Annotation of imach/src/imach.c, revision 1.296
1.296 ! brouard 1: /* $Id: imach.c,v 1.295 2019/05/18 09:52:50 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.296 ! brouard 4: Revision 1.295 2019/05/18 09:52:50 brouard
! 5: Summary: doxygen tex bug
! 6:
1.295 brouard 7: Revision 1.294 2019/05/16 14:54:33 brouard
8: Summary: There was some wrong lines added
9:
1.294 brouard 10: Revision 1.293 2019/05/09 15:17:34 brouard
11: *** empty log message ***
12:
1.293 brouard 13: Revision 1.292 2019/05/09 14:17:20 brouard
14: Summary: Some updates
15:
1.292 brouard 16: Revision 1.291 2019/05/09 13:44:18 brouard
17: Summary: Before ncovmax
18:
1.291 brouard 19: Revision 1.290 2019/05/09 13:39:37 brouard
20: Summary: 0.99r18 unlimited number of individuals
21:
22: 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.
23:
1.290 brouard 24: Revision 1.289 2018/12/13 09:16:26 brouard
25: Summary: Bug for young ages (<-30) will be in r17
26:
1.289 brouard 27: Revision 1.288 2018/05/02 20:58:27 brouard
28: Summary: Some bugs fixed
29:
1.288 brouard 30: Revision 1.287 2018/05/01 17:57:25 brouard
31: Summary: Bug fixed by providing frequencies only for non missing covariates
32:
1.287 brouard 33: Revision 1.286 2018/04/27 14:27:04 brouard
34: Summary: some minor bugs
35:
1.286 brouard 36: Revision 1.285 2018/04/21 21:02:16 brouard
37: Summary: Some bugs fixed, valgrind tested
38:
1.285 brouard 39: Revision 1.284 2018/04/20 05:22:13 brouard
40: Summary: Computing mean and stdeviation of fixed quantitative variables
41:
1.284 brouard 42: Revision 1.283 2018/04/19 14:49:16 brouard
43: Summary: Some minor bugs fixed
44:
1.283 brouard 45: Revision 1.282 2018/02/27 22:50:02 brouard
46: *** empty log message ***
47:
1.282 brouard 48: Revision 1.281 2018/02/27 19:25:23 brouard
49: Summary: Adding second argument for quitting
50:
1.281 brouard 51: Revision 1.280 2018/02/21 07:58:13 brouard
52: Summary: 0.99r15
53:
54: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
55:
1.280 brouard 56: Revision 1.279 2017/07/20 13:35:01 brouard
57: Summary: temporary working
58:
1.279 brouard 59: Revision 1.278 2017/07/19 14:09:02 brouard
60: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
61:
1.278 brouard 62: Revision 1.277 2017/07/17 08:53:49 brouard
63: Summary: BOM files can be read now
64:
1.277 brouard 65: Revision 1.276 2017/06/30 15:48:31 brouard
66: Summary: Graphs improvements
67:
1.276 brouard 68: Revision 1.275 2017/06/30 13:39:33 brouard
69: Summary: Saito's color
70:
1.275 brouard 71: Revision 1.274 2017/06/29 09:47:08 brouard
72: Summary: Version 0.99r14
73:
1.274 brouard 74: Revision 1.273 2017/06/27 11:06:02 brouard
75: Summary: More documentation on projections
76:
1.273 brouard 77: Revision 1.272 2017/06/27 10:22:40 brouard
78: Summary: Color of backprojection changed from 6 to 5(yellow)
79:
1.272 brouard 80: Revision 1.271 2017/06/27 10:17:50 brouard
81: Summary: Some bug with rint
82:
1.271 brouard 83: Revision 1.270 2017/05/24 05:45:29 brouard
84: *** empty log message ***
85:
1.270 brouard 86: Revision 1.269 2017/05/23 08:39:25 brouard
87: Summary: Code into subroutine, cleanings
88:
1.269 brouard 89: Revision 1.268 2017/05/18 20:09:32 brouard
90: Summary: backprojection and confidence intervals of backprevalence
91:
1.268 brouard 92: Revision 1.267 2017/05/13 10:25:05 brouard
93: Summary: temporary save for backprojection
94:
1.267 brouard 95: Revision 1.266 2017/05/13 07:26:12 brouard
96: Summary: Version 0.99r13 (improvements and bugs fixed)
97:
1.266 brouard 98: Revision 1.265 2017/04/26 16:22:11 brouard
99: Summary: imach 0.99r13 Some bugs fixed
100:
1.265 brouard 101: Revision 1.264 2017/04/26 06:01:29 brouard
102: Summary: Labels in graphs
103:
1.264 brouard 104: Revision 1.263 2017/04/24 15:23:15 brouard
105: Summary: to save
106:
1.263 brouard 107: Revision 1.262 2017/04/18 16:48:12 brouard
108: *** empty log message ***
109:
1.262 brouard 110: Revision 1.261 2017/04/05 10:14:09 brouard
111: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
112:
1.261 brouard 113: Revision 1.260 2017/04/04 17:46:59 brouard
114: Summary: Gnuplot indexations fixed (humm)
115:
1.260 brouard 116: Revision 1.259 2017/04/04 13:01:16 brouard
117: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
118:
1.259 brouard 119: Revision 1.258 2017/04/03 10:17:47 brouard
120: Summary: Version 0.99r12
121:
122: Some cleanings, conformed with updated documentation.
123:
1.258 brouard 124: Revision 1.257 2017/03/29 16:53:30 brouard
125: Summary: Temp
126:
1.257 brouard 127: Revision 1.256 2017/03/27 05:50:23 brouard
128: Summary: Temporary
129:
1.256 brouard 130: Revision 1.255 2017/03/08 16:02:28 brouard
131: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
132:
1.255 brouard 133: Revision 1.254 2017/03/08 07:13:00 brouard
134: Summary: Fixing data parameter line
135:
1.254 brouard 136: Revision 1.253 2016/12/15 11:59:41 brouard
137: Summary: 0.99 in progress
138:
1.253 brouard 139: Revision 1.252 2016/09/15 21:15:37 brouard
140: *** empty log message ***
141:
1.252 brouard 142: Revision 1.251 2016/09/15 15:01:13 brouard
143: Summary: not working
144:
1.251 brouard 145: Revision 1.250 2016/09/08 16:07:27 brouard
146: Summary: continue
147:
1.250 brouard 148: Revision 1.249 2016/09/07 17:14:18 brouard
149: Summary: Starting values from frequencies
150:
1.249 brouard 151: Revision 1.248 2016/09/07 14:10:18 brouard
152: *** empty log message ***
153:
1.248 brouard 154: Revision 1.247 2016/09/02 11:11:21 brouard
155: *** empty log message ***
156:
1.247 brouard 157: Revision 1.246 2016/09/02 08:49:22 brouard
158: *** empty log message ***
159:
1.246 brouard 160: Revision 1.245 2016/09/02 07:25:01 brouard
161: *** empty log message ***
162:
1.245 brouard 163: Revision 1.244 2016/09/02 07:17:34 brouard
164: *** empty log message ***
165:
1.244 brouard 166: Revision 1.243 2016/09/02 06:45:35 brouard
167: *** empty log message ***
168:
1.243 brouard 169: Revision 1.242 2016/08/30 15:01:20 brouard
170: Summary: Fixing a lots
171:
1.242 brouard 172: Revision 1.241 2016/08/29 17:17:25 brouard
173: Summary: gnuplot problem in Back projection to fix
174:
1.241 brouard 175: Revision 1.240 2016/08/29 07:53:18 brouard
176: Summary: Better
177:
1.240 brouard 178: Revision 1.239 2016/08/26 15:51:03 brouard
179: Summary: Improvement in Powell output in order to copy and paste
180:
181: Author:
182:
1.239 brouard 183: Revision 1.238 2016/08/26 14:23:35 brouard
184: Summary: Starting tests of 0.99
185:
1.238 brouard 186: Revision 1.237 2016/08/26 09:20:19 brouard
187: Summary: to valgrind
188:
1.237 brouard 189: Revision 1.236 2016/08/25 10:50:18 brouard
190: *** empty log message ***
191:
1.236 brouard 192: Revision 1.235 2016/08/25 06:59:23 brouard
193: *** empty log message ***
194:
1.235 brouard 195: Revision 1.234 2016/08/23 16:51:20 brouard
196: *** empty log message ***
197:
1.234 brouard 198: Revision 1.233 2016/08/23 07:40:50 brouard
199: Summary: not working
200:
1.233 brouard 201: Revision 1.232 2016/08/22 14:20:21 brouard
202: Summary: not working
203:
1.232 brouard 204: Revision 1.231 2016/08/22 07:17:15 brouard
205: Summary: not working
206:
1.231 brouard 207: Revision 1.230 2016/08/22 06:55:53 brouard
208: Summary: Not working
209:
1.230 brouard 210: Revision 1.229 2016/07/23 09:45:53 brouard
211: Summary: Completing for func too
212:
1.229 brouard 213: Revision 1.228 2016/07/22 17:45:30 brouard
214: Summary: Fixing some arrays, still debugging
215:
1.227 brouard 216: Revision 1.226 2016/07/12 18:42:34 brouard
217: Summary: temp
218:
1.226 brouard 219: Revision 1.225 2016/07/12 08:40:03 brouard
220: Summary: saving but not running
221:
1.225 brouard 222: Revision 1.224 2016/07/01 13:16:01 brouard
223: Summary: Fixes
224:
1.224 brouard 225: Revision 1.223 2016/02/19 09:23:35 brouard
226: Summary: temporary
227:
1.223 brouard 228: Revision 1.222 2016/02/17 08:14:50 brouard
229: Summary: Probably last 0.98 stable version 0.98r6
230:
1.222 brouard 231: Revision 1.221 2016/02/15 23:35:36 brouard
232: Summary: minor bug
233:
1.220 brouard 234: Revision 1.219 2016/02/15 00:48:12 brouard
235: *** empty log message ***
236:
1.219 brouard 237: Revision 1.218 2016/02/12 11:29:23 brouard
238: Summary: 0.99 Back projections
239:
1.218 brouard 240: Revision 1.217 2015/12/23 17:18:31 brouard
241: Summary: Experimental backcast
242:
1.217 brouard 243: Revision 1.216 2015/12/18 17:32:11 brouard
244: Summary: 0.98r4 Warning and status=-2
245:
246: Version 0.98r4 is now:
247: - displaying an error when status is -1, date of interview unknown and date of death known;
248: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
249: Older changes concerning s=-2, dating from 2005 have been supersed.
250:
1.216 brouard 251: Revision 1.215 2015/12/16 08:52:24 brouard
252: Summary: 0.98r4 working
253:
1.215 brouard 254: Revision 1.214 2015/12/16 06:57:54 brouard
255: Summary: temporary not working
256:
1.214 brouard 257: Revision 1.213 2015/12/11 18:22:17 brouard
258: Summary: 0.98r4
259:
1.213 brouard 260: Revision 1.212 2015/11/21 12:47:24 brouard
261: Summary: minor typo
262:
1.212 brouard 263: Revision 1.211 2015/11/21 12:41:11 brouard
264: Summary: 0.98r3 with some graph of projected cross-sectional
265:
266: Author: Nicolas Brouard
267:
1.211 brouard 268: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 269: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 270: Summary: Adding ftolpl parameter
271: Author: N Brouard
272:
273: We had difficulties to get smoothed confidence intervals. It was due
274: to the period prevalence which wasn't computed accurately. The inner
275: parameter ftolpl is now an outer parameter of the .imach parameter
276: file after estepm. If ftolpl is small 1.e-4 and estepm too,
277: computation are long.
278:
1.209 brouard 279: Revision 1.208 2015/11/17 14:31:57 brouard
280: Summary: temporary
281:
1.208 brouard 282: Revision 1.207 2015/10/27 17:36:57 brouard
283: *** empty log message ***
284:
1.207 brouard 285: Revision 1.206 2015/10/24 07:14:11 brouard
286: *** empty log message ***
287:
1.206 brouard 288: Revision 1.205 2015/10/23 15:50:53 brouard
289: Summary: 0.98r3 some clarification for graphs on likelihood contributions
290:
1.205 brouard 291: Revision 1.204 2015/10/01 16:20:26 brouard
292: Summary: Some new graphs of contribution to likelihood
293:
1.204 brouard 294: Revision 1.203 2015/09/30 17:45:14 brouard
295: Summary: looking at better estimation of the hessian
296:
297: Also a better criteria for convergence to the period prevalence And
298: therefore adding the number of years needed to converge. (The
299: prevalence in any alive state shold sum to one
300:
1.203 brouard 301: Revision 1.202 2015/09/22 19:45:16 brouard
302: Summary: Adding some overall graph on contribution to likelihood. Might change
303:
1.202 brouard 304: Revision 1.201 2015/09/15 17:34:58 brouard
305: Summary: 0.98r0
306:
307: - Some new graphs like suvival functions
308: - Some bugs fixed like model=1+age+V2.
309:
1.201 brouard 310: Revision 1.200 2015/09/09 16:53:55 brouard
311: Summary: Big bug thanks to Flavia
312:
313: Even model=1+age+V2. did not work anymore
314:
1.200 brouard 315: Revision 1.199 2015/09/07 14:09:23 brouard
316: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
317:
1.199 brouard 318: Revision 1.198 2015/09/03 07:14:39 brouard
319: Summary: 0.98q5 Flavia
320:
1.198 brouard 321: Revision 1.197 2015/09/01 18:24:39 brouard
322: *** empty log message ***
323:
1.197 brouard 324: Revision 1.196 2015/08/18 23:17:52 brouard
325: Summary: 0.98q5
326:
1.196 brouard 327: Revision 1.195 2015/08/18 16:28:39 brouard
328: Summary: Adding a hack for testing purpose
329:
330: After reading the title, ftol and model lines, if the comment line has
331: a q, starting with #q, the answer at the end of the run is quit. It
332: permits to run test files in batch with ctest. The former workaround was
333: $ echo q | imach foo.imach
334:
1.195 brouard 335: Revision 1.194 2015/08/18 13:32:00 brouard
336: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
337:
1.194 brouard 338: Revision 1.193 2015/08/04 07:17:42 brouard
339: Summary: 0.98q4
340:
1.193 brouard 341: Revision 1.192 2015/07/16 16:49:02 brouard
342: Summary: Fixing some outputs
343:
1.192 brouard 344: Revision 1.191 2015/07/14 10:00:33 brouard
345: Summary: Some fixes
346:
1.191 brouard 347: Revision 1.190 2015/05/05 08:51:13 brouard
348: Summary: Adding digits in output parameters (7 digits instead of 6)
349:
350: Fix 1+age+.
351:
1.190 brouard 352: Revision 1.189 2015/04/30 14:45:16 brouard
353: Summary: 0.98q2
354:
1.189 brouard 355: Revision 1.188 2015/04/30 08:27:53 brouard
356: *** empty log message ***
357:
1.188 brouard 358: Revision 1.187 2015/04/29 09:11:15 brouard
359: *** empty log message ***
360:
1.187 brouard 361: Revision 1.186 2015/04/23 12:01:52 brouard
362: Summary: V1*age is working now, version 0.98q1
363:
364: Some codes had been disabled in order to simplify and Vn*age was
365: working in the optimization phase, ie, giving correct MLE parameters,
366: but, as usual, outputs were not correct and program core dumped.
367:
1.186 brouard 368: Revision 1.185 2015/03/11 13:26:42 brouard
369: Summary: Inclusion of compile and links command line for Intel Compiler
370:
1.185 brouard 371: Revision 1.184 2015/03/11 11:52:39 brouard
372: Summary: Back from Windows 8. Intel Compiler
373:
1.184 brouard 374: Revision 1.183 2015/03/10 20:34:32 brouard
375: Summary: 0.98q0, trying with directest, mnbrak fixed
376:
377: We use directest instead of original Powell test; probably no
378: incidence on the results, but better justifications;
379: We fixed Numerical Recipes mnbrak routine which was wrong and gave
380: wrong results.
381:
1.183 brouard 382: Revision 1.182 2015/02/12 08:19:57 brouard
383: Summary: Trying to keep directest which seems simpler and more general
384: Author: Nicolas Brouard
385:
1.182 brouard 386: Revision 1.181 2015/02/11 23:22:24 brouard
387: Summary: Comments on Powell added
388:
389: Author:
390:
1.181 brouard 391: Revision 1.180 2015/02/11 17:33:45 brouard
392: Summary: Finishing move from main to function (hpijx and prevalence_limit)
393:
1.180 brouard 394: Revision 1.179 2015/01/04 09:57:06 brouard
395: Summary: back to OS/X
396:
1.179 brouard 397: Revision 1.178 2015/01/04 09:35:48 brouard
398: *** empty log message ***
399:
1.178 brouard 400: Revision 1.177 2015/01/03 18:40:56 brouard
401: Summary: Still testing ilc32 on OSX
402:
1.177 brouard 403: Revision 1.176 2015/01/03 16:45:04 brouard
404: *** empty log message ***
405:
1.176 brouard 406: Revision 1.175 2015/01/03 16:33:42 brouard
407: *** empty log message ***
408:
1.175 brouard 409: Revision 1.174 2015/01/03 16:15:49 brouard
410: Summary: Still in cross-compilation
411:
1.174 brouard 412: Revision 1.173 2015/01/03 12:06:26 brouard
413: Summary: trying to detect cross-compilation
414:
1.173 brouard 415: Revision 1.172 2014/12/27 12:07:47 brouard
416: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
417:
1.172 brouard 418: Revision 1.171 2014/12/23 13:26:59 brouard
419: Summary: Back from Visual C
420:
421: Still problem with utsname.h on Windows
422:
1.171 brouard 423: Revision 1.170 2014/12/23 11:17:12 brouard
424: Summary: Cleaning some \%% back to %%
425:
426: The escape was mandatory for a specific compiler (which one?), but too many warnings.
427:
1.170 brouard 428: Revision 1.169 2014/12/22 23:08:31 brouard
429: Summary: 0.98p
430:
431: Outputs some informations on compiler used, OS etc. Testing on different platforms.
432:
1.169 brouard 433: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 434: Summary: update
1.169 brouard 435:
1.168 brouard 436: Revision 1.167 2014/12/22 13:50:56 brouard
437: Summary: Testing uname and compiler version and if compiled 32 or 64
438:
439: Testing on Linux 64
440:
1.167 brouard 441: Revision 1.166 2014/12/22 11:40:47 brouard
442: *** empty log message ***
443:
1.166 brouard 444: Revision 1.165 2014/12/16 11:20:36 brouard
445: Summary: After compiling on Visual C
446:
447: * imach.c (Module): Merging 1.61 to 1.162
448:
1.165 brouard 449: Revision 1.164 2014/12/16 10:52:11 brouard
450: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
451:
452: * imach.c (Module): Merging 1.61 to 1.162
453:
1.164 brouard 454: Revision 1.163 2014/12/16 10:30:11 brouard
455: * imach.c (Module): Merging 1.61 to 1.162
456:
1.163 brouard 457: Revision 1.162 2014/09/25 11:43:39 brouard
458: Summary: temporary backup 0.99!
459:
1.162 brouard 460: Revision 1.1 2014/09/16 11:06:58 brouard
461: Summary: With some code (wrong) for nlopt
462:
463: Author:
464:
465: Revision 1.161 2014/09/15 20:41:41 brouard
466: Summary: Problem with macro SQR on Intel compiler
467:
1.161 brouard 468: Revision 1.160 2014/09/02 09:24:05 brouard
469: *** empty log message ***
470:
1.160 brouard 471: Revision 1.159 2014/09/01 10:34:10 brouard
472: Summary: WIN32
473: Author: Brouard
474:
1.159 brouard 475: Revision 1.158 2014/08/27 17:11:51 brouard
476: *** empty log message ***
477:
1.158 brouard 478: Revision 1.157 2014/08/27 16:26:55 brouard
479: Summary: Preparing windows Visual studio version
480: Author: Brouard
481:
482: In order to compile on Visual studio, time.h is now correct and time_t
483: and tm struct should be used. difftime should be used but sometimes I
484: just make the differences in raw time format (time(&now).
485: Trying to suppress #ifdef LINUX
486: Add xdg-open for __linux in order to open default browser.
487:
1.157 brouard 488: Revision 1.156 2014/08/25 20:10:10 brouard
489: *** empty log message ***
490:
1.156 brouard 491: Revision 1.155 2014/08/25 18:32:34 brouard
492: Summary: New compile, minor changes
493: Author: Brouard
494:
1.155 brouard 495: Revision 1.154 2014/06/20 17:32:08 brouard
496: Summary: Outputs now all graphs of convergence to period prevalence
497:
1.154 brouard 498: Revision 1.153 2014/06/20 16:45:46 brouard
499: Summary: If 3 live state, convergence to period prevalence on same graph
500: Author: Brouard
501:
1.153 brouard 502: Revision 1.152 2014/06/18 17:54:09 brouard
503: Summary: open browser, use gnuplot on same dir than imach if not found in the path
504:
1.152 brouard 505: Revision 1.151 2014/06/18 16:43:30 brouard
506: *** empty log message ***
507:
1.151 brouard 508: Revision 1.150 2014/06/18 16:42:35 brouard
509: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
510: Author: brouard
511:
1.150 brouard 512: Revision 1.149 2014/06/18 15:51:14 brouard
513: Summary: Some fixes in parameter files errors
514: Author: Nicolas Brouard
515:
1.149 brouard 516: Revision 1.148 2014/06/17 17:38:48 brouard
517: Summary: Nothing new
518: Author: Brouard
519:
520: Just a new packaging for OS/X version 0.98nS
521:
1.148 brouard 522: Revision 1.147 2014/06/16 10:33:11 brouard
523: *** empty log message ***
524:
1.147 brouard 525: Revision 1.146 2014/06/16 10:20:28 brouard
526: Summary: Merge
527: Author: Brouard
528:
529: Merge, before building revised version.
