(gmp,nlstate+1,nlstate+ndeath);
6495: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6496: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6497: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6498: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6499: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6500: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6501: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6502: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6503: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6504: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6505: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6506: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6507: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6508: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6509: 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);
6510: /* 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 6511: */
1.218 brouard 6512: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6513: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6514:
1.218 brouard 6515: free_vector(xp,1,npar);
6516: free_matrix(doldm,1,nlstate,1,nlstate);
6517: free_matrix(dnewm,1,nlstate,1,npar);
6518: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6519: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6520: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6521: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6522: fclose(ficresprobmorprev);
6523: fflush(ficgp);
6524: fflush(fichtm);
6525: } /* end varevsij */
1.126 brouard 6526:
6527: /************ Variance of prevlim ******************/
1.269 brouard 6528: 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 6529: {
1.205 brouard 6530: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6531: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6532:
1.268 brouard 6533: double **dnewmpar,**doldm;
1.126 brouard 6534: int i, j, nhstepm, hstepm;
6535: double *xp;
6536: double *gp, *gm;
6537: double **gradg, **trgradg;
1.208 brouard 6538: double **mgm, **mgp;
1.126 brouard 6539: double age,agelim;
6540: int theta;
6541:
6542: pstamp(ficresvpl);
1.288 brouard 6543: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6544: fprintf(ficresvpl,"# Age ");
6545: if(nresult >=1)
6546: fprintf(ficresvpl," Result# ");
1.126 brouard 6547: for(i=1; i<=nlstate;i++)
6548: fprintf(ficresvpl," %1d-%1d",i,i);
6549: fprintf(ficresvpl,"\n");
6550:
6551: xp=vector(1,npar);
1.268 brouard 6552: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6553: doldm=matrix(1,nlstate,1,nlstate);
6554:
6555: hstepm=1*YEARM; /* Every year of age */
6556: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6557: agelim = AGESUP;
6558: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6559: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6560: if (stepm >= YEARM) hstepm=1;
6561: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6562: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6563: mgp=matrix(1,npar,1,nlstate);
6564: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6565: gp=vector(1,nlstate);
6566: gm=vector(1,nlstate);
6567:
6568: for(theta=1; theta <=npar; theta++){
6569: for(i=1; i<=npar; i++){ /* Computes gradient */
6570: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6571: }
1.288 brouard 6572: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6573: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6574: /* else */
6575: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6576: for(i=1;i<=nlstate;i++){
1.126 brouard 6577: gp[i] = prlim[i][i];
1.208 brouard 6578: mgp[theta][i] = prlim[i][i];
6579: }
1.126 brouard 6580: for(i=1; i<=npar; i++) /* Computes gradient */
6581: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6582: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6583: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6584: /* else */
6585: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6586: for(i=1;i<=nlstate;i++){
1.126 brouard 6587: gm[i] = prlim[i][i];
1.208 brouard 6588: mgm[theta][i] = prlim[i][i];
6589: }
1.126 brouard 6590: for(i=1;i<=nlstate;i++)
6591: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6592: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6593: } /* End theta */
6594:
6595: trgradg =matrix(1,nlstate,1,npar);
6596:
6597: for(j=1; j<=nlstate;j++)
6598: for(theta=1; theta <=npar; theta++)
6599: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6600: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6601: /* printf("\nmgm mgp %d ",(int)age); */
6602: /* for(j=1; j<=nlstate;j++){ */
6603: /* printf(" %d ",j); */
6604: /* for(theta=1; theta <=npar; theta++) */
6605: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6606: /* printf("\n "); */
6607: /* } */
6608: /* } */
6609: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6610: /* printf("\n gradg %d ",(int)age); */
6611: /* for(j=1; j<=nlstate;j++){ */
6612: /* printf("%d ",j); */
6613: /* for(theta=1; theta <=npar; theta++) */
6614: /* printf("%d %lf ",theta,gradg[theta][j]); */
6615: /* printf("\n "); */
6616: /* } */
6617: /* } */
1.126 brouard 6618:
6619: for(i=1;i<=nlstate;i++)
6620: varpl[i][(int)age] =0.;
1.209 brouard 6621: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6622: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6623: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6624: }else{
1.268 brouard 6625: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6626: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6627: }
1.126 brouard 6628: for(i=1;i<=nlstate;i++)
6629: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6630:
6631: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6632: if(nresult >=1)
6633: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6634: for(i=1; i<=nlstate;i++){
1.126 brouard 6635: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6636: /* for(j=1;j<=nlstate;j++) */
6637: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6638: }
1.126 brouard 6639: fprintf(ficresvpl,"\n");
6640: free_vector(gp,1,nlstate);
6641: free_vector(gm,1,nlstate);
1.208 brouard 6642: free_matrix(mgm,1,npar,1,nlstate);
6643: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6644: free_matrix(gradg,1,npar,1,nlstate);
6645: free_matrix(trgradg,1,nlstate,1,npar);
6646: } /* End age */
6647:
6648: free_vector(xp,1,npar);
6649: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6650: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6651:
6652: }
6653:
6654:
6655: /************ Variance of backprevalence limit ******************/
1.269 brouard 6656: 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 6657: {
6658: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6659: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6660:
6661: double **dnewmpar,**doldm;
6662: int i, j, nhstepm, hstepm;
6663: double *xp;
6664: double *gp, *gm;
6665: double **gradg, **trgradg;
6666: double **mgm, **mgp;
6667: double age,agelim;
6668: int theta;
6669:
6670: pstamp(ficresvbl);
6671: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6672: fprintf(ficresvbl,"# Age ");
6673: if(nresult >=1)
6674: fprintf(ficresvbl," Result# ");
6675: for(i=1; i<=nlstate;i++)
6676: fprintf(ficresvbl," %1d-%1d",i,i);
6677: fprintf(ficresvbl,"\n");
6678:
6679: xp=vector(1,npar);
6680: dnewmpar=matrix(1,nlstate,1,npar);
6681: doldm=matrix(1,nlstate,1,nlstate);
6682:
6683: hstepm=1*YEARM; /* Every year of age */
6684: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6685: agelim = AGEINF;
6686: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6687: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6688: if (stepm >= YEARM) hstepm=1;
6689: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6690: gradg=matrix(1,npar,1,nlstate);
6691: mgp=matrix(1,npar,1,nlstate);
6692: mgm=matrix(1,npar,1,nlstate);
6693: gp=vector(1,nlstate);
6694: gm=vector(1,nlstate);
6695:
6696: for(theta=1; theta <=npar; theta++){
6697: for(i=1; i<=npar; i++){ /* Computes gradient */
6698: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6699: }
6700: if(mobilavproj > 0 )
6701: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6702: else
6703: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6704: for(i=1;i<=nlstate;i++){
6705: gp[i] = bprlim[i][i];
6706: mgp[theta][i] = bprlim[i][i];
6707: }
6708: for(i=1; i<=npar; i++) /* Computes gradient */
6709: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6710: if(mobilavproj > 0 )
6711: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6712: else
6713: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6714: for(i=1;i<=nlstate;i++){
6715: gm[i] = bprlim[i][i];
6716: mgm[theta][i] = bprlim[i][i];
6717: }
6718: for(i=1;i<=nlstate;i++)
6719: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6720: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6721: } /* End theta */
6722:
6723: trgradg =matrix(1,nlstate,1,npar);
6724:
6725: for(j=1; j<=nlstate;j++)
6726: for(theta=1; theta <=npar; theta++)
6727: trgradg[j][theta]=gradg[theta][j];
6728: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6729: /* printf("\nmgm mgp %d ",(int)age); */
6730: /* for(j=1; j<=nlstate;j++){ */
6731: /* printf(" %d ",j); */
6732: /* for(theta=1; theta <=npar; theta++) */
6733: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6734: /* printf("\n "); */
6735: /* } */
6736: /* } */
6737: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6738: /* printf("\n gradg %d ",(int)age); */
6739: /* for(j=1; j<=nlstate;j++){ */
6740: /* printf("%d ",j); */
6741: /* for(theta=1; theta <=npar; theta++) */
6742: /* printf("%d %lf ",theta,gradg[theta][j]); */
6743: /* printf("\n "); */
6744: /* } */
6745: /* } */
6746:
6747: for(i=1;i<=nlstate;i++)
6748: varbpl[i][(int)age] =0.;
6749: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6750: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6751: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6752: }else{
6753: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6754: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6755: }
6756: for(i=1;i<=nlstate;i++)
6757: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6758:
6759: fprintf(ficresvbl,"%.0f ",age );
6760: if(nresult >=1)
6761: fprintf(ficresvbl,"%d ",nres );
6762: for(i=1; i<=nlstate;i++)
6763: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6764: fprintf(ficresvbl,"\n");
6765: free_vector(gp,1,nlstate);
6766: free_vector(gm,1,nlstate);
6767: free_matrix(mgm,1,npar,1,nlstate);
6768: free_matrix(mgp,1,npar,1,nlstate);
6769: free_matrix(gradg,1,npar,1,nlstate);
6770: free_matrix(trgradg,1,nlstate,1,npar);
6771: } /* End age */
6772:
6773: free_vector(xp,1,npar);
6774: free_matrix(doldm,1,nlstate,1,npar);
6775: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6776:
6777: }
6778:
6779: /************ Variance of one-step probabilities ******************/
6780: 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 6781: {
6782: int i, j=0, k1, l1, tj;
6783: int k2, l2, j1, z1;
6784: int k=0, l;
6785: int first=1, first1, first2;
6786: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6787: double **dnewm,**doldm;
6788: double *xp;
6789: double *gp, *gm;
6790: double **gradg, **trgradg;
6791: double **mu;
6792: double age, cov[NCOVMAX+1];
6793: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6794: int theta;
6795: char fileresprob[FILENAMELENGTH];
6796: char fileresprobcov[FILENAMELENGTH];
6797: char fileresprobcor[FILENAMELENGTH];
6798: double ***varpij;
6799:
6800: strcpy(fileresprob,"PROB_");
6801: strcat(fileresprob,fileres);
6802: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6803: printf("Problem with resultfile: %s\n", fileresprob);
6804: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6805: }
6806: strcpy(fileresprobcov,"PROBCOV_");
6807: strcat(fileresprobcov,fileresu);
6808: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6809: printf("Problem with resultfile: %s\n", fileresprobcov);
6810: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6811: }
6812: strcpy(fileresprobcor,"PROBCOR_");
6813: strcat(fileresprobcor,fileresu);
6814: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6815: printf("Problem with resultfile: %s\n", fileresprobcor);
6816: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6817: }
6818: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6819: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6820: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6821: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6822: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6823: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6824: pstamp(ficresprob);
6825: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6826: fprintf(ficresprob,"# Age");
6827: pstamp(ficresprobcov);
6828: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6829: fprintf(ficresprobcov,"# Age");
6830: pstamp(ficresprobcor);
6831: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6832: fprintf(ficresprobcor,"# Age");
1.126 brouard 6833:
6834:
1.222 brouard 6835: for(i=1; i<=nlstate;i++)
6836: for(j=1; j<=(nlstate+ndeath);j++){
6837: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6838: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6839: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6840: }
6841: /* fprintf(ficresprob,"\n");
6842: fprintf(ficresprobcov,"\n");
6843: fprintf(ficresprobcor,"\n");
6844: */
6845: xp=vector(1,npar);
6846: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6847: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6848: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6849: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6850: first=1;
6851: fprintf(ficgp,"\n# Routine varprob");
6852: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6853: fprintf(fichtm,"\n");
6854:
1.288 brouard 6855: 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 6856: 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);
6857: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6858: and drawn. It helps understanding how is the covariance between two incidences.\
6859: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6860: 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 6861: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6862: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6863: standard deviations wide on each axis. <br>\
6864: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6865: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6866: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6867:
1.222 brouard 6868: cov[1]=1;
6869: /* tj=cptcoveff; */
1.225 brouard 6870: tj = (int) pow(2,cptcoveff);
1.222 brouard 6871: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6872: j1=0;
1.224 brouard 6873: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6874: if (cptcovn>0) {
6875: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6876: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6877: fprintf(ficresprob, "**********\n#\n");
6878: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6879: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6880: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6881:
1.222 brouard 6882: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6883: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6884: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6885:
6886:
1.222 brouard 6887: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.319 brouard 6888: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); */
6889: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtmcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6890: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6891:
1.222 brouard 6892: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6893: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6894: fprintf(ficresprobcor, "**********\n#");
6895: if(invalidvarcomb[j1]){
6896: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6897: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6898: continue;
6899: }
6900: }
6901: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6902: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6903: gp=vector(1,(nlstate)*(nlstate+ndeath));
6904: gm=vector(1,(nlstate)*(nlstate+ndeath));
6905: for (age=bage; age<=fage; age ++){
6906: cov[2]=age;
6907: if(nagesqr==1)
6908: cov[3]= age*age;
6909: for (k=1; k<=cptcovn;k++) {
6910: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6911: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6912: * 1 1 1 1 1
6913: * 2 2 1 1 1
6914: * 3 1 2 1 1
6915: */
6916: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6917: }
1.319 brouard 6918: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
6919: /* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] */
6920: /*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6921: for (k=1; k<=cptcovage;k++)
6922: cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.222 brouard 6923: for (k=1; k<=cptcovprod;k++)
6924: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6925:
6926:
1.222 brouard 6927: for(theta=1; theta <=npar; theta++){
6928: for(i=1; i<=npar; i++)
6929: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6930:
1.222 brouard 6931: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6932:
1.222 brouard 6933: k=0;
6934: for(i=1; i<= (nlstate); i++){
6935: for(j=1; j<=(nlstate+ndeath);j++){
6936: k=k+1;
6937: gp[k]=pmmij[i][j];
6938: }
6939: }
1.220 brouard 6940:
1.222 brouard 6941: for(i=1; i<=npar; i++)
6942: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6943:
1.222 brouard 6944: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6945: k=0;
6946: for(i=1; i<=(nlstate); i++){
6947: for(j=1; j<=(nlstate+ndeath);j++){
6948: k=k+1;
6949: gm[k]=pmmij[i][j];
6950: }
6951: }
1.220 brouard 6952:
1.222 brouard 6953: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6954: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6955: }
1.126 brouard 6956:
1.222 brouard 6957: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6958: for(theta=1; theta <=npar; theta++)
6959: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6960:
1.222 brouard 6961: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6962: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6963:
1.222 brouard 6964: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6965:
1.222 brouard 6966: k=0;
6967: for(i=1; i<=(nlstate); i++){
6968: for(j=1; j<=(nlstate+ndeath);j++){
6969: k=k+1;
6970: mu[k][(int) age]=pmmij[i][j];
6971: }
6972: }
6973: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6974: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6975: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6976:
1.222 brouard 6977: /*printf("\n%d ",(int)age);
6978: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6979: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6980: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6981: }*/
1.220 brouard 6982:
1.222 brouard 6983: fprintf(ficresprob,"\n%d ",(int)age);
6984: fprintf(ficresprobcov,"\n%d ",(int)age);
6985: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6986:
1.222 brouard 6987: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6988: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6989: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6990: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6991: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6992: }
6993: i=0;
6994: for (k=1; k<=(nlstate);k++){
6995: for (l=1; l<=(nlstate+ndeath);l++){
6996: i++;
6997: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6998: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6999: for (j=1; j<=i;j++){
7000: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7001: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7002: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7003: }
7004: }
7005: }/* end of loop for state */
7006: } /* end of loop for age */
7007: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7008: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7009: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7010: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7011:
7012: /* Confidence intervalle of pij */
7013: /*
7014: fprintf(ficgp,"\nunset parametric;unset label");
7015: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7016: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7017: 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);
7018: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7019: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7020: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7021: */
7022:
7023: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7024: first1=1;first2=2;
7025: for (k2=1; k2<=(nlstate);k2++){
7026: for (l2=1; l2<=(nlstate+ndeath);l2++){
7027: if(l2==k2) continue;
7028: j=(k2-1)*(nlstate+ndeath)+l2;
7029: for (k1=1; k1<=(nlstate);k1++){
7030: for (l1=1; l1<=(nlstate+ndeath);l1++){
7031: if(l1==k1) continue;
7032: i=(k1-1)*(nlstate+ndeath)+l1;
7033: if(i<=j) continue;
7034: for (age=bage; age<=fage; age ++){
7035: if ((int)age %5==0){
7036: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7037: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7038: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7039: mu1=mu[i][(int) age]/stepm*YEARM ;
7040: mu2=mu[j][(int) age]/stepm*YEARM;
7041: c12=cv12/sqrt(v1*v2);
7042: /* Computing eigen value of matrix of covariance */
7043: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7044: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7045: if ((lc2 <0) || (lc1 <0) ){
7046: if(first2==1){
7047: first1=0;
7048: 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);
7049: }
7050: 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);
7051: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7052: /* lc2=fabs(lc2); */
7053: }
1.220 brouard 7054:
1.222 brouard 7055: /* Eigen vectors */
1.280 brouard 7056: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7057: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7058: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7059: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7060: }else
7061: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7062: /*v21=sqrt(1.-v11*v11); *//* error */
7063: v21=(lc1-v1)/cv12*v11;
7064: v12=-v21;
7065: v22=v11;
7066: tnalp=v21/v11;
7067: if(first1==1){
7068: first1=0;
7069: 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);
7070: }
7071: 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);
7072: /*printf(fignu*/
7073: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7074: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7075: if(first==1){
7076: first=0;
7077: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7078: fprintf(ficgp,"\nset parametric;unset label");
7079: 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);
7080: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7081: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7082: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7083: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7084: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7085: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7086: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7087: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7088: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7089: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7090: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7091: 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 7092: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7093: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7094: }else{
7095: first=0;
7096: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7097: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7098: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7099: 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 7100: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7101: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7102: }/* if first */
7103: } /* age mod 5 */
7104: } /* end loop age */
7105: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7106: first=1;
7107: } /*l12 */
7108: } /* k12 */
7109: } /*l1 */
7110: }/* k1 */
7111: } /* loop on combination of covariates j1 */
7112: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7113: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7114: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7115: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7116: free_vector(xp,1,npar);
7117: fclose(ficresprob);
7118: fclose(ficresprobcov);
7119: fclose(ficresprobcor);
7120: fflush(ficgp);
7121: fflush(fichtmcov);
7122: }
1.126 brouard 7123:
7124:
7125: /******************* Printing html file ***********/
1.201 brouard 7126: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7127: int lastpass, int stepm, int weightopt, char model[],\
7128: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7129: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7130: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7131: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7132: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7133: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7134: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7135: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7136: </ul>");
1.319 brouard 7137: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7138: /* </ul>", model); */
1.214 brouard 7139: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7140: 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",
7141: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
7142: 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 7143: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7144: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7145: fprintf(fichtm,"\
7146: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7147: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7148: fprintf(fichtm,"\
1.217 brouard 7149: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7150: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7151: fprintf(fichtm,"\
1.288 brouard 7152: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7153: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7154: fprintf(fichtm,"\
1.288 brouard 7155: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7156: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7157: fprintf(fichtm,"\
1.211 brouard 7158: - (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 7159: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7160: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7161: if(prevfcast==1){
7162: fprintf(fichtm,"\
7163: - Prevalence projections by age and states: \
1.201 brouard 7164: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7165: }
1.126 brouard 7166:
7167:
1.225 brouard 7168: m=pow(2,cptcoveff);
1.222 brouard 7169: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7170:
1.317 brouard 7171: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7172:
7173: jj1=0;
7174:
7175: fprintf(fichtm," \n<ul>");
7176: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7177: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7178: if(m != 1 && TKresult[nres]!= k1)
7179: continue;
7180: jj1++;
7181: if (cptcovn > 0) {
7182: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
7183: for (cpt=1; cpt<=cptcoveff;cpt++){
7184: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7185: }
7186: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7187: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7188: }
7189: fprintf(fichtm,"\">");
7190:
7191: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7192: fprintf(fichtm,"************ Results for covariates");
7193: for (cpt=1; cpt<=cptcoveff;cpt++){
7194: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7195: }
7196: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7197: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7198: }
7199: if(invalidvarcomb[k1]){
7200: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7201: continue;
7202: }
7203: fprintf(fichtm,"</a></li>");
7204: } /* cptcovn >0 */
7205: }
1.317 brouard 7206: fprintf(fichtm," \n</ul>");
1.264 brouard 7207:
1.222 brouard 7208: jj1=0;
1.237 brouard 7209:
7210: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7211: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7212: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7213: continue;
1.220 brouard 7214:
1.222 brouard 7215: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7216: jj1++;
7217: if (cptcovn > 0) {
1.264 brouard 7218: fprintf(fichtm,"\n<p><a name=\"rescov");
7219: for (cpt=1; cpt<=cptcoveff;cpt++){
7220: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7221: }
7222: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7223: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7224: }
7225: fprintf(fichtm,"\"</a>");
7226:
1.222 brouard 7227: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7228: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7229: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7230: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7231: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7232: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7233: }
1.237 brouard 7234: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7235: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7236: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7237: }
7238:
1.230 brouard 7239: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 7240: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
7241: if(invalidvarcomb[k1]){
7242: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7243: printf("\nCombination (%d) ignored because no cases \n",k1);
7244: continue;
7245: }
7246: }
7247: /* aij, bij */
1.259 brouard 7248: 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 7249: <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 7250: /* Pij */
1.241 brouard 7251: 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> \
7252: <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 7253: /* Quasi-incidences */
7254: 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 7255: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7256: 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 7257: 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> \
7258: <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 7259: /* Survival functions (period) in state j */
7260: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7261: 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 7262: <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 7263: }
7264: /* State specific survival functions (period) */
7265: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7266: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7267: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 7268: <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 7269: }
1.288 brouard 7270: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7271: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7272: 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> \
7273: <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 7274: }
1.296 brouard 7275: if(prevbcast==1){
1.288 brouard 7276: /* Backward prevalence in each health state */
1.222 brouard 7277: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7278: 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 7279: <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 7280: }
1.217 brouard 7281: }
1.222 brouard 7282: if(prevfcast==1){
1.288 brouard 7283: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7284: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7285: 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);
7286: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7287: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7288: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7289: }
7290: }
1.296 brouard 7291: if(prevbcast==1){
1.268 brouard 7292: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7293: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7294: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7295: 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 \
7296: 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 7297: 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);
7298: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7299: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7300: }
7301: }
1.220 brouard 7302:
1.222 brouard 7303: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7304: 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);
7305: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7306: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7307: }
7308: /* } /\* end i1 *\/ */
7309: }/* End k1 */
7310: fprintf(fichtm,"</ul>");
1.126 brouard 7311:
1.222 brouard 7312: fprintf(fichtm,"\
1.126 brouard 7313: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7314: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7315: - 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 7316: But because parameters are usually highly correlated (a higher incidence of disability \
7317: and a higher incidence of recovery can give very close observed transition) it might \
7318: be very useful to look not only at linear confidence intervals estimated from the \
7319: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7320: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7321: covariance matrix of the one-step probabilities. \
7322: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7323:
1.222 brouard 7324: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7325: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7326: fprintf(fichtm,"\
1.126 brouard 7327: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7328: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7329:
1.222 brouard 7330: fprintf(fichtm,"\
1.126 brouard 7331: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7332: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7333: fprintf(fichtm,"\
1.126 brouard 7334: - 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): \
7335: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7336: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7337: fprintf(fichtm,"\
1.126 brouard 7338: - (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): \
7339: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7340: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7341: fprintf(fichtm,"\
1.288 brouard 7342: - 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 7343: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7344: fprintf(fichtm,"\
1.128 brouard 7345: - 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 7346: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7347: fprintf(fichtm,"\
1.288 brouard 7348: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7349: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7350:
7351: /* if(popforecast==1) fprintf(fichtm,"\n */
7352: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7353: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7354: /* <br>",fileres,fileres,fileres,fileres); */
7355: /* else */
7356: /* 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 7357: fflush(fichtm);
1.126 brouard 7358:
1.225 brouard 7359: m=pow(2,cptcoveff);
1.222 brouard 7360: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7361:
1.317 brouard 7362: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7363:
7364: jj1=0;
7365:
7366: fprintf(fichtm," \n<ul>");
7367: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7368: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7369: if(m != 1 && TKresult[nres]!= k1)
7370: continue;
7371: jj1++;
7372: if (cptcovn > 0) {
7373: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
7374: for (cpt=1; cpt<=cptcoveff;cpt++){
7375: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7376: }
7377: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7378: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7379: }
7380: fprintf(fichtm,"\">");
7381:
7382: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7383: fprintf(fichtm,"************ Results for covariates");
7384: for (cpt=1; cpt<=cptcoveff;cpt++){
7385: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7386: }
7387: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7388: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7389: }
7390: if(invalidvarcomb[k1]){
7391: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7392: continue;
7393: }
7394: fprintf(fichtm,"</a></li>");
7395: } /* cptcovn >0 */
7396: }
7397: fprintf(fichtm," \n</ul>");
7398:
1.222 brouard 7399: jj1=0;
1.237 brouard 7400:
1.241 brouard 7401: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7402: for(k1=1; k1<=m;k1++){
1.253 brouard 7403: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7404: continue;
1.222 brouard 7405: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7406: jj1++;
1.126 brouard 7407: if (cptcovn > 0) {
1.317 brouard 7408: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
7409: for (cpt=1; cpt<=cptcoveff;cpt++){
7410: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7411: }
7412: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7413: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7414: }
7415: fprintf(fichtm,"\"</a>");
7416:
1.126 brouard 7417: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.317 brouard 7418: for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */
1.237 brouard 7419: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
1.317 brouard 7420: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
1.237 brouard 7421: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7422: }
1.237 brouard 7423: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7424: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7425: }
7426:
1.126 brouard 7427: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7428:
1.222 brouard 7429: if(invalidvarcomb[k1]){
7430: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7431: continue;
7432: }
1.126 brouard 7433: }
7434: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7435: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7436: 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);
7437: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7438: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7439: }
7440: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7441: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7442: true period expectancies (those weighted with period prevalences are also\
7443: drawn in addition to the population based expectancies computed using\
1.314 brouard 7444: 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);
7445: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7446: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7447: /* } /\* end i1 *\/ */
7448: }/* End k1 */
1.241 brouard 7449: }/* End nres */
1.222 brouard 7450: fprintf(fichtm,"</ul>");
7451: fflush(fichtm);
1.126 brouard 7452: }
7453:
7454: /******************* Gnuplot file **************/
1.296 brouard 7455: 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 7456:
7457: char dirfileres[132],optfileres[132];
1.264 brouard 7458: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7459: 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 7460: int lv=0, vlv=0, kl=0;
1.130 brouard 7461: int ng=0;
1.201 brouard 7462: int vpopbased;
1.223 brouard 7463: int ioffset; /* variable offset for columns */
1.270 brouard 7464: int iyearc=1; /* variable column for year of projection */
7465: int iagec=1; /* variable column for age of projection */
1.235 brouard 7466: int nres=0; /* Index of resultline */
1.266 brouard 7467: int istart=1; /* For starting graphs in projections */
1.219 brouard 7468:
1.126 brouard 7469: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7470: /* printf("Problem with file %s",optionfilegnuplot); */
7471: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7472: /* } */
7473:
7474: /*#ifdef windows */
7475: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7476: /*#endif */
1.225 brouard 7477: m=pow(2,cptcoveff);
1.126 brouard 7478:
1.274 brouard 7479: /* diagram of the model */
7480: fprintf(ficgp,"\n#Diagram of the model \n");
7481: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7482: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7483: 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);
7484:
7485: 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);
7486: fprintf(ficgp,"\n#show arrow\nunset label\n");
7487: 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);
7488: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7489: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7490: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7491: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7492:
1.202 brouard 7493: /* Contribution to likelihood */
7494: /* Plot the probability implied in the likelihood */
1.223 brouard 7495: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7496: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7497: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7498: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7499: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7500: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7501: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7502: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7503: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7504: 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));
7505: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7506: 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));
7507: for (i=1; i<= nlstate ; i ++) {
7508: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7509: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7510: 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);
7511: for (j=2; j<= nlstate+ndeath ; j ++) {
7512: 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);
7513: }
7514: fprintf(ficgp,";\nset out; unset ylabel;\n");
7515: }
7516: /* 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 */
7517: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7518: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7519: fprintf(ficgp,"\nset out;unset log\n");
7520: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7521:
1.126 brouard 7522: strcpy(dirfileres,optionfilefiname);
7523: strcpy(optfileres,"vpl");
1.223 brouard 7524: /* 1eme*/
1.238 brouard 7525: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7526: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7527: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7528: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7529: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7530: continue;
7531: /* We are interested in selected combination by the resultline */
1.246 brouard 7532: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7533: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7534: strcpy(gplotlabel,"(");
1.238 brouard 7535: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7536: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7537: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7538: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7539: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7540: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7541: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7542: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7543: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7544: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7545: }
7546: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7547: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7548: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7549: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7550: }
7551: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7552: /* printf("\n#\n"); */
1.238 brouard 7553: fprintf(ficgp,"\n#\n");
7554: if(invalidvarcomb[k1]){
1.260 brouard 7555: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7556: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7557: continue;
7558: }
1.235 brouard 7559:
1.241 brouard 7560: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7561: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7562: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7563: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7564: 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);
7565: /* 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); */
7566: /* k1-1 error should be nres-1*/
1.238 brouard 7567: for (i=1; i<= nlstate ; i ++) {
7568: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7569: else fprintf(ficgp," %%*lf (%%*lf)");
7570: }
1.288 brouard 7571: 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 7572: for (i=1; i<= nlstate ; i ++) {
7573: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7574: else fprintf(ficgp," %%*lf (%%*lf)");
7575: }
1.260 brouard 7576: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7577: for (i=1; i<= nlstate ; i ++) {
7578: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7579: else fprintf(ficgp," %%*lf (%%*lf)");
7580: }
1.265 brouard 7581: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7582:
7583: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7584: if(cptcoveff ==0){
1.271 brouard 7585: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7586: }else{
7587: kl=0;
7588: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7589: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7590: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7591: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7592: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7593: vlv= nbcode[Tvaraff[k]][lv];
7594: kl++;
7595: /* 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 *\/ */
7596: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7597: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7598: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7599: if(k==cptcoveff){
7600: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7601: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7602: }else{
7603: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7604: kl++;
7605: }
7606: } /* end covariate */
7607: } /* end if no covariate */
7608:
1.296 brouard 7609: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7610: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7611: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7612: if(cptcoveff ==0){
1.245 brouard 7613: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7614: }else{
7615: kl=0;
7616: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7617: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7618: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7619: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7620: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7621: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7622: kl++;
1.238 brouard 7623: /* 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 *\/ */
7624: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7625: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7626: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7627: if(k==cptcoveff){
1.245 brouard 7628: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7629: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7630: }else{
7631: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7632: kl++;
7633: }
7634: } /* end covariate */
7635: } /* end if no covariate */
1.296 brouard 7636: if(prevbcast == 1){
1.268 brouard 7637: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7638: /* k1-1 error should be nres-1*/
7639: for (i=1; i<= nlstate ; i ++) {
7640: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7641: else fprintf(ficgp," %%*lf (%%*lf)");
7642: }
1.271 brouard 7643: 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 7644: for (i=1; i<= nlstate ; i ++) {
7645: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7646: else fprintf(ficgp," %%*lf (%%*lf)");
7647: }
1.276 brouard 7648: 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 7649: for (i=1; i<= nlstate ; i ++) {
7650: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7651: else fprintf(ficgp," %%*lf (%%*lf)");
7652: }
1.274 brouard 7653: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7654: } /* end if backprojcast */
1.296 brouard 7655: } /* end if prevbcast */
1.276 brouard 7656: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7657: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7658: } /* nres */
1.201 brouard 7659: } /* k1 */
7660: } /* cpt */
1.235 brouard 7661:
7662:
1.126 brouard 7663: /*2 eme*/
1.238 brouard 7664: for (k1=1; k1<= m ; k1 ++){
7665: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7666: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7667: continue;
7668: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7669: strcpy(gplotlabel,"(");
1.238 brouard 7670: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7671: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7672: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7673: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7674: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7675: vlv= nbcode[Tvaraff[k]][lv];
7676: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7677: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7678: }
1.237 brouard 7679: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7680: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7681: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7682: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7683: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7684: }
1.264 brouard 7685: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7686: fprintf(ficgp,"\n#\n");
1.223 brouard 7687: if(invalidvarcomb[k1]){
7688: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7689: continue;
7690: }
1.219 brouard 7691:
1.241 brouard 7692: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7693: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7694: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7695: if(vpopbased==0){
1.238 brouard 7696: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7697: }else
1.238 brouard 7698: fprintf(ficgp,"\nreplot ");
7699: for (i=1; i<= nlstate+1 ; i ++) {
7700: k=2*i;
1.261 brouard 7701: 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 7702: for (j=1; j<= nlstate+1 ; j ++) {
7703: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7704: else fprintf(ficgp," %%*lf (%%*lf)");
7705: }
7706: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7707: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7708: 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 7709: for (j=1; j<= nlstate+1 ; j ++) {
7710: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7711: else fprintf(ficgp," %%*lf (%%*lf)");
7712: }
7713: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7714: 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 7715: for (j=1; j<= nlstate+1 ; j ++) {
7716: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7717: else fprintf(ficgp," %%*lf (%%*lf)");
7718: }
7719: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7720: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7721: } /* state */
7722: } /* vpopbased */
1.264 brouard 7723: 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 7724: } /* end nres */
7725: } /* k1 end 2 eme*/
7726:
7727:
7728: /*3eme*/
7729: for (k1=1; k1<= m ; k1 ++){
7730: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7731: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7732: continue;
7733:
7734: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7735: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7736: strcpy(gplotlabel,"(");
1.238 brouard 7737: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7738: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7739: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7740: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7741: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7742: vlv= nbcode[Tvaraff[k]][lv];
7743: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7744: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7745: }
7746: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7747: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7748: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7749: }
1.264 brouard 7750: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7751: fprintf(ficgp,"\n#\n");
7752: if(invalidvarcomb[k1]){
7753: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7754: continue;
7755: }
7756:
7757: /* k=2+nlstate*(2*cpt-2); */
7758: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7759: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7760: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7761: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7762: 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 7763: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7764: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7765: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7766: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7767: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7768: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7769:
1.238 brouard 7770: */
7771: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7772: 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 7773: /* 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 7774:
1.238 brouard 7775: }
1.261 brouard 7776: 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 7777: }
1.264 brouard 7778: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7779: } /* end nres */
7780: } /* end kl 3eme */
1.126 brouard 7781:
1.223 brouard 7782: /* 4eme */
1.201 brouard 7783: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7784: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7785: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7786: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7787: continue;
1.238 brouard 7788: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7789: strcpy(gplotlabel,"(");
1.238 brouard 7790: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7791: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7792: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7793: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7794: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7795: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7796: vlv= nbcode[Tvaraff[k]][lv];
7797: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7798: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7799: }
7800: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7801: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7802: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7803: }
1.264 brouard 7804: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7805: fprintf(ficgp,"\n#\n");
7806: if(invalidvarcomb[k1]){
7807: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7808: continue;
1.223 brouard 7809: }
1.238 brouard 7810:
1.241 brouard 7811: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7812: 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 7813: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7814: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7815: k=3;
7816: for (i=1; i<= nlstate ; i ++){
7817: if(i==1){
7818: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7819: }else{
7820: fprintf(ficgp,", '' ");
7821: }
7822: l=(nlstate+ndeath)*(i-1)+1;
7823: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7824: for (j=2; j<= nlstate+ndeath ; j ++)
7825: fprintf(ficgp,"+$%d",k+l+j-1);
7826: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7827: } /* nlstate */
1.264 brouard 7828: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7829: } /* end cpt state*/
7830: } /* end nres */
7831: } /* end covariate k1 */
7832:
1.220 brouard 7833: /* 5eme */
1.201 brouard 7834: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7835: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7836: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7837: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7838: continue;
1.238 brouard 7839: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7840: strcpy(gplotlabel,"(");
1.238 brouard 7841: 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);
7842: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7843: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7844: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7845: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7846: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7847: vlv= nbcode[Tvaraff[k]][lv];
7848: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7849: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7850: }
7851: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7852: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7853: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7854: }
1.264 brouard 7855: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7856: fprintf(ficgp,"\n#\n");
7857: if(invalidvarcomb[k1]){
7858: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7859: continue;
7860: }
1.227 brouard 7861:
1.241 brouard 7862: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7863: 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 7864: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7865: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7866: k=3;
7867: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7868: if(j==1)
7869: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7870: else
7871: fprintf(ficgp,", '' ");
7872: l=(nlstate+ndeath)*(cpt-1) +j;
7873: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7874: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7875: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7876: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7877: } /* nlstate */
7878: fprintf(ficgp,", '' ");
7879: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7880: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7881: l=(nlstate+ndeath)*(cpt-1) +j;
7882: if(j < nlstate)
7883: fprintf(ficgp,"$%d +",k+l);
7884: else
7885: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7886: }
1.264 brouard 7887: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7888: } /* end cpt state*/
7889: } /* end covariate */
7890: } /* end nres */
1.227 brouard 7891:
1.220 brouard 7892: /* 6eme */
1.202 brouard 7893: /* CV preval stable (period) for each covariate */
1.237 brouard 7894: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7895: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7896: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7897: continue;
1.255 brouard 7898: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7899: strcpy(gplotlabel,"(");
1.288 brouard 7900: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7901: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7902: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7903: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7904: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7905: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7906: vlv= nbcode[Tvaraff[k]][lv];
7907: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7908: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7909: }
1.237 brouard 7910: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7911: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7912: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7913: }
1.264 brouard 7914: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7915: fprintf(ficgp,"\n#\n");
1.223 brouard 7916: if(invalidvarcomb[k1]){
1.227 brouard 7917: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7918: continue;
1.223 brouard 7919: }
1.227 brouard 7920:
1.241 brouard 7921: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7922: 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 7923: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7924: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7925: k=3; /* Offset */
1.255 brouard 7926: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7927: if(i==1)
7928: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7929: else
7930: fprintf(ficgp,", '' ");
1.255 brouard 7931: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7932: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7933: for (j=2; j<= nlstate ; j ++)
7934: fprintf(ficgp,"+$%d",k+l+j-1);
7935: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7936: } /* nlstate */
1.264 brouard 7937: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7938: } /* end cpt state*/
7939: } /* end covariate */
1.227 brouard 7940:
7941:
1.220 brouard 7942: /* 7eme */
1.296 brouard 7943: if(prevbcast == 1){
1.288 brouard 7944: /* CV backward prevalence for each covariate */
1.237 brouard 7945: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7946: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7947: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7948: continue;
1.268 brouard 7949: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7950: strcpy(gplotlabel,"(");
1.288 brouard 7951: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7952: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7953: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7954: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7955: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7956: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7957: vlv= nbcode[Tvaraff[k]][lv];
7958: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7959: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7960: }
1.237 brouard 7961: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7962: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7963: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7964: }
1.264 brouard 7965: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7966: fprintf(ficgp,"\n#\n");
7967: if(invalidvarcomb[k1]){
7968: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7969: continue;
7970: }
7971:
1.241 brouard 7972: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7973: 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 7974: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7975: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7976: k=3; /* Offset */
1.268 brouard 7977: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7978: if(i==1)
7979: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7980: else
7981: fprintf(ficgp,", '' ");
7982: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7983: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7984: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7985: /* 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 7986: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7987: /* for (j=2; j<= nlstate ; j ++) */
7988: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7989: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7990: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7991: } /* nlstate */
1.264 brouard 7992: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7993: } /* end cpt state*/
7994: } /* end covariate */
1.296 brouard 7995: } /* End if prevbcast */
1.218 brouard 7996:
1.223 brouard 7997: /* 8eme */
1.218 brouard 7998: if(prevfcast==1){
1.288 brouard 7999: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8000:
1.237 brouard 8001: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8002: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8003: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8004: continue;
1.211 brouard 8005: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8006: strcpy(gplotlabel,"(");
1.288 brouard 8007: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8008: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8009: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8010: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8011: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8012: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8013: vlv= nbcode[Tvaraff[k]][lv];
8014: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8015: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8016: }
1.237 brouard 8017: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8018: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8019: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8020: }
1.264 brouard 8021: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8022: fprintf(ficgp,"\n#\n");
8023: if(invalidvarcomb[k1]){
8024: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8025: continue;
8026: }
8027:
8028: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8029: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8030: 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 8031: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8032: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8033:
8034: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8035: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8036: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8037: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8038: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8039: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8040: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8041: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8042: if(i==istart){
1.227 brouard 8043: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8044: }else{
8045: fprintf(ficgp,",\\\n '' ");
8046: }
8047: if(cptcoveff ==0){ /* No covariate */
8048: ioffset=2; /* Age is in 2 */
8049: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8050: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8051: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8052: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8053: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8054: if(i==nlstate+1){
1.270 brouard 8055: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8056: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8057: fprintf(ficgp,",\\\n '' ");
8058: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8059: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8060: offyear, \
1.268 brouard 8061: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8062: }else
1.227 brouard 8063: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8064: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8065: }else{ /* more than 2 covariates */
1.270 brouard 8066: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8067: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8068: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8069: iyearc=ioffset-1;
8070: iagec=ioffset;
1.227 brouard 8071: fprintf(ficgp," u %d:(",ioffset);
8072: kl=0;
8073: strcpy(gplotcondition,"(");
8074: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8075: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8076: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8077: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8078: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8079: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8080: kl++;
8081: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8082: kl++;
8083: if(k <cptcoveff && cptcoveff>1)
8084: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8085: }
8086: strcpy(gplotcondition+strlen(gplotcondition),")");
8087: /* 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 *\/ */
8088: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8089: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8090: /* '' 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*/
8091: if(i==nlstate+1){
1.270 brouard 8092: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8093: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8094: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8095: fprintf(ficgp," u %d:(",iagec);
8096: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8097: iyearc, iagec, offyear, \
8098: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8099: /* '' 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 8100: }else{
8101: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8102: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8103: }
8104: } /* end if covariate */
8105: } /* nlstate */
1.264 brouard 8106: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8107: } /* end cpt state*/
8108: } /* end covariate */
8109: } /* End if prevfcast */
1.227 brouard 8110:
1.296 brouard 8111: if(prevbcast==1){
1.268 brouard 8112: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8113:
8114: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8115: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8116: if(m != 1 && TKresult[nres]!= k1)
8117: continue;
8118: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8119: strcpy(gplotlabel,"(");
8120: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
8121: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8122: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8123: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8124: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8125: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8126: vlv= nbcode[Tvaraff[k]][lv];
8127: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8128: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8129: }
8130: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8131: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8132: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8133: }
8134: strcpy(gplotlabel+strlen(gplotlabel),")");
8135: fprintf(ficgp,"\n#\n");
8136: if(invalidvarcomb[k1]){
8137: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8138: continue;
8139: }
8140:
8141: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8142: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8143: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8144: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8145: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8146:
8147: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8148: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8149: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8150: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8151: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8152: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8153: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8154: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8155: if(i==istart){
8156: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8157: }else{
8158: fprintf(ficgp,",\\\n '' ");
8159: }
8160: if(cptcoveff ==0){ /* No covariate */
8161: ioffset=2; /* Age is in 2 */
8162: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8163: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8164: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8165: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8166: fprintf(ficgp," u %d:(", ioffset);
8167: if(i==nlstate+1){
1.270 brouard 8168: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8169: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8170: fprintf(ficgp,",\\\n '' ");
8171: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8172: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8173: offbyear, \
8174: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8175: }else
8176: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8177: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8178: }else{ /* more than 2 covariates */
1.270 brouard 8179: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8180: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8181: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8182: iyearc=ioffset-1;
8183: iagec=ioffset;
1.268 brouard 8184: fprintf(ficgp," u %d:(",ioffset);
8185: kl=0;
8186: strcpy(gplotcondition,"(");
8187: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8188: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8189: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8190: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8191: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8192: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8193: kl++;
8194: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8195: kl++;
8196: if(k <cptcoveff && cptcoveff>1)
8197: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8198: }
8199: strcpy(gplotcondition+strlen(gplotcondition),")");
8200: /* 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 *\/ */
8201: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8202: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8203: /* '' 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*/
8204: if(i==nlstate+1){
1.270 brouard 8205: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8206: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8207: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8208: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8209: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8210: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8211: iyearc,iagec,offbyear, \
8212: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8213: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8214: }else{
8215: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8216: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8217: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8218: }
8219: } /* end if covariate */
8220: } /* nlstate */
8221: fprintf(ficgp,"\nset out; unset label;\n");
8222: } /* end cpt state*/
8223: } /* end covariate */
1.296 brouard 8224: } /* End if prevbcast */
1.268 brouard 8225:
1.227 brouard 8226:
1.238 brouard 8227: /* 9eme writing MLE parameters */
8228: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8229: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8230: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8231: for(k=1; k <=(nlstate+ndeath); k++){
8232: if (k != i) {
1.227 brouard 8233: fprintf(ficgp,"# current state %d\n",k);
8234: for(j=1; j <=ncovmodel; j++){
8235: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8236: jk++;
8237: }
8238: fprintf(ficgp,"\n");
1.126 brouard 8239: }
8240: }
1.223 brouard 8241: }
1.187 brouard 8242: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8243:
1.145 brouard 8244: /*goto avoid;*/
1.238 brouard 8245: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8246: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8247: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8248: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8249: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8250: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8251: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8252: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8253: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8254: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8255: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8256: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8257: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8258: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8259: fprintf(ficgp,"#\n");
1.223 brouard 8260: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8261: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8262: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8263: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8264: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8265: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8266: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8267: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8268: continue;
1.264 brouard 8269: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8270: strcpy(gplotlabel,"(");
1.276 brouard 8271: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8272: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8273: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8274: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8275: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8276: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8277: vlv= nbcode[Tvaraff[k]][lv];
8278: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8279: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8280: }
1.237 brouard 8281: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8282: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8283: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8284: }
1.264 brouard 8285: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8286: fprintf(ficgp,"\n#\n");
1.264 brouard 8287: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8288: fprintf(ficgp,"\nset key outside ");
8289: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8290: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8291: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8292: if (ng==1){
8293: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8294: fprintf(ficgp,"\nunset log y");
8295: }else if (ng==2){
8296: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8297: fprintf(ficgp,"\nset log y");
8298: }else if (ng==3){
8299: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8300: fprintf(ficgp,"\nset log y");
8301: }else
8302: fprintf(ficgp,"\nunset title ");
8303: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8304: i=1;
8305: for(k2=1; k2<=nlstate; k2++) {
8306: k3=i;
8307: for(k=1; k<=(nlstate+ndeath); k++) {
8308: if (k != k2){
8309: switch( ng) {
8310: case 1:
8311: if(nagesqr==0)
8312: fprintf(ficgp," p%d+p%d*x",i,i+1);
8313: else /* nagesqr =1 */
8314: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8315: break;
8316: case 2: /* ng=2 */
8317: if(nagesqr==0)
8318: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8319: else /* nagesqr =1 */
8320: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8321: break;
8322: case 3:
8323: if(nagesqr==0)
8324: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8325: else /* nagesqr =1 */
8326: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8327: break;
8328: }
8329: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8330: ijp=1; /* product no age */
8331: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8332: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8333: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 8334: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8335: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
8336: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8337: if(DummyV[j]==0){
8338: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8339: }else{ /* quantitative */
8340: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8341: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8342: }
8343: ij++;
1.237 brouard 8344: }
1.268 brouard 8345: }
8346: }else if(cptcovprod >0){
8347: if(j==Tprod[ijp]) { /* */
8348: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8349: if(ijp <=cptcovprod) { /* Product */
8350: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8351: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8352: /* 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)]); */
8353: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8354: }else{ /* Vn is dummy and Vm is quanti */
8355: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8356: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8357: }
8358: }else{ /* Vn*Vm Vn is quanti */
8359: if(DummyV[Tvard[ijp][2]]==0){
8360: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8361: }else{ /* Both quanti */
8362: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8363: }
1.237 brouard 8364: }
1.268 brouard 8365: ijp++;
1.237 brouard 8366: }
1.268 brouard 8367: } /* end Tprod */
1.237 brouard 8368: } else{ /* simple covariate */
1.264 brouard 8369: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8370: if(Dummy[j]==0){
8371: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8372: }else{ /* quantitative */
8373: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8374: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8375: }
1.237 brouard 8376: } /* end simple */
8377: } /* end j */
1.223 brouard 8378: }else{
8379: i=i-ncovmodel;
8380: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8381: fprintf(ficgp," (1.");
8382: }
1.227 brouard 8383:
1.223 brouard 8384: if(ng != 1){
8385: fprintf(ficgp,")/(1");
1.227 brouard 8386:
1.264 brouard 8387: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8388: if(nagesqr==0)
1.264 brouard 8389: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8390: else /* nagesqr =1 */
1.264 brouard 8391: 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 8392:
1.223 brouard 8393: ij=1;
8394: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8395: if(cptcovage >0){
8396: if((j-2)==Tage[ij]) { /* Bug valgrind */
8397: if(ij <=cptcovage) { /* Bug valgrind */
8398: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8399: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8400: ij++;
8401: }
8402: }
8403: }else
8404: 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 8405: }
8406: fprintf(ficgp,")");
8407: }
8408: fprintf(ficgp,")");
8409: if(ng ==2)
1.276 brouard 8410: 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 8411: else /* ng= 3 */
1.276 brouard 8412: 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 8413: }else{ /* end ng <> 1 */
8414: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8415: 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 8416: }
8417: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8418: fprintf(ficgp,",");
8419: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8420: fprintf(ficgp,",");
8421: i=i+ncovmodel;
8422: } /* end k */
8423: } /* end k2 */
1.276 brouard 8424: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8425: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8426: } /* end k1 */
1.223 brouard 8427: } /* end ng */
8428: /* avoid: */
8429: fflush(ficgp);
1.126 brouard 8430: } /* end gnuplot */
8431:
8432:
8433: /*************** Moving average **************/
1.219 brouard 8434: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8435: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8436:
1.222 brouard 8437: int i, cpt, cptcod;
8438: int modcovmax =1;
8439: int mobilavrange, mob;
8440: int iage=0;
1.288 brouard 8441: int firstA1=0, firstA2=0;
1.222 brouard 8442:
1.266 brouard 8443: double sum=0., sumr=0.;
1.222 brouard 8444: double age;
1.266 brouard 8445: double *sumnewp, *sumnewm, *sumnewmr;
8446: double *agemingood, *agemaxgood;
8447: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8448:
8449:
1.278 brouard 8450: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8451: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8452:
8453: sumnewp = vector(1,ncovcombmax);
8454: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8455: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8456: agemingood = vector(1,ncovcombmax);
1.266 brouard 8457: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8458: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8459: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8460:
8461: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8462: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8463: sumnewp[cptcod]=0.;
1.266 brouard 8464: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8465: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8466: }
8467: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8468:
1.266 brouard 8469: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8470: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8471: else mobilavrange=mobilav;
8472: for (age=bage; age<=fage; age++)
8473: for (i=1; i<=nlstate;i++)
8474: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8475: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8476: /* We keep the original values on the extreme ages bage, fage and for
8477: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8478: we use a 5 terms etc. until the borders are no more concerned.