530:
1.146 brouard 531: Revision 1.145 2014/06/10 21:23:15 brouard
532: Summary: Debugging with valgrind
533: Author: Nicolas Brouard
534:
535: Lot of changes in order to output the results with some covariates
536: After the Edimburgh REVES conference 2014, it seems mandatory to
537: improve the code.
538: No more memory valgrind error but a lot has to be done in order to
539: continue the work of splitting the code into subroutines.
540: Also, decodemodel has been improved. Tricode is still not
541: optimal. nbcode should be improved. Documentation has been added in
542: the source code.
543:
1.144 brouard 544: Revision 1.143 2014/01/26 09:45:38 brouard
545: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
546:
547: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
548: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
549:
1.143 brouard 550: Revision 1.142 2014/01/26 03:57:36 brouard
551: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
552:
553: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
554:
1.142 brouard 555: Revision 1.141 2014/01/26 02:42:01 brouard
556: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
557:
1.141 brouard 558: Revision 1.140 2011/09/02 10:37:54 brouard
559: Summary: times.h is ok with mingw32 now.
560:
1.140 brouard 561: Revision 1.139 2010/06/14 07:50:17 brouard
562: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
563: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
564:
1.139 brouard 565: Revision 1.138 2010/04/30 18:19:40 brouard
566: *** empty log message ***
567:
1.138 brouard 568: Revision 1.137 2010/04/29 18:11:38 brouard
569: (Module): Checking covariates for more complex models
570: than V1+V2. A lot of change to be done. Unstable.
571:
1.137 brouard 572: Revision 1.136 2010/04/26 20:30:53 brouard
573: (Module): merging some libgsl code. Fixing computation
574: of likelione (using inter/intrapolation if mle = 0) in order to
575: get same likelihood as if mle=1.
576: Some cleaning of code and comments added.
577:
1.136 brouard 578: Revision 1.135 2009/10/29 15:33:14 brouard
579: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
580:
1.135 brouard 581: Revision 1.134 2009/10/29 13:18:53 brouard
582: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
583:
1.134 brouard 584: Revision 1.133 2009/07/06 10:21:25 brouard
585: just nforces
586:
1.133 brouard 587: Revision 1.132 2009/07/06 08:22:05 brouard
588: Many tings
589:
1.132 brouard 590: Revision 1.131 2009/06/20 16:22:47 brouard
591: Some dimensions resccaled
592:
1.131 brouard 593: Revision 1.130 2009/05/26 06:44:34 brouard
594: (Module): Max Covariate is now set to 20 instead of 8. A
595: lot of cleaning with variables initialized to 0. Trying to make
596: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
597:
1.130 brouard 598: Revision 1.129 2007/08/31 13:49:27 lievre
599: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
600:
1.129 lievre 601: Revision 1.128 2006/06/30 13:02:05 brouard
602: (Module): Clarifications on computing e.j
603:
1.128 brouard 604: Revision 1.127 2006/04/28 18:11:50 brouard
605: (Module): Yes the sum of survivors was wrong since
606: imach-114 because nhstepm was no more computed in the age
607: loop. Now we define nhstepma in the age loop.
608: (Module): In order to speed up (in case of numerous covariates) we
609: compute health expectancies (without variances) in a first step
610: and then all the health expectancies with variances or standard
611: deviation (needs data from the Hessian matrices) which slows the
612: computation.
613: In the future we should be able to stop the program is only health
614: expectancies and graph are needed without standard deviations.
615:
1.127 brouard 616: Revision 1.126 2006/04/28 17:23:28 brouard
617: (Module): Yes the sum of survivors was wrong since
618: imach-114 because nhstepm was no more computed in the age
619: loop. Now we define nhstepma in the age loop.
620: Version 0.98h
621:
1.126 brouard 622: Revision 1.125 2006/04/04 15:20:31 lievre
623: Errors in calculation of health expectancies. Age was not initialized.
624: Forecasting file added.
625:
626: Revision 1.124 2006/03/22 17:13:53 lievre
627: Parameters are printed with %lf instead of %f (more numbers after the comma).
628: The log-likelihood is printed in the log file
629:
630: Revision 1.123 2006/03/20 10:52:43 brouard
631: * imach.c (Module): <title> changed, corresponds to .htm file
632: name. <head> headers where missing.
633:
634: * imach.c (Module): Weights can have a decimal point as for
635: English (a comma might work with a correct LC_NUMERIC environment,
636: otherwise the weight is truncated).
637: Modification of warning when the covariates values are not 0 or
638: 1.
639: Version 0.98g
640:
641: Revision 1.122 2006/03/20 09:45:41 brouard
642: (Module): Weights can have a decimal point as for
643: English (a comma might work with a correct LC_NUMERIC environment,
644: otherwise the weight is truncated).
645: Modification of warning when the covariates values are not 0 or
646: 1.
647: Version 0.98g
648:
649: Revision 1.121 2006/03/16 17:45:01 lievre
650: * imach.c (Module): Comments concerning covariates added
651:
652: * imach.c (Module): refinements in the computation of lli if
653: status=-2 in order to have more reliable computation if stepm is
654: not 1 month. Version 0.98f
655:
656: Revision 1.120 2006/03/16 15:10:38 lievre
657: (Module): refinements in the computation of lli if
658: status=-2 in order to have more reliable computation if stepm is
659: not 1 month. Version 0.98f
660:
661: Revision 1.119 2006/03/15 17:42:26 brouard
662: (Module): Bug if status = -2, the loglikelihood was
663: computed as likelihood omitting the logarithm. Version O.98e
664:
665: Revision 1.118 2006/03/14 18:20:07 brouard
666: (Module): varevsij Comments added explaining the second
667: table of variances if popbased=1 .
668: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
669: (Module): Function pstamp added
670: (Module): Version 0.98d
671:
672: Revision 1.117 2006/03/14 17:16:22 brouard
673: (Module): varevsij Comments added explaining the second
674: table of variances if popbased=1 .
675: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
676: (Module): Function pstamp added
677: (Module): Version 0.98d
678:
679: Revision 1.116 2006/03/06 10:29:27 brouard
680: (Module): Variance-covariance wrong links and
681: varian-covariance of ej. is needed (Saito).
682:
683: Revision 1.115 2006/02/27 12:17:45 brouard
684: (Module): One freematrix added in mlikeli! 0.98c
685:
686: Revision 1.114 2006/02/26 12:57:58 brouard
687: (Module): Some improvements in processing parameter
688: filename with strsep.
689:
690: Revision 1.113 2006/02/24 14:20:24 brouard
691: (Module): Memory leaks checks with valgrind and:
692: datafile was not closed, some imatrix were not freed and on matrix
693: allocation too.
694:
695: Revision 1.112 2006/01/30 09:55:26 brouard
696: (Module): Back to gnuplot.exe instead of wgnuplot.exe
697:
698: Revision 1.111 2006/01/25 20:38:18 brouard
699: (Module): Lots of cleaning and bugs added (Gompertz)
700: (Module): Comments can be added in data file. Missing date values
701: can be a simple dot '.'.
702:
703: Revision 1.110 2006/01/25 00:51:50 brouard
704: (Module): Lots of cleaning and bugs added (Gompertz)
705:
706: Revision 1.109 2006/01/24 19:37:15 brouard
707: (Module): Comments (lines starting with a #) are allowed in data.
708:
709: Revision 1.108 2006/01/19 18:05:42 lievre
710: Gnuplot problem appeared...
711: To be fixed
712:
713: Revision 1.107 2006/01/19 16:20:37 brouard
714: Test existence of gnuplot in imach path
715:
716: Revision 1.106 2006/01/19 13:24:36 brouard
717: Some cleaning and links added in html output
718:
719: Revision 1.105 2006/01/05 20:23:19 lievre
720: *** empty log message ***
721:
722: Revision 1.104 2005/09/30 16:11:43 lievre
723: (Module): sump fixed, loop imx fixed, and simplifications.
724: (Module): If the status is missing at the last wave but we know
725: that the person is alive, then we can code his/her status as -2
726: (instead of missing=-1 in earlier versions) and his/her
727: contributions to the likelihood is 1 - Prob of dying from last
728: health status (= 1-p13= p11+p12 in the easiest case of somebody in
729: the healthy state at last known wave). Version is 0.98
730:
731: Revision 1.103 2005/09/30 15:54:49 lievre
732: (Module): sump fixed, loop imx fixed, and simplifications.
733:
734: Revision 1.102 2004/09/15 17:31:30 brouard
735: Add the possibility to read data file including tab characters.
736:
737: Revision 1.101 2004/09/15 10:38:38 brouard
738: Fix on curr_time
739:
740: Revision 1.100 2004/07/12 18:29:06 brouard
741: Add version for Mac OS X. Just define UNIX in Makefile
742:
743: Revision 1.99 2004/06/05 08:57:40 brouard
744: *** empty log message ***
745:
746: Revision 1.98 2004/05/16 15:05:56 brouard
747: New version 0.97 . First attempt to estimate force of mortality
748: directly from the data i.e. without the need of knowing the health
749: state at each age, but using a Gompertz model: log u =a + b*age .
750: This is the basic analysis of mortality and should be done before any
751: other analysis, in order to test if the mortality estimated from the
752: cross-longitudinal survey is different from the mortality estimated
753: from other sources like vital statistic data.
754:
755: The same imach parameter file can be used but the option for mle should be -3.
756:
1.133 brouard 757: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 758: former routines in order to include the new code within the former code.
759:
760: The output is very simple: only an estimate of the intercept and of
761: the slope with 95% confident intervals.
762:
763: Current limitations:
764: A) Even if you enter covariates, i.e. with the
765: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
766: B) There is no computation of Life Expectancy nor Life Table.
767:
768: Revision 1.97 2004/02/20 13:25:42 lievre
769: Version 0.96d. Population forecasting command line is (temporarily)
770: suppressed.
771:
772: Revision 1.96 2003/07/15 15:38:55 brouard
773: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
774: rewritten within the same printf. Workaround: many printfs.
775:
776: Revision 1.95 2003/07/08 07:54:34 brouard
777: * imach.c (Repository):
778: (Repository): Using imachwizard code to output a more meaningful covariance
779: matrix (cov(a12,c31) instead of numbers.
780:
781: Revision 1.94 2003/06/27 13:00:02 brouard
782: Just cleaning
783:
784: Revision 1.93 2003/06/25 16:33:55 brouard
785: (Module): On windows (cygwin) function asctime_r doesn't
786: exist so I changed back to asctime which exists.
787: (Module): Version 0.96b
788:
789: Revision 1.92 2003/06/25 16:30:45 brouard
790: (Module): On windows (cygwin) function asctime_r doesn't
791: exist so I changed back to asctime which exists.
792:
793: Revision 1.91 2003/06/25 15:30:29 brouard
794: * imach.c (Repository): Duplicated warning errors corrected.
795: (Repository): Elapsed time after each iteration is now output. It
796: helps to forecast when convergence will be reached. Elapsed time
797: is stamped in powell. We created a new html file for the graphs
798: concerning matrix of covariance. It has extension -cov.htm.
799:
800: Revision 1.90 2003/06/24 12:34:15 brouard
801: (Module): Some bugs corrected for windows. Also, when
802: mle=-1 a template is output in file "or"mypar.txt with the design
803: of the covariance matrix to be input.
804:
805: Revision 1.89 2003/06/24 12:30:52 brouard
806: (Module): Some bugs corrected for windows. Also, when
807: mle=-1 a template is output in file "or"mypar.txt with the design
808: of the covariance matrix to be input.
809:
810: Revision 1.88 2003/06/23 17:54:56 brouard
811: * 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.
812:
813: Revision 1.87 2003/06/18 12:26:01 brouard
814: Version 0.96
815:
816: Revision 1.86 2003/06/17 20:04:08 brouard
817: (Module): Change position of html and gnuplot routines and added
818: routine fileappend.
819:
820: Revision 1.85 2003/06/17 13:12:43 brouard
821: * imach.c (Repository): Check when date of death was earlier that
822: current date of interview. It may happen when the death was just
823: prior to the death. In this case, dh was negative and likelihood
824: was wrong (infinity). We still send an "Error" but patch by
825: assuming that the date of death was just one stepm after the
826: interview.
827: (Repository): Because some people have very long ID (first column)
828: we changed int to long in num[] and we added a new lvector for
829: memory allocation. But we also truncated to 8 characters (left
830: truncation)
831: (Repository): No more line truncation errors.
832:
833: Revision 1.84 2003/06/13 21:44:43 brouard
834: * imach.c (Repository): Replace "freqsummary" at a correct
835: place. It differs from routine "prevalence" which may be called
836: many times. Probs is memory consuming and must be used with
837: parcimony.
838: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
839:
840: Revision 1.83 2003/06/10 13:39:11 lievre
841: *** empty log message ***
842:
843: Revision 1.82 2003/06/05 15:57:20 brouard
844: Add log in imach.c and fullversion number is now printed.
845:
846: */
847: /*
848: Interpolated Markov Chain
849:
850: Short summary of the programme:
851:
1.227 brouard 852: This program computes Healthy Life Expectancies or State-specific
853: (if states aren't health statuses) Expectancies from
854: cross-longitudinal data. Cross-longitudinal data consist in:
855:
856: -1- a first survey ("cross") where individuals from different ages
857: are interviewed on their health status or degree of disability (in
858: the case of a health survey which is our main interest)
859:
860: -2- at least a second wave of interviews ("longitudinal") which
861: measure each change (if any) in individual health status. Health
862: expectancies are computed from the time spent in each health state
863: according to a model. More health states you consider, more time is
864: necessary to reach the Maximum Likelihood of the parameters involved
865: in the model. The simplest model is the multinomial logistic model
866: where pij is the probability to be observed in state j at the second
867: wave conditional to be observed in state i at the first
868: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
869: etc , where 'age' is age and 'sex' is a covariate. If you want to
870: have a more complex model than "constant and age", you should modify
871: the program where the markup *Covariates have to be included here
872: again* invites you to do it. More covariates you add, slower the
1.126 brouard 873: convergence.
874:
875: The advantage of this computer programme, compared to a simple
876: multinomial logistic model, is clear when the delay between waves is not
877: identical for each individual. Also, if a individual missed an
878: intermediate interview, the information is lost, but taken into
879: account using an interpolation or extrapolation.
880:
881: hPijx is the probability to be observed in state i at age x+h
882: conditional to the observed state i at age x. The delay 'h' can be
883: split into an exact number (nh*stepm) of unobserved intermediate
884: states. This elementary transition (by month, quarter,
885: semester or year) is modelled as a multinomial logistic. The hPx
886: matrix is simply the matrix product of nh*stepm elementary matrices
887: and the contribution of each individual to the likelihood is simply
888: hPijx.
889:
890: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 891: of the life expectancies. It also computes the period (stable) prevalence.
892:
893: Back prevalence and projections:
1.227 brouard 894:
895: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
896: double agemaxpar, double ftolpl, int *ncvyearp, double
897: dateprev1,double dateprev2, int firstpass, int lastpass, int
898: mobilavproj)
899:
900: Computes the back prevalence limit for any combination of
901: covariate values k at any age between ageminpar and agemaxpar and
902: returns it in **bprlim. In the loops,
903:
904: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
905: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
906:
907: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 908: Computes for any combination of covariates k and any age between bage and fage
909: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
910: oldm=oldms;savm=savms;
1.227 brouard 911:
1.267 brouard 912: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 913: Computes the transition matrix starting at age 'age' over
914: 'nhstepm*hstepm*stepm' months (i.e. until
915: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 916: nhstepm*hstepm matrices.
917:
918: Returns p3mat[i][j][h] after calling
919: p3mat[i][j][h]=matprod2(newm,
920: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
921: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
922: oldm);
1.226 brouard 923:
924: Important routines
925:
926: - func (or funcone), computes logit (pij) distinguishing
927: o fixed variables (single or product dummies or quantitative);
928: o varying variables by:
929: (1) wave (single, product dummies, quantitative),
930: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
931: % fixed dummy (treated) or quantitative (not done because time-consuming);
932: % varying dummy (not done) or quantitative (not done);
933: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
934: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
935: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
936: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
937: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 938:
1.226 brouard 939:
940:
1.133 brouard 941: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
942: Institut national d'études démographiques, Paris.
1.126 brouard 943: This software have been partly granted by Euro-REVES, a concerted action
944: from the European Union.
945: It is copyrighted identically to a GNU software product, ie programme and
946: software can be distributed freely for non commercial use. Latest version
947: can be accessed at http://euroreves.ined.fr/imach .
948:
949: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
950: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
951:
952: **********************************************************************/
953: /*
954: main
955: read parameterfile
956: read datafile
957: concatwav
958: freqsummary
959: if (mle >= 1)
960: mlikeli
961: print results files
962: if mle==1
963: computes hessian
964: read end of parameter file: agemin, agemax, bage, fage, estepm
965: begin-prev-date,...
966: open gnuplot file
967: open html file
1.145 brouard 968: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
969: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
970: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
971: freexexit2 possible for memory heap.