8479: */
8480: for (mob=3;mob <=mobilavrange;mob=mob+2){
8481: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8482: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8483: sumnewm[cptcod]=0.;
8484: for (i=1; i<=nlstate;i++){
1.222 brouard 8485: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8486: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8487: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8488: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8489: }
8490: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8491: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8492: } /* end i */
8493: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8494: } /* end cptcod */
1.222 brouard 8495: }/* end age */
8496: }/* end mob */
1.266 brouard 8497: }else{
8498: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8499: return -1;
1.266 brouard 8500: }
8501:
8502: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8503: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8504: if(invalidvarcomb[cptcod]){
8505: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8506: continue;
8507: }
1.219 brouard 8508:
1.266 brouard 8509: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8510: sumnewm[cptcod]=0.;
8511: sumnewmr[cptcod]=0.;
8512: for (i=1; i<=nlstate;i++){
8513: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8514: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8515: }
8516: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8517: agemingoodr[cptcod]=age;
8518: }
8519: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8520: agemingood[cptcod]=age;
8521: }
8522: } /* age */
8523: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8524: sumnewm[cptcod]=0.;
1.266 brouard 8525: sumnewmr[cptcod]=0.;
1.222 brouard 8526: for (i=1; i<=nlstate;i++){
8527: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8528: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8529: }
8530: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8531: agemaxgoodr[cptcod]=age;
1.222 brouard 8532: }
8533: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8534: agemaxgood[cptcod]=age;
8535: }
8536: } /* age */
8537: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8538: /* but they will change */
1.288 brouard 8539: firstA1=0;firstA2=0;
1.266 brouard 8540: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8541: sumnewm[cptcod]=0.;
8542: sumnewmr[cptcod]=0.;
8543: for (i=1; i<=nlstate;i++){
8544: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8545: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8546: }
8547: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8548: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8549: agemaxgoodr[cptcod]=age; /* age min */
8550: for (i=1; i<=nlstate;i++)
8551: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8552: }else{ /* bad we change the value with the values of good ages */
8553: for (i=1; i<=nlstate;i++){
8554: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8555: } /* i */
8556: } /* end bad */
8557: }else{
8558: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8559: agemaxgood[cptcod]=age;
8560: }else{ /* bad we change the value with the values of good ages */
8561: for (i=1; i<=nlstate;i++){
8562: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8563: } /* i */
8564: } /* end bad */
8565: }/* end else */
8566: sum=0.;sumr=0.;
8567: for (i=1; i<=nlstate;i++){
8568: sum+=mobaverage[(int)age][i][cptcod];
8569: sumr+=probs[(int)age][i][cptcod];
8570: }
8571: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8572: if(!firstA1){
8573: firstA1=1;
8574: 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);
8575: }
8576: 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 8577: } /* end bad */
8578: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8579: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8580: if(!firstA2){
8581: firstA2=1;
8582: 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);
8583: }
8584: 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 8585: } /* end bad */
8586: }/* age */
1.266 brouard 8587:
8588: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8589: sumnewm[cptcod]=0.;
1.266 brouard 8590: sumnewmr[cptcod]=0.;
1.222 brouard 8591: for (i=1; i<=nlstate;i++){
8592: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8593: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8594: }
8595: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8596: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8597: agemingoodr[cptcod]=age;
8598: for (i=1; i<=nlstate;i++)
8599: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8600: }else{ /* bad we change the value with the values of good ages */
8601: for (i=1; i<=nlstate;i++){
8602: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8603: } /* i */
8604: } /* end bad */
8605: }else{
8606: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8607: agemingood[cptcod]=age;
8608: }else{ /* bad */
8609: for (i=1; i<=nlstate;i++){
8610: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8611: } /* i */
8612: } /* end bad */
8613: }/* end else */
8614: sum=0.;sumr=0.;
8615: for (i=1; i<=nlstate;i++){
8616: sum+=mobaverage[(int)age][i][cptcod];
8617: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8618: }
1.266 brouard 8619: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8620: 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 8621: } /* end bad */
8622: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8623: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8624: 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 8625: } /* end bad */
8626: }/* age */
1.266 brouard 8627:
1.222 brouard 8628:
8629: for (age=bage; age<=fage; age++){
1.235 brouard 8630: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8631: sumnewp[cptcod]=0.;
8632: sumnewm[cptcod]=0.;
8633: for (i=1; i<=nlstate;i++){
8634: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8635: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8636: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8637: }
8638: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8639: }
8640: /* printf("\n"); */
8641: /* } */
1.266 brouard 8642:
1.222 brouard 8643: /* brutal averaging */
1.266 brouard 8644: /* for (i=1; i<=nlstate;i++){ */
8645: /* for (age=1; age<=bage; age++){ */
8646: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8647: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8648: /* } */
8649: /* for (age=fage; age<=AGESUP; age++){ */
8650: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8651: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8652: /* } */
8653: /* } /\* end i status *\/ */
8654: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8655: /* for (age=1; age<=AGESUP; age++){ */
8656: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8657: /* mobaverage[(int)age][i][cptcod]=0.; */
8658: /* } */
8659: /* } */
1.222 brouard 8660: }/* end cptcod */
1.266 brouard 8661: free_vector(agemaxgoodr,1, ncovcombmax);
8662: free_vector(agemaxgood,1, ncovcombmax);
8663: free_vector(agemingood,1, ncovcombmax);
8664: free_vector(agemingoodr,1, ncovcombmax);
8665: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8666: free_vector(sumnewm,1, ncovcombmax);
8667: free_vector(sumnewp,1, ncovcombmax);
8668: return 0;
8669: }/* End movingaverage */
1.218 brouard 8670:
1.126 brouard 8671:
1.296 brouard 8672:
1.126 brouard 8673: /************** Forecasting ******************/
1.296 brouard 8674: /* 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)*/
8675: 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){
8676: /* dateintemean, mean date of interviews
8677: dateprojd, year, month, day of starting projection
8678: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8679: agemin, agemax range of age
8680: dateprev1 dateprev2 range of dates during which prevalence is computed
8681: */
1.296 brouard 8682: /* double anprojd, mprojd, jprojd; */
8683: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8684: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8685: double agec; /* generic age */
1.296 brouard 8686: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8687: double *popeffectif,*popcount;
8688: double ***p3mat;
1.218 brouard 8689: /* double ***mobaverage; */
1.126 brouard 8690: char fileresf[FILENAMELENGTH];
8691:
8692: agelim=AGESUP;
1.211 brouard 8693: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8694: in each health status at the date of interview (if between dateprev1 and dateprev2).
8695: We still use firstpass and lastpass as another selection.
8696: */
1.214 brouard 8697: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8698: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8699:
1.201 brouard 8700: strcpy(fileresf,"F_");
8701: strcat(fileresf,fileresu);
1.126 brouard 8702: if((ficresf=fopen(fileresf,"w"))==NULL) {
8703: printf("Problem with forecast resultfile: %s\n", fileresf);
8704: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8705: }
1.235 brouard 8706: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8707: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8708:
1.225 brouard 8709: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8710:
8711:
8712: stepsize=(int) (stepm+YEARM-1)/YEARM;
8713: if (stepm<=12) stepsize=1;
8714: if(estepm < stepm){
8715: printf ("Problem %d lower than %d\n",estepm, stepm);
8716: }
1.270 brouard 8717: else{
8718: hstepm=estepm;
8719: }
8720: if(estepm > stepm){ /* Yes every two year */
8721: stepsize=2;
8722: }
1.296 brouard 8723: hstepm=hstepm/stepm;
1.126 brouard 8724:
1.296 brouard 8725:
8726: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8727: /* fractional in yp1 *\/ */
8728: /* aintmean=yp; */
8729: /* yp2=modf((yp1*12),&yp); */
8730: /* mintmean=yp; */
8731: /* yp1=modf((yp2*30.5),&yp); */
8732: /* jintmean=yp; */
8733: /* if(jintmean==0) jintmean=1; */
8734: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8735:
1.296 brouard 8736:
8737: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8738: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8739: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8740: i1=pow(2,cptcoveff);
1.126 brouard 8741: if (cptcovn < 1){i1=1;}
8742:
1.296 brouard 8743: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8744:
8745: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8746:
1.126 brouard 8747: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8748: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8749: for(k=1; k<=i1;k++){
1.253 brouard 8750: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8751: continue;
1.227 brouard 8752: if(invalidvarcomb[k]){
8753: printf("\nCombination (%d) projection ignored because no cases \n",k);
8754: continue;
8755: }
8756: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8757: for(j=1;j<=cptcoveff;j++) {
8758: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8759: }
1.235 brouard 8760: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8761: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8762: }
1.227 brouard 8763: fprintf(ficresf," yearproj age");
8764: for(j=1; j<=nlstate+ndeath;j++){
8765: for(i=1; i<=nlstate;i++)
8766: fprintf(ficresf," p%d%d",i,j);
8767: fprintf(ficresf," wp.%d",j);
8768: }
1.296 brouard 8769: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8770: fprintf(ficresf,"\n");
1.296 brouard 8771: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8772: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8773: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8774: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8775: nhstepm = nhstepm/hstepm;
8776: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8777: oldm=oldms;savm=savms;
1.268 brouard 8778: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8779: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8780: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8781: for (h=0; h<=nhstepm; h++){
8782: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8783: break;
8784: }
8785: }
8786: fprintf(ficresf,"\n");
8787: for(j=1;j<=cptcoveff;j++)
8788: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8789: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8790:
8791: for(j=1; j<=nlstate+ndeath;j++) {
8792: ppij=0.;
8793: for(i=1; i<=nlstate;i++) {
1.278 brouard 8794: if (mobilav>=1)
8795: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8796: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8797: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8798: }
1.268 brouard 8799: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8800: } /* end i */
8801: fprintf(ficresf," %.3f", ppij);
8802: }/* end j */
1.227 brouard 8803: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8804: } /* end agec */
1.266 brouard 8805: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8806: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8807: } /* end yearp */
8808: } /* end k */
1.219 brouard 8809:
1.126 brouard 8810: fclose(ficresf);
1.215 brouard 8811: printf("End of Computing forecasting \n");
8812: fprintf(ficlog,"End of Computing forecasting\n");
8813:
1.126 brouard 8814: }
8815:
1.269 brouard 8816: /************** Back Forecasting ******************/
1.296 brouard 8817: /* 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){ */
8818: 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){
8819: /* back1, year, month, day of starting backprojection
1.267 brouard 8820: agemin, agemax range of age
8821: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8822: anback2 year of end of backprojection (same day and month as back1).
8823: prevacurrent and prev are prevalences.
1.267 brouard 8824: */
8825: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8826: double agec; /* generic age */
1.302 brouard 8827: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 8828: double *popeffectif,*popcount;
8829: double ***p3mat;
8830: /* double ***mobaverage; */
8831: char fileresfb[FILENAMELENGTH];
8832:
1.268 brouard 8833: agelim=AGEINF;
1.267 brouard 8834: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8835: in each health status at the date of interview (if between dateprev1 and dateprev2).
8836: We still use firstpass and lastpass as another selection.
8837: */
8838: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8839: /* firstpass, lastpass, stepm, weightopt, model); */
8840:
8841: /*Do we need to compute prevalence again?*/
8842:
8843: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8844:
8845: strcpy(fileresfb,"FB_");
8846: strcat(fileresfb,fileresu);
8847: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8848: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8849: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8850: }
8851: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8852: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8853:
8854: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8855:
8856:
8857: stepsize=(int) (stepm+YEARM-1)/YEARM;
8858: if (stepm<=12) stepsize=1;
8859: if(estepm < stepm){
8860: printf ("Problem %d lower than %d\n",estepm, stepm);
8861: }
1.270 brouard 8862: else{
8863: hstepm=estepm;
8864: }
8865: if(estepm >= stepm){ /* Yes every two year */
8866: stepsize=2;
8867: }
1.267 brouard 8868:
8869: hstepm=hstepm/stepm;
1.296 brouard 8870: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8871: /* fractional in yp1 *\/ */
8872: /* aintmean=yp; */
8873: /* yp2=modf((yp1*12),&yp); */
8874: /* mintmean=yp; */
8875: /* yp1=modf((yp2*30.5),&yp); */
8876: /* jintmean=yp; */
8877: /* if(jintmean==0) jintmean=1; */
8878: /* if(mintmean==0) jintmean=1; */
1.267 brouard 8879:
8880: i1=pow(2,cptcoveff);
8881: if (cptcovn < 1){i1=1;}
8882:
1.296 brouard 8883: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
8884: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8885:
8886: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8887:
8888: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8889: for(k=1; k<=i1;k++){
8890: if(i1 != 1 && TKresult[nres]!= k)
8891: continue;
8892: if(invalidvarcomb[k]){
8893: printf("\nCombination (%d) projection ignored because no cases \n",k);
8894: continue;
8895: }
1.268 brouard 8896: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8897: for(j=1;j<=cptcoveff;j++) {
8898: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8899: }
8900: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8901: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8902: }
8903: fprintf(ficresfb," yearbproj age");
8904: for(j=1; j<=nlstate+ndeath;j++){
8905: for(i=1; i<=nlstate;i++)
1.268 brouard 8906: fprintf(ficresfb," b%d%d",i,j);
8907: fprintf(ficresfb," b.%d",j);
1.267 brouard 8908: }
1.296 brouard 8909: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 8910: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8911: fprintf(ficresfb,"\n");
1.296 brouard 8912: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 8913: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8914: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8915: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8916: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8917: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8918: nhstepm = nhstepm/hstepm;
8919: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8920: oldm=oldms;savm=savms;
1.268 brouard 8921: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8922: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8923: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8924: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8925: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8926: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8927: for (h=0; h<=nhstepm; h++){
1.268 brouard 8928: if (h*hstepm/YEARM*stepm ==-yearp) {
8929: break;
8930: }
8931: }
8932: fprintf(ficresfb,"\n");
8933: for(j=1;j<=cptcoveff;j++)
8934: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8935: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 8936: for(i=1; i<=nlstate+ndeath;i++) {
8937: ppij=0.;ppi=0.;
8938: for(j=1; j<=nlstate;j++) {
8939: /* if (mobilav==1) */
1.269 brouard 8940: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8941: ppi=ppi+prevacurrent[(int)agec][j][k];
8942: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8943: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8944: /* else { */
8945: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8946: /* } */
1.268 brouard 8947: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8948: } /* end j */
8949: if(ppi <0.99){
8950: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8951: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8952: }
8953: fprintf(ficresfb," %.3f", ppij);
8954: }/* end j */
1.267 brouard 8955: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8956: } /* end agec */
8957: } /* end yearp */
8958: } /* end k */
1.217 brouard 8959:
1.267 brouard 8960: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8961:
1.267 brouard 8962: fclose(ficresfb);
8963: printf("End of Computing Back forecasting \n");
8964: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8965:
1.267 brouard 8966: }
1.217 brouard 8967:
1.269 brouard 8968: /* Variance of prevalence limit: varprlim */
8969: 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 8970: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8971:
8972: char fileresvpl[FILENAMELENGTH];
8973: FILE *ficresvpl;
8974: double **oldm, **savm;
8975: double **varpl; /* Variances of prevalence limits by age */
8976: int i1, k, nres, j ;
8977:
8978: strcpy(fileresvpl,"VPL_");
8979: strcat(fileresvpl,fileresu);
8980: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8981: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8982: exit(0);
8983: }
1.288 brouard 8984: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8985: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8986:
8987: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8988: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8989:
8990: i1=pow(2,cptcoveff);
8991: if (cptcovn < 1){i1=1;}
8992:
8993: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8994: for(k=1; k<=i1;k++){
8995: if(i1 != 1 && TKresult[nres]!= k)
8996: continue;
8997: fprintf(ficresvpl,"\n#****** ");
8998: printf("\n#****** ");
8999: fprintf(ficlog,"\n#****** ");
9000: for(j=1;j<=cptcoveff;j++) {
9001: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9002: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9003: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9004: }
9005: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9006: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9007: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9008: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9009: }
9010: fprintf(ficresvpl,"******\n");
9011: printf("******\n");
9012: fprintf(ficlog,"******\n");
9013:
9014: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9015: oldm=oldms;savm=savms;
9016: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9017: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9018: /*}*/
9019: }
9020:
9021: fclose(ficresvpl);
1.288 brouard 9022: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9023: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9024:
9025: }
9026: /* Variance of back prevalence: varbprlim */
9027: 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){
9028: /*------- Variance of back (stable) prevalence------*/
9029:
9030: char fileresvbl[FILENAMELENGTH];
9031: FILE *ficresvbl;
9032:
9033: double **oldm, **savm;
9034: double **varbpl; /* Variances of back prevalence limits by age */
9035: int i1, k, nres, j ;
9036:
9037: strcpy(fileresvbl,"VBL_");
9038: strcat(fileresvbl,fileresu);
9039: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9040: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9041: exit(0);
9042: }
9043: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9044: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9045:
9046:
9047: i1=pow(2,cptcoveff);
9048: if (cptcovn < 1){i1=1;}
9049:
9050: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9051: for(k=1; k<=i1;k++){
9052: if(i1 != 1 && TKresult[nres]!= k)
9053: continue;
9054: fprintf(ficresvbl,"\n#****** ");
9055: printf("\n#****** ");
9056: fprintf(ficlog,"\n#****** ");
9057: for(j=1;j<=cptcoveff;j++) {
9058: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9059: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9060: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9061: }
9062: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9063: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9064: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9065: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9066: }
9067: fprintf(ficresvbl,"******\n");
9068: printf("******\n");
9069: fprintf(ficlog,"******\n");
9070:
9071: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9072: oldm=oldms;savm=savms;
9073:
9074: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9075: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9076: /*}*/
9077: }
9078:
9079: fclose(ficresvbl);
9080: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9081: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9082:
9083: } /* End of varbprlim */
9084:
1.126 brouard 9085: /************** Forecasting *****not tested NB*************/
1.227 brouard 9086: /* 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 9087:
1.227 brouard 9088: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9089: /* int *popage; */
9090: /* double calagedatem, agelim, kk1, kk2; */
9091: /* double *popeffectif,*popcount; */
9092: /* double ***p3mat,***tabpop,***tabpopprev; */
9093: /* /\* double ***mobaverage; *\/ */
9094: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9095:
1.227 brouard 9096: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9097: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9098: /* agelim=AGESUP; */
9099: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9100:
1.227 brouard 9101: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9102:
9103:
1.227 brouard 9104: /* strcpy(filerespop,"POP_"); */
9105: /* strcat(filerespop,fileresu); */
9106: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9107: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9108: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9109: /* } */
9110: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9111: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9112:
1.227 brouard 9113: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9114:
1.227 brouard 9115: /* /\* if (mobilav!=0) { *\/ */
9116: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9117: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9118: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9119: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9120: /* /\* } *\/ */
9121: /* /\* } *\/ */
1.126 brouard 9122:
1.227 brouard 9123: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9124: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9125:
1.227 brouard 9126: /* agelim=AGESUP; */
1.126 brouard 9127:
1.227 brouard 9128: /* hstepm=1; */
9129: /* hstepm=hstepm/stepm; */
1.218 brouard 9130:
1.227 brouard 9131: /* if (popforecast==1) { */
9132: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9133: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9134: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9135: /* } */
9136: /* popage=ivector(0,AGESUP); */
9137: /* popeffectif=vector(0,AGESUP); */
9138: /* popcount=vector(0,AGESUP); */
1.126 brouard 9139:
1.227 brouard 9140: /* i=1; */
9141: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9142:
1.227 brouard 9143: /* imx=i; */
9144: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9145: /* } */
1.218 brouard 9146:
1.227 brouard 9147: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9148: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9149: /* k=k+1; */
9150: /* fprintf(ficrespop,"\n#******"); */
9151: /* for(j=1;j<=cptcoveff;j++) { */
9152: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9153: /* } */
9154: /* fprintf(ficrespop,"******\n"); */
9155: /* fprintf(ficrespop,"# Age"); */
9156: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9157: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9158:
1.227 brouard 9159: /* for (cpt=0; cpt<=0;cpt++) { */
9160: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9161:
1.227 brouard 9162: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9163: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9164: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9165:
1.227 brouard 9166: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9167: /* oldm=oldms;savm=savms; */
9168: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9169:
1.227 brouard 9170: /* for (h=0; h<=nhstepm; h++){ */
9171: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9172: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9173: /* } */
9174: /* for(j=1; j<=nlstate+ndeath;j++) { */
9175: /* kk1=0.;kk2=0; */
9176: /* for(i=1; i<=nlstate;i++) { */
9177: /* if (mobilav==1) */
9178: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9179: /* else { */
9180: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9181: /* } */
9182: /* } */
9183: /* if (h==(int)(calagedatem+12*cpt)){ */
9184: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9185: /* /\*fprintf(ficrespop," %.3f", kk1); */
9186: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9187: /* } */
9188: /* } */
9189: /* for(i=1; i<=nlstate;i++){ */
9190: /* kk1=0.; */
9191: /* for(j=1; j<=nlstate;j++){ */
9192: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9193: /* } */
9194: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9195: /* } */
1.218 brouard 9196:
1.227 brouard 9197: /* if (h==(int)(calagedatem+12*cpt)) */
9198: /* for(j=1; j<=nlstate;j++) */
9199: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9200: /* } */
9201: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9202: /* } */
9203: /* } */
1.218 brouard 9204:
1.227 brouard 9205: /* /\******\/ */
1.218 brouard 9206:
1.227 brouard 9207: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9208: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9209: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9210: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9211: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9212:
1.227 brouard 9213: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9214: /* oldm=oldms;savm=savms; */
9215: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9216: /* for (h=0; h<=nhstepm; h++){ */
9217: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9218: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9219: /* } */
9220: /* for(j=1; j<=nlstate+ndeath;j++) { */
9221: /* kk1=0.;kk2=0; */
9222: /* for(i=1; i<=nlstate;i++) { */
9223: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9224: /* } */
9225: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9226: /* } */
9227: /* } */
9228: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9229: /* } */
9230: /* } */
9231: /* } */
9232: /* } */
1.218 brouard 9233:
1.227 brouard 9234: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9235:
1.227 brouard 9236: /* if (popforecast==1) { */
9237: /* free_ivector(popage,0,AGESUP); */
9238: /* free_vector(popeffectif,0,AGESUP); */
9239: /* free_vector(popcount,0,AGESUP); */
9240: /* } */
9241: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9242: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9243: /* fclose(ficrespop); */
9244: /* } /\* End of popforecast *\/ */
1.218 brouard 9245:
1.126 brouard 9246: int fileappend(FILE *fichier, char *optionfich)
9247: {
9248: if((fichier=fopen(optionfich,"a"))==NULL) {
9249: printf("Problem with file: %s\n", optionfich);
9250: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9251: return (0);
9252: }
9253: fflush(fichier);
9254: return (1);
9255: }
9256:
9257:
9258: /**************** function prwizard **********************/
9259: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9260: {
9261:
9262: /* Wizard to print covariance matrix template */
9263:
1.164 brouard 9264: char ca[32], cb[32];
9265: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9266: int numlinepar;
9267:
9268: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9269: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9270: for(i=1; i <=nlstate; i++){
9271: jj=0;
9272: for(j=1; j <=nlstate+ndeath; j++){
9273: if(j==i) continue;
9274: jj++;
9275: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9276: printf("%1d%1d",i,j);
9277: fprintf(ficparo,"%1d%1d",i,j);
9278: for(k=1; k<=ncovmodel;k++){
9279: /* printf(" %lf",param[i][j][k]); */
9280: /* fprintf(ficparo," %lf",param[i][j][k]); */
9281: printf(" 0.");
9282: fprintf(ficparo," 0.");
9283: }
9284: printf("\n");
9285: fprintf(ficparo,"\n");
9286: }
9287: }
9288: printf("# Scales (for hessian or gradient estimation)\n");
9289: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9290: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9291: for(i=1; i <=nlstate; i++){
9292: jj=0;
9293: for(j=1; j <=nlstate+ndeath; j++){
9294: if(j==i) continue;
9295: jj++;
9296: fprintf(ficparo,"%1d%1d",i,j);
9297: printf("%1d%1d",i,j);
9298: fflush(stdout);
9299: for(k=1; k<=ncovmodel;k++){
9300: /* printf(" %le",delti3[i][j][k]); */
9301: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9302: printf(" 0.");
9303: fprintf(ficparo," 0.");
9304: }
9305: numlinepar++;
9306: printf("\n");
9307: fprintf(ficparo,"\n");
9308: }
9309: }
9310: printf("# Covariance matrix\n");
9311: /* # 121 Var(a12)\n\ */
9312: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9313: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9314: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9315: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9316: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9317: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9318: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9319: fflush(stdout);
9320: fprintf(ficparo,"# Covariance matrix\n");
9321: /* # 121 Var(a12)\n\ */
9322: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9323: /* # ...\n\ */
9324: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9325:
9326: for(itimes=1;itimes<=2;itimes++){
9327: jj=0;
9328: for(i=1; i <=nlstate; i++){
9329: for(j=1; j <=nlstate+ndeath; j++){
9330: if(j==i) continue;
9331: for(k=1; k<=ncovmodel;k++){
9332: jj++;
9333: ca[0]= k+'a'-1;ca[1]='\0';
9334: if(itimes==1){
9335: printf("#%1d%1d%d",i,j,k);
9336: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9337: }else{
9338: printf("%1d%1d%d",i,j,k);
9339: fprintf(ficparo,"%1d%1d%d",i,j,k);
9340: /* printf(" %.5le",matcov[i][j]); */
9341: }
9342: ll=0;
9343: for(li=1;li <=nlstate; li++){
9344: for(lj=1;lj <=nlstate+ndeath; lj++){
9345: if(lj==li) continue;
9346: for(lk=1;lk<=ncovmodel;lk++){
9347: ll++;
9348: if(ll<=jj){
9349: cb[0]= lk +'a'-1;cb[1]='\0';
9350: if(ll<jj){
9351: if(itimes==1){
9352: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9353: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9354: }else{
9355: printf(" 0.");
9356: fprintf(ficparo," 0.");
9357: }
9358: }else{
9359: if(itimes==1){
9360: printf(" Var(%s%1d%1d)",ca,i,j);
9361: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9362: }else{
9363: printf(" 0.");
9364: fprintf(ficparo," 0.");
9365: }
9366: }
9367: }
9368: } /* end lk */
9369: } /* end lj */
9370: } /* end li */
9371: printf("\n");
9372: fprintf(ficparo,"\n");
9373: numlinepar++;
9374: } /* end k*/
9375: } /*end j */
9376: } /* end i */
9377: } /* end itimes */
9378:
9379: } /* end of prwizard */
9380: /******************* Gompertz Likelihood ******************************/
9381: double gompertz(double x[])
9382: {
1.302 brouard 9383: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9384: int i,n=0; /* n is the size of the sample */
9385:
1.220 brouard 9386: for (i=1;i<=imx ; i++) {
1.126 brouard 9387: sump=sump+weight[i];
9388: /* sump=sump+1;*/
9389: num=num+1;
9390: }
1.302 brouard 9391: L=0.0;
9392: /* agegomp=AGEGOMP; */
1.126 brouard 9393: /* for (i=0; i<=imx; i++)
9394: 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]);*/
9395:
1.302 brouard 9396: for (i=1;i<=imx ; i++) {
9397: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9398: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9399: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9400: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9401: * +
9402: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9403: */
9404: if (wav[i] > 1 || agedc[i] < AGESUP) {
9405: if (cens[i] == 1){
9406: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9407: } else if (cens[i] == 0){
1.126 brouard 9408: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9409: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9410: } else
9411: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9412: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9413: L=L+A*weight[i];
1.126 brouard 9414: /* 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 9415: }
9416: }
1.126 brouard 9417:
1.302 brouard 9418: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9419:
9420: return -2*L*num/sump;
9421: }
9422:
1.136 brouard 9423: #ifdef GSL
9424: /******************* Gompertz_f Likelihood ******************************/
9425: double gompertz_f(const gsl_vector *v, void *params)
9426: {
1.302 brouard 9427: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9428: double *x= (double *) v->data;
9429: int i,n=0; /* n is the size of the sample */
9430:
9431: for (i=0;i<=imx-1 ; i++) {
9432: sump=sump+weight[i];
9433: /* sump=sump+1;*/
9434: num=num+1;
9435: }
9436:
9437:
9438: /* for (i=0; i<=imx; i++)
9439: 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]);*/
9440: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9441: for (i=1;i<=imx ; i++)
9442: {
9443: if (cens[i] == 1 && wav[i]>1)
9444: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9445:
9446: if (cens[i] == 0 && wav[i]>1)
9447: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9448: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9449:
9450: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9451: if (wav[i] > 1 ) { /* ??? */
9452: LL=LL+A*weight[i];
9453: /* 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]);*/
9454: }
9455: }
9456:
9457: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9458: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9459:
9460: return -2*LL*num/sump;
9461: }
9462: #endif
9463:
1.126 brouard 9464: /******************* Printing html file ***********/
1.201 brouard 9465: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9466: int lastpass, int stepm, int weightopt, char model[],\
9467: int imx, double p[],double **matcov,double agemortsup){
9468: int i,k;
9469:
9470: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9471: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9472: for (i=1;i<=2;i++)
9473: 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 9474: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9475: fprintf(fichtm,"</ul>");
9476:
9477: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9478:
9479: 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>");
9480:
9481: for (k=agegomp;k<(agemortsup-2);k++)
9482: 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]);
9483:
9484:
9485: fflush(fichtm);
9486: }
9487:
9488: /******************* Gnuplot file **************/
1.201 brouard 9489: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9490:
9491: char dirfileres[132],optfileres[132];
1.164 brouard 9492:
1.126 brouard 9493: int ng;
9494:
9495:
9496: /*#ifdef windows */
9497: fprintf(ficgp,"cd \"%s\" \n",pathc);
9498: /*#endif */
9499:
9500:
9501: strcpy(dirfileres,optionfilefiname);
9502: strcpy(optfileres,"vpl");
1.199 brouard 9503: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9504: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9505: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9506: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9507: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9508:
9509: }
9510:
1.136 brouard 9511: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9512: {
1.126 brouard 9513:
1.136 brouard 9514: /*-------- data file ----------*/
9515: FILE *fic;
9516: char dummy[]=" ";
1.240 brouard 9517: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9518: int lstra;
1.136 brouard 9519: int linei, month, year,iout;
1.302 brouard 9520: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9521: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9522: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9523: char *stratrunc;
1.223 brouard 9524:
1.240 brouard 9525: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9526: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9527:
1.240 brouard 9528: for(v=1; v <=ncovcol;v++){
9529: DummyV[v]=0;
9530: FixedV[v]=0;
9531: }
9532: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9533: DummyV[v]=1;
9534: FixedV[v]=0;
9535: }
9536: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9537: DummyV[v]=0;
9538: FixedV[v]=1;
9539: }
9540: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9541: DummyV[v]=1;
9542: FixedV[v]=1;
9543: }
9544: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9545: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9546: 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]);
9547: }
1.126 brouard 9548:
1.136 brouard 9549: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9550: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9551: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9552: }
1.126 brouard 9553:
1.302 brouard 9554: /* Is it a BOM UTF-8 Windows file? */
9555: /* First data line */
9556: linei=0;
9557: while(fgets(line, MAXLINE, fic)) {
9558: noffset=0;
9559: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9560: {
9561: noffset=noffset+3;
9562: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9563: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9564: fflush(ficlog); return 1;
9565: }
9566: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9567: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9568: {
9569: noffset=noffset+2;
1.304 brouard 9570: 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);
9571: 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 9572: fflush(ficlog); return 1;
9573: }
9574: else if( line[0] == 0 && line[1] == 0)
9575: {
9576: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9577: noffset=noffset+4;
1.304 brouard 9578: 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);
9579: 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 9580: fflush(ficlog); return 1;
9581: }
9582: } else{
9583: ;/*printf(" Not a BOM file\n");*/
9584: }
9585: /* If line starts with a # it is a comment */
9586: if (line[noffset] == '#') {
9587: linei=linei+1;
9588: break;
9589: }else{
9590: break;
9591: }
9592: }
9593: fclose(fic);
9594: if((fic=fopen(datafile,"r"))==NULL) {
9595: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9596: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9597: }
9598: /* Not a Bom file */
9599:
1.136 brouard 9600: i=1;
9601: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9602: linei=linei+1;
9603: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9604: if(line[j] == '\t')
9605: line[j] = ' ';
9606: }
9607: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9608: ;
9609: };
9610: line[j+1]=0; /* Trims blanks at end of line */
9611: if(line[0]=='#'){
9612: fprintf(ficlog,"Comment line\n%s\n",line);
9613: printf("Comment line\n%s\n",line);
9614: continue;
9615: }
9616: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9617: strcpy(line, linetmp);
1.223 brouard 9618:
9619: /* Loops on waves */
9620: for (j=maxwav;j>=1;j--){
9621: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9622: cutv(stra, strb, line, ' ');
9623: if(strb[0]=='.') { /* Missing value */
9624: lval=-1;
9625: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9626: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9627: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9628: 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);
9629: 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);
9630: return 1;
9631: }
9632: }else{
9633: errno=0;
9634: /* what_kind_of_number(strb); */
9635: dval=strtod(strb,&endptr);
9636: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9637: /* if(strb != endptr && *endptr == '\0') */
9638: /* dval=dlval; */
9639: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9640: if( strb[0]=='\0' || (*endptr != '\0')){
9641: 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);
9642: 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);
9643: return 1;
9644: }
9645: cotqvar[j][iv][i]=dval;
9646: cotvar[j][ntv+iv][i]=dval;
9647: }
9648: strcpy(line,stra);
1.223 brouard 9649: }/* end loop ntqv */
1.225 brouard 9650:
1.223 brouard 9651: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9652: cutv(stra, strb, line, ' ');
9653: if(strb[0]=='.') { /* Missing value */
9654: lval=-1;
9655: }else{
9656: errno=0;
9657: lval=strtol(strb,&endptr,10);
9658: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9659: if( strb[0]=='\0' || (*endptr != '\0')){
9660: 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);
9661: 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);
9662: return 1;
9663: }
9664: }
9665: if(lval <-1 || lval >1){
9666: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9667: 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 9668: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9669: For example, for multinomial values like 1, 2 and 3,\n \
9670: build V1=0 V2=0 for the reference value (1),\n \
9671: V1=1 V2=0 for (2) \n \
1.223 brouard 9672: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9673: output of IMaCh is often meaningless.\n \
1.319 brouard 9674: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 9675: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9676: 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 9677: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9678: For example, for multinomial values like 1, 2 and 3,\n \
9679: build V1=0 V2=0 for the reference value (1),\n \
9680: V1=1 V2=0 for (2) \n \
1.223 brouard 9681: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9682: output of IMaCh is often meaningless.\n \
1.319 brouard 9683: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 9684: return 1;
9685: }
9686: cotvar[j][iv][i]=(double)(lval);
9687: strcpy(line,stra);
1.223 brouard 9688: }/* end loop ntv */
1.225 brouard 9689:
1.223 brouard 9690: /* Statuses at wave */
1.137 brouard 9691: cutv(stra, strb, line, ' ');
1.223 brouard 9692: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9693: lval=-1;
1.136 brouard 9694: }else{
1.238 brouard 9695: errno=0;
9696: lval=strtol(strb,&endptr,10);
9697: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9698: if( strb[0]=='\0' || (*endptr != '\0')){
9699: 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);
9700: 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);
9701: return 1;
9702: }
1.136 brouard 9703: }
1.225 brouard 9704:
1.136 brouard 9705: s[j][i]=lval;
1.225 brouard 9706:
1.223 brouard 9707: /* Date of Interview */
1.136 brouard 9708: strcpy(line,stra);
9709: cutv(stra, strb,line,' ');
1.169 brouard 9710: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9711: }
1.169 brouard 9712: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9713: month=99;
9714: year=9999;
1.136 brouard 9715: }else{
1.225 brouard 9716: 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);
9717: 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);
9718: return 1;
1.136 brouard 9719: }
9720: anint[j][i]= (double) year;
1.302 brouard 9721: mint[j][i]= (double)month;
9722: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
9723: /* 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]); */
9724: /* 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]); */
9725: /* } */
1.136 brouard 9726: strcpy(line,stra);
1.223 brouard 9727: } /* End loop on waves */
1.225 brouard 9728:
1.223 brouard 9729: /* Date of death */
1.136 brouard 9730: cutv(stra, strb,line,' ');
1.169 brouard 9731: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9732: }
1.169 brouard 9733: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9734: month=99;
9735: year=9999;
9736: }else{
1.141 brouard 9737: 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 9738: 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);
9739: return 1;
1.136 brouard 9740: }
9741: andc[i]=(double) year;
9742: moisdc[i]=(double) month;
9743: strcpy(line,stra);
9744:
1.223 brouard 9745: /* Date of birth */
1.136 brouard 9746: cutv(stra, strb,line,' ');
1.169 brouard 9747: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9748: }
1.169 brouard 9749: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9750: month=99;
9751: year=9999;
9752: }else{
1.141 brouard 9753: 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);
9754: 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 9755: return 1;
1.136 brouard 9756: }
9757: if (year==9999) {
1.141 brouard 9758: 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);
9759: 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 9760: return 1;
9761:
1.136 brouard 9762: }
9763: annais[i]=(double)(year);
1.302 brouard 9764: moisnais[i]=(double)(month);
9765: for (j=1;j<=maxwav;j++){
9766: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
9767: 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]);
9768: 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]);
9769: }
9770: }
9771:
1.136 brouard 9772: strcpy(line,stra);
1.225 brouard 9773:
1.223 brouard 9774: /* Sample weight */
1.136 brouard 9775: cutv(stra, strb,line,' ');
9776: errno=0;
9777: dval=strtod(strb,&endptr);
9778: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9779: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9780: 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 9781: fflush(ficlog);
9782: return 1;
9783: }
9784: weight[i]=dval;
9785: strcpy(line,stra);
1.225 brouard 9786:
1.223 brouard 9787: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9788: cutv(stra, strb, line, ' ');
9789: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9790: lval=-1;
1.311 brouard 9791: coqvar[iv][i]=NAN;
9792: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 9793: }else{
1.225 brouard 9794: errno=0;
9795: /* what_kind_of_number(strb); */
9796: dval=strtod(strb,&endptr);
9797: /* if(strb != endptr && *endptr == '\0') */
9798: /* dval=dlval; */
9799: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9800: if( strb[0]=='\0' || (*endptr != '\0')){
9801: 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);
9802: 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);
9803: return 1;
9804: }
9805: coqvar[iv][i]=dval;
1.226 brouard 9806: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9807: }
9808: strcpy(line,stra);
9809: }/* end loop nqv */
1.136 brouard 9810:
1.223 brouard 9811: /* Covariate values */
1.136 brouard 9812: for (j=ncovcol;j>=1;j--){
9813: cutv(stra, strb,line,' ');
1.223 brouard 9814: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9815: lval=-1;
1.136 brouard 9816: }else{
1.225 brouard 9817: errno=0;
9818: lval=strtol(strb,&endptr,10);
9819: if( strb[0]=='\0' || (*endptr != '\0')){
9820: 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);
9821: 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);
9822: return 1;
9823: }
1.136 brouard 9824: }
9825: if(lval <-1 || lval >1){
1.225 brouard 9826: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9827: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9828: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9829: For example, for multinomial values like 1, 2 and 3,\n \
9830: build V1=0 V2=0 for the reference value (1),\n \
9831: V1=1 V2=0 for (2) \n \
1.136 brouard 9832: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9833: output of IMaCh is often meaningless.\n \
1.136 brouard 9834: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9835: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9836: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9837: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9838: For example, for multinomial values like 1, 2 and 3,\n \
9839: build V1=0 V2=0 for the reference value (1),\n \
9840: V1=1 V2=0 for (2) \n \
1.136 brouard 9841: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9842: output of IMaCh is often meaningless.\n \
1.136 brouard 9843: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9844: return 1;
1.136 brouard 9845: }
9846: covar[j][i]=(double)(lval);
9847: strcpy(line,stra);
9848: }
9849: lstra=strlen(stra);
1.225 brouard 9850:
1.136 brouard 9851: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9852: stratrunc = &(stra[lstra-9]);
9853: num[i]=atol(stratrunc);
9854: }
9855: else
9856: num[i]=atol(stra);
9857: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9858: 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;}*/
9859:
9860: i=i+1;
9861: } /* End loop reading data */
1.225 brouard 9862:
1.136 brouard 9863: *imax=i-1; /* Number of individuals */
9864: fclose(fic);
1.225 brouard 9865:
1.136 brouard 9866: return (0);
1.164 brouard 9867: /* endread: */
1.225 brouard 9868: printf("Exiting readdata: ");
9869: fclose(fic);
9870: return (1);
1.223 brouard 9871: }
1.126 brouard 9872:
1.234 brouard 9873: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9874: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9875: while (*p2 == ' ')
1.234 brouard 9876: p2++;
9877: /* while ((*p1++ = *p2++) !=0) */
9878: /* ; */
9879: /* do */
9880: /* while (*p2 == ' ') */
9881: /* p2++; */
9882: /* while (*p1++ == *p2++); */
9883: *stri=p2;
1.145 brouard 9884: }
9885:
1.235 brouard 9886: int decoderesult ( char resultline[], int nres)
1.230 brouard 9887: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9888: {
1.235 brouard 9889: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9890: char resultsav[MAXLINE];
1.234 brouard 9891: int resultmodel[MAXLINE];
9892: int modelresult[MAXLINE];
1.230 brouard 9893: char stra[80], strb[80], strc[80], strd[80],stre[80];
9894:
1.234 brouard 9895: removefirstspace(&resultline);
1.230 brouard 9896:
9897: if (strstr(resultline,"v") !=0){
9898: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9899: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9900: return 1;
9901: }
9902: trimbb(resultsav, resultline);
9903: if (strlen(resultsav) >1){
9904: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9905: }
1.253 brouard 9906: if(j == 0){ /* Resultline but no = */
9907: TKresult[nres]=0; /* Combination for the nresult and the model */
9908: return (0);
9909: }
1.234 brouard 9910: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.318 brouard 9911: 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 9912: 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 9913: }
9914: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9915: if(nbocc(resultsav,'=') >1){
1.318 brouard 9916: 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" */
9917: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.234 brouard 9918: }else
9919: cutl(strc,strd,resultsav,'=');
1.318 brouard 9920: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 9921:
1.230 brouard 9922: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 9923: 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 9924: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9925: /* cptcovsel++; */
9926: if (nbocc(stra,'=') >0)
9927: strcpy(resultsav,stra); /* and analyzes it */
9928: }
1.235 brouard 9929: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 9930: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on model. model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9931: 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 9932: match=0;
1.318 brouard 9933: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9934: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9935: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 9936: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 9937: break;
9938: }
9939: }
9940: if(match == 0){
1.310 brouard 9941: printf("Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9942: fprintf(ficlog,"Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9943: return 1;
1.234 brouard 9944: }
9945: }
9946: }
1.235 brouard 9947: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 9948: 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 9949: match=0;
1.318 brouard 9950: 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 9951: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9952: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.318 brouard 9953: 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 9954: ++match;
9955: }
9956: }
9957: }
9958: if(match == 0){
9959: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
1.310 brouard 9960: fprintf(ficlog,"Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9961: return 1;
1.234 brouard 9962: }else if(match > 1){
9963: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 9964: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9965: return 1;
1.234 brouard 9966: }
9967: }
1.235 brouard 9968:
1.234 brouard 9969: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9970: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9971: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9972: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9973: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9974: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9975: /* 1 0 0 0 */
9976: /* 2 1 0 0 */
9977: /* 3 0 1 0 */
9978: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9979: /* 5 0 0 1 */
9980: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9981: /* 7 0 1 1 */
9982: /* 8 1 1 1 */
1.237 brouard 9983: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9984: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9985: /* V5*age V5 known which value for nres? */
9986: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.318 brouard 9987: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* loop on model line */
1.235 brouard 9988: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9989: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9990: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9991: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9992: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9993: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9994: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9995: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9996: k4++;;
9997: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
1.318 brouard 9998: k3q= resultmodel[k1]; /* resultmodel[1(V5)] = 25.1=k3q */
9999: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.237 brouard 10000: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10001: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
10002: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 10003: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
10004: k4q++;;
10005: }
10006: }
1.234 brouard 10007:
1.235 brouard 10008: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 10009: return (0);
10010: }
1.235 brouard 10011:
1.230 brouard 10012: int decodemodel( char model[], int lastobs)
10013: /**< This routine decodes the model and returns:
1.224 brouard 10014: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10015: * - nagesqr = 1 if age*age in the model, otherwise 0.
10016: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10017: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10018: * - cptcovage number of covariates with age*products =2
10019: * - cptcovs number of simple covariates
10020: * - 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
10021: * which is a new column after the 9 (ncovcol) variables.
1.319 brouard 10022: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10023: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10024: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10025: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10026: */
1.319 brouard 10027: /* 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 10028: {
1.238 brouard 10029: int i, j, k, ks, v;
1.227 brouard 10030: int j1, k1, k2, k3, k4;
1.136 brouard 10031: char modelsav[80];
1.145 brouard 10032: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10033: char *strpt;
1.136 brouard 10034:
1.145 brouard 10035: /*removespace(model);*/
1.136 brouard 10036: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10037: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10038: if (strstr(model,"AGE") !=0){
1.192 brouard 10039: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10040: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10041: return 1;
10042: }
1.141 brouard 10043: if (strstr(model,"v") !=0){
10044: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
10045: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
10046: return 1;
10047: }
1.187 brouard 10048: strcpy(modelsav,model);
10049: if ((strpt=strstr(model,"age*age")) !=0){
10050: printf(" strpt=%s, model=%s\n",strpt, model);
10051: if(strpt != model){
1.234 brouard 10052: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10053: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10054: corresponding column of parameters.\n",model);
1.234 brouard 10055: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10056: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10057: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10058: return 1;
1.225 brouard 10059: }
1.187 brouard 10060: nagesqr=1;
10061: if (strstr(model,"+age*age") !=0)
1.234 brouard 10062: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10063: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10064: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10065: else
1.234 brouard 10066: substrchaine(modelsav, model, "age*age");
1.187 brouard 10067: }else
10068: nagesqr=0;
10069: if (strlen(modelsav) >1){
10070: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10071: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10072: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10073: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10074: * cst, age and age*age
10075: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10076: /* including age products which are counted in cptcovage.