972:
973: h Pij x | pij_nom ficrestpij
974: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
975: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
976: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
977:
978: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
979: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
980: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
981: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
982: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
983:
1.126 brouard 984: forecasting if prevfcast==1 prevforecast call prevalence()
985: health expectancies
986: Variance-covariance of DFLE
987: prevalence()
988: movingaverage()
989: varevsij()
990: if popbased==1 varevsij(,popbased)
991: total life expectancies
992: Variance of period (stable) prevalence
993: end
994: */
995:
1.187 brouard 996: /* #define DEBUG */
997: /* #define DEBUGBRENT */
1.203 brouard 998: /* #define DEBUGLINMIN */
999: /* #define DEBUGHESS */
1000: #define DEBUGHESSIJ
1.224 brouard 1001: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1002: #define POWELL /* Instead of NLOPT */
1.224 brouard 1003: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1004: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1005: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 1006:
1007: #include <math.h>
1008: #include <stdio.h>
1009: #include <stdlib.h>
1010: #include <string.h>
1.226 brouard 1011: #include <ctype.h>
1.159 brouard 1012:
1013: #ifdef _WIN32
1014: #include <io.h>
1.172 brouard 1015: #include <windows.h>
1016: #include <tchar.h>
1.159 brouard 1017: #else
1.126 brouard 1018: #include <unistd.h>
1.159 brouard 1019: #endif
1.126 brouard 1020:
1021: #include <limits.h>
1022: #include <sys/types.h>
1.171 brouard 1023:
1024: #if defined(__GNUC__)
1025: #include <sys/utsname.h> /* Doesn't work on Windows */
1026: #endif
1027:
1.126 brouard 1028: #include <sys/stat.h>
1029: #include <errno.h>
1.159 brouard 1030: /* extern int errno; */
1.126 brouard 1031:
1.157 brouard 1032: /* #ifdef LINUX */
1033: /* #include <time.h> */
1034: /* #include "timeval.h" */
1035: /* #else */
1036: /* #include <sys/time.h> */
1037: /* #endif */
1038:
1.126 brouard 1039: #include <time.h>
1040:
1.136 brouard 1041: #ifdef GSL
1042: #include <gsl/gsl_errno.h>
1043: #include <gsl/gsl_multimin.h>
1044: #endif
1045:
1.167 brouard 1046:
1.162 brouard 1047: #ifdef NLOPT
1048: #include <nlopt.h>
1049: typedef struct {
1050: double (* function)(double [] );
1051: } myfunc_data ;
1052: #endif
1053:
1.126 brouard 1054: /* #include <libintl.h> */
1055: /* #define _(String) gettext (String) */
1056:
1.251 brouard 1057: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1058:
1059: #define GNUPLOTPROGRAM "gnuplot"
1060: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1061: #define FILENAMELENGTH 132
1062:
1063: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1064: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1065:
1.144 brouard 1066: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1067: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1068:
1069: #define NINTERVMAX 8
1.144 brouard 1070: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1071: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.291 brouard 1072: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1073: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1074: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1075: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1076: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1077: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1078: /* #define AGESUP 130 */
1.288 brouard 1079: /* #define AGESUP 150 */
1080: #define AGESUP 200
1.268 brouard 1081: #define AGEINF 0
1.218 brouard 1082: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1083: #define AGEBASE 40
1.194 brouard 1084: #define AGEOVERFLOW 1.e20
1.164 brouard 1085: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1086: #ifdef _WIN32
1087: #define DIRSEPARATOR '\\'
1088: #define CHARSEPARATOR "\\"
1089: #define ODIRSEPARATOR '/'
1090: #else
1.126 brouard 1091: #define DIRSEPARATOR '/'
1092: #define CHARSEPARATOR "/"
1093: #define ODIRSEPARATOR '\\'
1094: #endif
1095:
1.296 ! brouard 1096: /* $Id: imach.c,v 1.295 2019/05/18 09:52:50 brouard Exp $ */
1.126 brouard 1097: /* $State: Exp $ */
1.196 brouard 1098: #include "version.h"
1099: char version[]=__IMACH_VERSION__;
1.283 brouard 1100: char copyright[]="April 2018,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2018";
1.296 ! brouard 1101: char fullversion[]="$Revision: 1.295 $ $Date: 2019/05/18 09:52:50 $";
1.126 brouard 1102: char strstart[80];
1103: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1104: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1105: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1106: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1107: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1108: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1109: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1110: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1111: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1112: int cptcovprodnoage=0; /**< Number of covariate products without age */
1113: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1114: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1115: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1116: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1117: int nsd=0; /**< Total number of single dummy variables (output) */
1118: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1119: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1120: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1121: int ntveff=0; /**< ntveff number of effective time varying variables */
1122: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1123: int cptcov=0; /* Working variable */
1.290 brouard 1124: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1125: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1126: int npar=NPARMAX;
1127: int nlstate=2; /* Number of live states */
1128: int ndeath=1; /* Number of dead states */
1.130 brouard 1129: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1130: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1131: int popbased=0;
1132:
1133: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1134: int maxwav=0; /* Maxim number of waves */
1135: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1136: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1137: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1138: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1139: int mle=1, weightopt=0;
1.126 brouard 1140: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1141: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1142: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1143: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1144: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1145: int selected(int kvar); /* Is covariate kvar selected for printing results */
1146:
1.130 brouard 1147: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1148: double **matprod2(); /* test */
1.126 brouard 1149: double **oldm, **newm, **savm; /* Working pointers to matrices */
1150: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1151: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1152:
1.136 brouard 1153: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1154: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1155: FILE *ficlog, *ficrespow;
1.130 brouard 1156: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1157: double fretone; /* Only one call to likelihood */
1.130 brouard 1158: long ipmx=0; /* Number of contributions */
1.126 brouard 1159: double sw; /* Sum of weights */
1160: char filerespow[FILENAMELENGTH];
1161: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1162: FILE *ficresilk;
1163: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1164: FILE *ficresprobmorprev;
1165: FILE *fichtm, *fichtmcov; /* Html File */
1166: FILE *ficreseij;
1167: char filerese[FILENAMELENGTH];
1168: FILE *ficresstdeij;
1169: char fileresstde[FILENAMELENGTH];
1170: FILE *ficrescveij;
1171: char filerescve[FILENAMELENGTH];
1172: FILE *ficresvij;
1173: char fileresv[FILENAMELENGTH];
1.269 brouard 1174:
1.126 brouard 1175: char title[MAXLINE];
1.234 brouard 1176: char model[MAXLINE]; /**< The model line */
1.217 brouard 1177: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1178: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1179: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1180: char command[FILENAMELENGTH];
1181: int outcmd=0;
1182:
1.217 brouard 1183: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1184: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1185: char filelog[FILENAMELENGTH]; /* Log file */
1186: char filerest[FILENAMELENGTH];
1187: char fileregp[FILENAMELENGTH];
1188: char popfile[FILENAMELENGTH];
1189:
1190: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1191:
1.157 brouard 1192: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1193: /* struct timezone tzp; */
1194: /* extern int gettimeofday(); */
1195: struct tm tml, *gmtime(), *localtime();
1196:
1197: extern time_t time();
1198:
1199: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1200: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1201: struct tm tm;
1202:
1.126 brouard 1203: char strcurr[80], strfor[80];
1204:
1205: char *endptr;
1206: long lval;
1207: double dval;
1208:
1209: #define NR_END 1
1210: #define FREE_ARG char*
1211: #define FTOL 1.0e-10
1212:
1213: #define NRANSI
1.240 brouard 1214: #define ITMAX 200
1215: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1216:
1217: #define TOL 2.0e-4
1218:
1219: #define CGOLD 0.3819660
1220: #define ZEPS 1.0e-10
1221: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1222:
1223: #define GOLD 1.618034
1224: #define GLIMIT 100.0
1225: #define TINY 1.0e-20
1226:
1227: static double maxarg1,maxarg2;
1228: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1229: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1230:
1231: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1232: #define rint(a) floor(a+0.5)
1.166 brouard 1233: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1234: #define mytinydouble 1.0e-16
1.166 brouard 1235: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1236: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1237: /* static double dsqrarg; */
1238: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1239: static double sqrarg;
1240: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1241: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1242: int agegomp= AGEGOMP;
1243:
1244: int imx;
1245: int stepm=1;
1246: /* Stepm, step in month: minimum step interpolation*/
1247:
1248: int estepm;
1249: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1250:
1251: int m,nb;
1252: long *num;
1.197 brouard 1253: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1254: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1255: covariate for which somebody answered excluding
1256: undefined. Usually 2: 0 and 1. */
1257: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1258: covariate for which somebody answered including
1259: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1260: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1261: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1262: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1263: double *ageexmed,*agecens;
1264: double dateintmean=0;
1.296 ! brouard 1265: double anprojd, mprojd, jprojd; /* For eventual projections */
! 1266: double anprojf, mprojf, jprojf;
1.126 brouard 1267:
1.296 ! brouard 1268: double anbackd, mbackd, jbackd; /* For eventual backprojections */
! 1269: double anbackf, mbackf, jbackf;
! 1270: double jintmean,mintmean,aintmean;
1.126 brouard 1271: double *weight;
1272: int **s; /* Status */
1.141 brouard 1273: double *agedc;
1.145 brouard 1274: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1275: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1276: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1277: double **coqvar; /* Fixed quantitative covariate nqv */
1278: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1279: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1280: double idx;
1281: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1282: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1283: /*k 1 2 3 4 5 6 7 8 9 */
1284: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1285: /* Tndvar[k] 1 2 3 4 5 */
1286: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1287: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1288: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1289: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1290: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1291: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1292: /* Tprod[i]=k 4 7 */
1293: /* Tage[i]=k 5 8 */
1294: /* */
1295: /* Type */
1296: /* V 1 2 3 4 5 */
1297: /* F F V V V */
1298: /* D Q D D Q */
1299: /* */
1300: int *TvarsD;
1301: int *TvarsDind;
1302: int *TvarsQ;
1303: int *TvarsQind;
1304:
1.235 brouard 1305: #define MAXRESULTLINES 10
1306: int nresult=0;
1.258 brouard 1307: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1308: int TKresult[MAXRESULTLINES];
1.237 brouard 1309: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1310: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1311: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1312: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1313: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1314: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1315:
1.234 brouard 1316: /* 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 1317: 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 */
1318: 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 */
1319: 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 */
1320: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1321: 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 */
1322: 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 1323: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1324: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1325: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1326: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1327: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1328: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1329: 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 */
1330: 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 */
1331:
1.230 brouard 1332: int *Tvarsel; /**< Selected covariates for output */
1333: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1334: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1335: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1336: 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 1337: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1338: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1339: int *Tage;
1.227 brouard 1340: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1341: 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 1342: 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*/
1343: 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 1344: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1345: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1346: int **Tvard;
1347: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1348: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1349: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1350: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1351: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1352: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1353: double *lsurv, *lpop, *tpop;
1354:
1.231 brouard 1355: #define FD 1; /* Fixed dummy covariate */
1356: #define FQ 2; /* Fixed quantitative covariate */
1357: #define FP 3; /* Fixed product covariate */
1358: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1359: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1360: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1361: #define VD 10; /* Varying dummy covariate */
1362: #define VQ 11; /* Varying quantitative covariate */
1363: #define VP 12; /* Varying product covariate */
1364: #define VPDD 13; /* Varying product dummy*dummy covariate */
1365: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1366: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1367: #define APFD 16; /* Age product * fixed dummy covariate */
1368: #define APFQ 17; /* Age product * fixed quantitative covariate */
1369: #define APVD 18; /* Age product * varying dummy covariate */
1370: #define APVQ 19; /* Age product * varying quantitative covariate */
1371:
1372: #define FTYPE 1; /* Fixed covariate */
1373: #define VTYPE 2; /* Varying covariate (loop in wave) */
1374: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1375:
1376: struct kmodel{
1377: int maintype; /* main type */
1378: int subtype; /* subtype */
1379: };
1380: struct kmodel modell[NCOVMAX];
1381:
1.143 brouard 1382: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1383: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1384:
1385: /**************** split *************************/
1386: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1387: {
1388: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1389: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1390: */
1391: char *ss; /* pointer */
1.186 brouard 1392: int l1=0, l2=0; /* length counters */
1.126 brouard 1393:
1394: l1 = strlen(path ); /* length of path */
1395: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1396: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1397: if ( ss == NULL ) { /* no directory, so determine current directory */
1398: strcpy( name, path ); /* we got the fullname name because no directory */
1399: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1400: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1401: /* get current working directory */
1402: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1403: #ifdef WIN32
1404: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1405: #else
1406: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1407: #endif
1.126 brouard 1408: return( GLOCK_ERROR_GETCWD );
1409: }
1410: /* got dirc from getcwd*/
1411: printf(" DIRC = %s \n",dirc);
1.205 brouard 1412: } else { /* strip directory from path */
1.126 brouard 1413: ss++; /* after this, the filename */
1414: l2 = strlen( ss ); /* length of filename */
1415: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1416: strcpy( name, ss ); /* save file name */
1417: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1418: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1419: printf(" DIRC2 = %s \n",dirc);
1420: }
1421: /* We add a separator at the end of dirc if not exists */
1422: l1 = strlen( dirc ); /* length of directory */
1423: if( dirc[l1-1] != DIRSEPARATOR ){
1424: dirc[l1] = DIRSEPARATOR;
1425: dirc[l1+1] = 0;
1426: printf(" DIRC3 = %s \n",dirc);
1427: }
1428: ss = strrchr( name, '.' ); /* find last / */
1429: if (ss >0){
1430: ss++;
1431: strcpy(ext,ss); /* save extension */
1432: l1= strlen( name);
1433: l2= strlen(ss)+1;
1434: strncpy( finame, name, l1-l2);
1435: finame[l1-l2]= 0;
1436: }
1437:
1438: return( 0 ); /* we're done */
1439: }
1440:
1441:
1442: /******************************************/
1443:
1444: void replace_back_to_slash(char *s, char*t)
1445: {
1446: int i;
1447: int lg=0;
1448: i=0;
1449: lg=strlen(t);
1450: for(i=0; i<= lg; i++) {
1451: (s[i] = t[i]);
1452: if (t[i]== '\\') s[i]='/';
1453: }
1454: }
1455:
1.132 brouard 1456: char *trimbb(char *out, char *in)
1.137 brouard 1457: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1458: char *s;
1459: s=out;
1460: while (*in != '\0'){
1.137 brouard 1461: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1462: in++;
1463: }
1464: *out++ = *in++;
1465: }
1466: *out='\0';
1467: return s;
1468: }
1469:
1.187 brouard 1470: /* char *substrchaine(char *out, char *in, char *chain) */
1471: /* { */
1472: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1473: /* char *s, *t; */
1474: /* t=in;s=out; */
1475: /* while ((*in != *chain) && (*in != '\0')){ */
1476: /* *out++ = *in++; */
1477: /* } */
1478:
1479: /* /\* *in matches *chain *\/ */
1480: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1481: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1482: /* } */
1483: /* in--; chain--; */
1484: /* while ( (*in != '\0')){ */
1485: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1486: /* *out++ = *in++; */
1487: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1488: /* } */
1489: /* *out='\0'; */
1490: /* out=s; */
1491: /* return out; */
1492: /* } */
1493: char *substrchaine(char *out, char *in, char *chain)
1494: {
1495: /* Substract chain 'chain' from 'in', return and output 'out' */
1496: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1497:
1498: char *strloc;
1499:
1500: strcpy (out, in);
1501: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1502: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1503: if(strloc != NULL){
1504: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1505: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1506: /* strcpy (strloc, strloc +strlen(chain));*/
1507: }
1508: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1509: return out;
1510: }
1511:
1512:
1.145 brouard 1513: char *cutl(char *blocc, char *alocc, char *in, char occ)
1514: {
1.187 brouard 1515: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1516: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1517: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1518: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1519: */
1.160 brouard 1520: char *s, *t;
1.145 brouard 1521: t=in;s=in;
1522: while ((*in != occ) && (*in != '\0')){
1523: *alocc++ = *in++;
1524: }
1525: if( *in == occ){
1526: *(alocc)='\0';
1527: s=++in;
1528: }
1529:
1530: if (s == t) {/* occ not found */
1531: *(alocc-(in-s))='\0';
1532: in=s;
1533: }
1534: while ( *in != '\0'){
1535: *blocc++ = *in++;
1536: }
1537:
1538: *blocc='\0';
1539: return t;
1540: }
1.137 brouard 1541: char *cutv(char *blocc, char *alocc, char *in, char occ)
1542: {
1.187 brouard 1543: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1544: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1545: gives blocc="abcdef2ghi" and alocc="j".
1546: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1547: */
1548: char *s, *t;
1549: t=in;s=in;
1550: while (*in != '\0'){
1551: while( *in == occ){
1552: *blocc++ = *in++;
1553: s=in;
1554: }
1555: *blocc++ = *in++;
1556: }
1557: if (s == t) /* occ not found */
1558: *(blocc-(in-s))='\0';
1559: else
1560: *(blocc-(in-s)-1)='\0';
1561: in=s;
1562: while ( *in != '\0'){
1563: *alocc++ = *in++;
1564: }
1565:
1566: *alocc='\0';
1567: return s;
1568: }
1569:
1.126 brouard 1570: int nbocc(char *s, char occ)
1571: {
1572: int i,j=0;
1573: int lg=20;
1574: i=0;
1575: lg=strlen(s);
1576: for(i=0; i<= lg; i++) {
1.234 brouard 1577: if (s[i] == occ ) j++;
1.126 brouard 1578: }
1579: return j;
1580: }
1581:
1.137 brouard 1582: /* void cutv(char *u,char *v, char*t, char occ) */
1583: /* { */
1584: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1585: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1586: /* gives u="abcdef2ghi" and v="j" *\/ */
1587: /* int i,lg,j,p=0; */
1588: /* i=0; */
1589: /* lg=strlen(t); */
1590: /* for(j=0; j<=lg-1; j++) { */
1591: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1592: /* } */
1.126 brouard 1593:
1.137 brouard 1594: /* for(j=0; j<p; j++) { */
1595: /* (u[j] = t[j]); */
1596: /* } */
1597: /* u[p]='\0'; */
1.126 brouard 1598:
1.137 brouard 1599: /* for(j=0; j<= lg; j++) { */
1600: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1601: /* } */
1602: /* } */
1.126 brouard 1603:
1.160 brouard 1604: #ifdef _WIN32
1605: char * strsep(char **pp, const char *delim)
1606: {
1607: char *p, *q;
1608:
1609: if ((p = *pp) == NULL)
1610: return 0;
1611: if ((q = strpbrk (p, delim)) != NULL)
1612: {
1613: *pp = q + 1;
1614: *q = '\0';
1615: }
1616: else
1617: *pp = 0;
1618: return p;
1619: }
1620: #endif
1621:
1.126 brouard 1622: /********************** nrerror ********************/
1623:
1624: void nrerror(char error_text[])
1625: {
1626: fprintf(stderr,"ERREUR ...\n");
1627: fprintf(stderr,"%s\n",error_text);
1628: exit(EXIT_FAILURE);
1629: }
1630: /*********************** vector *******************/
1631: double *vector(int nl, int nh)
1632: {
1633: double *v;
1634: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1635: if (!v) nrerror("allocation failure in vector");
1636: return v-nl+NR_END;
1637: }
1638:
1639: /************************ free vector ******************/
1640: void free_vector(double*v, int nl, int nh)
1641: {
1642: free((FREE_ARG)(v+nl-NR_END));
1643: }
1644:
1645: /************************ivector *******************************/
1646: int *ivector(long nl,long nh)
1647: {
1648: int *v;
1649: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1650: if (!v) nrerror("allocation failure in ivector");
1651: return v-nl+NR_END;
1652: }
1653:
1654: /******************free ivector **************************/
1655: void free_ivector(int *v, long nl, long nh)
1656: {
1657: free((FREE_ARG)(v+nl-NR_END));
1658: }
1659:
1660: /************************lvector *******************************/
1661: long *lvector(long nl,long nh)
1662: {
1663: long *v;
1664: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1665: if (!v) nrerror("allocation failure in ivector");
1666: return v-nl+NR_END;
1667: }
1668:
1669: /******************free lvector **************************/
1670: void free_lvector(long *v, long nl, long nh)
1671: {
1672: free((FREE_ARG)(v+nl-NR_END));
1673: }
1674:
1675: /******************* imatrix *******************************/
1676: int **imatrix(long nrl, long nrh, long ncl, long nch)
1677: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1678: {
1679: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1680: int **m;
1681:
1682: /* allocate pointers to rows */
1683: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1684: if (!m) nrerror("allocation failure 1 in matrix()");
1685: m += NR_END;
1686: m -= nrl;
1687:
1688:
1689: /* allocate rows and set pointers to them */
1690: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1691: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1692: m[nrl] += NR_END;
1693: m[nrl] -= ncl;
1694:
1695: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1696:
1697: /* return pointer to array of pointers to rows */
1698: return m;
1699: }
1700:
1701: /****************** free_imatrix *************************/
1702: void free_imatrix(m,nrl,nrh,ncl,nch)
1703: int **m;
1704: long nch,ncl,nrh,nrl;
1705: /* free an int matrix allocated by imatrix() */
1706: {
1707: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1708: free((FREE_ARG) (m+nrl-NR_END));
1709: }
1710:
1711: /******************* matrix *******************************/
1712: double **matrix(long nrl, long nrh, long ncl, long nch)
1713: {
1714: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1715: double **m;
1716:
1717: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1718: if (!m) nrerror("allocation failure 1 in matrix()");
1719: m += NR_END;
1720: m -= nrl;
1721:
1722: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1723: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1724: m[nrl] += NR_END;
1725: m[nrl] -= ncl;
1726:
1727: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1728: return m;
1.145 brouard 1729: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1730: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1731: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1732: */
1733: }
1734:
1735: /*************************free matrix ************************/
1736: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1737: {
1738: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1739: free((FREE_ARG)(m+nrl-NR_END));
1740: }
1741:
1742: /******************* ma3x *******************************/
1743: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1744: {
1745: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1746: double ***m;
1747:
1748: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1749: if (!m) nrerror("allocation failure 1 in matrix()");
1750: m += NR_END;
1751: m -= nrl;
1752:
1753: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1754: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1755: m[nrl] += NR_END;
1756: m[nrl] -= ncl;
1757:
1758: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1759:
1760: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1761: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1762: m[nrl][ncl] += NR_END;
1763: m[nrl][ncl] -= nll;
1764: for (j=ncl+1; j<=nch; j++)
1765: m[nrl][j]=m[nrl][j-1]+nlay;
1766:
1767: for (i=nrl+1; i<=nrh; i++) {
1768: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1769: for (j=ncl+1; j<=nch; j++)
1770: m[i][j]=m[i][j-1]+nlay;
1771: }
1772: return m;
1773: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1774: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1775: */
1776: }
1777:
1778: /*************************free ma3x ************************/
1779: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1780: {
1781: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1782: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1783: free((FREE_ARG)(m+nrl-NR_END));
1784: }
1785:
1786: /*************** function subdirf ***********/
1787: char *subdirf(char fileres[])
1788: {
1789: /* Caution optionfilefiname is hidden */
1790: strcpy(tmpout,optionfilefiname);
1791: strcat(tmpout,"/"); /* Add to the right */
1792: strcat(tmpout,fileres);
1793: return tmpout;
1794: }
1795:
1796: /*************** function subdirf2 ***********/
1797: char *subdirf2(char fileres[], char *preop)
1798: {
1799:
1800: /* Caution optionfilefiname is hidden */
1801: strcpy(tmpout,optionfilefiname);
1802: strcat(tmpout,"/");
1803: strcat(tmpout,preop);
1804: strcat(tmpout,fileres);
1805: return tmpout;
1806: }
1807:
1808: /*************** function subdirf3 ***********/
1809: char *subdirf3(char fileres[], char *preop, char *preop2)
1810: {
1811:
1812: /* Caution optionfilefiname is hidden */
1813: strcpy(tmpout,optionfilefiname);
1814: strcat(tmpout,"/");
1815: strcat(tmpout,preop);
1816: strcat(tmpout,preop2);
1817: strcat(tmpout,fileres);
1818: return tmpout;
1819: }
1.213 brouard 1820:
1821: /*************** function subdirfext ***********/
1822: char *subdirfext(char fileres[], char *preop, char *postop)
1823: {
1824:
1825: strcpy(tmpout,preop);
1826: strcat(tmpout,fileres);
1827: strcat(tmpout,postop);
1828: return tmpout;
1829: }
1.126 brouard 1830:
1.213 brouard 1831: /*************** function subdirfext3 ***********/
1832: char *subdirfext3(char fileres[], char *preop, char *postop)
1833: {
1834:
1835: /* Caution optionfilefiname is hidden */
1836: strcpy(tmpout,optionfilefiname);
1837: strcat(tmpout,"/");
1838: strcat(tmpout,preop);
1839: strcat(tmpout,fileres);
1840: strcat(tmpout,postop);
1841: return tmpout;
1842: }
1843:
1.162 brouard 1844: char *asc_diff_time(long time_sec, char ascdiff[])
1845: {
1846: long sec_left, days, hours, minutes;
1847: days = (time_sec) / (60*60*24);
1848: sec_left = (time_sec) % (60*60*24);
1849: hours = (sec_left) / (60*60) ;
1850: sec_left = (sec_left) %(60*60);
1851: minutes = (sec_left) /60;
1852: sec_left = (sec_left) % (60);
1853: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1854: return ascdiff;
1855: }
1856:
1.126 brouard 1857: /***************** f1dim *************************/
1858: extern int ncom;
1859: extern double *pcom,*xicom;
1860: extern double (*nrfunc)(double []);
1861:
1862: double f1dim(double x)
1863: {
1864: int j;
1865: double f;
1866: double *xt;
1867:
1868: xt=vector(1,ncom);
1869: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1870: f=(*nrfunc)(xt);
1871: free_vector(xt,1,ncom);
1872: return f;
1873: }
1874:
1875: /*****************brent *************************/
1876: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1877: {
1878: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1879: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1880: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1881: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1882: * returned function value.