10077: * but the covariates which are products must be treated
10078: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10079: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10080: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10081:
10082:
1.187 brouard 10083: /* Design
10084: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10085: * < ncovcol=8 >
10086: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10087: * k= 1 2 3 4 5 6 7 8
10088: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10089: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10090: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10091: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10092: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10093: * Tage[++cptcovage]=k
10094: * if products, new covar are created after ncovcol with k1
10095: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10096: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10097: * 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
10098: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10099: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10100: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10101: * < ncovcol=8 >
10102: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10103: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10104: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10105: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10106: * p Tprod[1]@2={ 6, 5}
10107: *p Tvard[1][1]@4= {7, 8, 5, 6}
10108: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10109: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10110: *How to reorganize? Tvars(orted)
1.187 brouard 10111: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10112: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10113: * {2, 1, 4, 8, 5, 6, 3, 7}
10114: * Struct []
10115: */
1.225 brouard 10116:
1.187 brouard 10117: /* This loop fills the array Tvar from the string 'model'.*/
10118: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10119: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10120: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10121: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10122: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10123: /* k=1 Tvar[1]=2 (from V2) */
10124: /* k=5 Tvar[5] */
10125: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10126: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10127: /* } */
1.198 brouard 10128: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10129: /*
10130: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10131: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10132: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10133: }
1.187 brouard 10134: cptcovage=0;
1.319 brouard 10135: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10136: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10137: 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" */
10138: if (nbocc(modelsav,'+')==0)
10139: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10140: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10141: /*scanf("%d",i);*/
1.319 brouard 10142: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10143: 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 10144: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10145: /* covar is not filled and then is empty */
10146: cptcovprod--;
10147: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10148: 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 10149: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10150: cptcovage++; /* Counts the number of covariates which include age as a product */
10151: 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 10152: /*printf("stre=%s ", stre);*/
10153: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10154: cptcovprod--;
10155: cutl(stre,strb,strc,'V');
10156: Tvar[k]=atoi(stre);
10157: Typevar[k]=1; /* 1 for age product */
10158: cptcovage++;
10159: Tage[cptcovage]=k;
10160: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10161: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10162: cptcovn++;
10163: cptcovprodnoage++;k1++;
10164: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10165: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10166: because this model-covariate is a construction we invent a new column
10167: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.319 brouard 10168: If already ncovcol=4 and model=V2 + V1 +V1*V4 +age*V3 +V3*V2
10169: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
10170: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */
1.234 brouard 10171: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10172: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10173: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10174: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10175: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
10176: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
10177: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10178: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10179: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10180: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10181: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10182: for (i=1; i<=lastobs;i++){
10183: /* Computes the new covariate which is a product of
10184: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10185: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10186: }
10187: } /* End age is not in the model */
10188: } /* End if model includes a product */
1.319 brouard 10189: else { /* not a product */
1.234 brouard 10190: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10191: /* scanf("%d",i);*/
10192: cutl(strd,strc,strb,'V');
10193: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10194: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10195: Tvar[k]=atoi(strd);
10196: Typevar[k]=0; /* 0 for simple covariates */
10197: }
10198: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10199: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10200: scanf("%d",i);*/
1.187 brouard 10201: } /* end of loop + on total covariates */
10202: } /* end if strlen(modelsave == 0) age*age might exist */
10203: } /* end if strlen(model == 0) */
1.136 brouard 10204:
10205: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10206: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10207:
1.136 brouard 10208: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10209: printf("cptcovprod=%d ", cptcovprod);
10210: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10211: scanf("%d ",i);*/
10212:
10213:
1.230 brouard 10214: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10215: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10216: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10217: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10218: k = 1 2 3 4 5 6 7 8 9
10219: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 10220: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 10221: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10222: Dummy[k] 1 0 0 0 3 1 1 2 3
10223: Tmodelind[combination of covar]=k;
1.225 brouard 10224: */
10225: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10226: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10227: /* 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 10228: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 10229: printf("Model=1+age+%s\n\
1.227 brouard 10230: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10231: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10232: 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 10233: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10234: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10235: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10236: 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 10237: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10238: 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 */
10239: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10240: Fixed[k]= 0;
10241: Dummy[k]= 0;
1.225 brouard 10242: ncoveff++;
1.232 brouard 10243: ncovf++;
1.234 brouard 10244: nsd++;
10245: modell[k].maintype= FTYPE;
10246: TvarsD[nsd]=Tvar[k];
10247: TvarsDind[nsd]=k;
10248: TvarF[ncovf]=Tvar[k];
10249: TvarFind[ncovf]=k;
10250: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10251: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10252: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10253: Fixed[k]= 0;
10254: Dummy[k]= 0;
10255: ncoveff++;
10256: ncovf++;
10257: modell[k].maintype= FTYPE;
10258: TvarF[ncovf]=Tvar[k];
10259: TvarFind[ncovf]=k;
1.230 brouard 10260: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10261: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10262: }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 10263: Fixed[k]= 0;
10264: Dummy[k]= 1;
1.230 brouard 10265: nqfveff++;
1.234 brouard 10266: modell[k].maintype= FTYPE;
10267: modell[k].subtype= FQ;
10268: nsq++;
10269: TvarsQ[nsq]=Tvar[k];
10270: TvarsQind[nsq]=k;
1.232 brouard 10271: ncovf++;
1.234 brouard 10272: TvarF[ncovf]=Tvar[k];
10273: TvarFind[ncovf]=k;
1.231 brouard 10274: 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 10275: 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 10276: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10277: Fixed[k]= 1;
10278: Dummy[k]= 0;
1.225 brouard 10279: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10280: modell[k].maintype= VTYPE;
10281: modell[k].subtype= VD;
10282: nsd++;
10283: TvarsD[nsd]=Tvar[k];
10284: TvarsDind[nsd]=k;
10285: ncovv++; /* Only simple time varying variables */
10286: TvarV[ncovv]=Tvar[k];
1.242 brouard 10287: 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 10288: 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 */
10289: 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 10290: 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);
10291: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10292: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10293: Fixed[k]= 1;
10294: Dummy[k]= 1;
10295: nqtveff++;
10296: modell[k].maintype= VTYPE;
10297: modell[k].subtype= VQ;
10298: ncovv++; /* Only simple time varying variables */
10299: nsq++;
1.319 brouard 10300: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */
1.234 brouard 10301: TvarsQind[nsq]=k;
10302: TvarV[ncovv]=Tvar[k];
1.242 brouard 10303: 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 10304: 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 */
10305: 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 10306: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10307: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10308: 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 10309: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10310: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10311: ncova++;
10312: TvarA[ncova]=Tvar[k];
10313: TvarAind[ncova]=k;
1.231 brouard 10314: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10315: Fixed[k]= 2;
10316: Dummy[k]= 2;
10317: modell[k].maintype= ATYPE;
10318: modell[k].subtype= APFD;
10319: /* ncoveff++; */
1.227 brouard 10320: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10321: Fixed[k]= 2;
10322: Dummy[k]= 3;
10323: modell[k].maintype= ATYPE;
10324: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10325: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10326: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10327: Fixed[k]= 3;
10328: Dummy[k]= 2;
10329: modell[k].maintype= ATYPE;
10330: modell[k].subtype= APVD; /* Product age * varying dummy */
10331: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10332: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10333: Fixed[k]= 3;
10334: Dummy[k]= 3;
10335: modell[k].maintype= ATYPE;
10336: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10337: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10338: }
10339: }else if (Typevar[k] == 2) { /* product without age */
10340: k1=Tposprod[k];
10341: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10342: if(Tvard[k1][2] <=ncovcol){
10343: Fixed[k]= 1;
10344: Dummy[k]= 0;
10345: modell[k].maintype= FTYPE;
10346: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10347: ncovf++; /* Fixed variables without age */
10348: TvarF[ncovf]=Tvar[k];
10349: TvarFind[ncovf]=k;
10350: }else if(Tvard[k1][2] <=ncovcol+nqv){
10351: Fixed[k]= 0; /* or 2 ?*/
10352: Dummy[k]= 1;
10353: modell[k].maintype= FTYPE;
10354: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10355: ncovf++; /* Varying variables without age */
10356: TvarF[ncovf]=Tvar[k];
10357: TvarFind[ncovf]=k;
10358: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10359: Fixed[k]= 1;
10360: Dummy[k]= 0;
10361: modell[k].maintype= VTYPE;
10362: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10363: ncovv++; /* Varying variables without age */
10364: TvarV[ncovv]=Tvar[k];
10365: TvarVind[ncovv]=k;
10366: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10367: Fixed[k]= 1;
10368: Dummy[k]= 1;
10369: modell[k].maintype= VTYPE;
10370: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10371: ncovv++; /* Varying variables without age */
10372: TvarV[ncovv]=Tvar[k];
10373: TvarVind[ncovv]=k;
10374: }
1.227 brouard 10375: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10376: if(Tvard[k1][2] <=ncovcol){
10377: Fixed[k]= 0; /* or 2 ?*/
10378: Dummy[k]= 1;
10379: modell[k].maintype= FTYPE;
10380: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10381: ncovf++; /* Fixed variables without age */
10382: TvarF[ncovf]=Tvar[k];
10383: TvarFind[ncovf]=k;
10384: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10385: Fixed[k]= 1;
10386: Dummy[k]= 1;
10387: modell[k].maintype= VTYPE;
10388: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10389: ncovv++; /* Varying variables without age */
10390: TvarV[ncovv]=Tvar[k];
10391: TvarVind[ncovv]=k;
10392: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10393: Fixed[k]= 1;
10394: Dummy[k]= 1;
10395: modell[k].maintype= VTYPE;
10396: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10397: ncovv++; /* Varying variables without age */
10398: TvarV[ncovv]=Tvar[k];
10399: TvarVind[ncovv]=k;
10400: ncovv++; /* Varying variables without age */
10401: TvarV[ncovv]=Tvar[k];
10402: TvarVind[ncovv]=k;
10403: }
1.227 brouard 10404: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10405: if(Tvard[k1][2] <=ncovcol){
10406: Fixed[k]= 1;
10407: Dummy[k]= 1;
10408: modell[k].maintype= VTYPE;
10409: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10410: ncovv++; /* Varying variables without age */
10411: TvarV[ncovv]=Tvar[k];
10412: TvarVind[ncovv]=k;
10413: }else if(Tvard[k1][2] <=ncovcol+nqv){
10414: Fixed[k]= 1;
10415: Dummy[k]= 1;
10416: modell[k].maintype= VTYPE;
10417: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10418: ncovv++; /* Varying variables without age */
10419: TvarV[ncovv]=Tvar[k];
10420: TvarVind[ncovv]=k;
10421: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10422: Fixed[k]= 1;
10423: Dummy[k]= 0;
10424: modell[k].maintype= VTYPE;
10425: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10426: ncovv++; /* Varying variables without age */
10427: TvarV[ncovv]=Tvar[k];
10428: TvarVind[ncovv]=k;
10429: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10430: Fixed[k]= 1;
10431: Dummy[k]= 1;
10432: modell[k].maintype= VTYPE;
10433: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10434: ncovv++; /* Varying variables without age */
10435: TvarV[ncovv]=Tvar[k];
10436: TvarVind[ncovv]=k;
10437: }
1.227 brouard 10438: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10439: if(Tvard[k1][2] <=ncovcol){
10440: Fixed[k]= 1;
10441: Dummy[k]= 1;
10442: modell[k].maintype= VTYPE;
10443: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10444: ncovv++; /* Varying variables without age */
10445: TvarV[ncovv]=Tvar[k];
10446: TvarVind[ncovv]=k;
10447: }else if(Tvard[k1][2] <=ncovcol+nqv){
10448: Fixed[k]= 1;
10449: Dummy[k]= 1;
10450: modell[k].maintype= VTYPE;
10451: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10452: ncovv++; /* Varying variables without age */
10453: TvarV[ncovv]=Tvar[k];
10454: TvarVind[ncovv]=k;
10455: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10456: Fixed[k]= 1;
10457: Dummy[k]= 1;
10458: modell[k].maintype= VTYPE;
10459: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10460: ncovv++; /* Varying variables without age */
10461: TvarV[ncovv]=Tvar[k];
10462: TvarVind[ncovv]=k;
10463: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10464: Fixed[k]= 1;
10465: Dummy[k]= 1;
10466: modell[k].maintype= VTYPE;
10467: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10468: ncovv++; /* Varying variables without age */
10469: TvarV[ncovv]=Tvar[k];
10470: TvarVind[ncovv]=k;
10471: }
1.227 brouard 10472: }else{
1.240 brouard 10473: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10474: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10475: } /*end k1*/
1.225 brouard 10476: }else{
1.226 brouard 10477: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10478: 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 10479: }
1.227 brouard 10480: 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 10481: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10482: 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]);
10483: }
10484: /* Searching for doublons in the model */
10485: for(k1=1; k1<= cptcovt;k1++){
10486: for(k2=1; k2 <k1;k2++){
1.285 brouard 10487: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10488: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10489: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10490: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10491: 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]);
10492: 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 10493: return(1);
10494: }
10495: }else if (Typevar[k1] ==2){
10496: k3=Tposprod[k1];
10497: k4=Tposprod[k2];
10498: 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])) ){
10499: 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]]);
10500: 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);
10501: return(1);
10502: }
10503: }
1.227 brouard 10504: }
10505: }
1.225 brouard 10506: }
10507: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10508: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10509: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10510: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10511: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10512: /*endread:*/
1.225 brouard 10513: printf("Exiting decodemodel: ");
10514: return (1);
1.136 brouard 10515: }
10516:
1.169 brouard 10517: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10518: {/* Check ages at death */
1.136 brouard 10519: int i, m;
1.218 brouard 10520: int firstone=0;
10521:
1.136 brouard 10522: for (i=1; i<=imx; i++) {
10523: for(m=2; (m<= maxwav); m++) {
10524: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10525: anint[m][i]=9999;
1.216 brouard 10526: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10527: s[m][i]=-1;
1.136 brouard 10528: }
10529: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10530: *nberr = *nberr + 1;
1.218 brouard 10531: if(firstone == 0){
10532: firstone=1;
1.260 brouard 10533: 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 10534: }
1.262 brouard 10535: 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 10536: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10537: }
10538: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10539: (*nberr)++;
1.259 brouard 10540: 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 10541: 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 10542: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10543: }
10544: }
10545: }
10546:
10547: for (i=1; i<=imx; i++) {
10548: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10549: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10550: 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 10551: if (s[m][i] >= nlstate+1) {
1.169 brouard 10552: if(agedc[i]>0){
10553: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10554: agev[m][i]=agedc[i];
1.214 brouard 10555: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10556: }else {
1.136 brouard 10557: if ((int)andc[i]!=9999){
10558: nbwarn++;
10559: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10560: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10561: agev[m][i]=-1;
10562: }
10563: }
1.169 brouard 10564: } /* agedc > 0 */
1.214 brouard 10565: } /* end if */
1.136 brouard 10566: else if(s[m][i] !=9){ /* Standard case, age in fractional
10567: years but with the precision of a month */
10568: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10569: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10570: agev[m][i]=1;
10571: else if(agev[m][i] < *agemin){
10572: *agemin=agev[m][i];
10573: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10574: }
10575: else if(agev[m][i] >*agemax){
10576: *agemax=agev[m][i];
1.156 brouard 10577: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10578: }
10579: /*agev[m][i]=anint[m][i]-annais[i];*/
10580: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10581: } /* en if 9*/
1.136 brouard 10582: else { /* =9 */
1.214 brouard 10583: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10584: agev[m][i]=1;
10585: s[m][i]=-1;
10586: }
10587: }
1.214 brouard 10588: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10589: agev[m][i]=1;
1.214 brouard 10590: else{
10591: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10592: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10593: agev[m][i]=0;
10594: }
10595: } /* End for lastpass */
10596: }
1.136 brouard 10597:
10598: for (i=1; i<=imx; i++) {
10599: for(m=firstpass; (m<=lastpass); m++){
10600: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10601: (*nberr)++;
1.136 brouard 10602: 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);
10603: 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);
10604: return 1;
10605: }
10606: }
10607: }
10608:
10609: /*for (i=1; i<=imx; i++){
10610: for (m=firstpass; (m<lastpass); m++){
10611: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10612: }
10613:
10614: }*/
10615:
10616:
1.139 brouard 10617: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10618: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10619:
10620: return (0);
1.164 brouard 10621: /* endread:*/
1.136 brouard 10622: printf("Exiting calandcheckages: ");
10623: return (1);
10624: }
10625:
1.172 brouard 10626: #if defined(_MSC_VER)
10627: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10628: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10629: //#include "stdafx.h"
10630: //#include <stdio.h>
10631: //#include <tchar.h>
10632: //#include <windows.h>
10633: //#include <iostream>
10634: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10635:
10636: LPFN_ISWOW64PROCESS fnIsWow64Process;
10637:
10638: BOOL IsWow64()
10639: {
10640: BOOL bIsWow64 = FALSE;
10641:
10642: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10643: // (HANDLE, PBOOL);
10644:
10645: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10646:
10647: HMODULE module = GetModuleHandle(_T("kernel32"));
10648: const char funcName[] = "IsWow64Process";
10649: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10650: GetProcAddress(module, funcName);
10651:
10652: if (NULL != fnIsWow64Process)
10653: {
10654: if (!fnIsWow64Process(GetCurrentProcess(),
10655: &bIsWow64))
10656: //throw std::exception("Unknown error");
10657: printf("Unknown error\n");
10658: }
10659: return bIsWow64 != FALSE;
10660: }
10661: #endif
1.177 brouard 10662:
1.191 brouard 10663: void syscompilerinfo(int logged)
1.292 brouard 10664: {
10665: #include <stdint.h>
10666:
10667: /* #include "syscompilerinfo.h"*/
1.185 brouard 10668: /* command line Intel compiler 32bit windows, XP compatible:*/
10669: /* /GS /W3 /Gy
10670: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10671: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10672: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10673: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10674: */
10675: /* 64 bits */
1.185 brouard 10676: /*
10677: /GS /W3 /Gy
10678: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10679: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10680: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10681: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10682: /* Optimization are useless and O3 is slower than O2 */
10683: /*
10684: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10685: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10686: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10687: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10688: */
1.186 brouard 10689: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10690: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10691: /PDB:"visual studio
10692: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10693: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10694: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10695: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10696: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10697: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10698: uiAccess='false'"
10699: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10700: /NOLOGO /TLBID:1
10701: */
1.292 brouard 10702:
10703:
1.177 brouard 10704: #if defined __INTEL_COMPILER
1.178 brouard 10705: #if defined(__GNUC__)
10706: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10707: #endif
1.177 brouard 10708: #elif defined(__GNUC__)
1.179 brouard 10709: #ifndef __APPLE__
1.174 brouard 10710: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10711: #endif
1.177 brouard 10712: struct utsname sysInfo;
1.178 brouard 10713: int cross = CROSS;
10714: if (cross){
10715: printf("Cross-");
1.191 brouard 10716: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10717: }
1.174 brouard 10718: #endif
10719:
1.191 brouard 10720: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10721: #if defined(__clang__)
1.191 brouard 10722: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10723: #endif
10724: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10725: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10726: #endif
10727: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10728: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10729: #endif
10730: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10731: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10732: #endif
10733: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10734: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10735: #endif
10736: #if defined(_MSC_VER)
1.191 brouard 10737: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10738: #endif
10739: #if defined(__PGI)
1.191 brouard 10740: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10741: #endif
10742: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10743: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10744: #endif
1.191 brouard 10745: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10746:
1.167 brouard 10747: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10748: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10749: // Windows (x64 and x86)
1.191 brouard 10750: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10751: #elif __unix__ // all unices, not all compilers
10752: // Unix
1.191 brouard 10753: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10754: #elif __linux__
10755: // linux
1.191 brouard 10756: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10757: #elif __APPLE__
1.174 brouard 10758: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10759: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10760: #endif
10761:
10762: /* __MINGW32__ */
10763: /* __CYGWIN__ */
10764: /* __MINGW64__ */
10765: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10766: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10767: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10768: /* _WIN64 // Defined for applications for Win64. */
10769: /* _M_X64 // Defined for compilations that target x64 processors. */
10770: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10771:
1.167 brouard 10772: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10773: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10774: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10775: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10776: #else
1.191 brouard 10777: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10778: #endif
10779:
1.169 brouard 10780: #if defined(__GNUC__)
10781: # if defined(__GNUC_PATCHLEVEL__)
10782: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10783: + __GNUC_MINOR__ * 100 \
10784: + __GNUC_PATCHLEVEL__)
10785: # else
10786: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10787: + __GNUC_MINOR__ * 100)
10788: # endif
1.174 brouard 10789: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10790: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10791:
10792: if (uname(&sysInfo) != -1) {
10793: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10794: 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 10795: }
10796: else
10797: perror("uname() error");
1.179 brouard 10798: //#ifndef __INTEL_COMPILER
10799: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10800: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10801: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10802: #endif
1.169 brouard 10803: #endif
1.172 brouard 10804:
1.286 brouard 10805: // void main ()
1.172 brouard 10806: // {
1.169 brouard 10807: #if defined(_MSC_VER)
1.174 brouard 10808: if (IsWow64()){
1.191 brouard 10809: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10810: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10811: }
10812: else{
1.191 brouard 10813: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10814: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10815: }
1.172 brouard 10816: // printf("\nPress Enter to continue...");
10817: // getchar();
10818: // }
10819:
1.169 brouard 10820: #endif
10821:
1.167 brouard 10822:
1.219 brouard 10823: }
1.136 brouard 10824:
1.219 brouard 10825: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10826: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10827: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10828: /* double ftolpl = 1.e-10; */
1.180 brouard 10829: double age, agebase, agelim;
1.203 brouard 10830: double tot;
1.180 brouard 10831:
1.202 brouard 10832: strcpy(filerespl,"PL_");
10833: strcat(filerespl,fileresu);
10834: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10835: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10836: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10837: }
1.288 brouard 10838: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10839: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10840: pstamp(ficrespl);
1.288 brouard 10841: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10842: fprintf(ficrespl,"#Age ");
10843: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10844: fprintf(ficrespl,"\n");
1.180 brouard 10845:
1.219 brouard 10846: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10847:
1.219 brouard 10848: agebase=ageminpar;
10849: agelim=agemaxpar;
1.180 brouard 10850:
1.227 brouard 10851: /* i1=pow(2,ncoveff); */
1.234 brouard 10852: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10853: if (cptcovn < 1){i1=1;}
1.180 brouard 10854:
1.238 brouard 10855: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10856: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10857: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10858: continue;
1.235 brouard 10859:
1.238 brouard 10860: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10861: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10862: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10863: /* k=k+1; */
10864: /* to clean */
10865: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10866: fprintf(ficrespl,"#******");
10867: printf("#******");
10868: fprintf(ficlog,"#******");
10869: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10870: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10871: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10872: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10873: }
10874: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10875: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10876: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10877: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10878: }
10879: fprintf(ficrespl,"******\n");
10880: printf("******\n");
10881: fprintf(ficlog,"******\n");
10882: if(invalidvarcomb[k]){
10883: printf("\nCombination (%d) ignored because no case \n",k);
10884: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10885: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10886: continue;
10887: }
1.219 brouard 10888:
1.238 brouard 10889: fprintf(ficrespl,"#Age ");
10890: for(j=1;j<=cptcoveff;j++) {
10891: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10892: }
10893: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10894: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10895:
1.238 brouard 10896: for (age=agebase; age<=agelim; age++){
10897: /* for (age=agebase; age<=agebase; age++){ */
10898: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10899: fprintf(ficrespl,"%.0f ",age );
10900: for(j=1;j<=cptcoveff;j++)
10901: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10902: tot=0.;
10903: for(i=1; i<=nlstate;i++){
10904: tot += prlim[i][i];
10905: fprintf(ficrespl," %.5f", prlim[i][i]);
10906: }
10907: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10908: } /* Age */
10909: /* was end of cptcod */
10910: } /* cptcov */
10911: } /* nres */
1.219 brouard 10912: return 0;
1.180 brouard 10913: }
10914:
1.218 brouard 10915: 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 10916: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10917:
10918: /* Computes the back prevalence limit for any combination of covariate values
10919: * at any age between ageminpar and agemaxpar
10920: */
1.235 brouard 10921: int i, j, k, i1, nres=0 ;
1.217 brouard 10922: /* double ftolpl = 1.e-10; */
10923: double age, agebase, agelim;
10924: double tot;
1.218 brouard 10925: /* double ***mobaverage; */
10926: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10927:
10928: strcpy(fileresplb,"PLB_");
10929: strcat(fileresplb,fileresu);
10930: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10931: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10932: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10933: }
1.288 brouard 10934: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10935: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10936: pstamp(ficresplb);
1.288 brouard 10937: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10938: fprintf(ficresplb,"#Age ");
10939: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10940: fprintf(ficresplb,"\n");
10941:
1.218 brouard 10942:
10943: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10944:
10945: agebase=ageminpar;
10946: agelim=agemaxpar;
10947:
10948:
1.227 brouard 10949: i1=pow(2,cptcoveff);
1.218 brouard 10950: if (cptcovn < 1){i1=1;}
1.227 brouard 10951:
1.238 brouard 10952: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10953: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10954: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10955: continue;
10956: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10957: fprintf(ficresplb,"#******");
10958: printf("#******");
10959: fprintf(ficlog,"#******");
10960: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10961: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10962: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10963: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10964: }
10965: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10966: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10967: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10968: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10969: }
10970: fprintf(ficresplb,"******\n");
10971: printf("******\n");
10972: fprintf(ficlog,"******\n");
10973: if(invalidvarcomb[k]){
10974: printf("\nCombination (%d) ignored because no cases \n",k);
10975: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10976: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10977: continue;
10978: }
1.218 brouard 10979:
1.238 brouard 10980: fprintf(ficresplb,"#Age ");
10981: for(j=1;j<=cptcoveff;j++) {
10982: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10983: }
10984: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10985: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10986:
10987:
1.238 brouard 10988: for (age=agebase; age<=agelim; age++){
10989: /* for (age=agebase; age<=agebase; age++){ */
10990: if(mobilavproj > 0){
10991: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10992: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10993: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10994: }else if (mobilavproj == 0){
10995: 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);
10996: 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);
10997: exit(1);
10998: }else{
10999: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11000: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11001: /* printf("TOTOT\n"); */
11002: /* exit(1); */
1.238 brouard 11003: }
11004: fprintf(ficresplb,"%.0f ",age );
11005: for(j=1;j<=cptcoveff;j++)
11006: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11007: tot=0.;
11008: for(i=1; i<=nlstate;i++){
11009: tot += bprlim[i][i];
11010: fprintf(ficresplb," %.5f", bprlim[i][i]);
11011: }
11012: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11013: } /* Age */
11014: /* was end of cptcod */
1.255 brouard 11015: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 11016: } /* end of any combination */
11017: } /* end of nres */
1.218 brouard 11018: /* hBijx(p, bage, fage); */
11019: /* fclose(ficrespijb); */
11020:
11021: return 0;
1.217 brouard 11022: }
1.218 brouard 11023:
1.180 brouard 11024: int hPijx(double *p, int bage, int fage){
11025: /*------------- h Pij x at various ages ------------*/
11026:
11027: int stepsize;
11028: int agelim;
11029: int hstepm;
11030: int nhstepm;
1.235 brouard 11031: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11032:
11033: double agedeb;
11034: double ***p3mat;
11035:
1.201 brouard 11036: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 11037: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11038: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11039: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11040: }
11041: printf("Computing pij: result on file '%s' \n", filerespij);
11042: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11043:
11044: stepsize=(int) (stepm+YEARM-1)/YEARM;
11045: /*if (stepm<=24) stepsize=2;*/
11046:
11047: agelim=AGESUP;
11048: hstepm=stepsize*YEARM; /* Every year of age */
11049: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 11050:
1.180 brouard 11051: /* hstepm=1; aff par mois*/
11052: pstamp(ficrespij);
11053: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 11054: i1= pow(2,cptcoveff);
1.218 brouard 11055: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11056: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11057: /* k=k+1; */
1.235 brouard 11058: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11059: for(k=1; k<=i1;k++){
1.253 brouard 11060: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11061: continue;
1.183 brouard 11062: fprintf(ficrespij,"\n#****** ");
1.227 brouard 11063: for(j=1;j<=cptcoveff;j++)
1.198 brouard 11064: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11065: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11066: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11067: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11068: }
1.183 brouard 11069: fprintf(ficrespij,"******\n");
11070:
11071: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11072: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11073: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11074:
11075: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 11076:
1.183 brouard 11077: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11078: oldm=oldms;savm=savms;
1.235 brouard 11079: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 11080: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11081: for(i=1; i<=nlstate;i++)
11082: for(j=1; j<=nlstate+ndeath;j++)
11083: fprintf(ficrespij," %1d-%1d",i,j);
11084: fprintf(ficrespij,"\n");
11085: for (h=0; h<=nhstepm; h++){
11086: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11087: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 11088: for(i=1; i<=nlstate;i++)
11089: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 11090: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 11091: fprintf(ficrespij,"\n");
11092: }
1.183 brouard 11093: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11094: fprintf(ficrespij,"\n");
11095: }
1.180 brouard 11096: /*}*/
11097: }
1.218 brouard 11098: return 0;
1.180 brouard 11099: }
1.218 brouard 11100:
11101: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11102: /*------------- h Bij x at various ages ------------*/
11103:
11104: int stepsize;
1.218 brouard 11105: /* int agelim; */
11106: int ageminl;
1.217 brouard 11107: int hstepm;
11108: int nhstepm;
1.238 brouard 11109: int h, i, i1, j, k, nres;
1.218 brouard 11110:
1.217 brouard 11111: double agedeb;
11112: double ***p3mat;
1.218 brouard 11113:
11114: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11115: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11116: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11117: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11118: }
11119: printf("Computing pij back: result on file '%s' \n", filerespijb);
11120: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11121:
11122: stepsize=(int) (stepm+YEARM-1)/YEARM;
11123: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11124:
1.218 brouard 11125: /* agelim=AGESUP; */
1.289 brouard 11126: ageminl=AGEINF; /* was 30 */
1.218 brouard 11127: hstepm=stepsize*YEARM; /* Every year of age */
11128: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11129:
11130: /* hstepm=1; aff par mois*/
11131: pstamp(ficrespijb);
1.255 brouard 11132: 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 11133: i1= pow(2,cptcoveff);
1.218 brouard 11134: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11135: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11136: /* k=k+1; */
1.238 brouard 11137: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11138: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11139: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11140: continue;
11141: fprintf(ficrespijb,"\n#****** ");
11142: for(j=1;j<=cptcoveff;j++)
11143: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11144: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11145: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11146: }
11147: fprintf(ficrespijb,"******\n");
1.264 brouard 11148: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 11149: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
11150: continue;
11151: }
11152:
11153: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11154: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11155: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 11156: 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 */
11157: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 11158:
11159: /* nhstepm=nhstepm*YEARM; aff par mois*/
11160:
1.266 brouard 11161: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11162: /* and memory limitations if stepm is small */
11163:
1.238 brouard 11164: /* oldm=oldms;savm=savms; */
11165: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 11166: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 11167: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 11168: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 11169: for(i=1; i<=nlstate;i++)
11170: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 11171: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 11172: fprintf(ficrespijb,"\n");
1.238 brouard 11173: for (h=0; h<=nhstepm; h++){
11174: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11175: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11176: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
11177: for(i=1; i<=nlstate;i++)
11178: for(j=1; j<=nlstate+ndeath;j++)
11179: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
11180: fprintf(ficrespijb,"\n");
11181: }
11182: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11183: fprintf(ficrespijb,"\n");
11184: } /* end age deb */
11185: } /* end combination */
11186: } /* end nres */
1.218 brouard 11187: return 0;
11188: } /* hBijx */
1.217 brouard 11189:
1.180 brouard 11190:
1.136 brouard 11191: /***********************************************/
11192: /**************** Main Program *****************/
11193: /***********************************************/
11194:
11195: int main(int argc, char *argv[])
11196: {
11197: #ifdef GSL
11198: const gsl_multimin_fminimizer_type *T;
11199: size_t iteri = 0, it;
11200: int rval = GSL_CONTINUE;
11201: int status = GSL_SUCCESS;
11202: double ssval;
11203: #endif
11204: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11205: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11206: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11207: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11208: int jj, ll, li, lj, lk;
1.136 brouard 11209: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11210: int num_filled;
1.136 brouard 11211: int itimes;
11212: int NDIM=2;
11213: int vpopbased=0;
1.235 brouard 11214: int nres=0;
1.258 brouard 11215: int endishere=0;
1.277 brouard 11216: int noffset=0;
1.274 brouard 11217: int ncurrv=0; /* Temporary variable */
11218:
1.164 brouard 11219: char ca[32], cb[32];
1.136 brouard 11220: /* FILE *fichtm; *//* Html File */
11221: /* FILE *ficgp;*/ /*Gnuplot File */
11222: struct stat info;
1.191 brouard 11223: double agedeb=0.;
1.194 brouard 11224:
11225: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11226: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11227:
1.165 brouard 11228: double fret;
1.191 brouard 11229: double dum=0.; /* Dummy variable */
1.136 brouard 11230: double ***p3mat;
1.218 brouard 11231: /* double ***mobaverage; */
1.319 brouard 11232: double wald;
1.164 brouard 11233:
11234: char line[MAXLINE];
1.197 brouard 11235: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11236:
1.234 brouard 11237: char modeltemp[MAXLINE];
1.230 brouard 11238: char resultline[MAXLINE];
11239:
1.136 brouard 11240: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11241: char *tok, *val; /* pathtot */
1.290 brouard 11242: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 11243: int c, h , cpt, c2;
1.191 brouard 11244: int jl=0;
11245: int i1, j1, jk, stepsize=0;
1.194 brouard 11246: int count=0;
11247:
1.164 brouard 11248: int *tab;
1.136 brouard 11249: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11250: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11251: /* double anprojf, mprojf, jprojf; */
11252: /* double jintmean,mintmean,aintmean; */
11253: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11254: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11255: double yrfproj= 10.0; /* Number of years of forward projections */
11256: double yrbproj= 10.0; /* Number of years of backward projections */
11257: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11258: int mobilav=0,popforecast=0;
1.191 brouard 11259: int hstepm=0, nhstepm=0;
1.136 brouard 11260: int agemortsup;
11261: float sumlpop=0.;
11262: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11263: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11264:
1.191 brouard 11265: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11266: double ftolpl=FTOL;
11267: double **prlim;
1.217 brouard 11268: double **bprlim;
1.317 brouard 11269: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
11270: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 11271: double ***paramstart; /* Matrix of starting parameter values */
11272: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11273: double **matcov; /* Matrix of covariance */
1.203 brouard 11274: double **hess; /* Hessian matrix */
1.136 brouard 11275: double ***delti3; /* Scale */
11276: double *delti; /* Scale */
11277: double ***eij, ***vareij;
11278: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11279:
1.136 brouard 11280: double *epj, vepp;
1.164 brouard 11281:
1.273 brouard 11282: double dateprev1, dateprev2;
1.296 brouard 11283: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11284: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11285:
1.217 brouard 11286:
1.136 brouard 11287: double **ximort;
1.145 brouard 11288: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11289: int *dcwave;
11290:
1.164 brouard 11291: char z[1]="c";
1.136 brouard 11292:
11293: /*char *strt;*/
11294: char strtend[80];
1.126 brouard 11295:
1.164 brouard 11296:
1.126 brouard 11297: /* setlocale (LC_ALL, ""); */
11298: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11299: /* textdomain (PACKAGE); */
11300: /* setlocale (LC_CTYPE, ""); */
11301: /* setlocale (LC_MESSAGES, ""); */
11302:
11303: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11304: rstart_time = time(NULL);
11305: /* (void) gettimeofday(&start_time,&tzp);*/
11306: start_time = *localtime(&rstart_time);
1.126 brouard 11307: curr_time=start_time;
1.157 brouard 11308: /*tml = *localtime(&start_time.tm_sec);*/
11309: /* strcpy(strstart,asctime(&tml)); */
11310: strcpy(strstart,asctime(&start_time));
1.126 brouard 11311:
11312: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11313: /* tp.tm_sec = tp.tm_sec +86400; */
11314: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11315: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11316: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11317: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11318: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11319: /* strt=asctime(&tmg); */
11320: /* printf("Time(after) =%s",strstart); */
11321: /* (void) time (&time_value);
11322: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11323: * tm = *localtime(&time_value);
11324: * strstart=asctime(&tm);
11325: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11326: */
11327:
11328: nberr=0; /* Number of errors and warnings */
11329: nbwarn=0;
1.184 brouard 11330: #ifdef WIN32
11331: _getcwd(pathcd, size);
11332: #else
1.126 brouard 11333: getcwd(pathcd, size);
1.184 brouard 11334: #endif
1.191 brouard 11335: syscompilerinfo(0);
1.196 brouard 11336: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11337: if(argc <=1){
11338: printf("\nEnter the parameter file name: ");
1.205 brouard 11339: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11340: printf("ERROR Empty parameter file name\n");
11341: goto end;
11342: }
1.126 brouard 11343: i=strlen(pathr);
11344: if(pathr[i-1]=='\n')
11345: pathr[i-1]='\0';
1.156 brouard 11346: i=strlen(pathr);
1.205 brouard 11347: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11348: pathr[i-1]='\0';
1.205 brouard 11349: }
11350: i=strlen(pathr);
11351: if( i==0 ){
11352: printf("ERROR Empty parameter file name\n");
11353: goto end;
11354: }
11355: for (tok = pathr; tok != NULL; ){
1.126 brouard 11356: printf("Pathr |%s|\n",pathr);
11357: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11358: printf("val= |%s| pathr=%s\n",val,pathr);
11359: strcpy (pathtot, val);
11360: if(pathr[0] == '\0') break; /* Dirty */
11361: }
11362: }
1.281 brouard 11363: else if (argc<=2){
11364: strcpy(pathtot,argv[1]);
11365: }
1.126 brouard 11366: else{
11367: strcpy(pathtot,argv[1]);
1.281 brouard 11368: strcpy(z,argv[2]);
11369: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11370: }
11371: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11372: /*cygwin_split_path(pathtot,path,optionfile);
11373: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11374: /* cutv(path,optionfile,pathtot,'\\');*/
11375:
11376: /* Split argv[0], imach program to get pathimach */
11377: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11378: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11379: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11380: /* strcpy(pathimach,argv[0]); */
11381: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11382: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11383: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11384: #ifdef WIN32
11385: _chdir(path); /* Can be a relative path */
11386: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11387: #else
1.126 brouard 11388: chdir(path); /* Can be a relative path */
1.184 brouard 11389: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11390: #endif
11391: printf("Current directory %s!\n",pathcd);
1.126 brouard 11392: strcpy(command,"mkdir ");
11393: strcat(command,optionfilefiname);
11394: if((outcmd=system(command)) != 0){
1.169 brouard 11395: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11396: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11397: /* fclose(ficlog); */
11398: /* exit(1); */
11399: }
11400: /* if((imk=mkdir(optionfilefiname))<0){ */
11401: /* perror("mkdir"); */
11402: /* } */
11403:
11404: /*-------- arguments in the command line --------*/
11405:
1.186 brouard 11406: /* Main Log file */
1.126 brouard 11407: strcat(filelog, optionfilefiname);
11408: strcat(filelog,".log"); /* */
11409: if((ficlog=fopen(filelog,"w"))==NULL) {
11410: printf("Problem with logfile %s\n",filelog);
11411: goto end;
11412: }
11413: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11414: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11415: fprintf(ficlog,"\nEnter the parameter file name: \n");
11416: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11417: path=%s \n\
11418: optionfile=%s\n\
11419: optionfilext=%s\n\
1.156 brouard 11420: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11421:
1.197 brouard 11422: syscompilerinfo(1);
1.167 brouard 11423:
1.126 brouard 11424: printf("Local time (at start):%s",strstart);
11425: fprintf(ficlog,"Local time (at start): %s",strstart);
11426: fflush(ficlog);
11427: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11428: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11429:
11430: /* */
11431: strcpy(fileres,"r");
11432: strcat(fileres, optionfilefiname);
1.201 brouard 11433: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11434: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11435: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11436:
1.186 brouard 11437: /* Main ---------arguments file --------*/
1.126 brouard 11438:
11439: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11440: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11441: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11442: fflush(ficlog);
1.149 brouard 11443: /* goto end; */
11444: exit(70);
1.126 brouard 11445: }
11446:
11447: strcpy(filereso,"o");
1.201 brouard 11448: strcat(filereso,fileresu);
1.126 brouard 11449: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11450: printf("Problem with Output resultfile: %s\n", filereso);
11451: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11452: fflush(ficlog);
11453: goto end;
11454: }
1.278 brouard 11455: /*-------- Rewriting parameter file ----------*/
11456: strcpy(rfileres,"r"); /* "Rparameterfile */
11457: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11458: strcat(rfileres,"."); /* */
11459: strcat(rfileres,optionfilext); /* Other files have txt extension */
11460: if((ficres =fopen(rfileres,"w"))==NULL) {
11461: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11462: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11463: fflush(ficlog);
11464: goto end;
11465: }
11466: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11467:
1.278 brouard 11468:
1.126 brouard 11469: /* Reads comments: lines beginning with '#' */
11470: numlinepar=0;
1.277 brouard 11471: /* Is it a BOM UTF-8 Windows file? */
11472: /* First parameter line */
1.197 brouard 11473: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11474: noffset=0;
11475: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11476: {
11477: noffset=noffset+3;
11478: printf("# File is an UTF8 Bom.\n"); // 0xBF
11479: }
1.302 brouard 11480: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11481: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11482: {
11483: noffset=noffset+2;
11484: printf("# File is an UTF16BE BOM file\n");
11485: }
11486: else if( line[0] == 0 && line[1] == 0)
11487: {
11488: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11489: noffset=noffset+4;
11490: printf("# File is an UTF16BE BOM file\n");
11491: }
11492: } else{
11493: ;/*printf(" Not a BOM file\n");*/
11494: }
11495:
1.197 brouard 11496: /* If line starts with a # it is a comment */
1.277 brouard 11497: if (line[noffset] == '#') {
1.197 brouard 11498: numlinepar++;
11499: fputs(line,stdout);
11500: fputs(line,ficparo);
1.278 brouard 11501: fputs(line,ficres);
1.197 brouard 11502: fputs(line,ficlog);
11503: continue;
11504: }else
11505: break;
11506: }
11507: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11508: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11509: if (num_filled != 5) {
11510: printf("Should be 5 parameters\n");
1.283 brouard 11511: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11512: }
1.126 brouard 11513: numlinepar++;
1.197 brouard 11514: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11515: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11516: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11517: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11518: }
11519: /* Second parameter line */
11520: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11521: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11522: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11523: if (line[0] == '#') {
11524: numlinepar++;
1.283 brouard 11525: printf("%s",line);
11526: fprintf(ficres,"%s",line);
11527: fprintf(ficparo,"%s",line);
11528: fprintf(ficlog,"%s",line);
1.197 brouard 11529: continue;
11530: }else
11531: break;
11532: }
1.223 brouard 11533: 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", \
11534: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11535: if (num_filled != 11) {
11536: 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 11537: printf("but line=%s\n",line);
1.283 brouard 11538: 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");
11539: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11540: }
1.286 brouard 11541: if( lastpass > maxwav){
11542: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11543: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11544: fflush(ficlog);
11545: goto end;
11546: }
11547: 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 11548: 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 11549: 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 11550: 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 11551: }
1.203 brouard 11552: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11553: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11554: /* Third parameter line */
11555: while(fgets(line, MAXLINE, ficpar)) {
11556: /* If line starts with a # it is a comment */
11557: if (line[0] == '#') {
11558: numlinepar++;
1.283 brouard 11559: printf("%s",line);
11560: fprintf(ficres,"%s",line);
11561: fprintf(ficparo,"%s",line);
11562: fprintf(ficlog,"%s",line);
1.197 brouard 11563: continue;
11564: }else
11565: break;
11566: }
1.201 brouard 11567: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11568: if (num_filled != 1){
1.302 brouard 11569: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
11570: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 11571: model[0]='\0';
11572: goto end;
11573: }
11574: else{
11575: if (model[0]=='+'){
11576: for(i=1; i<=strlen(model);i++)
11577: modeltemp[i-1]=model[i];
1.201 brouard 11578: strcpy(model,modeltemp);
1.197 brouard 11579: }
11580: }
1.199 brouard 11581: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11582: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11583: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11584: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11585: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11586: }
11587: /* 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); */
11588: /* numlinepar=numlinepar+3; /\* In general *\/ */
11589: /* 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 11590: /* 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); */
11591: /* 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 11592: fflush(ficlog);
1.190 brouard 11593: /* if(model[0]=='#'|| model[0]== '\0'){ */
11594: if(model[0]=='#'){
1.279 brouard 11595: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11596: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11597: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11598: if(mle != -1){
1.279 brouard 11599: 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 11600: exit(1);
11601: }
11602: }
1.126 brouard 11603: while((c=getc(ficpar))=='#' && c!= EOF){
11604: ungetc(c,ficpar);
11605: fgets(line, MAXLINE, ficpar);
11606: numlinepar++;
1.195 brouard 11607: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11608: z[0]=line[1];
11609: }
11610: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11611: fputs(line, stdout);
11612: //puts(line);
1.126 brouard 11613: fputs(line,ficparo);
11614: fputs(line,ficlog);
11615: }
11616: ungetc(c,ficpar);
11617:
11618:
1.290 brouard 11619: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11620: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11621: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11622: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11623: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11624: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11625: v1+v2*age+v2*v3 makes cptcovn = 3
11626: */
11627: if (strlen(model)>1)
1.187 brouard 11628: 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 11629: else
1.187 brouard 11630: ncovmodel=2; /* Constant and age */
1.133 brouard 11631: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11632: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11633: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11634: 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);
11635: 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);
11636: fflush(stdout);
11637: fclose (ficlog);
11638: goto end;
11639: }
1.126 brouard 11640: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11641: delti=delti3[1][1];
11642: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11643: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11644: /* We could also provide initial parameters values giving by simple logistic regression
11645: * only one way, that is without matrix product. We will have nlstate maximizations */
11646: /* for(i=1;i<nlstate;i++){ */
11647: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11648: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11649: /* } */
1.126 brouard 11650: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11651: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11652: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11653: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11654: fclose (ficparo);
11655: fclose (ficlog);
11656: goto end;
11657: exit(0);
1.220 brouard 11658: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11659: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11660: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11661: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11662: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11663: matcov=matrix(1,npar,1,npar);
1.203 brouard 11664: hess=matrix(1,npar,1,npar);
1.220 brouard 11665: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11666: /* Read guessed parameters */
1.126 brouard 11667: /* Reads comments: lines beginning with '#' */
11668: while((c=getc(ficpar))=='#' && c!= EOF){
11669: ungetc(c,ficpar);
11670: fgets(line, MAXLINE, ficpar);
11671: numlinepar++;
1.141 brouard 11672: fputs(line,stdout);
1.126 brouard 11673: fputs(line,ficparo);
11674: fputs(line,ficlog);
11675: }
11676: ungetc(c,ficpar);
11677:
11678: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11679: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11680: for(i=1; i <=nlstate; i++){
1.234 brouard 11681: j=0;
1.126 brouard 11682: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11683: if(jj==i) continue;
11684: j++;
1.292 brouard 11685: while((c=getc(ficpar))=='#' && c!= EOF){
11686: ungetc(c,ficpar);
11687: fgets(line, MAXLINE, ficpar);
11688: numlinepar++;
11689: fputs(line,stdout);
11690: fputs(line,ficparo);
11691: fputs(line,ficlog);
11692: }
11693: ungetc(c,ficpar);
1.234 brouard 11694: fscanf(ficpar,"%1d%1d",&i1,&j1);
11695: if ((i1 != i) || (j1 != jj)){
11696: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11697: It might be a problem of design; if ncovcol and the model are correct\n \
11698: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11699: exit(1);
11700: }
11701: fprintf(ficparo,"%1d%1d",i1,j1);
11702: if(mle==1)
11703: printf("%1d%1d",i,jj);
11704: fprintf(ficlog,"%1d%1d",i,jj);
11705: for(k=1; k<=ncovmodel;k++){
11706: fscanf(ficpar," %lf",¶m[i][j][k]);
11707: if(mle==1){
11708: printf(" %lf",param[i][j][k]);
11709: fprintf(ficlog," %lf",param[i][j][k]);
11710: }
11711: else
11712: fprintf(ficlog," %lf",param[i][j][k]);
11713: fprintf(ficparo," %lf",param[i][j][k]);
11714: }
11715: fscanf(ficpar,"\n");
11716: numlinepar++;
11717: if(mle==1)
11718: printf("\n");
11719: fprintf(ficlog,"\n");
11720: fprintf(ficparo,"\n");
1.126 brouard 11721: }
11722: }
11723: fflush(ficlog);
1.234 brouard 11724:
1.251 brouard 11725: /* Reads parameters values */
1.126 brouard 11726: p=param[1][1];
1.251 brouard 11727: pstart=paramstart[1][1];
1.126 brouard 11728:
11729: /* Reads comments: lines beginning with '#' */
11730: while((c=getc(ficpar))=='#' && c!= EOF){
11731: ungetc(c,ficpar);
11732: fgets(line, MAXLINE, ficpar);
11733: numlinepar++;
1.141 brouard 11734: fputs(line,stdout);
1.126 brouard 11735: fputs(line,ficparo);
11736: fputs(line,ficlog);
11737: }
11738: ungetc(c,ficpar);
11739:
11740: for(i=1; i <=nlstate; i++){
11741: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11742: fscanf(ficpar,"%1d%1d",&i1,&j1);
11743: if ( (i1-i) * (j1-j) != 0){
11744: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11745: exit(1);
11746: }
11747: printf("%1d%1d",i,j);
11748: fprintf(ficparo,"%1d%1d",i1,j1);
11749: fprintf(ficlog,"%1d%1d",i1,j1);
11750: for(k=1; k<=ncovmodel;k++){
11751: fscanf(ficpar,"%le",&delti3[i][j][k]);
11752: printf(" %le",delti3[i][j][k]);
11753: fprintf(ficparo," %le",delti3[i][j][k]);
11754: fprintf(ficlog," %le",delti3[i][j][k]);
11755: }
11756: fscanf(ficpar,"\n");
11757: numlinepar++;
11758: printf("\n");
11759: fprintf(ficparo,"\n");
11760: fprintf(ficlog,"\n");
1.126 brouard 11761: }
11762: }
11763: fflush(ficlog);
1.234 brouard 11764:
1.145 brouard 11765: /* Reads covariance matrix */
1.126 brouard 11766: delti=delti3[1][1];
1.220 brouard 11767:
11768:
1.126 brouard 11769: /* 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 11770:
1.126 brouard 11771: /* Reads comments: lines beginning with '#' */
11772: while((c=getc(ficpar))=='#' && c!= EOF){
11773: ungetc(c,ficpar);
11774: fgets(line, MAXLINE, ficpar);
11775: numlinepar++;
1.141 brouard 11776: fputs(line,stdout);
1.126 brouard 11777: fputs(line,ficparo);
11778: fputs(line,ficlog);
11779: }
11780: ungetc(c,ficpar);
1.220 brouard 11781:
1.126 brouard 11782: matcov=matrix(1,npar,1,npar);
1.203 brouard 11783: hess=matrix(1,npar,1,npar);
1.131 brouard 11784: for(i=1; i <=npar; i++)
11785: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11786:
1.194 brouard 11787: /* Scans npar lines */
1.126 brouard 11788: for(i=1; i <=npar; i++){
1.226 brouard 11789: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11790: if(count != 3){
1.226 brouard 11791: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11792: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11793: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11794: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11795: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11796: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11797: exit(1);
1.220 brouard 11798: }else{
1.226 brouard 11799: if(mle==1)
11800: printf("%1d%1d%d",i1,j1,jk);
11801: }
11802: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11803: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11804: for(j=1; j <=i; j++){
1.226 brouard 11805: fscanf(ficpar," %le",&matcov[i][j]);
11806: if(mle==1){
11807: printf(" %.5le",matcov[i][j]);
11808: }
11809: fprintf(ficlog," %.5le",matcov[i][j]);
11810: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11811: }
11812: fscanf(ficpar,"\n");
11813: numlinepar++;
11814: if(mle==1)
1.220 brouard 11815: printf("\n");
1.126 brouard 11816: fprintf(ficlog,"\n");
11817: fprintf(ficparo,"\n");
11818: }
1.194 brouard 11819: /* End of read covariance matrix npar lines */
1.126 brouard 11820: for(i=1; i <=npar; i++)
11821: for(j=i+1;j<=npar;j++)
1.226 brouard 11822: matcov[i][j]=matcov[j][i];
1.126 brouard 11823:
11824: if(mle==1)
11825: printf("\n");
11826: fprintf(ficlog,"\n");
11827:
11828: fflush(ficlog);
11829:
11830: } /* End of mle != -3 */
1.218 brouard 11831:
1.186 brouard 11832: /* Main data
11833: */
1.290 brouard 11834: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11835: /* num=lvector(1,n); */
11836: /* moisnais=vector(1,n); */
11837: /* annais=vector(1,n); */
11838: /* moisdc=vector(1,n); */
11839: /* andc=vector(1,n); */
11840: /* weight=vector(1,n); */
11841: /* agedc=vector(1,n); */
11842: /* cod=ivector(1,n); */
11843: /* for(i=1;i<=n;i++){ */
11844: num=lvector(firstobs,lastobs);
11845: moisnais=vector(firstobs,lastobs);
11846: annais=vector(firstobs,lastobs);
11847: moisdc=vector(firstobs,lastobs);
11848: andc=vector(firstobs,lastobs);
11849: weight=vector(firstobs,lastobs);
11850: agedc=vector(firstobs,lastobs);
11851: cod=ivector(firstobs,lastobs);
11852: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11853: num[i]=0;
11854: moisnais[i]=0;
11855: annais[i]=0;
11856: moisdc[i]=0;
11857: andc[i]=0;
11858: agedc[i]=0;
11859: cod[i]=0;
11860: weight[i]=1.0; /* Equal weights, 1 by default */
11861: }
1.290 brouard 11862: mint=matrix(1,maxwav,firstobs,lastobs);
11863: anint=matrix(1,maxwav,firstobs,lastobs);
11864: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11865: tab=ivector(1,NCOVMAX);
1.144 brouard 11866: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11867: 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 11868:
1.136 brouard 11869: /* Reads data from file datafile */
11870: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11871: goto end;
11872:
11873: /* Calculation of the number of parameters from char model */
1.234 brouard 11874: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11875: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11876: k=3 V4 Tvar[k=3]= 4 (from V4)
11877: k=2 V1 Tvar[k=2]= 1 (from V1)
11878: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11879: */
11880:
11881: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11882: TvarsDind=ivector(1,NCOVMAX); /* */
11883: TvarsD=ivector(1,NCOVMAX); /* */
11884: TvarsQind=ivector(1,NCOVMAX); /* */
11885: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11886: TvarF=ivector(1,NCOVMAX); /* */
11887: TvarFind=ivector(1,NCOVMAX); /* */
11888: TvarV=ivector(1,NCOVMAX); /* */
11889: TvarVind=ivector(1,NCOVMAX); /* */
11890: TvarA=ivector(1,NCOVMAX); /* */
11891: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11892: TvarFD=ivector(1,NCOVMAX); /* */
11893: TvarFDind=ivector(1,NCOVMAX); /* */
11894: TvarFQ=ivector(1,NCOVMAX); /* */
11895: TvarFQind=ivector(1,NCOVMAX); /* */
11896: TvarVD=ivector(1,NCOVMAX); /* */
11897: TvarVDind=ivector(1,NCOVMAX); /* */
11898: TvarVQ=ivector(1,NCOVMAX); /* */
11899: TvarVQind=ivector(1,NCOVMAX); /* */
11900:
1.230 brouard 11901: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11902: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11903: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11904: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11905: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11906: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11907: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11908: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11909: */
11910: /* For model-covariate k tells which data-covariate to use but
11911: because this model-covariate is a construction we invent a new column
11912: ncovcol + k1
11913: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11914: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11915: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11916: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11917: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11918: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11919: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11920: */
1.145 brouard 11921: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11922: 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 11923: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11924: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11925: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11926: 4 covariates (3 plus signs)
11927: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11928: */
1.230 brouard 11929: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11930: * individual dummy, fixed or varying:
11931: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11932: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11933: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11934: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11935: * Tmodelind[1]@9={9,0,3,2,}*/
11936: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11937: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11938: * individual quantitative, fixed or varying:
11939: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11940: * 3, 1, 0, 0, 0, 0, 0, 0},
11941: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11942: /* Main decodemodel */
11943:
1.187 brouard 11944:
1.223 brouard 11945: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11946: goto end;
11947:
1.137 brouard 11948: if((double)(lastobs-imx)/(double)imx > 1.10){
11949: nbwarn++;
11950: 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);
11951: 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);
11952: }
1.136 brouard 11953: /* if(mle==1){*/
1.137 brouard 11954: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11955: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11956: }
11957:
11958: /*-calculation of age at interview from date of interview and age at death -*/
11959: agev=matrix(1,maxwav,1,imx);
11960:
11961: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11962: goto end;
11963:
1.126 brouard 11964:
1.136 brouard 11965: agegomp=(int)agemin;
1.290 brouard 11966: free_vector(moisnais,firstobs,lastobs);
11967: free_vector(annais,firstobs,lastobs);
1.126 brouard 11968: /* free_matrix(mint,1,maxwav,1,n);
11969: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11970: /* free_vector(moisdc,1,n); */
11971: /* free_vector(andc,1,n); */
1.145 brouard 11972: /* */
11973:
1.126 brouard 11974: wav=ivector(1,imx);
1.214 brouard 11975: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11976: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11977: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11978: 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.*/
11979: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11980: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11981:
11982: /* Concatenates waves */
1.214 brouard 11983: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11984: Death is a valid wave (if date is known).