1883: */
1.126 brouard 1884: int iter;
1885: double a,b,d,etemp;
1.159 brouard 1886: double fu=0,fv,fw,fx;
1.164 brouard 1887: double ftemp=0.;
1.126 brouard 1888: double p,q,r,tol1,tol2,u,v,w,x,xm;
1889: double e=0.0;
1890:
1891: a=(ax < cx ? ax : cx);
1892: b=(ax > cx ? ax : cx);
1893: x=w=v=bx;
1894: fw=fv=fx=(*f)(x);
1895: for (iter=1;iter<=ITMAX;iter++) {
1896: xm=0.5*(a+b);
1897: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1898: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1899: printf(".");fflush(stdout);
1900: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1901: #ifdef DEBUGBRENT
1.126 brouard 1902: 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);
1903: 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);
1904: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1905: #endif
1906: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1907: *xmin=x;
1908: return fx;
1909: }
1910: ftemp=fu;
1911: if (fabs(e) > tol1) {
1912: r=(x-w)*(fx-fv);
1913: q=(x-v)*(fx-fw);
1914: p=(x-v)*q-(x-w)*r;
1915: q=2.0*(q-r);
1916: if (q > 0.0) p = -p;
1917: q=fabs(q);
1918: etemp=e;
1919: e=d;
1920: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1921: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1922: else {
1.224 brouard 1923: d=p/q;
1924: u=x+d;
1925: if (u-a < tol2 || b-u < tol2)
1926: d=SIGN(tol1,xm-x);
1.126 brouard 1927: }
1928: } else {
1929: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1930: }
1931: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1932: fu=(*f)(u);
1933: if (fu <= fx) {
1934: if (u >= x) a=x; else b=x;
1935: SHFT(v,w,x,u)
1.183 brouard 1936: SHFT(fv,fw,fx,fu)
1937: } else {
1938: if (u < x) a=u; else b=u;
1939: if (fu <= fw || w == x) {
1.224 brouard 1940: v=w;
1941: w=u;
1942: fv=fw;
1943: fw=fu;
1.183 brouard 1944: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1945: v=u;
1946: fv=fu;
1.183 brouard 1947: }
1948: }
1.126 brouard 1949: }
1950: nrerror("Too many iterations in brent");
1951: *xmin=x;
1952: return fx;
1953: }
1954:
1955: /****************** mnbrak ***********************/
1956:
1957: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1958: double (*func)(double))
1.183 brouard 1959: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1960: the downhill direction (defined by the function as evaluated at the initial points) and returns
1961: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1962: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1963: */
1.126 brouard 1964: double ulim,u,r,q, dum;
1965: double fu;
1.187 brouard 1966:
1967: double scale=10.;
1968: int iterscale=0;
1969:
1970: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1971: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1972:
1973:
1974: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1975: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1976: /* *bx = *ax - (*ax - *bx)/scale; */
1977: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1978: /* } */
1979:
1.126 brouard 1980: if (*fb > *fa) {
1981: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1982: SHFT(dum,*fb,*fa,dum)
1983: }
1.126 brouard 1984: *cx=(*bx)+GOLD*(*bx-*ax);
1985: *fc=(*func)(*cx);
1.183 brouard 1986: #ifdef DEBUG
1.224 brouard 1987: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1988: 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 1989: #endif
1.224 brouard 1990: 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 1991: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1992: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1993: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1994: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1995: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1996: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1997: fu=(*func)(u);
1.163 brouard 1998: #ifdef DEBUG
1999: /* f(x)=A(x-u)**2+f(u) */
2000: double A, fparabu;
2001: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2002: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2003: 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);
2004: 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 2005: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2006: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2007: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2008: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2009: #endif
1.184 brouard 2010: #ifdef MNBRAKORIGINAL
1.183 brouard 2011: #else
1.191 brouard 2012: /* if (fu > *fc) { */
2013: /* #ifdef DEBUG */
2014: /* printf("mnbrak4 fu > fc \n"); */
2015: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2016: /* #endif */
2017: /* /\* 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 *\\/ *\/ */
2018: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2019: /* dum=u; /\* Shifting c and u *\/ */
2020: /* u = *cx; */
2021: /* *cx = dum; */
2022: /* dum = fu; */
2023: /* fu = *fc; */
2024: /* *fc =dum; */
2025: /* } else { /\* end *\/ */
2026: /* #ifdef DEBUG */
2027: /* printf("mnbrak3 fu < fc \n"); */
2028: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2029: /* #endif */
2030: /* dum=u; /\* Shifting c and u *\/ */
2031: /* u = *cx; */
2032: /* *cx = dum; */
2033: /* dum = fu; */
2034: /* fu = *fc; */
2035: /* *fc =dum; */
2036: /* } */
1.224 brouard 2037: #ifdef DEBUGMNBRAK
2038: double A, fparabu;
2039: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2040: fparabu= *fa - A*(*ax-u)*(*ax-u);
2041: 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);
2042: 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 2043: #endif
1.191 brouard 2044: dum=u; /* Shifting c and u */
2045: u = *cx;
2046: *cx = dum;
2047: dum = fu;
2048: fu = *fc;
2049: *fc =dum;
1.183 brouard 2050: #endif
1.162 brouard 2051: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2052: #ifdef DEBUG
1.224 brouard 2053: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2054: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2055: #endif
1.126 brouard 2056: fu=(*func)(u);
2057: if (fu < *fc) {
1.183 brouard 2058: #ifdef DEBUG
1.224 brouard 2059: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2060: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2061: #endif
2062: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2063: SHFT(*fb,*fc,fu,(*func)(u))
2064: #ifdef DEBUG
2065: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2066: #endif
2067: }
1.162 brouard 2068: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2069: #ifdef DEBUG
1.224 brouard 2070: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2071: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2072: #endif
1.126 brouard 2073: u=ulim;
2074: fu=(*func)(u);
1.183 brouard 2075: } else { /* u could be left to b (if r > q parabola has a maximum) */
2076: #ifdef DEBUG
1.224 brouard 2077: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2078: 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 2079: #endif
1.126 brouard 2080: u=(*cx)+GOLD*(*cx-*bx);
2081: fu=(*func)(u);
1.224 brouard 2082: #ifdef DEBUG
2083: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2084: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2085: #endif
1.183 brouard 2086: } /* end tests */
1.126 brouard 2087: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2088: SHFT(*fa,*fb,*fc,fu)
2089: #ifdef DEBUG
1.224 brouard 2090: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2091: 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 2092: #endif
2093: } /* 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 2094: }
2095:
2096: /*************** linmin ************************/
1.162 brouard 2097: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2098: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2099: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2100: the value of func at the returned location p . This is actually all accomplished by calling the
2101: routines mnbrak and brent .*/
1.126 brouard 2102: int ncom;
2103: double *pcom,*xicom;
2104: double (*nrfunc)(double []);
2105:
1.224 brouard 2106: #ifdef LINMINORIGINAL
1.126 brouard 2107: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2108: #else
2109: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2110: #endif
1.126 brouard 2111: {
2112: double brent(double ax, double bx, double cx,
2113: double (*f)(double), double tol, double *xmin);
2114: double f1dim(double x);
2115: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2116: double *fc, double (*func)(double));
2117: int j;
2118: double xx,xmin,bx,ax;
2119: double fx,fb,fa;
1.187 brouard 2120:
1.203 brouard 2121: #ifdef LINMINORIGINAL
2122: #else
2123: double scale=10., axs, xxs; /* Scale added for infinity */
2124: #endif
2125:
1.126 brouard 2126: ncom=n;
2127: pcom=vector(1,n);
2128: xicom=vector(1,n);
2129: nrfunc=func;
2130: for (j=1;j<=n;j++) {
2131: pcom[j]=p[j];
1.202 brouard 2132: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2133: }
1.187 brouard 2134:
1.203 brouard 2135: #ifdef LINMINORIGINAL
2136: xx=1.;
2137: #else
2138: axs=0.0;
2139: xxs=1.;
2140: do{
2141: xx= xxs;
2142: #endif
1.187 brouard 2143: ax=0.;
2144: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2145: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2146: /* 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)) */
2147: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2148: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2149: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2150: /* 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 2151: #ifdef LINMINORIGINAL
2152: #else
2153: if (fx != fx){
1.224 brouard 2154: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2155: printf("|");
2156: fprintf(ficlog,"|");
1.203 brouard 2157: #ifdef DEBUGLINMIN
1.224 brouard 2158: 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 2159: #endif
2160: }
1.224 brouard 2161: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2162: #endif
2163:
1.191 brouard 2164: #ifdef DEBUGLINMIN
2165: 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 2166: 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 2167: #endif
1.224 brouard 2168: #ifdef LINMINORIGINAL
2169: #else
2170: if(fb == fx){ /* Flat function in the direction */
2171: xmin=xx;
2172: *flat=1;
2173: }else{
2174: *flat=0;
2175: #endif
2176: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2177: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2178: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2179: /* fmin = f(p[j] + xmin * xi[j]) */
2180: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2181: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2182: #ifdef DEBUG
1.224 brouard 2183: 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);
2184: 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);
2185: #endif
2186: #ifdef LINMINORIGINAL
2187: #else
2188: }
1.126 brouard 2189: #endif
1.191 brouard 2190: #ifdef DEBUGLINMIN
2191: printf("linmin end ");
1.202 brouard 2192: fprintf(ficlog,"linmin end ");
1.191 brouard 2193: #endif
1.126 brouard 2194: for (j=1;j<=n;j++) {
1.203 brouard 2195: #ifdef LINMINORIGINAL
2196: xi[j] *= xmin;
2197: #else
2198: #ifdef DEBUGLINMIN
2199: if(xxs <1.0)
2200: printf(" before xi[%d]=%12.8f", j,xi[j]);
2201: #endif
2202: 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) */
2203: #ifdef DEBUGLINMIN
2204: if(xxs <1.0)
2205: 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 );
2206: #endif
2207: #endif
1.187 brouard 2208: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2209: }
1.191 brouard 2210: #ifdef DEBUGLINMIN
1.203 brouard 2211: printf("\n");
1.191 brouard 2212: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2213: 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 2214: for (j=1;j<=n;j++) {
1.202 brouard 2215: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2216: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2217: if(j % ncovmodel == 0){
1.191 brouard 2218: printf("\n");
1.202 brouard 2219: fprintf(ficlog,"\n");
2220: }
1.191 brouard 2221: }
1.203 brouard 2222: #else
1.191 brouard 2223: #endif
1.126 brouard 2224: free_vector(xicom,1,n);
2225: free_vector(pcom,1,n);
2226: }
2227:
2228:
2229: /*************** powell ************************/
1.162 brouard 2230: /*
2231: Minimization of a function func of n variables. Input consists of an initial starting point
2232: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2233: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2234: such that failure to decrease by more than this amount on one iteration signals doneness. On
2235: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2236: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2237: */
1.224 brouard 2238: #ifdef LINMINORIGINAL
2239: #else
2240: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2241: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2242: #endif
1.126 brouard 2243: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2244: double (*func)(double []))
2245: {
1.224 brouard 2246: #ifdef LINMINORIGINAL
2247: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2248: double (*func)(double []));
1.224 brouard 2249: #else
1.241 brouard 2250: void linmin(double p[], double xi[], int n, double *fret,
2251: double (*func)(double []),int *flat);
1.224 brouard 2252: #endif
1.239 brouard 2253: int i,ibig,j,jk,k;
1.126 brouard 2254: double del,t,*pt,*ptt,*xit;
1.181 brouard 2255: double directest;
1.126 brouard 2256: double fp,fptt;
2257: double *xits;
2258: int niterf, itmp;
1.224 brouard 2259: #ifdef LINMINORIGINAL
2260: #else
2261:
2262: flatdir=ivector(1,n);
2263: for (j=1;j<=n;j++) flatdir[j]=0;
2264: #endif
1.126 brouard 2265:
2266: pt=vector(1,n);
2267: ptt=vector(1,n);
2268: xit=vector(1,n);
2269: xits=vector(1,n);
2270: *fret=(*func)(p);
2271: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2272: rcurr_time = time(NULL);
1.126 brouard 2273: for (*iter=1;;++(*iter)) {
1.187 brouard 2274: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2275: ibig=0;
2276: del=0.0;
1.157 brouard 2277: rlast_time=rcurr_time;
2278: /* (void) gettimeofday(&curr_time,&tzp); */
2279: rcurr_time = time(NULL);
2280: curr_time = *localtime(&rcurr_time);
2281: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2282: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2283: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2284: for (i=1;i<=n;i++) {
1.126 brouard 2285: fprintf(ficrespow," %.12lf", p[i]);
2286: }
1.239 brouard 2287: fprintf(ficrespow,"\n");fflush(ficrespow);
2288: printf("\n#model= 1 + age ");
2289: fprintf(ficlog,"\n#model= 1 + age ");
2290: if(nagesqr==1){
1.241 brouard 2291: printf(" + age*age ");
2292: fprintf(ficlog," + age*age ");
1.239 brouard 2293: }
2294: for(j=1;j <=ncovmodel-2;j++){
2295: if(Typevar[j]==0) {
2296: printf(" + V%d ",Tvar[j]);
2297: fprintf(ficlog," + V%d ",Tvar[j]);
2298: }else if(Typevar[j]==1) {
2299: printf(" + V%d*age ",Tvar[j]);
2300: fprintf(ficlog," + V%d*age ",Tvar[j]);
2301: }else if(Typevar[j]==2) {
2302: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2303: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2304: }
2305: }
1.126 brouard 2306: printf("\n");
1.239 brouard 2307: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2308: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2309: fprintf(ficlog,"\n");
1.239 brouard 2310: for(i=1,jk=1; i <=nlstate; i++){
2311: for(k=1; k <=(nlstate+ndeath); k++){
2312: if (k != i) {
2313: printf("%d%d ",i,k);
2314: fprintf(ficlog,"%d%d ",i,k);
2315: for(j=1; j <=ncovmodel; j++){
2316: printf("%12.7f ",p[jk]);
2317: fprintf(ficlog,"%12.7f ",p[jk]);
2318: jk++;
2319: }
2320: printf("\n");
2321: fprintf(ficlog,"\n");
2322: }
2323: }
2324: }
1.241 brouard 2325: if(*iter <=3 && *iter >1){
1.157 brouard 2326: tml = *localtime(&rcurr_time);
2327: strcpy(strcurr,asctime(&tml));
2328: rforecast_time=rcurr_time;
1.126 brouard 2329: itmp = strlen(strcurr);
2330: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2331: strcurr[itmp-1]='\0';
1.162 brouard 2332: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2333: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2334: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2335: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2336: forecast_time = *localtime(&rforecast_time);
2337: strcpy(strfor,asctime(&forecast_time));
2338: itmp = strlen(strfor);
2339: if(strfor[itmp-1]=='\n')
2340: strfor[itmp-1]='\0';
2341: 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);
2342: 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 2343: }
2344: }
1.187 brouard 2345: for (i=1;i<=n;i++) { /* For each direction i */
2346: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2347: fptt=(*fret);
2348: #ifdef DEBUG
1.203 brouard 2349: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2350: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2351: #endif
1.203 brouard 2352: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2353: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2354: #ifdef LINMINORIGINAL
1.188 brouard 2355: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2356: #else
2357: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2358: flatdir[i]=flat; /* Function is vanishing in that direction i */
2359: #endif
2360: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2361: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2362: /* because that direction will be replaced unless the gain del is small */
2363: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2364: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2365: /* with the new direction. */
2366: del=fabs(fptt-(*fret));
2367: ibig=i;
1.126 brouard 2368: }
2369: #ifdef DEBUG
2370: printf("%d %.12e",i,(*fret));
2371: fprintf(ficlog,"%d %.12e",i,(*fret));
2372: for (j=1;j<=n;j++) {
1.224 brouard 2373: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2374: printf(" x(%d)=%.12e",j,xit[j]);
2375: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2376: }
2377: for(j=1;j<=n;j++) {
1.225 brouard 2378: printf(" p(%d)=%.12e",j,p[j]);
2379: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2380: }
2381: printf("\n");
2382: fprintf(ficlog,"\n");
2383: #endif
1.187 brouard 2384: } /* end loop on each direction i */
2385: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2386: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2387: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2388: for(j=1;j<=n;j++) {
1.225 brouard 2389: if(flatdir[j] >0){
2390: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2391: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2392: }
2393: /* printf("\n"); */
2394: /* fprintf(ficlog,"\n"); */
2395: }
1.243 brouard 2396: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2397: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2398: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2399: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2400: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2401: /* decreased of more than 3.84 */
2402: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2403: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2404: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2405:
1.188 brouard 2406: /* Starting the program with initial values given by a former maximization will simply change */
2407: /* the scales of the directions and the directions, because the are reset to canonical directions */
2408: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2409: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2410: #ifdef DEBUG
2411: int k[2],l;
2412: k[0]=1;
2413: k[1]=-1;
2414: printf("Max: %.12e",(*func)(p));
2415: fprintf(ficlog,"Max: %.12e",(*func)(p));
2416: for (j=1;j<=n;j++) {
2417: printf(" %.12e",p[j]);
2418: fprintf(ficlog," %.12e",p[j]);
2419: }
2420: printf("\n");
2421: fprintf(ficlog,"\n");
2422: for(l=0;l<=1;l++) {
2423: for (j=1;j<=n;j++) {
2424: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2425: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2426: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2427: }
2428: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2429: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2430: }
2431: #endif
2432:
1.224 brouard 2433: #ifdef LINMINORIGINAL
2434: #else
2435: free_ivector(flatdir,1,n);
2436: #endif
1.126 brouard 2437: free_vector(xit,1,n);
2438: free_vector(xits,1,n);
2439: free_vector(ptt,1,n);
2440: free_vector(pt,1,n);
2441: return;
1.192 brouard 2442: } /* enough precision */
1.240 brouard 2443: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2444: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2445: ptt[j]=2.0*p[j]-pt[j];
2446: xit[j]=p[j]-pt[j];
2447: pt[j]=p[j];
2448: }
1.181 brouard 2449: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2450: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2451: if (*iter <=4) {
1.225 brouard 2452: #else
2453: #endif
1.224 brouard 2454: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2455: #else
1.161 brouard 2456: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2457: #endif
1.162 brouard 2458: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2459: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2460: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2461: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2462: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2463: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2464: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2465: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2466: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2467: /* Even if f3 <f1, directest can be negative and t >0 */
2468: /* mu² and del² are equal when f3=f1 */
2469: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2470: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2471: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2472: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2473: #ifdef NRCORIGINAL
2474: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2475: #else
2476: 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 2477: t= t- del*SQR(fp-fptt);
1.183 brouard 2478: #endif
1.202 brouard 2479: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2480: #ifdef DEBUG
1.181 brouard 2481: 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);
2482: 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 2483: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2484: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2485: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2486: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2487: 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);
2488: 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);
2489: #endif
1.183 brouard 2490: #ifdef POWELLORIGINAL
2491: if (t < 0.0) { /* Then we use it for new direction */
2492: #else
1.182 brouard 2493: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2494: 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 2495: 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 2496: 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 2497: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2498: }
1.181 brouard 2499: if (directest < 0.0) { /* Then we use it for new direction */
2500: #endif
1.191 brouard 2501: #ifdef DEBUGLINMIN
1.234 brouard 2502: printf("Before linmin in direction P%d-P0\n",n);
2503: for (j=1;j<=n;j++) {
2504: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2505: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2506: if(j % ncovmodel == 0){
2507: printf("\n");
2508: fprintf(ficlog,"\n");
2509: }
2510: }
1.224 brouard 2511: #endif
2512: #ifdef LINMINORIGINAL
1.234 brouard 2513: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2514: #else
1.234 brouard 2515: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2516: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2517: #endif
1.234 brouard 2518:
1.191 brouard 2519: #ifdef DEBUGLINMIN
1.234 brouard 2520: for (j=1;j<=n;j++) {
2521: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2522: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2523: if(j % ncovmodel == 0){
2524: printf("\n");
2525: fprintf(ficlog,"\n");
2526: }
2527: }
1.224 brouard 2528: #endif
1.234 brouard 2529: for (j=1;j<=n;j++) {
2530: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2531: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2532: }
1.224 brouard 2533: #ifdef LINMINORIGINAL
2534: #else
1.234 brouard 2535: for (j=1, flatd=0;j<=n;j++) {
2536: if(flatdir[j]>0)
2537: flatd++;
2538: }
2539: if(flatd >0){
1.255 brouard 2540: printf("%d flat directions: ",flatd);
2541: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2542: for (j=1;j<=n;j++) {
2543: if(flatdir[j]>0){
2544: printf("%d ",j);
2545: fprintf(ficlog,"%d ",j);
2546: }
2547: }
2548: printf("\n");
2549: fprintf(ficlog,"\n");
2550: }
1.191 brouard 2551: #endif
1.234 brouard 2552: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2553: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2554:
1.126 brouard 2555: #ifdef DEBUG
1.234 brouard 2556: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2557: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2558: for(j=1;j<=n;j++){
2559: printf(" %lf",xit[j]);
2560: fprintf(ficlog," %lf",xit[j]);
2561: }
2562: printf("\n");
2563: fprintf(ficlog,"\n");
1.126 brouard 2564: #endif
1.192 brouard 2565: } /* end of t or directest negative */
1.224 brouard 2566: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2567: #else
1.234 brouard 2568: } /* end if (fptt < fp) */
1.192 brouard 2569: #endif
1.225 brouard 2570: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2571: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2572: #else
1.224 brouard 2573: #endif
1.234 brouard 2574: } /* loop iteration */
1.126 brouard 2575: }
1.234 brouard 2576:
1.126 brouard 2577: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2578:
1.235 brouard 2579: 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 2580: {
1.279 brouard 2581: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2582: * (and selected quantitative values in nres)
2583: * by left multiplying the unit
2584: * matrix by transitions matrix until convergence is reached with precision ftolpl
2585: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2586: * Wx is row vector: population in state 1, population in state 2, population dead
2587: * or prevalence in state 1, prevalence in state 2, 0
2588: * newm is the matrix after multiplications, its rows are identical at a factor.
2589: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2590: * Output is prlim.
2591: * Initial matrix pimij
2592: */
1.206 brouard 2593: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2594: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2595: /* 0, 0 , 1} */
2596: /*
2597: * and after some iteration: */
2598: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2599: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2600: /* 0, 0 , 1} */
2601: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2602: /* {0.51571254859325999, 0.4842874514067399, */
2603: /* 0.51326036147820708, 0.48673963852179264} */
2604: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2605:
1.126 brouard 2606: int i, ii,j,k;
1.209 brouard 2607: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2608: /* double **matprod2(); */ /* test */
1.218 brouard 2609: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2610: double **newm;
1.209 brouard 2611: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2612: int ncvloop=0;
1.288 brouard 2613: int first=0;
1.169 brouard 2614:
1.209 brouard 2615: min=vector(1,nlstate);
2616: max=vector(1,nlstate);
2617: meandiff=vector(1,nlstate);
2618:
1.218 brouard 2619: /* Starting with matrix unity */
1.126 brouard 2620: for (ii=1;ii<=nlstate+ndeath;ii++)
2621: for (j=1;j<=nlstate+ndeath;j++){
2622: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2623: }
1.169 brouard 2624:
2625: cov[1]=1.;
2626:
2627: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2628: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2629: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2630: ncvloop++;
1.126 brouard 2631: newm=savm;
2632: /* Covariates have to be included here again */
1.138 brouard 2633: cov[2]=agefin;
1.187 brouard 2634: if(nagesqr==1)
2635: cov[3]= agefin*agefin;;
1.234 brouard 2636: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2637: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2638: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2639: /* 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 2640: }
2641: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2642: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2643: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2644: /* 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 2645: }
1.237 brouard 2646: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2647: if(Dummy[Tvar[Tage[k]]]){
2648: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2649: } else{
1.235 brouard 2650: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2651: }
1.235 brouard 2652: /* 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 2653: }
1.237 brouard 2654: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2655: /* 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 2656: if(Dummy[Tvard[k][1]==0]){
2657: if(Dummy[Tvard[k][2]==0]){
2658: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2659: }else{
2660: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2661: }
2662: }else{
2663: if(Dummy[Tvard[k][2]==0]){
2664: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2665: }else{
2666: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2667: }
2668: }
1.234 brouard 2669: }
1.138 brouard 2670: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2671: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2672: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2673: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2674: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2675: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2676: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2677:
1.126 brouard 2678: savm=oldm;
2679: oldm=newm;
1.209 brouard 2680:
2681: for(j=1; j<=nlstate; j++){
2682: max[j]=0.;
2683: min[j]=1.;
2684: }
2685: for(i=1;i<=nlstate;i++){
2686: sumnew=0;
2687: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2688: for(j=1; j<=nlstate; j++){
2689: prlim[i][j]= newm[i][j]/(1-sumnew);
2690: max[j]=FMAX(max[j],prlim[i][j]);
2691: min[j]=FMIN(min[j],prlim[i][j]);
2692: }
2693: }
2694:
1.126 brouard 2695: maxmax=0.;
1.209 brouard 2696: for(j=1; j<=nlstate; j++){
2697: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2698: maxmax=FMAX(maxmax,meandiff[j]);
2699: /* 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 2700: } /* j loop */
1.203 brouard 2701: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2702: /* 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 2703: if(maxmax < ftolpl){
1.209 brouard 2704: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2705: free_vector(min,1,nlstate);
2706: free_vector(max,1,nlstate);
2707: free_vector(meandiff,1,nlstate);
1.126 brouard 2708: return prlim;
2709: }
1.288 brouard 2710: } /* agefin loop */
1.208 brouard 2711: /* After some age loop it doesn't converge */
1.288 brouard 2712: if(!first){
2713: first=1;
2714: 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);
2715: }
2716: 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);
2717:
1.209 brouard 2718: /* 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); */
2719: free_vector(min,1,nlstate);
2720: free_vector(max,1,nlstate);
2721: free_vector(meandiff,1,nlstate);
1.208 brouard 2722:
1.169 brouard 2723: return prlim; /* should not reach here */
1.126 brouard 2724: }
2725:
1.217 brouard 2726:
2727: /**** Back Prevalence limit (stable or period prevalence) ****************/
2728:
1.218 brouard 2729: /* 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) */
2730: /* 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 2731: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2732: {
1.264 brouard 2733: /* 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 2734: matrix by transitions matrix until convergence is reached with precision ftolpl */
2735: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2736: /* Wx is row vector: population in state 1, population in state 2, population dead */
2737: /* or prevalence in state 1, prevalence in state 2, 0 */
2738: /* newm is the matrix after multiplications, its rows are identical at a factor */
2739: /* Initial matrix pimij */
2740: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2741: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2742: /* 0, 0 , 1} */
2743: /*
2744: * and after some iteration: */
2745: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2746: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2747: /* 0, 0 , 1} */
2748: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2749: /* {0.51571254859325999, 0.4842874514067399, */
2750: /* 0.51326036147820708, 0.48673963852179264} */
2751: /* If we start from prlim again, prlim tends to a constant matrix */
2752:
2753: int i, ii,j,k;
1.247 brouard 2754: int first=0;
1.217 brouard 2755: double *min, *max, *meandiff, maxmax,sumnew=0.;
2756: /* double **matprod2(); */ /* test */
2757: double **out, cov[NCOVMAX+1], **bmij();
2758: double **newm;
1.218 brouard 2759: double **dnewm, **doldm, **dsavm; /* for use */
2760: double **oldm, **savm; /* for use */
2761:
1.217 brouard 2762: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2763: int ncvloop=0;
2764:
2765: min=vector(1,nlstate);
2766: max=vector(1,nlstate);
2767: meandiff=vector(1,nlstate);
2768:
1.266 brouard 2769: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2770: oldm=oldms; savm=savms;
2771:
2772: /* Starting with matrix unity */
2773: for (ii=1;ii<=nlstate+ndeath;ii++)
2774: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2775: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2776: }
2777:
2778: cov[1]=1.;
2779:
2780: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2781: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2782: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2783: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2784: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2785: ncvloop++;
1.218 brouard 2786: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2787: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2788: /* Covariates have to be included here again */
2789: cov[2]=agefin;
2790: if(nagesqr==1)
2791: cov[3]= agefin*agefin;;
1.242 brouard 2792: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2793: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2794: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2795: /* 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 2796: }
2797: /* for (k=1; k<=cptcovn;k++) { */
2798: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2799: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2800: /* /\* 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])]); *\/ */
2801: /* } */
2802: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2803: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2804: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2805: /* 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]); */
2806: }
2807: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2808: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2809: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2810: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2811: for (k=1; k<=cptcovage;k++){ /* For product with age */
2812: if(Dummy[Tvar[Tage[k]]]){
2813: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2814: } else{
2815: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2816: }
2817: /* 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]); */
2818: }
2819: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2820: /* 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]); */
2821: if(Dummy[Tvard[k][1]==0]){
2822: if(Dummy[Tvard[k][2]==0]){
2823: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2824: }else{
2825: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2826: }
2827: }else{
2828: if(Dummy[Tvard[k][2]==0]){
2829: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2830: }else{
2831: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2832: }
2833: }
1.217 brouard 2834: }
2835:
2836: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2837: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2838: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2839: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2840: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2841: /* ij should be linked to the correct index of cov */
2842: /* age and covariate values ij are in 'cov', but we need to pass
2843: * ij for the observed prevalence at age and status and covariate
2844: * number: prevacurrent[(int)agefin][ii][ij]
2845: */
2846: /* 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 *\/ */
2847: /* 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 *\/ */
2848: 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 2849: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2850: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2851: /* for(i=1; i<=nlstate+ndeath; i++) { */
2852: /* printf("%d newm= ",i); */
2853: /* for(j=1;j<=nlstate+ndeath;j++) { */
2854: /* printf("%f ",newm[i][j]); */
2855: /* } */
2856: /* printf("oldm * "); */
2857: /* for(j=1;j<=nlstate+ndeath;j++) { */
2858: /* printf("%f ",oldm[i][j]); */
2859: /* } */
1.268 brouard 2860: /* printf(" bmmij "); */
1.266 brouard 2861: /* for(j=1;j<=nlstate+ndeath;j++) { */
2862: /* printf("%f ",pmmij[i][j]); */
2863: /* } */
2864: /* printf("\n"); */
2865: /* } */
2866: /* } */
1.217 brouard 2867: savm=oldm;
2868: oldm=newm;
1.266 brouard 2869:
1.217 brouard 2870: for(j=1; j<=nlstate; j++){
2871: max[j]=0.;
2872: min[j]=1.;
2873: }
2874: for(j=1; j<=nlstate; j++){
2875: for(i=1;i<=nlstate;i++){
1.234 brouard 2876: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2877: bprlim[i][j]= newm[i][j];
2878: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2879: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2880: }
2881: }
1.218 brouard 2882:
1.217 brouard 2883: maxmax=0.;
2884: for(i=1; i<=nlstate; i++){
2885: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2886: maxmax=FMAX(maxmax,meandiff[i]);
2887: /* 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 2888: } /* i loop */
1.217 brouard 2889: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2890: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2891: if(maxmax < ftolpl){
1.220 brouard 2892: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2893: free_vector(min,1,nlstate);
2894: free_vector(max,1,nlstate);
2895: free_vector(meandiff,1,nlstate);
2896: return bprlim;
2897: }
1.288 brouard 2898: } /* agefin loop */
1.217 brouard 2899: /* After some age loop it doesn't converge */
1.288 brouard 2900: if(!first){
1.247 brouard 2901: first=1;
2902: 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\
2903: 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);
2904: }
2905: 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 2906: 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);
2907: /* 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); */
2908: free_vector(min,1,nlstate);
2909: free_vector(max,1,nlstate);
2910: free_vector(meandiff,1,nlstate);
2911:
2912: return bprlim; /* should not reach here */
2913: }
2914:
1.126 brouard 2915: /*************** transition probabilities ***************/
2916:
2917: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2918: {
1.138 brouard 2919: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2920: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2921: model to the ncovmodel covariates (including constant and age).
2922: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2923: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2924: ncth covariate in the global vector x is given by the formula:
2925: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2926: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2927: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2928: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2929: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2930: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2931: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2932: */
2933: double s1, lnpijopii;
1.126 brouard 2934: /*double t34;*/
1.164 brouard 2935: int i,j, nc, ii, jj;
1.126 brouard 2936:
1.223 brouard 2937: for(i=1; i<= nlstate; i++){
2938: for(j=1; j<i;j++){
2939: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2940: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2941: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2942: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2943: }
2944: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2945: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2946: }
2947: for(j=i+1; j<=nlstate+ndeath;j++){
2948: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2949: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2950: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2951: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2952: }
2953: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2954: }
2955: }
1.218 brouard 2956:
1.223 brouard 2957: for(i=1; i<= nlstate; i++){
2958: s1=0;
2959: for(j=1; j<i; j++){
2960: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2961: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2962: }
2963: for(j=i+1; j<=nlstate+ndeath; j++){
2964: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2965: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2966: }
2967: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2968: ps[i][i]=1./(s1+1.);
2969: /* Computing other pijs */
2970: for(j=1; j<i; j++)
2971: ps[i][j]= exp(ps[i][j])*ps[i][i];
2972: for(j=i+1; j<=nlstate+ndeath; j++)
2973: ps[i][j]= exp(ps[i][j])*ps[i][i];
2974: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2975: } /* end i */
1.218 brouard 2976:
1.223 brouard 2977: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2978: for(jj=1; jj<= nlstate+ndeath; jj++){
2979: ps[ii][jj]=0;
2980: ps[ii][ii]=1;
2981: }
2982: }
1.294 brouard 2983:
2984:
1.223 brouard 2985: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2986: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2987: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2988: /* } */
2989: /* printf("\n "); */
2990: /* } */
2991: /* printf("\n ");printf("%lf ",cov[2]);*/
2992: /*
2993: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2994: goto end;*/
1.266 brouard 2995: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2996: }
2997:
1.218 brouard 2998: /*************** backward transition probabilities ***************/
2999:
3000: /* 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 ) */
3001: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3002: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3003: {
1.266 brouard 3004: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
3005: * 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 3006: */
1.218 brouard 3007: int i, ii, j,k;
1.222 brouard 3008:
3009: double **out, **pmij();
3010: double sumnew=0.;
1.218 brouard 3011: double agefin;
1.292 brouard 3012: 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 3013: double **dnewm, **dsavm, **doldm;
3014: double **bbmij;
3015:
1.218 brouard 3016: doldm=ddoldms; /* global pointers */
1.222 brouard 3017: dnewm=ddnewms;
3018: dsavm=ddsavms;
3019:
3020: agefin=cov[2];
1.268 brouard 3021: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3022: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3023: the observed prevalence (with this covariate ij) at beginning of transition */
3024: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3025:
3026: /* P_x */
1.266 brouard 3027: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3028: /* outputs pmmij which is a stochastic matrix in row */
3029:
3030: /* Diag(w_x) */
1.292 brouard 3031: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3032: sumnew=0.;
1.269 brouard 3033: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3034: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 3035: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3036: sumnew+=prevacurrent[(int)agefin][ii][ij];
3037: }
3038: if(sumnew >0.01){ /* At least some value in the prevalence */
3039: for (ii=1;ii<=nlstate+ndeath;ii++){
3040: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3041: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3042: }
3043: }else{
3044: for (ii=1;ii<=nlstate+ndeath;ii++){
3045: for (j=1;j<=nlstate+ndeath;j++)
3046: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3047: }
3048: /* if(sumnew <0.9){ */
3049: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3050: /* } */
3051: }
3052: k3=0.0; /* We put the last diagonal to 0 */
3053: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3054: doldm[ii][ii]= k3;
3055: }
3056: /* End doldm, At the end doldm is diag[(w_i)] */
3057:
1.292 brouard 3058: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3059: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3060:
1.292 brouard 3061: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3062: /* 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 3063: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3064: sumnew=0.;
1.222 brouard 3065: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3066: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3067: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3068: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3069: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3070: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3071: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3072: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3073: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3074: /* }else */
1.268 brouard 3075: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3076: } /*End ii */
3077: } /* 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 */
3078:
1.292 brouard 3079: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3080: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3081: /* end bmij */
1.266 brouard 3082: return ps; /*pointer is unchanged */
1.218 brouard 3083: }
1.217 brouard 3084: /*************** transition probabilities ***************/
3085:
1.218 brouard 3086: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3087: {
3088: /* According to parameters values stored in x and the covariate's values stored in cov,
3089: computes the probability to be observed in state j being in state i by appying the
3090: model to the ncovmodel covariates (including constant and age).
3091: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3092: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3093: ncth covariate in the global vector x is given by the formula:
3094: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3095: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3096: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3097: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3098: Outputs ps[i][j] the probability to be observed in j being in j according to
3099: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3100: */
3101: double s1, lnpijopii;
3102: /*double t34;*/
3103: int i,j, nc, ii, jj;
3104:
1.234 brouard 3105: for(i=1; i<= nlstate; i++){
3106: for(j=1; j<i;j++){
3107: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3108: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3109: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3110: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3111: }
3112: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3113: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3114: }
3115: for(j=i+1; j<=nlstate+ndeath;j++){
3116: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3117: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3118: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3119: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3120: }
3121: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3122: }
3123: }
3124:
3125: for(i=1; i<= nlstate; i++){
3126: s1=0;
3127: for(j=1; j<i; j++){
3128: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3129: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3130: }
3131: for(j=i+1; j<=nlstate+ndeath; j++){
3132: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3133: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3134: }
3135: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3136: ps[i][i]=1./(s1+1.);
3137: /* Computing other pijs */
3138: for(j=1; j<i; j++)
3139: ps[i][j]= exp(ps[i][j])*ps[i][i];
3140: for(j=i+1; j<=nlstate+ndeath; j++)
3141: ps[i][j]= exp(ps[i][j])*ps[i][i];
3142: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3143: } /* end i */
3144:
3145: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3146: for(jj=1; jj<= nlstate+ndeath; jj++){
3147: ps[ii][jj]=0;
3148: ps[ii][ii]=1;
3149: }
3150: }
1.296 ! brouard 3151: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3152: for(jj=1; jj<= nlstate+ndeath; jj++){
3153: s1=0.;
3154: for(ii=1; ii<= nlstate+ndeath; ii++){
3155: s1+=ps[ii][jj];
3156: }
3157: for(ii=1; ii<= nlstate; ii++){
3158: ps[ii][jj]=ps[ii][jj]/s1;
3159: }
3160: }
3161: /* Transposition */
3162: for(jj=1; jj<= nlstate+ndeath; jj++){
3163: for(ii=jj; ii<= nlstate+ndeath; ii++){
3164: s1=ps[ii][jj];
3165: ps[ii][jj]=ps[jj][ii];
3166: ps[jj][ii]=s1;
3167: }
3168: }
3169: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3170: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3171: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3172: /* } */
3173: /* printf("\n "); */
3174: /* } */
3175: /* printf("\n ");printf("%lf ",cov[2]);*/
3176: /*
3177: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3178: goto end;*/
3179: return ps;
1.217 brouard 3180: }
3181:
3182:
1.126 brouard 3183: /**************** Product of 2 matrices ******************/
3184:
1.145 brouard 3185: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3186: {
3187: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3188: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3189: /* in, b, out are matrice of pointers which should have been initialized
3190: before: only the contents of out is modified. The function returns
3191: a pointer to pointers identical to out */
1.145 brouard 3192: int i, j, k;
1.126 brouard 3193: for(i=nrl; i<= nrh; i++)
1.145 brouard 3194: for(k=ncolol; k<=ncoloh; k++){
3195: out[i][k]=0.;
3196: for(j=ncl; j<=nch; j++)
3197: out[i][k] +=in[i][j]*b[j][k];
3198: }
1.126 brouard 3199: return out;
3200: }
3201:
3202:
3203: /************* Higher Matrix Product ***************/
3204:
1.235 brouard 3205: 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 3206: {
1.218 brouard 3207: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3208: 'nhstepm*hstepm*stepm' months (i.e. until
3209: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3210: nhstepm*hstepm matrices.
3211: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3212: (typically every 2 years instead of every month which is too big
3213: for the memory).
3214: Model is determined by parameters x and covariates have to be
3215: included manually here.
3216:
3217: */
3218:
3219: int i, j, d, h, k;
1.131 brouard 3220: double **out, cov[NCOVMAX+1];
1.126 brouard 3221: double **newm;
1.187 brouard 3222: double agexact;
1.214 brouard 3223: double agebegin, ageend;
1.126 brouard 3224:
3225: /* Hstepm could be zero and should return the unit matrix */
3226: for (i=1;i<=nlstate+ndeath;i++)
3227: for (j=1;j<=nlstate+ndeath;j++){
3228: oldm[i][j]=(i==j ? 1.0 : 0.0);
3229: po[i][j][0]=(i==j ? 1.0 : 0.0);
3230: }
3231: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3232: for(h=1; h <=nhstepm; h++){
3233: for(d=1; d <=hstepm; d++){
3234: newm=savm;
3235: /* Covariates have to be included here again */
3236: cov[1]=1.;
1.214 brouard 3237: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3238: cov[2]=agexact;
3239: if(nagesqr==1)
1.227 brouard 3240: cov[3]= agexact*agexact;
1.235 brouard 3241: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3242: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3243: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3244: /* 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)); */
3245: }
3246: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3247: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3248: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3249: /* 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]); */
3250: }
3251: for (k=1; k<=cptcovage;k++){
3252: if(Dummy[Tvar[Tage[k]]]){
3253: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3254: } else{
3255: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3256: }
3257: /* 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]); */
3258: }
3259: for (k=1; k<=cptcovprod;k++){ /* */
3260: /* 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]); */
3261: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3262: }
3263: /* for (k=1; k<=cptcovn;k++) */
3264: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3265: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3266: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3267: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3268: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3269:
3270:
1.126 brouard 3271: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3272: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3273: /* right multiplication of oldm by the current matrix */
1.126 brouard 3274: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3275: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3276: /* if((int)age == 70){ */
3277: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3278: /* for(i=1; i<=nlstate+ndeath; i++) { */
3279: /* printf("%d pmmij ",i); */
3280: /* for(j=1;j<=nlstate+ndeath;j++) { */
3281: /* printf("%f ",pmmij[i][j]); */
3282: /* } */
3283: /* printf(" oldm "); */
3284: /* for(j=1;j<=nlstate+ndeath;j++) { */
3285: /* printf("%f ",oldm[i][j]); */
3286: /* } */
3287: /* printf("\n"); */
3288: /* } */
3289: /* } */
1.126 brouard 3290: savm=oldm;
3291: oldm=newm;
3292: }
3293: for(i=1; i<=nlstate+ndeath; i++)
3294: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3295: po[i][j][h]=newm[i][j];
3296: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3297: }
1.128 brouard 3298: /*printf("h=%d ",h);*/
1.126 brouard 3299: } /* end h */
1.267 brouard 3300: /* printf("\n H=%d \n",h); */
1.126 brouard 3301: return po;
3302: }
3303:
1.217 brouard 3304: /************* Higher Back Matrix Product ***************/
1.218 brouard 3305: /* 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 3306: 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 3307: {
1.266 brouard 3308: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3309: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3310: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3311: nhstepm*hstepm matrices.
3312: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3313: (typically every 2 years instead of every month which is too big
1.217 brouard 3314: for the memory).