11985: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11986: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11987: and mw[mi+1][i]. dh depends on stepm.
11988: */
11989:
1.126 brouard 11990: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11991: /* Concatenates waves */
1.145 brouard 11992:
1.290 brouard 11993: free_vector(moisdc,firstobs,lastobs);
11994: free_vector(andc,firstobs,lastobs);
1.215 brouard 11995:
1.126 brouard 11996: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11997: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11998: ncodemax[1]=1;
1.145 brouard 11999: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12000: cptcoveff=0;
1.220 brouard 12001: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
12002: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 12003: }
12004:
12005: ncovcombmax=pow(2,cptcoveff);
12006: invalidvarcomb=ivector(1, ncovcombmax);
12007: for(i=1;i<ncovcombmax;i++)
12008: invalidvarcomb[i]=0;
12009:
1.211 brouard 12010: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12011: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12012: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12013:
1.200 brouard 12014: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12015: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12016: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12017: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12018: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12019: * (currently 0 or 1) in the data.
12020: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12021: * corresponding modality (h,j).
12022: */
12023:
1.145 brouard 12024: h=0;
12025: /*if (cptcovn > 0) */
1.126 brouard 12026: m=pow(2,cptcoveff);
12027:
1.144 brouard 12028: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12029: * For k=4 covariates, h goes from 1 to m=2**k
12030: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12031: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 12032: * h\k 1 2 3 4
1.143 brouard 12033: *______________________________
12034: * 1 i=1 1 i=1 1 i=1 1 i=1 1
12035: * 2 2 1 1 1
12036: * 3 i=2 1 2 1 1
12037: * 4 2 2 1 1
12038: * 5 i=3 1 i=2 1 2 1
12039: * 6 2 1 2 1
12040: * 7 i=4 1 2 2 1
12041: * 8 2 2 2 1
1.197 brouard 12042: * 9 i=5 1 i=3 1 i=2 1 2
12043: * 10 2 1 1 2
12044: * 11 i=6 1 2 1 2
12045: * 12 2 2 1 2
12046: * 13 i=7 1 i=4 1 2 2
12047: * 14 2 1 2 2
12048: * 15 i=8 1 2 2 2
12049: * 16 2 2 2 2
1.143 brouard 12050: */
1.212 brouard 12051: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12052: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12053: * and the value of each covariate?
12054: * V1=1, V2=1, V3=2, V4=1 ?
12055: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12056: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12057: * In order to get the real value in the data, we use nbcode
12058: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12059: * We are keeping this crazy system in order to be able (in the future?)
12060: * to have more than 2 values (0 or 1) for a covariate.
12061: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12062: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12063: * bbbbbbbb
12064: * 76543210
12065: * h-1 00000101 (6-1=5)
1.219 brouard 12066: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12067: * &
12068: * 1 00000001 (1)
1.219 brouard 12069: * 00000000 = 1 & ((h-1) >> (k-1))
12070: * +1= 00000001 =1
1.211 brouard 12071: *
12072: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12073: * h' 1101 =2^3+2^2+0x2^1+2^0
12074: * >>k' 11
12075: * & 00000001
12076: * = 00000001
12077: * +1 = 00000010=2 = codtabm(14,3)
12078: * Reverse h=6 and m=16?
12079: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12080: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12081: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12082: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12083: * V3=decodtabm(14,3,2**4)=2
12084: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12085: *(h-1) >> (j-1) 0011 =13 >> 2
12086: * &1 000000001
12087: * = 000000001
12088: * +1= 000000010 =2
12089: * 2211
12090: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12091: * V3=2
1.220 brouard 12092: * codtabm and decodtabm are identical
1.211 brouard 12093: */
12094:
1.145 brouard 12095:
12096: free_ivector(Ndum,-1,NCOVMAX);
12097:
12098:
1.126 brouard 12099:
1.186 brouard 12100: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12101: strcpy(optionfilegnuplot,optionfilefiname);
12102: if(mle==-3)
1.201 brouard 12103: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12104: strcat(optionfilegnuplot,".gp");
12105:
12106: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12107: printf("Problem with file %s",optionfilegnuplot);
12108: }
12109: else{
1.204 brouard 12110: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12111: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12112: //fprintf(ficgp,"set missing 'NaNq'\n");
12113: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12114: }
12115: /* fclose(ficgp);*/
1.186 brouard 12116:
12117:
12118: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12119:
12120: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12121: if(mle==-3)
1.201 brouard 12122: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12123: strcat(optionfilehtm,".htm");
12124: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12125: printf("Problem with %s \n",optionfilehtm);
12126: exit(0);
1.126 brouard 12127: }
12128:
12129: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
12130: strcat(optionfilehtmcov,"-cov.htm");
12131: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
12132: printf("Problem with %s \n",optionfilehtmcov), exit(0);
12133: }
12134: else{
12135: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
12136: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12137: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 12138: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
12139: }
12140:
1.213 brouard 12141: fprintf(fichtm,"<html><head>\n<head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<title>IMaCh %s</title></head>\n <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n<font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>-EUROREVES-Institut de longévité-2013-2016-Japan Society for the Promotion of Sciences 日本å¦è¡“振興会 (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \
1.204 brouard 12142: <hr size=\"2\" color=\"#EC5E5E\"> \n\
12143: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 12144: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12145: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 12146: \n\
12147: <hr size=\"2\" color=\"#EC5E5E\">\
12148: <ul><li><h4>Parameter files</h4>\n\
12149: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
12150: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
12151: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12152: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12153: - Date and time at start: %s</ul>\n",\
12154: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
12155: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12156: fileres,fileres,\
12157: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12158: fflush(fichtm);
12159:
12160: strcpy(pathr,path);
12161: strcat(pathr,optionfilefiname);
1.184 brouard 12162: #ifdef WIN32
12163: _chdir(optionfilefiname); /* Move to directory named optionfile */
12164: #else
1.126 brouard 12165: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12166: #endif
12167:
1.126 brouard 12168:
1.220 brouard 12169: /* Calculates basic frequencies. Computes observed prevalence at single age
12170: and for any valid combination of covariates
1.126 brouard 12171: and prints on file fileres'p'. */
1.251 brouard 12172: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12173: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12174:
12175: fprintf(fichtm,"\n");
1.286 brouard 12176: 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 12177: ftol, stepm);
12178: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12179: ncurrv=1;
12180: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12181: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12182: ncurrv=i;
12183: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12184: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12185: ncurrv=i;
12186: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12187: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12188: ncurrv=i;
12189: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12190: 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", \
12191: nlstate, ndeath, maxwav, mle, weightopt);
12192:
12193: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12194: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12195:
12196:
1.317 brouard 12197: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12198: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12199: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12200: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12201: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12202: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12203: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12204: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12205: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12206:
1.126 brouard 12207: /* For Powell, parameters are in a vector p[] starting at p[1]
12208: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12209: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12210:
12211: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12212: /* For mortality only */
1.126 brouard 12213: if (mle==-3){
1.136 brouard 12214: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12215: for(i=1;i<=NDIM;i++)
12216: for(j=1;j<=NDIM;j++)
12217: ximort[i][j]=0.;
1.186 brouard 12218: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12219: cens=ivector(firstobs,lastobs);
12220: ageexmed=vector(firstobs,lastobs);
12221: agecens=vector(firstobs,lastobs);
12222: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12223:
1.126 brouard 12224: for (i=1; i<=imx; i++){
12225: dcwave[i]=-1;
12226: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12227: if (s[m][i]>nlstate) {
12228: dcwave[i]=m;
12229: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12230: break;
12231: }
1.126 brouard 12232: }
1.226 brouard 12233:
1.126 brouard 12234: for (i=1; i<=imx; i++) {
12235: if (wav[i]>0){
1.226 brouard 12236: ageexmed[i]=agev[mw[1][i]][i];
12237: j=wav[i];
12238: agecens[i]=1.;
12239:
12240: if (ageexmed[i]> 1 && wav[i] > 0){
12241: agecens[i]=agev[mw[j][i]][i];
12242: cens[i]= 1;
12243: }else if (ageexmed[i]< 1)
12244: cens[i]= -1;
12245: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12246: cens[i]=0 ;
1.126 brouard 12247: }
12248: else cens[i]=-1;
12249: }
12250:
12251: for (i=1;i<=NDIM;i++) {
12252: for (j=1;j<=NDIM;j++)
1.226 brouard 12253: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12254: }
12255:
1.302 brouard 12256: p[1]=0.0268; p[NDIM]=0.083;
12257: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12258:
12259:
1.136 brouard 12260: #ifdef GSL
12261: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12262: #else
1.126 brouard 12263: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12264: #endif
1.201 brouard 12265: strcpy(filerespow,"POW-MORT_");
12266: strcat(filerespow,fileresu);
1.126 brouard 12267: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12268: printf("Problem with resultfile: %s\n", filerespow);
12269: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12270: }
1.136 brouard 12271: #ifdef GSL
12272: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12273: #else
1.126 brouard 12274: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12275: #endif
1.126 brouard 12276: /* for (i=1;i<=nlstate;i++)
12277: for(j=1;j<=nlstate+ndeath;j++)
12278: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12279: */
12280: fprintf(ficrespow,"\n");
1.136 brouard 12281: #ifdef GSL
12282: /* gsl starts here */
12283: T = gsl_multimin_fminimizer_nmsimplex;
12284: gsl_multimin_fminimizer *sfm = NULL;
12285: gsl_vector *ss, *x;
12286: gsl_multimin_function minex_func;
12287:
12288: /* Initial vertex size vector */
12289: ss = gsl_vector_alloc (NDIM);
12290:
12291: if (ss == NULL){
12292: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12293: }
12294: /* Set all step sizes to 1 */
12295: gsl_vector_set_all (ss, 0.001);
12296:
12297: /* Starting point */
1.126 brouard 12298:
1.136 brouard 12299: x = gsl_vector_alloc (NDIM);
12300:
12301: if (x == NULL){
12302: gsl_vector_free(ss);
12303: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12304: }
12305:
12306: /* Initialize method and iterate */
12307: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12308: /* gsl_vector_set(x, 0, 0.0268); */
12309: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12310: gsl_vector_set(x, 0, p[1]);
12311: gsl_vector_set(x, 1, p[2]);
12312:
12313: minex_func.f = &gompertz_f;
12314: minex_func.n = NDIM;
12315: minex_func.params = (void *)&p; /* ??? */
12316:
12317: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12318: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12319:
12320: printf("Iterations beginning .....\n\n");
12321: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12322:
12323: iteri=0;
12324: while (rval == GSL_CONTINUE){
12325: iteri++;
12326: status = gsl_multimin_fminimizer_iterate(sfm);
12327:
12328: if (status) printf("error: %s\n", gsl_strerror (status));
12329: fflush(0);
12330:
12331: if (status)
12332: break;
12333:
12334: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12335: ssval = gsl_multimin_fminimizer_size (sfm);
12336:
12337: if (rval == GSL_SUCCESS)
12338: printf ("converged to a local maximum at\n");
12339:
12340: printf("%5d ", iteri);
12341: for (it = 0; it < NDIM; it++){
12342: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12343: }
12344: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12345: }
12346:
12347: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12348:
12349: gsl_vector_free(x); /* initial values */
12350: gsl_vector_free(ss); /* inital step size */
12351: for (it=0; it<NDIM; it++){
12352: p[it+1]=gsl_vector_get(sfm->x,it);
12353: fprintf(ficrespow," %.12lf", p[it]);
12354: }
12355: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12356: #endif
12357: #ifdef POWELL
12358: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12359: #endif
1.126 brouard 12360: fclose(ficrespow);
12361:
1.203 brouard 12362: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12363:
12364: for(i=1; i <=NDIM; i++)
12365: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12366: matcov[i][j]=matcov[j][i];
1.126 brouard 12367:
12368: printf("\nCovariance matrix\n ");
1.203 brouard 12369: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12370: for(i=1; i <=NDIM; i++) {
12371: for(j=1;j<=NDIM;j++){
1.220 brouard 12372: printf("%f ",matcov[i][j]);
12373: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12374: }
1.203 brouard 12375: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12376: }
12377:
12378: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12379: for (i=1;i<=NDIM;i++) {
1.126 brouard 12380: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12381: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12382: }
1.302 brouard 12383: lsurv=vector(agegomp,AGESUP);
12384: lpop=vector(agegomp,AGESUP);
12385: tpop=vector(agegomp,AGESUP);
1.126 brouard 12386: lsurv[agegomp]=100000;
12387:
12388: for (k=agegomp;k<=AGESUP;k++) {
12389: agemortsup=k;
12390: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12391: }
12392:
12393: for (k=agegomp;k<agemortsup;k++)
12394: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12395:
12396: for (k=agegomp;k<agemortsup;k++){
12397: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12398: sumlpop=sumlpop+lpop[k];
12399: }
12400:
12401: tpop[agegomp]=sumlpop;
12402: for (k=agegomp;k<(agemortsup-3);k++){
12403: /* tpop[k+1]=2;*/
12404: tpop[k+1]=tpop[k]-lpop[k];
12405: }
12406:
12407:
12408: printf("\nAge lx qx dx Lx Tx e(x)\n");
12409: for (k=agegomp;k<(agemortsup-2);k++)
12410: 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]);
12411:
12412:
12413: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12414: ageminpar=50;
12415: agemaxpar=100;
1.194 brouard 12416: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12417: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12418: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12419: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12420: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12421: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12422: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12423: }else{
12424: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12425: 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 12426: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12427: }
1.201 brouard 12428: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12429: stepm, weightopt,\
12430: model,imx,p,matcov,agemortsup);
12431:
1.302 brouard 12432: free_vector(lsurv,agegomp,AGESUP);
12433: free_vector(lpop,agegomp,AGESUP);
12434: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12435: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12436: free_ivector(dcwave,firstobs,lastobs);
12437: free_vector(agecens,firstobs,lastobs);
12438: free_vector(ageexmed,firstobs,lastobs);
12439: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12440: #ifdef GSL
1.136 brouard 12441: #endif
1.186 brouard 12442: } /* Endof if mle==-3 mortality only */
1.205 brouard 12443: /* Standard */
12444: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12445: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12446: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12447: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12448: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12449: for (k=1; k<=npar;k++)
12450: printf(" %d %8.5f",k,p[k]);
12451: printf("\n");
1.205 brouard 12452: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12453: /* mlikeli uses func not funcone */
1.247 brouard 12454: /* for(i=1;i<nlstate;i++){ */
12455: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12456: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12457: /* } */
1.205 brouard 12458: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12459: }
12460: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12461: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12462: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12463: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12464: }
12465: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12466: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12467: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12468: for (k=1; k<=npar;k++)
12469: printf(" %d %8.5f",k,p[k]);
12470: printf("\n");
12471:
12472: /*--------- results files --------------*/
1.283 brouard 12473: /* 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 12474:
12475:
12476: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12477: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 12478: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12479:
12480: printf("#model= 1 + age ");
12481: fprintf(ficres,"#model= 1 + age ");
12482: fprintf(ficlog,"#model= 1 + age ");
12483: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
12484: </ul>", model);
12485:
12486: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
12487: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
12488: if(nagesqr==1){
12489: printf(" + age*age ");
12490: fprintf(ficres," + age*age ");
12491: fprintf(ficlog," + age*age ");
12492: fprintf(fichtm, "<th>+ age*age</th>");
12493: }
12494: for(j=1;j <=ncovmodel-2;j++){
12495: if(Typevar[j]==0) {
12496: printf(" + V%d ",Tvar[j]);
12497: fprintf(ficres," + V%d ",Tvar[j]);
12498: fprintf(ficlog," + V%d ",Tvar[j]);
12499: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12500: }else if(Typevar[j]==1) {
12501: printf(" + V%d*age ",Tvar[j]);
12502: fprintf(ficres," + V%d*age ",Tvar[j]);
12503: fprintf(ficlog," + V%d*age ",Tvar[j]);
12504: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12505: }else if(Typevar[j]==2) {
12506: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12507: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12508: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12509: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12510: }
12511: }
12512: printf("\n");
12513: fprintf(ficres,"\n");
12514: fprintf(ficlog,"\n");
12515: fprintf(fichtm, "</tr>");
12516: fprintf(fichtm, "\n");
12517:
12518:
1.126 brouard 12519: for(i=1,jk=1; i <=nlstate; i++){
12520: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12521: if (k != i) {
1.319 brouard 12522: fprintf(fichtm, "<tr>");
1.225 brouard 12523: printf("%d%d ",i,k);
12524: fprintf(ficlog,"%d%d ",i,k);
12525: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 12526: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12527: for(j=1; j <=ncovmodel; j++){
12528: printf("%12.7f ",p[jk]);
12529: fprintf(ficlog,"%12.7f ",p[jk]);
12530: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 12531: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 12532: jk++;
12533: }
12534: printf("\n");
12535: fprintf(ficlog,"\n");
12536: fprintf(ficres,"\n");
1.319 brouard 12537: fprintf(fichtm, "</tr>\n");
1.225 brouard 12538: }
1.126 brouard 12539: }
12540: }
1.319 brouard 12541: /* fprintf(fichtm,"</tr>\n"); */
12542: fprintf(fichtm,"</table>\n");
12543: fprintf(fichtm, "\n");
12544:
1.203 brouard 12545: if(mle != 0){
12546: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12547: ftolhess=ftol; /* Usually correct */
1.203 brouard 12548: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12549: 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");
12550: 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");
1.319 brouard 12551: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
12552: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
12553: if(nagesqr==1){
12554: printf(" + age*age ");
12555: fprintf(ficres," + age*age ");
12556: fprintf(ficlog," + age*age ");
12557: fprintf(fichtm, "<th>+ age*age</th>");
12558: }
12559: for(j=1;j <=ncovmodel-2;j++){
12560: if(Typevar[j]==0) {
12561: printf(" + V%d ",Tvar[j]);
12562: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12563: }else if(Typevar[j]==1) {
12564: printf(" + V%d*age ",Tvar[j]);
12565: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12566: }else if(Typevar[j]==2) {
12567: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12568: }
12569: }
12570: fprintf(fichtm, "</tr>\n");
12571:
1.203 brouard 12572: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12573: for(k=1; k <=(nlstate+ndeath); k++){
12574: if (k != i) {
1.319 brouard 12575: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 12576: printf("%d%d ",i,k);
12577: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 12578: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12579: for(j=1; j <=ncovmodel; j++){
1.319 brouard 12580: wald=p[jk]/sqrt(matcov[jk][jk]);
12581: 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]));
12582: 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]));
12583: if(fabs(wald) > 1.96){
12584: fprintf(fichtm, "<td><b>%12.7f</b> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
12585: fprintf(fichtm,"<b>W=%8.3f</b></br>",wald);
12586: }else{
12587: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
12588: fprintf(fichtm,"W=%8.3f</br>",wald);
12589: }
12590: 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 12591: jk++;
12592: }
12593: printf("\n");
12594: fprintf(ficlog,"\n");
1.319 brouard 12595: fprintf(fichtm, "</tr>\n");
1.225 brouard 12596: }
12597: }
1.193 brouard 12598: }
1.203 brouard 12599: } /* end of hesscov and Wald tests */
1.319 brouard 12600: fprintf(fichtm,"</table>\n");
1.225 brouard 12601:
1.203 brouard 12602: /* */
1.126 brouard 12603: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12604: printf("# Scales (for hessian or gradient estimation)\n");
12605: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12606: for(i=1,jk=1; i <=nlstate; i++){
12607: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12608: if (j!=i) {
12609: fprintf(ficres,"%1d%1d",i,j);
12610: printf("%1d%1d",i,j);
12611: fprintf(ficlog,"%1d%1d",i,j);
12612: for(k=1; k<=ncovmodel;k++){
12613: printf(" %.5e",delti[jk]);
12614: fprintf(ficlog," %.5e",delti[jk]);
12615: fprintf(ficres," %.5e",delti[jk]);
12616: jk++;
12617: }
12618: printf("\n");
12619: fprintf(ficlog,"\n");
12620: fprintf(ficres,"\n");
12621: }
1.126 brouard 12622: }
12623: }
12624:
12625: 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 12626: if(mle >= 1) /* To big for the screen */
1.126 brouard 12627: 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");
12628: 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");
12629: /* # 121 Var(a12)\n\ */
12630: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12631: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12632: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12633: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12634: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12635: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12636: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12637:
12638:
12639: /* Just to have a covariance matrix which will be more understandable
12640: even is we still don't want to manage dictionary of variables
12641: */
12642: for(itimes=1;itimes<=2;itimes++){
12643: jj=0;
12644: for(i=1; i <=nlstate; i++){
1.225 brouard 12645: for(j=1; j <=nlstate+ndeath; j++){
12646: if(j==i) continue;
12647: for(k=1; k<=ncovmodel;k++){
12648: jj++;
12649: ca[0]= k+'a'-1;ca[1]='\0';
12650: if(itimes==1){
12651: if(mle>=1)
12652: printf("#%1d%1d%d",i,j,k);
12653: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12654: fprintf(ficres,"#%1d%1d%d",i,j,k);
12655: }else{
12656: if(mle>=1)
12657: printf("%1d%1d%d",i,j,k);
12658: fprintf(ficlog,"%1d%1d%d",i,j,k);
12659: fprintf(ficres,"%1d%1d%d",i,j,k);
12660: }
12661: ll=0;
12662: for(li=1;li <=nlstate; li++){
12663: for(lj=1;lj <=nlstate+ndeath; lj++){
12664: if(lj==li) continue;
12665: for(lk=1;lk<=ncovmodel;lk++){
12666: ll++;
12667: if(ll<=jj){
12668: cb[0]= lk +'a'-1;cb[1]='\0';
12669: if(ll<jj){
12670: if(itimes==1){
12671: if(mle>=1)
12672: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12673: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12674: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12675: }else{
12676: if(mle>=1)
12677: printf(" %.5e",matcov[jj][ll]);
12678: fprintf(ficlog," %.5e",matcov[jj][ll]);
12679: fprintf(ficres," %.5e",matcov[jj][ll]);
12680: }
12681: }else{
12682: if(itimes==1){
12683: if(mle>=1)
12684: printf(" Var(%s%1d%1d)",ca,i,j);
12685: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12686: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12687: }else{
12688: if(mle>=1)
12689: printf(" %.7e",matcov[jj][ll]);
12690: fprintf(ficlog," %.7e",matcov[jj][ll]);
12691: fprintf(ficres," %.7e",matcov[jj][ll]);
12692: }
12693: }
12694: }
12695: } /* end lk */
12696: } /* end lj */
12697: } /* end li */
12698: if(mle>=1)
12699: printf("\n");
12700: fprintf(ficlog,"\n");
12701: fprintf(ficres,"\n");
12702: numlinepar++;
12703: } /* end k*/
12704: } /*end j */
1.126 brouard 12705: } /* end i */
12706: } /* end itimes */
12707:
12708: fflush(ficlog);
12709: fflush(ficres);
1.225 brouard 12710: while(fgets(line, MAXLINE, ficpar)) {
12711: /* If line starts with a # it is a comment */
12712: if (line[0] == '#') {
12713: numlinepar++;
12714: fputs(line,stdout);
12715: fputs(line,ficparo);
12716: fputs(line,ficlog);
1.299 brouard 12717: fputs(line,ficres);
1.225 brouard 12718: continue;
12719: }else
12720: break;
12721: }
12722:
1.209 brouard 12723: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12724: /* ungetc(c,ficpar); */
12725: /* fgets(line, MAXLINE, ficpar); */
12726: /* fputs(line,stdout); */
12727: /* fputs(line,ficparo); */
12728: /* } */
12729: /* ungetc(c,ficpar); */
1.126 brouard 12730:
12731: estepm=0;
1.209 brouard 12732: 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 12733:
12734: if (num_filled != 6) {
12735: 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);
12736: 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);
12737: goto end;
12738: }
12739: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12740: }
12741: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12742: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12743:
1.209 brouard 12744: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12745: if (estepm==0 || estepm < stepm) estepm=stepm;
12746: if (fage <= 2) {
12747: bage = ageminpar;
12748: fage = agemaxpar;
12749: }
12750:
12751: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12752: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12753: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12754:
1.186 brouard 12755: /* Other stuffs, more or less useful */
1.254 brouard 12756: while(fgets(line, MAXLINE, ficpar)) {
12757: /* If line starts with a # it is a comment */
12758: if (line[0] == '#') {
12759: numlinepar++;
12760: fputs(line,stdout);
12761: fputs(line,ficparo);
12762: fputs(line,ficlog);
1.299 brouard 12763: fputs(line,ficres);
1.254 brouard 12764: continue;
12765: }else
12766: break;
12767: }
12768:
12769: 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){
12770:
12771: if (num_filled != 7) {
12772: 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);
12773: 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);
12774: goto end;
12775: }
12776: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12777: 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);
12778: 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);
12779: 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 12780: }
1.254 brouard 12781:
12782: while(fgets(line, MAXLINE, ficpar)) {
12783: /* If line starts with a # it is a comment */
12784: if (line[0] == '#') {
12785: numlinepar++;
12786: fputs(line,stdout);
12787: fputs(line,ficparo);
12788: fputs(line,ficlog);
1.299 brouard 12789: fputs(line,ficres);
1.254 brouard 12790: continue;
12791: }else
12792: break;
1.126 brouard 12793: }
12794:
12795:
12796: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12797: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12798:
1.254 brouard 12799: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12800: if (num_filled != 1) {
12801: 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);
12802: 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);
12803: goto end;
12804: }
12805: printf("pop_based=%d\n",popbased);
12806: fprintf(ficlog,"pop_based=%d\n",popbased);
12807: fprintf(ficparo,"pop_based=%d\n",popbased);
12808: fprintf(ficres,"pop_based=%d\n",popbased);
12809: }
12810:
1.258 brouard 12811: /* Results */
1.307 brouard 12812: endishere=0;
1.258 brouard 12813: nresult=0;
1.308 brouard 12814: parameterline=0;
1.258 brouard 12815: do{
12816: if(!fgets(line, MAXLINE, ficpar)){
12817: endishere=1;
1.308 brouard 12818: parameterline=15;
1.258 brouard 12819: }else if (line[0] == '#') {
12820: /* If line starts with a # it is a comment */
1.254 brouard 12821: numlinepar++;
12822: fputs(line,stdout);
12823: fputs(line,ficparo);
12824: fputs(line,ficlog);
1.299 brouard 12825: fputs(line,ficres);
1.254 brouard 12826: continue;
1.258 brouard 12827: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12828: parameterline=11;
1.296 brouard 12829: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12830: parameterline=12;
1.307 brouard 12831: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 12832: parameterline=13;
1.307 brouard 12833: }
1.258 brouard 12834: else{
12835: parameterline=14;
1.254 brouard 12836: }
1.308 brouard 12837: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 12838: case 11:
1.296 brouard 12839: 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)){
12840: 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 12841: 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);
12842: 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);
12843: 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);
12844: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12845: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12846: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 12847: prvforecast = 1;
12848: }
12849: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 12850: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12851: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12852: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 12853: prvforecast = 2;
12854: }
12855: else {
12856: 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);
12857: 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);
12858: goto end;
1.258 brouard 12859: }
1.254 brouard 12860: break;
1.258 brouard 12861: case 12:
1.296 brouard 12862: 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)){
12863: 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);
12864: 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);
12865: 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);
12866: 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);
12867: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 12868: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12869: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 12870: prvbackcast = 1;
12871: }
12872: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 12873: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12874: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12875: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 12876: prvbackcast = 2;
12877: }
12878: else {
12879: 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);
12880: 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);
12881: goto end;
1.258 brouard 12882: }
1.230 brouard 12883: break;
1.258 brouard 12884: case 13:
1.307 brouard 12885: num_filled=sscanf(line,"result:%[^\n]\n",resultline);
12886: nresult++; /* Sum of resultlines */
12887: printf("Result %d: result:%s\n",nresult, resultline);
1.318 brouard 12888: if(nresult > MAXRESULTLINESPONE-1){
12889: 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);
12890: 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 12891: goto end;
12892: }
1.310 brouard 12893: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 12894: fprintf(ficparo,"result: %s\n",resultline);
12895: fprintf(ficres,"result: %s\n",resultline);
12896: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 12897: } else
12898: goto end;
1.307 brouard 12899: break;
12900: case 14:
12901: printf("Error: Unknown command '%s'\n",line);
12902: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 12903: if(line[0] == ' ' || line[0] == '\n'){
12904: printf("It should not be an empty line '%s'\n",line);
12905: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
12906: }
1.307 brouard 12907: if(ncovmodel >=2 && nresult==0 ){
12908: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
12909: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12910: }
1.307 brouard 12911: /* goto end; */
12912: break;
1.308 brouard 12913: case 15:
12914: printf("End of resultlines.\n");
12915: fprintf(ficlog,"End of resultlines.\n");
12916: break;
12917: default: /* parameterline =0 */
1.307 brouard 12918: nresult=1;
12919: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 12920: } /* End switch parameterline */
12921: }while(endishere==0); /* End do */
1.126 brouard 12922:
1.230 brouard 12923: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12924: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12925:
12926: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12927: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12928: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12929: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12930: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12931: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12932: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12933: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12934: }else{
1.270 brouard 12935: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 12936: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
12937: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
12938: if(prvforecast==1){
12939: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
12940: jprojd=jproj1;
12941: mprojd=mproj1;
12942: anprojd=anproj1;
12943: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
12944: jprojf=jproj2;
12945: mprojf=mproj2;
12946: anprojf=anproj2;
12947: } else if(prvforecast == 2){
12948: dateprojd=dateintmean;
12949: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
12950: dateprojf=dateintmean+yrfproj;
12951: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
12952: }
12953: if(prvbackcast==1){
12954: datebackd=(jback1+12*mback1+365*anback1)/365;
12955: jbackd=jback1;
12956: mbackd=mback1;
12957: anbackd=anback1;
12958: datebackf=(jback2+12*mback2+365*anback2)/365;
12959: jbackf=jback2;
12960: mbackf=mback2;
12961: anbackf=anback2;
12962: } else if(prvbackcast == 2){
12963: datebackd=dateintmean;
12964: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
12965: datebackf=dateintmean-yrbproj;
12966: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
12967: }
12968:
12969: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 12970: }
12971: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 12972: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
12973: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 12974:
1.225 brouard 12975: /*------------ free_vector -------------*/
12976: /* chdir(path); */
1.220 brouard 12977:
1.215 brouard 12978: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12979: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12980: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12981: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12982: free_lvector(num,firstobs,lastobs);
12983: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12984: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12985: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12986: fclose(ficparo);
12987: fclose(ficres);
1.220 brouard 12988:
12989:
1.186 brouard 12990: /* Other results (useful)*/
1.220 brouard 12991:
12992:
1.126 brouard 12993: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12994: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12995: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12996: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12997: fclose(ficrespl);
12998:
12999: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13000: /*#include "hpijx.h"*/
13001: hPijx(p, bage, fage);
1.145 brouard 13002: fclose(ficrespij);
1.227 brouard 13003:
1.220 brouard 13004: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 13005: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 13006: k=1;
1.126 brouard 13007: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13008:
1.269 brouard 13009: /* Prevalence for each covariate combination in probs[age][status][cov] */
13010: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13011: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13012: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13013: for(k=1;k<=ncovcombmax;k++)
13014: probs[i][j][k]=0.;
1.269 brouard 13015: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13016: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13017: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13018: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13019: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13020: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13021: for(k=1;k<=ncovcombmax;k++)
13022: mobaverages[i][j][k]=0.;
1.219 brouard 13023: mobaverage=mobaverages;
13024: if (mobilav!=0) {
1.235 brouard 13025: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13026: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13027: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13028: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13029: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13030: }
1.269 brouard 13031: } else if (mobilavproj !=0) {
1.235 brouard 13032: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13033: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13034: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13035: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13036: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13037: }
1.269 brouard 13038: }else{
13039: printf("Internal error moving average\n");
13040: fflush(stdout);
13041: exit(1);
1.219 brouard 13042: }
13043: }/* end if moving average */
1.227 brouard 13044:
1.126 brouard 13045: /*---------- Forecasting ------------------*/
1.296 brouard 13046: if(prevfcast==1){
13047: /* /\* if(stepm ==1){*\/ */
13048: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13049: /*This done previously after freqsummary.*/
13050: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13051: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13052:
13053: /* } else if (prvforecast==2){ */
13054: /* /\* if(stepm ==1){*\/ */
13055: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13056: /* } */
13057: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13058: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13059: }
1.269 brouard 13060:
1.296 brouard 13061: /* Prevbcasting */
13062: if(prevbcast==1){
1.219 brouard 13063: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13064: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13065: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13066:
13067: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13068:
13069: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13070:
1.219 brouard 13071: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13072: fclose(ficresplb);
13073:
1.222 brouard 13074: hBijx(p, bage, fage, mobaverage);
13075: fclose(ficrespijb);
1.219 brouard 13076:
1.296 brouard 13077: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13078: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13079: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13080: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13081: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13082: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13083:
13084:
1.269 brouard 13085: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13086:
13087:
1.269 brouard 13088: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13089: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13090: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13091: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13092: } /* end Prevbcasting */
1.268 brouard 13093:
1.186 brouard 13094:
13095: /* ------ Other prevalence ratios------------ */
1.126 brouard 13096:
1.215 brouard 13097: free_ivector(wav,1,imx);
13098: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13099: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13100: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13101:
13102:
1.127 brouard 13103: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 13104:
1.201 brouard 13105: strcpy(filerese,"E_");
13106: strcat(filerese,fileresu);
1.126 brouard 13107: if((ficreseij=fopen(filerese,"w"))==NULL) {
13108: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13109: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13110: }
1.208 brouard 13111: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
13112: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 13113:
13114: pstamp(ficreseij);
1.219 brouard 13115:
1.235 brouard 13116: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13117: if (cptcovn < 1){i1=1;}
13118:
13119: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13120: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13121: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13122: continue;
1.219 brouard 13123: fprintf(ficreseij,"\n#****** ");
1.235 brouard 13124: printf("\n#****** ");
1.225 brouard 13125: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13126: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13127: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13128: }
13129: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13130: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13131: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 13132: }
13133: fprintf(ficreseij,"******\n");
1.235 brouard 13134: printf("******\n");
1.219 brouard 13135:
13136: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13137: oldm=oldms;savm=savms;
1.235 brouard 13138: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 13139:
1.219 brouard 13140: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 13141: }
13142: fclose(ficreseij);
1.208 brouard 13143: printf("done evsij\n");fflush(stdout);
13144: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 13145:
1.218 brouard 13146:
1.227 brouard 13147: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 13148:
1.201 brouard 13149: strcpy(filerest,"T_");
13150: strcat(filerest,fileresu);
1.127 brouard 13151: if((ficrest=fopen(filerest,"w"))==NULL) {
13152: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
13153: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
13154: }
1.208 brouard 13155: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
13156: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 13157: strcpy(fileresstde,"STDE_");
13158: strcat(fileresstde,fileresu);
1.126 brouard 13159: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 13160: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
13161: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 13162: }
1.227 brouard 13163: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
13164: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 13165:
1.201 brouard 13166: strcpy(filerescve,"CVE_");
13167: strcat(filerescve,fileresu);
1.126 brouard 13168: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 13169: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
13170: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 13171: }
1.227 brouard 13172: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
13173: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 13174:
1.201 brouard 13175: strcpy(fileresv,"V_");
13176: strcat(fileresv,fileresu);
1.126 brouard 13177: if((ficresvij=fopen(fileresv,"w"))==NULL) {
13178: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
13179: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
13180: }
1.227 brouard 13181: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
13182: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 13183:
1.235 brouard 13184: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13185: if (cptcovn < 1){i1=1;}
13186:
13187: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13188: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13189: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13190: continue;
1.242 brouard 13191: printf("\n#****** Result for:");
13192: fprintf(ficrest,"\n#****** Result for:");
13193: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 13194: for(j=1;j<=cptcoveff;j++){
13195: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13196: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13197: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13198: }
1.235 brouard 13199: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13200: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13201: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13202: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13203: }
1.208 brouard 13204: fprintf(ficrest,"******\n");
1.227 brouard 13205: fprintf(ficlog,"******\n");
13206: printf("******\n");
1.208 brouard 13207:
13208: fprintf(ficresstdeij,"\n#****** ");
13209: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 13210: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13211: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13212: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 13213: }
1.235 brouard 13214: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13215: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13216: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13217: }
1.208 brouard 13218: fprintf(ficresstdeij,"******\n");
13219: fprintf(ficrescveij,"******\n");
13220:
13221: fprintf(ficresvij,"\n#****** ");
1.238 brouard 13222: /* pstamp(ficresvij); */
1.225 brouard 13223: for(j=1;j<=cptcoveff;j++)
1.227 brouard 13224: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13225: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13226: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13227: }
1.208 brouard 13228: fprintf(ficresvij,"******\n");
13229:
13230: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13231: oldm=oldms;savm=savms;
1.235 brouard 13232: printf(" cvevsij ");
13233: fprintf(ficlog, " cvevsij ");
13234: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 13235: printf(" end cvevsij \n ");
13236: fprintf(ficlog, " end cvevsij \n ");
13237:
13238: /*
13239: */
13240: /* goto endfree; */
13241:
13242: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13243: pstamp(ficrest);
13244:
1.269 brouard 13245: epj=vector(1,nlstate+1);
1.208 brouard 13246: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 13247: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
13248: cptcod= 0; /* To be deleted */
13249: printf("varevsij vpopbased=%d \n",vpopbased);
13250: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 13251: 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 13252: 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 ");
13253: if(vpopbased==1)
13254: 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);
13255: else
1.288 brouard 13256: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13257: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
13258: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
13259: fprintf(ficrest,"\n");
13260: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 13261: printf("Computing age specific forward period (stable) prevalences in each health state \n");
13262: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13263: for(age=bage; age <=fage ;age++){
1.235 brouard 13264: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 13265: if (vpopbased==1) {
13266: if(mobilav ==0){
13267: for(i=1; i<=nlstate;i++)
13268: prlim[i][i]=probs[(int)age][i][k];
13269: }else{ /* mobilav */
13270: for(i=1; i<=nlstate;i++)
13271: prlim[i][i]=mobaverage[(int)age][i][k];
13272: }
13273: }
1.219 brouard 13274:
1.227 brouard 13275: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
13276: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
13277: /* printf(" age %4.0f ",age); */
13278: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
13279: for(i=1, epj[j]=0.;i <=nlstate;i++) {
13280: epj[j] += prlim[i][i]*eij[i][j][(int)age];
13281: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
13282: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
13283: }
13284: epj[nlstate+1] +=epj[j];
13285: }
13286: /* printf(" age %4.0f \n",age); */
1.219 brouard 13287:
1.227 brouard 13288: for(i=1, vepp=0.;i <=nlstate;i++)
13289: for(j=1;j <=nlstate;j++)
13290: vepp += vareij[i][j][(int)age];
13291: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
13292: for(j=1;j <=nlstate;j++){
13293: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
13294: }
13295: fprintf(ficrest,"\n");
13296: }
1.208 brouard 13297: } /* End vpopbased */
1.269 brouard 13298: free_vector(epj,1,nlstate+1);
1.208 brouard 13299: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
13300: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 13301: printf("done selection\n");fflush(stdout);
13302: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 13303:
1.235 brouard 13304: } /* End k selection */
1.227 brouard 13305:
13306: printf("done State-specific expectancies\n");fflush(stdout);
13307: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
13308:
1.288 brouard 13309: /* variance-covariance of forward period prevalence*/
1.269 brouard 13310: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13311:
1.227 brouard 13312:
1.290 brouard 13313: free_vector(weight,firstobs,lastobs);
1.227 brouard 13314: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 13315: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
13316: free_matrix(anint,1,maxwav,firstobs,lastobs);
13317: free_matrix(mint,1,maxwav,firstobs,lastobs);
13318: free_ivector(cod,firstobs,lastobs);
1.227 brouard 13319: free_ivector(tab,1,NCOVMAX);
13320: fclose(ficresstdeij);
13321: fclose(ficrescveij);
13322: fclose(ficresvij);
13323: fclose(ficrest);
13324: fclose(ficpar);
13325:
13326:
1.126 brouard 13327: /*---------- End : free ----------------*/
1.219 brouard 13328: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 13329: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
13330: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 13331: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
13332: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 13333: } /* mle==-3 arrives here for freeing */
1.227 brouard 13334: /* endfree:*/
13335: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
13336: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
13337: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 13338: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13339: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13340: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13341: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13342: free_matrix(matcov,1,npar,1,npar);
13343: free_matrix(hess,1,npar,1,npar);
13344: /*free_vector(delti,1,npar);*/
13345: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13346: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13347: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13348: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13349:
13350: free_ivector(ncodemax,1,NCOVMAX);
13351: free_ivector(ncodemaxwundef,1,NCOVMAX);
13352: free_ivector(Dummy,-1,NCOVMAX);
13353: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13354: free_ivector(DummyV,1,NCOVMAX);
13355: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13356: free_ivector(Typevar,-1,NCOVMAX);
13357: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13358: free_ivector(TvarsQ,1,NCOVMAX);
13359: free_ivector(TvarsQind,1,NCOVMAX);
13360: free_ivector(TvarsD,1,NCOVMAX);
13361: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13362: free_ivector(TvarFD,1,NCOVMAX);
13363: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13364: free_ivector(TvarF,1,NCOVMAX);
13365: free_ivector(TvarFind,1,NCOVMAX);
13366: free_ivector(TvarV,1,NCOVMAX);
13367: free_ivector(TvarVind,1,NCOVMAX);
13368: free_ivector(TvarA,1,NCOVMAX);
13369: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13370: free_ivector(TvarFQ,1,NCOVMAX);
13371: free_ivector(TvarFQind,1,NCOVMAX);
13372: free_ivector(TvarVD,1,NCOVMAX);
13373: free_ivector(TvarVDind,1,NCOVMAX);
13374: free_ivector(TvarVQ,1,NCOVMAX);
13375: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13376: free_ivector(Tvarsel,1,NCOVMAX);
13377: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13378: free_ivector(Tposprod,1,NCOVMAX);
13379: free_ivector(Tprod,1,NCOVMAX);
13380: free_ivector(Tvaraff,1,NCOVMAX);
13381: free_ivector(invalidvarcomb,1,ncovcombmax);
13382: free_ivector(Tage,1,NCOVMAX);
13383: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 13384: free_ivector(TmodelInvind,1,NCOVMAX);
13385: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 13386:
13387: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
13388: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 13389: fflush(fichtm);
13390: fflush(ficgp);
13391:
1.227 brouard 13392:
1.126 brouard 13393: if((nberr >0) || (nbwarn>0)){
1.216 brouard 13394: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
13395: 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 13396: }else{
13397: printf("End of Imach\n");
13398: fprintf(ficlog,"End of Imach\n");
13399: }
13400: printf("See log file on %s\n",filelog);
13401: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 13402: /*(void) gettimeofday(&end_time,&tzp);*/
13403: rend_time = time(NULL);
13404: end_time = *localtime(&rend_time);
13405: /* tml = *localtime(&end_time.tm_sec); */
13406: strcpy(strtend,asctime(&end_time));
1.126 brouard 13407: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13408: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13409: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13410:
1.157 brouard 13411: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13412: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13413: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13414: /* printf("Total time was %d uSec.\n", total_usecs);*/
13415: /* if(fileappend(fichtm,optionfilehtm)){ */
13416: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13417: fclose(fichtm);
13418: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13419: fclose(fichtmcov);
13420: fclose(ficgp);
13421: fclose(ficlog);
13422: /*------ End -----------*/
1.227 brouard 13423:
1.281 brouard 13424:
13425: /* Executes gnuplot */
1.227 brouard 13426:
13427: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13428: #ifdef WIN32
1.227 brouard 13429: if (_chdir(pathcd) != 0)
13430: printf("Can't move to directory %s!\n",path);
13431: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13432: #else
1.227 brouard 13433: if(chdir(pathcd) != 0)
13434: printf("Can't move to directory %s!\n", path);
13435: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13436: #endif
1.126 brouard 13437: printf("Current directory %s!\n",pathcd);
13438: /*strcat(plotcmd,CHARSEPARATOR);*/
13439: sprintf(plotcmd,"gnuplot");
1.157 brouard 13440: #ifdef _WIN32
1.126 brouard 13441: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13442: #endif
13443: if(!stat(plotcmd,&info)){
1.158 brouard 13444: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13445: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13446: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13447: }else
13448: strcpy(pplotcmd,plotcmd);
1.157 brouard 13449: #ifdef __unix
1.126 brouard 13450: strcpy(plotcmd,GNUPLOTPROGRAM);
13451: if(!stat(plotcmd,&info)){
1.158 brouard 13452: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13453: }else
13454: strcpy(pplotcmd,plotcmd);
13455: #endif
13456: }else
13457: strcpy(pplotcmd,plotcmd);
13458:
13459: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13460: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13461: strcpy(pplotcmd,plotcmd);
1.227 brouard 13462:
1.126 brouard 13463: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13464: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13465: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13466: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13467: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13468: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13469: strcpy(plotcmd,pplotcmd);
13470: }
1.126 brouard 13471: }
1.158 brouard 13472: printf(" Successful, please wait...");
1.126 brouard 13473: while (z[0] != 'q') {
13474: /* chdir(path); */
1.154 brouard 13475: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13476: scanf("%s",z);
13477: /* if (z[0] == 'c') system("./imach"); */
13478: if (z[0] == 'e') {
1.158 brouard 13479: #ifdef __APPLE__
1.152 brouard 13480: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13481: #elif __linux
13482: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13483: #else
1.152 brouard 13484: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13485: #endif
13486: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13487: system(pplotcmd);
1.126 brouard 13488: }
13489: else if (z[0] == 'g') system(plotcmd);
13490: else if (z[0] == 'q') exit(0);
13491: }
1.227 brouard 13492: end:
1.126 brouard 13493: while (z[0] != 'q') {
1.195 brouard 13494: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13495: scanf("%s",z);
13496: }
1.283 brouard 13497: printf("End\n");
1.282 brouard 13498: exit(0);
1.126 brouard 13499: }
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