1.218 brouard 3315: Model is determined by parameters x and covariates have to be
1.266 brouard 3316: included manually here. Then we use a call to bmij(x and cov)
3317: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3318: */
1.217 brouard 3319:
3320: int i, j, d, h, k;
1.266 brouard 3321: double **out, cov[NCOVMAX+1], **bmij();
3322: double **newm, ***newmm;
1.217 brouard 3323: double agexact;
3324: double agebegin, ageend;
1.222 brouard 3325: double **oldm, **savm;
1.217 brouard 3326:
1.266 brouard 3327: newmm=po; /* To be saved */
3328: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3329: /* Hstepm could be zero and should return the unit matrix */
3330: for (i=1;i<=nlstate+ndeath;i++)
3331: for (j=1;j<=nlstate+ndeath;j++){
3332: oldm[i][j]=(i==j ? 1.0 : 0.0);
3333: po[i][j][0]=(i==j ? 1.0 : 0.0);
3334: }
3335: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3336: for(h=1; h <=nhstepm; h++){
3337: for(d=1; d <=hstepm; d++){
3338: newm=savm;
3339: /* Covariates have to be included here again */
3340: cov[1]=1.;
1.271 brouard 3341: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3342: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3343: cov[2]=agexact;
3344: if(nagesqr==1)
1.222 brouard 3345: cov[3]= agexact*agexact;
1.266 brouard 3346: for (k=1; k<=cptcovn;k++){
3347: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3348: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3349: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3350: /* 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)); */
3351: }
1.267 brouard 3352: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3353: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3354: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3355: /* 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]); */
3356: }
3357: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3358: if(Dummy[Tvar[Tage[k]]]){
3359: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3360: } else{
3361: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3362: }
3363: /* 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]); */
3364: }
3365: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3366: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3367: }
1.217 brouard 3368: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3369: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3370:
1.218 brouard 3371: /* Careful transposed matrix */
1.266 brouard 3372: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3373: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3374: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3375: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3376: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3377: /* if((int)age == 70){ */
3378: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3379: /* for(i=1; i<=nlstate+ndeath; i++) { */
3380: /* printf("%d pmmij ",i); */
3381: /* for(j=1;j<=nlstate+ndeath;j++) { */
3382: /* printf("%f ",pmmij[i][j]); */
3383: /* } */
3384: /* printf(" oldm "); */
3385: /* for(j=1;j<=nlstate+ndeath;j++) { */
3386: /* printf("%f ",oldm[i][j]); */
3387: /* } */
3388: /* printf("\n"); */
3389: /* } */
3390: /* } */
3391: savm=oldm;
3392: oldm=newm;
3393: }
3394: for(i=1; i<=nlstate+ndeath; i++)
3395: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3396: po[i][j][h]=newm[i][j];
1.268 brouard 3397: /* if(h==nhstepm) */
3398: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3399: }
1.268 brouard 3400: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3401: } /* end h */
1.268 brouard 3402: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3403: return po;
3404: }
3405:
3406:
1.162 brouard 3407: #ifdef NLOPT
3408: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3409: double fret;
3410: double *xt;
3411: int j;
3412: myfunc_data *d2 = (myfunc_data *) pd;
3413: /* xt = (p1-1); */
3414: xt=vector(1,n);
3415: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3416:
3417: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3418: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3419: printf("Function = %.12lf ",fret);
3420: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3421: printf("\n");
3422: free_vector(xt,1,n);
3423: return fret;
3424: }
3425: #endif
1.126 brouard 3426:
3427: /*************** log-likelihood *************/
3428: double func( double *x)
3429: {
1.226 brouard 3430: int i, ii, j, k, mi, d, kk;
3431: int ioffset=0;
3432: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3433: double **out;
3434: double lli; /* Individual log likelihood */
3435: int s1, s2;
1.228 brouard 3436: 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 3437: double bbh, survp;
3438: long ipmx;
3439: double agexact;
3440: /*extern weight */
3441: /* We are differentiating ll according to initial status */
3442: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3443: /*for(i=1;i<imx;i++)
3444: printf(" %d\n",s[4][i]);
3445: */
1.162 brouard 3446:
1.226 brouard 3447: ++countcallfunc;
1.162 brouard 3448:
1.226 brouard 3449: cov[1]=1.;
1.126 brouard 3450:
1.226 brouard 3451: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3452: ioffset=0;
1.226 brouard 3453: if(mle==1){
3454: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3455: /* Computes the values of the ncovmodel covariates of the model
3456: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3457: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3458: to be observed in j being in i according to the model.
3459: */
1.243 brouard 3460: ioffset=2+nagesqr ;
1.233 brouard 3461: /* Fixed */
1.234 brouard 3462: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3463: 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)*/
3464: }
1.226 brouard 3465: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3466: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3467: has been calculated etc */
3468: /* For an individual i, wav[i] gives the number of effective waves */
3469: /* We compute the contribution to Likelihood of each effective transition
3470: mw[mi][i] is real wave of the mi th effectve wave */
3471: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3472: s2=s[mw[mi+1][i]][i];
3473: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3474: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3475: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3476: */
3477: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3478: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3479: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3480: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3481: }
3482: for (ii=1;ii<=nlstate+ndeath;ii++)
3483: for (j=1;j<=nlstate+ndeath;j++){
3484: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3485: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3486: }
3487: for(d=0; d<dh[mi][i]; d++){
3488: newm=savm;
3489: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3490: cov[2]=agexact;
3491: if(nagesqr==1)
3492: cov[3]= agexact*agexact; /* Should be changed here */
3493: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3494: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3495: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3496: else
3497: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3498: }
3499: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3500: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3501: savm=oldm;
3502: oldm=newm;
3503: } /* end mult */
3504:
3505: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3506: /* But now since version 0.9 we anticipate for bias at large stepm.
3507: * If stepm is larger than one month (smallest stepm) and if the exact delay
3508: * (in months) between two waves is not a multiple of stepm, we rounded to
3509: * the nearest (and in case of equal distance, to the lowest) interval but now
3510: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3511: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3512: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3513: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3514: * -stepm/2 to stepm/2 .
3515: * For stepm=1 the results are the same as for previous versions of Imach.
3516: * For stepm > 1 the results are less biased than in previous versions.
3517: */
1.234 brouard 3518: s1=s[mw[mi][i]][i];
3519: s2=s[mw[mi+1][i]][i];
3520: bbh=(double)bh[mi][i]/(double)stepm;
3521: /* bias bh is positive if real duration
3522: * is higher than the multiple of stepm and negative otherwise.
3523: */
3524: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3525: if( s2 > nlstate){
3526: /* i.e. if s2 is a death state and if the date of death is known
3527: then the contribution to the likelihood is the probability to
3528: die between last step unit time and current step unit time,
3529: which is also equal to probability to die before dh
3530: minus probability to die before dh-stepm .
3531: In version up to 0.92 likelihood was computed
3532: as if date of death was unknown. Death was treated as any other
3533: health state: the date of the interview describes the actual state
3534: and not the date of a change in health state. The former idea was
3535: to consider that at each interview the state was recorded
3536: (healthy, disable or death) and IMaCh was corrected; but when we
3537: introduced the exact date of death then we should have modified
3538: the contribution of an exact death to the likelihood. This new
3539: contribution is smaller and very dependent of the step unit
3540: stepm. It is no more the probability to die between last interview
3541: and month of death but the probability to survive from last
3542: interview up to one month before death multiplied by the
3543: probability to die within a month. Thanks to Chris
3544: Jackson for correcting this bug. Former versions increased
3545: mortality artificially. The bad side is that we add another loop
3546: which slows down the processing. The difference can be up to 10%
3547: lower mortality.
3548: */
3549: /* If, at the beginning of the maximization mostly, the
3550: cumulative probability or probability to be dead is
3551: constant (ie = 1) over time d, the difference is equal to
3552: 0. out[s1][3] = savm[s1][3]: probability, being at state
3553: s1 at precedent wave, to be dead a month before current
3554: wave is equal to probability, being at state s1 at
3555: precedent wave, to be dead at mont of the current
3556: wave. Then the observed probability (that this person died)
3557: is null according to current estimated parameter. In fact,
3558: it should be very low but not zero otherwise the log go to
3559: infinity.
3560: */
1.183 brouard 3561: /* #ifdef INFINITYORIGINAL */
3562: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3563: /* #else */
3564: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3565: /* lli=log(mytinydouble); */
3566: /* else */
3567: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3568: /* #endif */
1.226 brouard 3569: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3570:
1.226 brouard 3571: } else if ( s2==-1 ) { /* alive */
3572: for (j=1,survp=0. ; j<=nlstate; j++)
3573: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3574: /*survp += out[s1][j]; */
3575: lli= log(survp);
3576: }
3577: else if (s2==-4) {
3578: for (j=3,survp=0. ; j<=nlstate; j++)
3579: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3580: lli= log(survp);
3581: }
3582: else if (s2==-5) {
3583: for (j=1,survp=0. ; j<=2; j++)
3584: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3585: lli= log(survp);
3586: }
3587: else{
3588: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3589: /* 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 */
3590: }
3591: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3592: /*if(lli ==000.0)*/
3593: /*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); */
3594: ipmx +=1;
3595: sw += weight[i];
3596: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3597: /* if (lli < log(mytinydouble)){ */
3598: /* 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); */
3599: /* 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]); */
3600: /* } */
3601: } /* end of wave */
3602: } /* end of individual */
3603: } else if(mle==2){
3604: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3605: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3606: for(mi=1; mi<= wav[i]-1; mi++){
3607: for (ii=1;ii<=nlstate+ndeath;ii++)
3608: for (j=1;j<=nlstate+ndeath;j++){
3609: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3610: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3611: }
3612: for(d=0; d<=dh[mi][i]; d++){
3613: newm=savm;
3614: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3615: cov[2]=agexact;
3616: if(nagesqr==1)
3617: cov[3]= agexact*agexact;
3618: for (kk=1; kk<=cptcovage;kk++) {
3619: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3620: }
3621: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3622: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3623: savm=oldm;
3624: oldm=newm;
3625: } /* end mult */
3626:
3627: s1=s[mw[mi][i]][i];
3628: s2=s[mw[mi+1][i]][i];
3629: bbh=(double)bh[mi][i]/(double)stepm;
3630: 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 */
3631: ipmx +=1;
3632: sw += weight[i];
3633: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3634: } /* end of wave */
3635: } /* end of individual */
3636: } else if(mle==3){ /* exponential inter-extrapolation */
3637: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3638: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3639: for(mi=1; mi<= wav[i]-1; mi++){
3640: for (ii=1;ii<=nlstate+ndeath;ii++)
3641: for (j=1;j<=nlstate+ndeath;j++){
3642: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3643: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3644: }
3645: for(d=0; d<dh[mi][i]; d++){
3646: newm=savm;
3647: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3648: cov[2]=agexact;
3649: if(nagesqr==1)
3650: cov[3]= agexact*agexact;
3651: for (kk=1; kk<=cptcovage;kk++) {
3652: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3653: }
3654: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3655: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3656: savm=oldm;
3657: oldm=newm;
3658: } /* end mult */
3659:
3660: s1=s[mw[mi][i]][i];
3661: s2=s[mw[mi+1][i]][i];
3662: bbh=(double)bh[mi][i]/(double)stepm;
3663: 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 */
3664: ipmx +=1;
3665: sw += weight[i];
3666: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3667: } /* end of wave */
3668: } /* end of individual */
3669: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3670: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3671: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3672: for(mi=1; mi<= wav[i]-1; mi++){
3673: for (ii=1;ii<=nlstate+ndeath;ii++)
3674: for (j=1;j<=nlstate+ndeath;j++){
3675: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3676: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3677: }
3678: for(d=0; d<dh[mi][i]; d++){
3679: newm=savm;
3680: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3681: cov[2]=agexact;
3682: if(nagesqr==1)
3683: cov[3]= agexact*agexact;
3684: for (kk=1; kk<=cptcovage;kk++) {
3685: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3686: }
1.126 brouard 3687:
1.226 brouard 3688: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3689: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3690: savm=oldm;
3691: oldm=newm;
3692: } /* end mult */
3693:
3694: s1=s[mw[mi][i]][i];
3695: s2=s[mw[mi+1][i]][i];
3696: if( s2 > nlstate){
3697: lli=log(out[s1][s2] - savm[s1][s2]);
3698: } else if ( s2==-1 ) { /* alive */
3699: for (j=1,survp=0. ; j<=nlstate; j++)
3700: survp += out[s1][j];
3701: lli= log(survp);
3702: }else{
3703: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3704: }
3705: ipmx +=1;
3706: sw += weight[i];
3707: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3708: /* 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 3709: } /* end of wave */
3710: } /* end of individual */
3711: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3712: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3713: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3714: for(mi=1; mi<= wav[i]-1; mi++){
3715: for (ii=1;ii<=nlstate+ndeath;ii++)
3716: for (j=1;j<=nlstate+ndeath;j++){
3717: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3718: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3719: }
3720: for(d=0; d<dh[mi][i]; d++){
3721: newm=savm;
3722: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3723: cov[2]=agexact;
3724: if(nagesqr==1)
3725: cov[3]= agexact*agexact;
3726: for (kk=1; kk<=cptcovage;kk++) {
3727: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3728: }
1.126 brouard 3729:
1.226 brouard 3730: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3731: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3732: savm=oldm;
3733: oldm=newm;
3734: } /* end mult */
3735:
3736: s1=s[mw[mi][i]][i];
3737: s2=s[mw[mi+1][i]][i];
3738: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3739: ipmx +=1;
3740: sw += weight[i];
3741: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3742: /*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]);*/
3743: } /* end of wave */
3744: } /* end of individual */
3745: } /* End of if */
3746: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3747: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3748: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3749: return -l;
1.126 brouard 3750: }
3751:
3752: /*************** log-likelihood *************/
3753: double funcone( double *x)
3754: {
1.228 brouard 3755: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3756: int i, ii, j, k, mi, d, kk;
1.228 brouard 3757: int ioffset=0;
1.131 brouard 3758: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3759: double **out;
3760: double lli; /* Individual log likelihood */
3761: double llt;
3762: int s1, s2;
1.228 brouard 3763: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3764:
1.126 brouard 3765: double bbh, survp;
1.187 brouard 3766: double agexact;
1.214 brouard 3767: double agebegin, ageend;
1.126 brouard 3768: /*extern weight */
3769: /* We are differentiating ll according to initial status */
3770: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3771: /*for(i=1;i<imx;i++)
3772: printf(" %d\n",s[4][i]);
3773: */
3774: cov[1]=1.;
3775:
3776: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3777: ioffset=0;
3778: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3779: /* ioffset=2+nagesqr+cptcovage; */
3780: ioffset=2+nagesqr;
1.232 brouard 3781: /* Fixed */
1.224 brouard 3782: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3783: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3784: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3785: 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)*/
3786: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3787: /* cov[2+6]=covar[Tvar[6]][i]; */
3788: /* cov[2+6]=covar[2][i]; V2 */
3789: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3790: /* cov[2+7]=covar[Tvar[7]][i]; */
3791: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3792: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3793: /* cov[2+9]=covar[Tvar[9]][i]; */
3794: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3795: }
1.232 brouard 3796: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3797: /* 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?)*\/ */
3798: /* } */
1.231 brouard 3799: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3800: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3801: /* } */
1.225 brouard 3802:
1.233 brouard 3803:
3804: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3805: /* Wave varying (but not age varying) */
3806: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3807: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3808: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3809: }
1.232 brouard 3810: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3811: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3812: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3813: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3814: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3815: /* 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 3816: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3817: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3818: /* /\* 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]); *\/ */
3819: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3820: /* } */
1.126 brouard 3821: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3822: for (j=1;j<=nlstate+ndeath;j++){
3823: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3824: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3825: }
1.214 brouard 3826:
3827: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3828: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3829: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3830: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3831: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3832: and mw[mi+1][i]. dh depends on stepm.*/
3833: newm=savm;
1.247 brouard 3834: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3835: cov[2]=agexact;
3836: if(nagesqr==1)
3837: cov[3]= agexact*agexact;
3838: for (kk=1; kk<=cptcovage;kk++) {
3839: if(!FixedV[Tvar[Tage[kk]]])
3840: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3841: else
3842: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3843: }
3844: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3845: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3846: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3847: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3848: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3849: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3850: savm=oldm;
3851: oldm=newm;
1.126 brouard 3852: } /* end mult */
3853:
3854: s1=s[mw[mi][i]][i];
3855: s2=s[mw[mi+1][i]][i];
1.217 brouard 3856: /* if(s2==-1){ */
1.268 brouard 3857: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3858: /* /\* exit(1); *\/ */
3859: /* } */
1.126 brouard 3860: bbh=(double)bh[mi][i]/(double)stepm;
3861: /* bias is positive if real duration
3862: * is higher than the multiple of stepm and negative otherwise.
3863: */
3864: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3865: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3866: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3867: for (j=1,survp=0. ; j<=nlstate; j++)
3868: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3869: lli= log(survp);
1.126 brouard 3870: }else if (mle==1){
1.242 brouard 3871: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3872: } else if(mle==2){
1.242 brouard 3873: 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 3874: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3875: 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 3876: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3877: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3878: } else{ /* mle=0 back to 1 */
1.242 brouard 3879: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3880: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3881: } /* End of if */
3882: ipmx +=1;
3883: sw += weight[i];
3884: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3885: /*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 3886: if(globpr){
1.246 brouard 3887: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3888: %11.6f %11.6f %11.6f ", \
1.242 brouard 3889: 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 3890: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3891: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3892: llt +=ll[k]*gipmx/gsw;
3893: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3894: }
3895: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3896: }
1.232 brouard 3897: } /* end of wave */
3898: } /* end of individual */
3899: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3900: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3901: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3902: if(globpr==0){ /* First time we count the contributions and weights */
3903: gipmx=ipmx;
3904: gsw=sw;
3905: }
3906: return -l;
1.126 brouard 3907: }
3908:
3909:
3910: /*************** function likelione ***********/
1.292 brouard 3911: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 3912: {
3913: /* This routine should help understanding what is done with
3914: the selection of individuals/waves and
3915: to check the exact contribution to the likelihood.
3916: Plotting could be done.
3917: */
3918: int k;
3919:
3920: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3921: strcpy(fileresilk,"ILK_");
1.202 brouard 3922: strcat(fileresilk,fileresu);
1.126 brouard 3923: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3924: printf("Problem with resultfile: %s\n", fileresilk);
3925: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3926: }
1.214 brouard 3927: 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");
3928: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3929: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3930: for(k=1; k<=nlstate; k++)
3931: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3932: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3933: }
3934:
1.292 brouard 3935: *fretone=(*func)(p);
1.126 brouard 3936: if(*globpri !=0){
3937: fclose(ficresilk);
1.205 brouard 3938: if (mle ==0)
3939: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3940: else if(mle >=1)
3941: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3942: 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 3943: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3944:
3945: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3946: 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 3947: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3948: }
1.207 brouard 3949: 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 3950: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3951: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3952: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3953: fflush(fichtm);
1.205 brouard 3954: }
1.126 brouard 3955: return;
3956: }
3957:
3958:
3959: /*********** Maximum Likelihood Estimation ***************/
3960:
3961: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3962: {
1.165 brouard 3963: int i,j, iter=0;
1.126 brouard 3964: double **xi;
3965: double fret;
3966: double fretone; /* Only one call to likelihood */
3967: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3968:
3969: #ifdef NLOPT
3970: int creturn;
3971: nlopt_opt opt;
3972: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3973: double *lb;
3974: double minf; /* the minimum objective value, upon return */
3975: double * p1; /* Shifted parameters from 0 instead of 1 */
3976: myfunc_data dinst, *d = &dinst;
3977: #endif
3978:
3979:
1.126 brouard 3980: xi=matrix(1,npar,1,npar);
3981: for (i=1;i<=npar;i++)
3982: for (j=1;j<=npar;j++)
3983: xi[i][j]=(i==j ? 1.0 : 0.0);
3984: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3985: strcpy(filerespow,"POW_");
1.126 brouard 3986: strcat(filerespow,fileres);
3987: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3988: printf("Problem with resultfile: %s\n", filerespow);
3989: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3990: }
3991: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3992: for (i=1;i<=nlstate;i++)
3993: for(j=1;j<=nlstate+ndeath;j++)
3994: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3995: fprintf(ficrespow,"\n");
1.162 brouard 3996: #ifdef POWELL
1.126 brouard 3997: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3998: #endif
1.126 brouard 3999:
1.162 brouard 4000: #ifdef NLOPT
4001: #ifdef NEWUOA
4002: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4003: #else
4004: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4005: #endif
4006: lb=vector(0,npar-1);
4007: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4008: nlopt_set_lower_bounds(opt, lb);
4009: nlopt_set_initial_step1(opt, 0.1);
4010:
4011: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4012: d->function = func;
4013: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4014: nlopt_set_min_objective(opt, myfunc, d);
4015: nlopt_set_xtol_rel(opt, ftol);
4016: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4017: printf("nlopt failed! %d\n",creturn);
4018: }
4019: else {
4020: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4021: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4022: iter=1; /* not equal */
4023: }
4024: nlopt_destroy(opt);
4025: #endif
1.126 brouard 4026: free_matrix(xi,1,npar,1,npar);
4027: fclose(ficrespow);
1.203 brouard 4028: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4029: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4030: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4031:
4032: }
4033:
4034: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4035: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4036: {
4037: double **a,**y,*x,pd;
1.203 brouard 4038: /* double **hess; */
1.164 brouard 4039: int i, j;
1.126 brouard 4040: int *indx;
4041:
4042: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4043: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4044: void lubksb(double **a, int npar, int *indx, double b[]) ;
4045: void ludcmp(double **a, int npar, int *indx, double *d) ;
4046: double gompertz(double p[]);
1.203 brouard 4047: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4048:
4049: printf("\nCalculation of the hessian matrix. Wait...\n");
4050: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4051: for (i=1;i<=npar;i++){
1.203 brouard 4052: printf("%d-",i);fflush(stdout);
4053: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4054:
4055: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4056:
4057: /* printf(" %f ",p[i]);
4058: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4059: }
4060:
4061: for (i=1;i<=npar;i++) {
4062: for (j=1;j<=npar;j++) {
4063: if (j>i) {
1.203 brouard 4064: printf(".%d-%d",i,j);fflush(stdout);
4065: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4066: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4067:
4068: hess[j][i]=hess[i][j];
4069: /*printf(" %lf ",hess[i][j]);*/
4070: }
4071: }
4072: }
4073: printf("\n");
4074: fprintf(ficlog,"\n");
4075:
4076: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4077: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4078:
4079: a=matrix(1,npar,1,npar);
4080: y=matrix(1,npar,1,npar);
4081: x=vector(1,npar);
4082: indx=ivector(1,npar);
4083: for (i=1;i<=npar;i++)
4084: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4085: ludcmp(a,npar,indx,&pd);
4086:
4087: for (j=1;j<=npar;j++) {
4088: for (i=1;i<=npar;i++) x[i]=0;
4089: x[j]=1;
4090: lubksb(a,npar,indx,x);
4091: for (i=1;i<=npar;i++){
4092: matcov[i][j]=x[i];
4093: }
4094: }
4095:
4096: printf("\n#Hessian matrix#\n");
4097: fprintf(ficlog,"\n#Hessian matrix#\n");
4098: for (i=1;i<=npar;i++) {
4099: for (j=1;j<=npar;j++) {
1.203 brouard 4100: printf("%.6e ",hess[i][j]);
4101: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4102: }
4103: printf("\n");
4104: fprintf(ficlog,"\n");
4105: }
4106:
1.203 brouard 4107: /* printf("\n#Covariance matrix#\n"); */
4108: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4109: /* for (i=1;i<=npar;i++) { */
4110: /* for (j=1;j<=npar;j++) { */
4111: /* printf("%.6e ",matcov[i][j]); */
4112: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4113: /* } */
4114: /* printf("\n"); */
4115: /* fprintf(ficlog,"\n"); */
4116: /* } */
4117:
1.126 brouard 4118: /* Recompute Inverse */
1.203 brouard 4119: /* for (i=1;i<=npar;i++) */
4120: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4121: /* ludcmp(a,npar,indx,&pd); */
4122:
4123: /* printf("\n#Hessian matrix recomputed#\n"); */
4124:
4125: /* for (j=1;j<=npar;j++) { */
4126: /* for (i=1;i<=npar;i++) x[i]=0; */
4127: /* x[j]=1; */
4128: /* lubksb(a,npar,indx,x); */
4129: /* for (i=1;i<=npar;i++){ */
4130: /* y[i][j]=x[i]; */
4131: /* printf("%.3e ",y[i][j]); */
4132: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4133: /* } */
4134: /* printf("\n"); */
4135: /* fprintf(ficlog,"\n"); */
4136: /* } */
4137:
4138: /* Verifying the inverse matrix */
4139: #ifdef DEBUGHESS
4140: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4141:
1.203 brouard 4142: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4143: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4144:
4145: for (j=1;j<=npar;j++) {
4146: for (i=1;i<=npar;i++){
1.203 brouard 4147: printf("%.2f ",y[i][j]);
4148: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4149: }
4150: printf("\n");
4151: fprintf(ficlog,"\n");
4152: }
1.203 brouard 4153: #endif
1.126 brouard 4154:
4155: free_matrix(a,1,npar,1,npar);
4156: free_matrix(y,1,npar,1,npar);
4157: free_vector(x,1,npar);
4158: free_ivector(indx,1,npar);
1.203 brouard 4159: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4160:
4161:
4162: }
4163:
4164: /*************** hessian matrix ****************/
4165: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4166: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4167: int i;
4168: int l=1, lmax=20;
1.203 brouard 4169: double k1,k2, res, fx;
1.132 brouard 4170: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4171: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4172: int k=0,kmax=10;
4173: double l1;
4174:
4175: fx=func(x);
4176: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4177: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4178: l1=pow(10,l);
4179: delts=delt;
4180: for(k=1 ; k <kmax; k=k+1){
4181: delt = delta*(l1*k);
4182: p2[theta]=x[theta] +delt;
1.145 brouard 4183: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4184: p2[theta]=x[theta]-delt;
4185: k2=func(p2)-fx;
4186: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4187: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4188:
1.203 brouard 4189: #ifdef DEBUGHESSII
1.126 brouard 4190: 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);
4191: 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);
4192: #endif
4193: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4194: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4195: k=kmax;
4196: }
4197: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4198: k=kmax; l=lmax*10;
1.126 brouard 4199: }
4200: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4201: delts=delt;
4202: }
1.203 brouard 4203: } /* End loop k */
1.126 brouard 4204: }
4205: delti[theta]=delts;
4206: return res;
4207:
4208: }
4209:
1.203 brouard 4210: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4211: {
4212: int i;
1.164 brouard 4213: int l=1, lmax=20;
1.126 brouard 4214: double k1,k2,k3,k4,res,fx;
1.132 brouard 4215: double p2[MAXPARM+1];
1.203 brouard 4216: int k, kmax=1;
4217: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4218:
4219: int firstime=0;
1.203 brouard 4220:
1.126 brouard 4221: fx=func(x);
1.203 brouard 4222: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4223: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4224: p2[thetai]=x[thetai]+delti[thetai]*k;
4225: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4226: k1=func(p2)-fx;
4227:
1.203 brouard 4228: p2[thetai]=x[thetai]+delti[thetai]*k;
4229: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4230: k2=func(p2)-fx;
4231:
1.203 brouard 4232: p2[thetai]=x[thetai]-delti[thetai]*k;
4233: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4234: k3=func(p2)-fx;
4235:
1.203 brouard 4236: p2[thetai]=x[thetai]-delti[thetai]*k;
4237: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4238: k4=func(p2)-fx;
1.203 brouard 4239: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4240: if(k1*k2*k3*k4 <0.){
1.208 brouard 4241: firstime=1;
1.203 brouard 4242: kmax=kmax+10;
1.208 brouard 4243: }
4244: if(kmax >=10 || firstime ==1){
1.246 brouard 4245: 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);
4246: 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 4247: 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);
4248: 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);
4249: }
4250: #ifdef DEBUGHESSIJ
4251: v1=hess[thetai][thetai];
4252: v2=hess[thetaj][thetaj];
4253: cv12=res;
4254: /* Computing eigen value of Hessian matrix */
4255: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4256: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4257: if ((lc2 <0) || (lc1 <0) ){
4258: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4259: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4260: 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);
4261: 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);
4262: }
1.126 brouard 4263: #endif
4264: }
4265: return res;
4266: }
4267:
1.203 brouard 4268: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4269: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4270: /* { */
4271: /* int i; */
4272: /* int l=1, lmax=20; */
4273: /* double k1,k2,k3,k4,res,fx; */
4274: /* double p2[MAXPARM+1]; */
4275: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4276: /* int k=0,kmax=10; */
4277: /* double l1; */
4278:
4279: /* fx=func(x); */
4280: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4281: /* l1=pow(10,l); */
4282: /* delts=delt; */
4283: /* for(k=1 ; k <kmax; k=k+1){ */
4284: /* delt = delti*(l1*k); */
4285: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4286: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4287: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4288: /* k1=func(p2)-fx; */
4289:
4290: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4291: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4292: /* k2=func(p2)-fx; */
4293:
4294: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4295: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4296: /* k3=func(p2)-fx; */
4297:
4298: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4299: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4300: /* k4=func(p2)-fx; */
4301: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4302: /* #ifdef DEBUGHESSIJ */
4303: /* 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); */
4304: /* 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); */
4305: /* #endif */
4306: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4307: /* k=kmax; */
4308: /* } */
4309: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4310: /* k=kmax; l=lmax*10; */
4311: /* } */
4312: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4313: /* delts=delt; */
4314: /* } */
4315: /* } /\* End loop k *\/ */
4316: /* } */
4317: /* delti[theta]=delts; */
4318: /* return res; */
4319: /* } */
4320:
4321:
1.126 brouard 4322: /************** Inverse of matrix **************/
4323: void ludcmp(double **a, int n, int *indx, double *d)
4324: {
4325: int i,imax,j,k;
4326: double big,dum,sum,temp;
4327: double *vv;
4328:
4329: vv=vector(1,n);
4330: *d=1.0;
4331: for (i=1;i<=n;i++) {
4332: big=0.0;
4333: for (j=1;j<=n;j++)
4334: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4335: if (big == 0.0){
4336: printf(" Singular Hessian matrix at row %d:\n",i);
4337: for (j=1;j<=n;j++) {
4338: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4339: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4340: }
4341: fflush(ficlog);
4342: fclose(ficlog);
4343: nrerror("Singular matrix in routine ludcmp");
4344: }
1.126 brouard 4345: vv[i]=1.0/big;
4346: }
4347: for (j=1;j<=n;j++) {
4348: for (i=1;i<j;i++) {
4349: sum=a[i][j];
4350: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4351: a[i][j]=sum;
4352: }
4353: big=0.0;
4354: for (i=j;i<=n;i++) {
4355: sum=a[i][j];
4356: for (k=1;k<j;k++)
4357: sum -= a[i][k]*a[k][j];
4358: a[i][j]=sum;
4359: if ( (dum=vv[i]*fabs(sum)) >= big) {
4360: big=dum;
4361: imax=i;
4362: }
4363: }
4364: if (j != imax) {
4365: for (k=1;k<=n;k++) {
4366: dum=a[imax][k];
4367: a[imax][k]=a[j][k];
4368: a[j][k]=dum;
4369: }
4370: *d = -(*d);
4371: vv[imax]=vv[j];
4372: }
4373: indx[j]=imax;
4374: if (a[j][j] == 0.0) a[j][j]=TINY;
4375: if (j != n) {
4376: dum=1.0/(a[j][j]);
4377: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4378: }
4379: }
4380: free_vector(vv,1,n); /* Doesn't work */
4381: ;
4382: }
4383:
4384: void lubksb(double **a, int n, int *indx, double b[])
4385: {
4386: int i,ii=0,ip,j;
4387: double sum;
4388:
4389: for (i=1;i<=n;i++) {
4390: ip=indx[i];
4391: sum=b[ip];
4392: b[ip]=b[i];
4393: if (ii)
4394: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4395: else if (sum) ii=i;
4396: b[i]=sum;
4397: }
4398: for (i=n;i>=1;i--) {
4399: sum=b[i];
4400: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4401: b[i]=sum/a[i][i];
4402: }
4403: }
4404:
4405: void pstamp(FILE *fichier)
4406: {
1.196 brouard 4407: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4408: }
4409:
1.253 brouard 4410:
4411:
1.126 brouard 4412: /************ Frequencies ********************/
1.251 brouard 4413: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4414: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4415: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4416: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4417:
1.265 brouard 4418: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4419: int iind=0, iage=0;
4420: int mi; /* Effective wave */
4421: int first;
4422: double ***freq; /* Frequencies */
1.268 brouard 4423: 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 */
4424: 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 4425: double *meanq, *stdq, *idq;
1.226 brouard 4426: double **meanqt;
4427: double *pp, **prop, *posprop, *pospropt;
4428: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4429: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4430: double agebegin, ageend;
4431:
4432: pp=vector(1,nlstate);
1.251 brouard 4433: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4434: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4435: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4436: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4437: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4438: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4439: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4440: meanqt=matrix(1,lastpass,1,nqtveff);
4441: strcpy(fileresp,"P_");
4442: strcat(fileresp,fileresu);
4443: /*strcat(fileresphtm,fileresu);*/
4444: if((ficresp=fopen(fileresp,"w"))==NULL) {
4445: printf("Problem with prevalence resultfile: %s\n", fileresp);
4446: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4447: exit(0);
4448: }
1.240 brouard 4449:
1.226 brouard 4450: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4451: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4452: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4453: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4454: fflush(ficlog);
4455: exit(70);
4456: }
4457: else{
4458: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4459: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4460: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4461: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4462: }
1.237 brouard 4463: fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm);
1.240 brouard 4464:
1.226 brouard 4465: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4466: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4467: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4468: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4469: fflush(ficlog);
4470: exit(70);
1.240 brouard 4471: } else{
1.226 brouard 4472: fprintf(ficresphtmfr,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4473: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4474: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4475: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4476: }
1.240 brouard 4477: fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>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);
4478:
1.253 brouard 4479: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4480: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4481: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4482: j1=0;
1.126 brouard 4483:
1.227 brouard 4484: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4485: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4486: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4487:
4488:
1.226 brouard 4489: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4490: reference=low_education V1=0,V2=0
4491: med_educ V1=1 V2=0,
4492: high_educ V1=0 V2=1
4493: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4494: */
1.249 brouard 4495: dateintsum=0;
4496: k2cpt=0;
4497:
1.253 brouard 4498: if(cptcoveff == 0 )
1.265 brouard 4499: nl=1; /* Constant and age model only */
1.253 brouard 4500: else
4501: nl=2;
1.265 brouard 4502:
4503: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4504: /* Loop on nj=1 or 2 if dummy covariates j!=0
4505: * Loop on j1(1 to 2**cptcoveff) covariate combination
4506: * freq[s1][s2][iage] =0.
4507: * Loop on iind
4508: * ++freq[s1][s2][iage] weighted
4509: * end iind
4510: * if covariate and j!0
4511: * headers Variable on one line
4512: * endif cov j!=0
4513: * header of frequency table by age
4514: * Loop on age
4515: * pp[s1]+=freq[s1][s2][iage] weighted
4516: * pos+=freq[s1][s2][iage] weighted
4517: * Loop on s1 initial state
4518: * fprintf(ficresp
4519: * end s1
4520: * end age
4521: * if j!=0 computes starting values
4522: * end compute starting values
4523: * end j1
4524: * end nl
4525: */
1.253 brouard 4526: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4527: if(nj==1)
4528: j=0; /* First pass for the constant */
1.265 brouard 4529: else{
1.253 brouard 4530: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4531: }
1.251 brouard 4532: first=1;
1.265 brouard 4533: 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 4534: posproptt=0.;
4535: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4536: scanf("%d", i);*/
4537: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4538: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4539: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4540: freq[i][s2][m]=0;
1.251 brouard 4541:
4542: for (i=1; i<=nlstate; i++) {
1.240 brouard 4543: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4544: prop[i][m]=0;
4545: posprop[i]=0;
4546: pospropt[i]=0;
4547: }
1.283 brouard 4548: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4549: idq[z1]=0.;
4550: meanq[z1]=0.;
4551: stdq[z1]=0.;
1.283 brouard 4552: }
4553: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4554: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4555: /* meanqt[m][z1]=0.; */
4556: /* } */
4557: /* } */
1.251 brouard 4558: /* dateintsum=0; */
4559: /* k2cpt=0; */
4560:
1.265 brouard 4561: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4562: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4563: bool=1;
4564: if(j !=0){
4565: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4566: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4567: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4568: /* if(Tvaraff[z1] ==-20){ */
4569: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4570: /* }else if(Tvaraff[z1] ==-10){ */
4571: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4572: /* }else */
4573: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4574: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4575: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4576: /* 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",
4577: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4578: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4579: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4580: } /* Onlyf fixed */
4581: } /* end z1 */
4582: } /* cptcovn > 0 */
4583: } /* end any */
4584: }/* end j==0 */
1.265 brouard 4585: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4586: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4587: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4588: m=mw[mi][iind];
4589: if(j!=0){
4590: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4591: for (z1=1; z1<=cptcoveff; z1++) {
4592: if( Fixed[Tmodelind[z1]]==1){
4593: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4594: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4595: value is -1, we don't select. It differs from the
4596: constant and age model which counts them. */
4597: bool=0; /* not selected */
4598: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4599: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4600: bool=0;
4601: }
4602: }
4603: }
4604: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4605: } /* end j==0 */
4606: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4607: if(bool==1){ /*Selected */
1.251 brouard 4608: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4609: and mw[mi+1][iind]. dh depends on stepm. */
4610: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4611: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4612: if(m >=firstpass && m <=lastpass){
4613: k2=anint[m][iind]+(mint[m][iind]/12.);
4614: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4615: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4616: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4617: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4618: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4619: if (m<lastpass) {
4620: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4621: /* 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]); */
4622: if(s[m][iind]==-1)
4623: 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.));
4624: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
1.284 brouard 4625: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4626: idq[z1]=idq[z1]+weight[iind];
4627: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4628: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4629: }
1.251 brouard 4630: /* if((int)agev[m][iind] == 55) */
4631: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4632: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4633: 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 4634: }
1.251 brouard 4635: } /* end if between passes */
4636: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4637: dateintsum=dateintsum+k2; /* on all covariates ?*/
4638: k2cpt++;
4639: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4640: }
1.251 brouard 4641: }else{
4642: bool=1;
4643: }/* end bool 2 */
4644: } /* end m */
1.284 brouard 4645: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4646: /* idq[z1]=idq[z1]+weight[iind]; */
4647: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4648: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4649: /* } */
1.251 brouard 4650: } /* end bool */
4651: } /* end iind = 1 to imx */
4652: /* prop[s][age] is feeded for any initial and valid live state as well as
4653: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4654:
4655:
4656: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4657: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4658: pstamp(ficresp);
1.251 brouard 4659: if (cptcoveff>0 && j!=0){
1.265 brouard 4660: pstamp(ficresp);
1.251 brouard 4661: printf( "\n#********** Variable ");
4662: fprintf(ficresp, "\n#********** Variable ");
4663: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4664: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4665: fprintf(ficlog, "\n#********** Variable ");
4666: for (z1=1; z1<=cptcoveff; z1++){
4667: if(!FixedV[Tvaraff[z1]]){
4668: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4669: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4670: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4671: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4672: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4673: }else{
1.251 brouard 4674: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4675: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4676: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4677: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4678: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4679: }
4680: }
4681: printf( "**********\n#");
4682: fprintf(ficresp, "**********\n#");
4683: fprintf(ficresphtm, "**********</h3>\n");
4684: fprintf(ficresphtmfr, "**********</h3>\n");
4685: fprintf(ficlog, "**********\n");
4686: }
1.284 brouard 4687: /*
4688: Printing means of quantitative variables if any
4689: */
4690: for (z1=1; z1<= nqfveff; z1++) {
1.285 brouard 4691: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4692: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4693: if(weightopt==1){
4694: printf(" Weighted mean and standard deviation of");
4695: fprintf(ficlog," Weighted mean and standard deviation of");
4696: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4697: }
1.285 brouard 4698: printf(" fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
4699: fprintf(ficlog," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
4700: fprintf(ficresphtmfr," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)<p>\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
1.284 brouard 4701: }
4702: /* for (z1=1; z1<= nqtveff; z1++) { */
4703: /* for(m=1;m<=lastpass;m++){ */
4704: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4705: /* } */
4706: /* } */
1.283 brouard 4707:
1.251 brouard 4708: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4709: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4710: fprintf(ficresp, " Age");
4711: 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 4712: for(i=1; i<=nlstate;i++) {
1.265 brouard 4713: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4714: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4715: }
1.265 brouard 4716: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4717: fprintf(ficresphtm, "\n");
4718:
4719: /* Header of frequency table by age */
4720: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4721: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4722: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4723: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4724: if(s2!=0 && m!=0)
4725: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4726: }
1.226 brouard 4727: }
1.251 brouard 4728: fprintf(ficresphtmfr, "\n");
4729:
4730: /* For each age */
4731: for(iage=iagemin; iage <= iagemax+3; iage++){
4732: fprintf(ficresphtm,"<tr>");
4733: if(iage==iagemax+1){
4734: fprintf(ficlog,"1");
4735: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4736: }else if(iage==iagemax+2){
4737: fprintf(ficlog,"0");
4738: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4739: }else if(iage==iagemax+3){
4740: fprintf(ficlog,"Total");
4741: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4742: }else{
1.240 brouard 4743: if(first==1){
1.251 brouard 4744: first=0;
4745: printf("See log file for details...\n");
4746: }
4747: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4748: fprintf(ficlog,"Age %d", iage);
4749: }
1.265 brouard 4750: for(s1=1; s1 <=nlstate ; s1++){
4751: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4752: pp[s1] += freq[s1][m][iage];
1.251 brouard 4753: }
1.265 brouard 4754: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4755: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4756: pos += freq[s1][m][iage];
4757: if(pp[s1]>=1.e-10){
1.251 brouard 4758: if(first==1){
1.265 brouard 4759: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4760: }
1.265 brouard 4761: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4762: }else{
4763: if(first==1)
1.265 brouard 4764: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4765: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4766: }
4767: }
4768:
1.265 brouard 4769: for(s1=1; s1 <=nlstate ; s1++){
4770: /* posprop[s1]=0; */
4771: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4772: pp[s1] += freq[s1][m][iage];
4773: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4774:
4775: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4776: pos += pp[s1]; /* pos is the total number of transitions until this age */
4777: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4778: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4779: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4780: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4781: }
4782:
4783: /* Writing ficresp */
4784: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4785: if( iage <= iagemax){
4786: fprintf(ficresp," %d",iage);
4787: }
4788: }else if( nj==2){
4789: if( iage <= iagemax){
4790: fprintf(ficresp," %d",iage);
4791: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4792: }
1.240 brouard 4793: }
1.265 brouard 4794: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4795: if(pos>=1.e-5){
1.251 brouard 4796: if(first==1)
1.265 brouard 4797: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4798: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4799: }else{
4800: if(first==1)
1.265 brouard 4801: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4802: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4803: }
4804: if( iage <= iagemax){
4805: if(pos>=1.e-5){
1.265 brouard 4806: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4807: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4808: }else if( nj==2){
4809: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4810: }
4811: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4812: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4813: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4814: } else{
4815: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4816: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4817: }
1.240 brouard 4818: }
1.265 brouard 4819: pospropt[s1] +=posprop[s1];
4820: } /* end loop s1 */
1.251 brouard 4821: /* pospropt=0.; */
1.265 brouard 4822: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4823: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4824: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4825: if(first==1){
1.265 brouard 4826: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4827: }
1.265 brouard 4828: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4829: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4830: }
1.265 brouard 4831: if(s1!=0 && m!=0)
4832: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4833: }
1.265 brouard 4834: } /* end loop s1 */
1.251 brouard 4835: posproptt=0.;
1.265 brouard 4836: for(s1=1; s1 <=nlstate; s1++){
4837: posproptt += pospropt[s1];
1.251 brouard 4838: }
4839: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4840: fprintf(ficresphtm,"</tr>\n");
4841: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4842: if(iage <= iagemax)
4843: fprintf(ficresp,"\n");
1.240 brouard 4844: }
1.251 brouard 4845: if(first==1)
4846: printf("Others in log...\n");
4847: fprintf(ficlog,"\n");
4848: } /* end loop age iage */
1.265 brouard 4849:
1.251 brouard 4850: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4851: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4852: if(posproptt < 1.e-5){
1.265 brouard 4853: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4854: }else{
1.265 brouard 4855: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4856: }
1.226 brouard 4857: }
1.251 brouard 4858: fprintf(ficresphtm,"</tr>\n");
4859: fprintf(ficresphtm,"</table>\n");
4860: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4861: if(posproptt < 1.e-5){
1.251 brouard 4862: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4863: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4864: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4865: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4866: invalidvarcomb[j1]=1;
1.226 brouard 4867: }else{
1.251 brouard 4868: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4869: invalidvarcomb[j1]=0;
1.226 brouard 4870: }
1.251 brouard 4871: fprintf(ficresphtmfr,"</table>\n");
4872: fprintf(ficlog,"\n");
4873: if(j!=0){
4874: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4875: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4876: for(k=1; k <=(nlstate+ndeath); k++){
4877: if (k != i) {
1.265 brouard 4878: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4879: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4880: if(j1==1){ /* All dummy covariates to zero */
4881: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4882: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4883: printf("%d%d ",i,k);
4884: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4885: 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]));
4886: 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]));
4887: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4888: }
1.253 brouard 4889: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4890: for(iage=iagemin; iage <= iagemax+3; iage++){
4891: x[iage]= (double)iage;
4892: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4893: /* 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 4894: }
1.268 brouard 4895: /* Some are not finite, but linreg will ignore these ages */
4896: no=0;
1.253 brouard 4897: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4898: pstart[s1]=b;
4899: pstart[s1-1]=a;
1.252 brouard 4900: }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 */
4901: 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]);
4902: 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 4903: 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 4904: printf("%d%d ",i,k);
4905: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4906: 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 4907: }else{ /* Other cases, like quantitative fixed or varying covariates */
4908: ;
4909: }
4910: /* printf("%12.7f )", param[i][jj][k]); */
4911: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4912: s1++;
1.251 brouard 4913: } /* end jj */
4914: } /* end k!= i */
4915: } /* end k */
1.265 brouard 4916: } /* end i, s1 */
1.251 brouard 4917: } /* end j !=0 */
4918: } /* end selected combination of covariate j1 */
4919: if(j==0){ /* We can estimate starting values from the occurences in each case */
4920: printf("#Freqsummary: Starting values for the constants:\n");
4921: fprintf(ficlog,"\n");
1.265 brouard 4922: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4923: for(k=1; k <=(nlstate+ndeath); k++){
4924: if (k != i) {
4925: printf("%d%d ",i,k);
4926: fprintf(ficlog,"%d%d ",i,k);
4927: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4928: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4929: if(jj==1){ /* Age has to be done */
1.265 brouard 4930: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4931: 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]));
4932: 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 4933: }
4934: /* printf("%12.7f )", param[i][jj][k]); */
4935: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4936: s1++;
1.250 brouard 4937: }
1.251 brouard 4938: printf("\n");
4939: fprintf(ficlog,"\n");
1.250 brouard 4940: }
4941: }
1.284 brouard 4942: } /* end of state i */
1.251 brouard 4943: printf("#Freqsummary\n");
4944: fprintf(ficlog,"\n");
1.265 brouard 4945: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4946: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4947: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4948: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4949: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4950: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4951: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4952: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4953: /* } */
4954: }
1.265 brouard 4955: } /* end loop s1 */
1.251 brouard 4956:
4957: printf("\n");
4958: fprintf(ficlog,"\n");
4959: } /* end j=0 */
1.249 brouard 4960: } /* end j */
1.252 brouard 4961:
1.253 brouard 4962: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4963: for(i=1, jk=1; i <=nlstate; i++){
4964: for(j=1; j <=nlstate+ndeath; j++){
4965: if(j!=i){
4966: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4967: printf("%1d%1d",i,j);
4968: fprintf(ficparo,"%1d%1d",i,j);
4969: for(k=1; k<=ncovmodel;k++){
4970: /* printf(" %lf",param[i][j][k]); */
4971: /* fprintf(ficparo," %lf",param[i][j][k]); */
4972: p[jk]=pstart[jk];
4973: printf(" %f ",pstart[jk]);
4974: fprintf(ficparo," %f ",pstart[jk]);
4975: jk++;
4976: }
4977: printf("\n");
4978: fprintf(ficparo,"\n");
4979: }
4980: }
4981: }
4982: } /* end mle=-2 */
1.226 brouard 4983: dateintmean=dateintsum/k2cpt;
1.296 ! brouard 4984: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 4985:
1.226 brouard 4986: fclose(ficresp);
4987: fclose(ficresphtm);
4988: fclose(ficresphtmfr);
1.283 brouard 4989: free_vector(idq,1,nqfveff);
1.226 brouard 4990: free_vector(meanq,1,nqfveff);
1.284 brouard 4991: free_vector(stdq,1,nqfveff);
1.226 brouard 4992: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4993: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4994: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4995: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4996: free_vector(pospropt,1,nlstate);
4997: free_vector(posprop,1,nlstate);
1.251 brouard 4998: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4999: free_vector(pp,1,nlstate);
5000: /* End of freqsummary */
5001: }
1.126 brouard 5002:
1.268 brouard 5003: /* Simple linear regression */
5004: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5005:
5006: /* y=a+bx regression */
5007: double sumx = 0.0; /* sum of x */
5008: double sumx2 = 0.0; /* sum of x**2 */
5009: double sumxy = 0.0; /* sum of x * y */
5010: double sumy = 0.0; /* sum of y */
5011: double sumy2 = 0.0; /* sum of y**2 */
5012: double sume2 = 0.0; /* sum of square or residuals */
5013: double yhat;
5014:
5015: double denom=0;
5016: int i;
5017: int ne=*no;
5018:
5019: for ( i=ifi, ne=0;i<=ila;i++) {
5020: if(!isfinite(x[i]) || !isfinite(y[i])){
5021: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5022: continue;
5023: }
5024: ne=ne+1;
5025: sumx += x[i];
5026: sumx2 += x[i]*x[i];
5027: sumxy += x[i] * y[i];
5028: sumy += y[i];
5029: sumy2 += y[i]*y[i];
5030: denom = (ne * sumx2 - sumx*sumx);
5031: /* 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); */
5032: }
5033:
5034: denom = (ne * sumx2 - sumx*sumx);
5035: if (denom == 0) {
5036: // vertical, slope m is infinity
5037: *b = INFINITY;
5038: *a = 0;
5039: if (r) *r = 0;
5040: return 1;
5041: }
5042:
5043: *b = (ne * sumxy - sumx * sumy) / denom;
5044: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5045: if (r!=NULL) {
5046: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5047: sqrt((sumx2 - sumx*sumx/ne) *
5048: (sumy2 - sumy*sumy/ne));
5049: }
5050: *no=ne;
5051: for ( i=ifi, ne=0;i<=ila;i++) {
5052: if(!isfinite(x[i]) || !isfinite(y[i])){
5053: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5054: continue;
5055: }
5056: ne=ne+1;
5057: yhat = y[i] - *a -*b* x[i];
5058: sume2 += yhat * yhat ;
5059:
5060: denom = (ne * sumx2 - sumx*sumx);
5061: /* 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); */
5062: }
5063: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5064: *sa= *sb * sqrt(sumx2/ne);
5065:
5066: return 0;
5067: }
5068:
1.126 brouard 5069: /************ Prevalence ********************/
1.227 brouard 5070: 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)
5071: {
5072: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5073: in each health status at the date of interview (if between dateprev1 and dateprev2).
5074: We still use firstpass and lastpass as another selection.
5075: */
1.126 brouard 5076:
1.227 brouard 5077: int i, m, jk, j1, bool, z1,j, iv;
5078: int mi; /* Effective wave */
5079: int iage;
5080: double agebegin, ageend;
5081:
5082: double **prop;
5083: double posprop;
5084: double y2; /* in fractional years */
5085: int iagemin, iagemax;
5086: int first; /** to stop verbosity which is redirected to log file */
5087:
5088: iagemin= (int) agemin;
5089: iagemax= (int) agemax;
5090: /*pp=vector(1,nlstate);*/
1.251 brouard 5091: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5092: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5093: j1=0;
1.222 brouard 5094:
1.227 brouard 5095: /*j=cptcoveff;*/
5096: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5097:
1.288 brouard 5098: first=0;
1.227 brouard 5099: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5100: for (i=1; i<=nlstate; i++)
1.251 brouard 5101: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5102: prop[i][iage]=0.0;
5103: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5104: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5105: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5106:
5107: for (i=1; i<=imx; i++) { /* Each individual */
5108: bool=1;
5109: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5110: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5111: m=mw[mi][i];
5112: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5113: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5114: for (z1=1; z1<=cptcoveff; z1++){
5115: if( Fixed[Tmodelind[z1]]==1){
5116: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5117: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5118: bool=0;
5119: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5120: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5121: bool=0;
5122: }
5123: }
5124: if(bool==1){ /* Otherwise we skip that wave/person */
5125: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5126: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5127: if(m >=firstpass && m <=lastpass){
5128: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5129: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5130: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5131: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5132: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5133: 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);
5134: exit(1);
5135: }
5136: if (s[m][i]>0 && s[m][i]<=nlstate) {
5137: /*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]]);*/
5138: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5139: prop[s[m][i]][iagemax+3] += weight[i];
5140: } /* end valid statuses */
5141: } /* end selection of dates */
5142: } /* end selection of waves */
5143: } /* end bool */
5144: } /* end wave */
5145: } /* end individual */
5146: for(i=iagemin; i <= iagemax+3; i++){
5147: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5148: posprop += prop[jk][i];
5149: }
5150:
5151: for(jk=1; jk <=nlstate ; jk++){
5152: if( i <= iagemax){
5153: if(posprop>=1.e-5){
5154: probs[i][jk][j1]= prop[jk][i]/posprop;
5155: } else{
1.288 brouard 5156: if(!first){
5157: first=1;
1.266 brouard 5158: 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]);
5159: }else{
1.288 brouard 5160: 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 5161: }
5162: }
5163: }
5164: }/* end jk */
5165: }/* end i */
1.222 brouard 5166: /*} *//* end i1 */
1.227 brouard 5167: } /* end j1 */
1.222 brouard 5168:
1.227 brouard 5169: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5170: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5171: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5172: } /* End of prevalence */
1.126 brouard 5173:
5174: /************* Waves Concatenation ***************/
5175:
5176: 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)
5177: {
5178: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5179: Death is a valid wave (if date is known).
5180: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5181: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5182: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5183: */
1.126 brouard 5184:
1.224 brouard 5185: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5186: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5187: double sum=0., jmean=0.;*/
1.224 brouard 5188: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5189: int j, k=0,jk, ju, jl;
5190: double sum=0.;
5191: first=0;
1.214 brouard 5192: firstwo=0;
1.217 brouard 5193: firsthree=0;
1.218 brouard 5194: firstfour=0;
1.164 brouard 5195: jmin=100000;
1.126 brouard 5196: jmax=-1;
5197: jmean=0.;
1.224 brouard 5198:
5199: /* Treating live states */
1.214 brouard 5200: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5201: mi=0; /* First valid wave */
1.227 brouard 5202: mli=0; /* Last valid wave */
1.126 brouard 5203: m=firstpass;
1.214 brouard 5204: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5205: 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 */
5206: mli=m-1;/* mw[++mi][i]=m-1; */
5207: }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 */
5208: mw[++mi][i]=m;
5209: mli=m;
1.224 brouard 5210: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5211: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5212: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5213: }
1.227 brouard 5214: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5215: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5216: break;
1.224 brouard 5217: #else
1.227 brouard 5218: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5219: if(firsthree == 0){
1.262 brouard 5220: 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 5221: firsthree=1;
5222: }
1.262 brouard 5223: 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);
1.227 brouard 5224: mw[++mi][i]=m;
5225: mli=m;
5226: }
5227: if(s[m][i]==-2){ /* Vital status is really unknown */
5228: nbwarn++;
5229: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5230: 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);
5231: 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);
5232: }
5233: break;
5234: }
5235: break;
1.224 brouard 5236: #endif
1.227 brouard 5237: }/* End m >= lastpass */
1.126 brouard 5238: }/* end while */
1.224 brouard 5239:
1.227 brouard 5240: /* 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 5241: /* After last pass */
1.224 brouard 5242: /* Treating death states */
1.214 brouard 5243: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5244: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5245: /* } */
1.126 brouard 5246: mi++; /* Death is another wave */
5247: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5248: /* Only death is a correct wave */
1.126 brouard 5249: mw[mi][i]=m;
1.257 brouard 5250: } /* else not in a death state */
1.224 brouard 5251: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5252: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5253: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5254: if((andc[i]+moisdc[i]/12.) <=(anint[m][i]+mint[m][i]/12.)){ /* death occured before last wave and status should have been death instead of -1 */
5255: nbwarn++;
5256: if(firstfiv==0){
5257: printf("Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d interviewed at %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 );
5258: firstfiv=1;
5259: }else{
5260: fprintf(ficlog,"Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d interviewed at %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 );
5261: }
5262: }else{ /* Death occured afer last wave potential bias */
5263: nberr++;
5264: if(firstwo==0){
1.257 brouard 5265: printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%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. Please add a new fictive wave at the date of last vital status scan, with a dead status or alive but unknown state status (-1). 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], i,m );
1.227 brouard 5266: firstwo=1;
5267: }
1.257 brouard 5268: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%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. Please add a new fictive wave at the date of last vital status scan, with a dead status or alive but unknown state status (-1). See documentation\n\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m );
1.227 brouard 5269: }
1.257 brouard 5270: }else{ /* if date of interview is unknown */
1.227 brouard 5271: /* death is known but not confirmed by death status at any wave */
5272: if(firstfour==0){
5273: 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. 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], i,m );
5274: firstfour=1;
5275: }
5276: 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. 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], i,m );
1.214 brouard 5277: }
1.224 brouard 5278: } /* end if date of death is known */
5279: #endif
5280: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5281: /* wav[i]=mw[mi][i]; */
1.126 brouard 5282: if(mi==0){
5283: nbwarn++;
5284: if(first==0){
1.227 brouard 5285: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5286: first=1;
1.126 brouard 5287: }
5288: if(first==1){
1.227 brouard 5289: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5290: }
5291: } /* end mi==0 */
5292: } /* End individuals */
1.214 brouard 5293: /* wav and mw are no more changed */
1.223 brouard 5294:
1.214 brouard 5295:
1.126 brouard 5296: for(i=1; i<=imx; i++){
5297: for(mi=1; mi<wav[i];mi++){
5298: if (stepm <=0)
1.227 brouard 5299: dh[mi][i]=1;
1.126 brouard 5300: else{
1.260 brouard 5301: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5302: if (agedc[i] < 2*AGESUP) {
5303: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5304: if(j==0) j=1; /* Survives at least one month after exam */
5305: else if(j<0){
5306: nberr++;
5307: 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]);
5308: j=1; /* Temporary Dangerous patch */
5309: 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);
5310: 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]);
5311: 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);
5312: }
5313: k=k+1;
5314: if (j >= jmax){
5315: jmax=j;
5316: ijmax=i;
5317: }
5318: if (j <= jmin){
5319: jmin=j;
5320: ijmin=i;
5321: }
5322: sum=sum+j;
5323: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5324: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5325: }
5326: }
5327: else{
5328: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5329: /* 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 5330:
1.227 brouard 5331: k=k+1;
5332: if (j >= jmax) {
5333: jmax=j;
5334: ijmax=i;
5335: }
5336: else if (j <= jmin){
5337: jmin=j;
5338: ijmin=i;
5339: }
5340: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5341: /*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]);*/
5342: if(j<0){
5343: nberr++;
5344: 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]);
5345: 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]);
5346: }
5347: sum=sum+j;
5348: }
5349: jk= j/stepm;
5350: jl= j -jk*stepm;
5351: ju= j -(jk+1)*stepm;
5352: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5353: if(jl==0){
5354: dh[mi][i]=jk;
5355: bh[mi][i]=0;
5356: }else{ /* We want a negative bias in order to only have interpolation ie
5357: * to avoid the price of an extra matrix product in likelihood */
5358: dh[mi][i]=jk+1;
5359: bh[mi][i]=ju;
5360: }
5361: }else{
5362: if(jl <= -ju){
5363: dh[mi][i]=jk;
5364: bh[mi][i]=jl; /* bias is positive if real duration
5365: * is higher than the multiple of stepm and negative otherwise.
5366: */
5367: }
5368: else{
5369: dh[mi][i]=jk+1;
5370: bh[mi][i]=ju;
5371: }
5372: if(dh[mi][i]==0){
5373: dh[mi][i]=1; /* At least one step */
5374: bh[mi][i]=ju; /* At least one step */
5375: /* 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);*/
5376: }
5377: } /* end if mle */
1.126 brouard 5378: }
5379: } /* end wave */
5380: }
5381: jmean=sum/k;
5382: 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 5383: 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 5384: }
1.126 brouard 5385:
5386: /*********** Tricode ****************************/
1.220 brouard 5387: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5388: {
5389: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5390: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5391: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5392: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5393: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5394: */
1.130 brouard 5395:
1.242 brouard 5396: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5397: int modmaxcovj=0; /* Modality max of covariates j */
5398: int cptcode=0; /* Modality max of covariates j */
5399: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5400:
5401:
1.242 brouard 5402: /* cptcoveff=0; */
5403: /* *cptcov=0; */
1.126 brouard 5404:
1.242 brouard 5405: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5406: for (k=1; k <= maxncov; k++)
5407: for(j=1; j<=2; j++)
5408: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5409:
1.242 brouard 5410: /* Loop on covariates without age and products and no quantitative variable */
5411: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5412: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5413: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5414: switch(Fixed[k]) {
5415: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5416: 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*/
5417: ij=(int)(covar[Tvar[k]][i]);
5418: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5419: * If product of Vn*Vm, still boolean *:
5420: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5421: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5422: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5423: modality of the nth covariate of individual i. */
5424: if (ij > modmaxcovj)
5425: modmaxcovj=ij;
5426: else if (ij < modmincovj)
5427: modmincovj=ij;
1.287 brouard 5428: if (ij <0 || ij >1 ){
5429: printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5430: fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5431: }
5432: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5433: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5434: exit(1);
5435: }else
5436: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5437: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5438: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5439: /* getting the maximum value of the modality of the covariate
5440: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5441: female ies 1, then modmaxcovj=1.
5442: */
5443: } /* end for loop on individuals i */
5444: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5445: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5446: cptcode=modmaxcovj;
5447: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5448: /*for (i=0; i<=cptcode; i++) {*/
5449: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5450: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5451: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5452: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5453: if( j != -1){
5454: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5455: covariate for which somebody answered excluding
5456: undefined. Usually 2: 0 and 1. */
5457: }
5458: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5459: covariate for which somebody answered including
5460: undefined. Usually 3: -1, 0 and 1. */
5461: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5462: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5463: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5464:
1.242 brouard 5465: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5466: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5467: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5468: /* modmincovj=3; modmaxcovj = 7; */
5469: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5470: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5471: /* defining two dummy variables: variables V1_1 and V1_2.*/
5472: /* nbcode[Tvar[j]][ij]=k; */
5473: /* nbcode[Tvar[j]][1]=0; */
5474: /* nbcode[Tvar[j]][2]=1; */
5475: /* nbcode[Tvar[j]][3]=2; */
5476: /* To be continued (not working yet). */
5477: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5478:
5479: /* 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*/
5480: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5481: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5482: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5483: /*, could be restored in the future */
5484: 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 5485: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5486: break;
5487: }
5488: ij++;
1.287 brouard 5489: 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 5490: cptcode = ij; /* New max modality for covar j */
5491: } /* end of loop on modality i=-1 to 1 or more */
5492: break;
5493: case 1: /* Testing on varying covariate, could be simple and
5494: * should look at waves or product of fixed *
5495: * varying. No time to test -1, assuming 0 and 1 only */
5496: ij=0;
5497: for(i=0; i<=1;i++){
5498: nbcode[Tvar[k]][++ij]=i;
5499: }
5500: break;
5501: default:
5502: break;
5503: } /* end switch */
5504: } /* end dummy test */
1.287 brouard 5505: } /* 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 5506:
5507: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5508: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5509: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5510: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5511: 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 */
5512: 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 */
5513: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5514: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5515:
5516: ij=0;
5517: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5518: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5519: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5520: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5521: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5522: /* If product not in single variable we don't print results */
5523: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5524: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5525: 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*/
5526: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5527: 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 */
5528: if(Fixed[k]!=0)
5529: anyvaryingduminmodel=1;
5530: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5531: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5532: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5533: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5534: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5535: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5536: }
5537: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5538: /* ij--; */
5539: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5540: *cptcov=ij; /*Number of total real effective covariates: effective
5541: * because they can be excluded from the model and real
5542: * if in the model but excluded because missing values, but how to get k from ij?*/
5543: for(j=ij+1; j<= cptcovt; j++){
5544: Tvaraff[j]=0;
5545: Tmodelind[j]=0;
5546: }
5547: for(j=ntveff+1; j<= cptcovt; j++){
5548: TmodelInvind[j]=0;
5549: }
5550: /* To be sorted */
5551: ;
5552: }
1.126 brouard 5553:
1.145 brouard 5554:
1.126 brouard 5555: /*********** Health Expectancies ****************/
5556:
1.235 brouard 5557: 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 5558:
5559: {
5560: /* Health expectancies, no variances */
1.164 brouard 5561: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5562: int nhstepma, nstepma; /* Decreasing with age */
5563: double age, agelim, hf;
5564: double ***p3mat;
5565: double eip;
5566:
1.238 brouard 5567: /* pstamp(ficreseij); */
1.126 brouard 5568: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5569: fprintf(ficreseij,"# Age");
5570: for(i=1; i<=nlstate;i++){
5571: for(j=1; j<=nlstate;j++){
5572: fprintf(ficreseij," e%1d%1d ",i,j);
5573: }
5574: fprintf(ficreseij," e%1d. ",i);
5575: }
5576: fprintf(ficreseij,"\n");
5577:
5578:
5579: if(estepm < stepm){
5580: printf ("Problem %d lower than %d\n",estepm, stepm);
5581: }
5582: else hstepm=estepm;
5583: /* We compute the life expectancy from trapezoids spaced every estepm months
5584: * This is mainly to measure the difference between two models: for example
5585: * if stepm=24 months pijx are given only every 2 years and by summing them
5586: * we are calculating an estimate of the Life Expectancy assuming a linear
5587: * progression in between and thus overestimating or underestimating according
5588: * to the curvature of the survival function. If, for the same date, we
5589: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5590: * to compare the new estimate of Life expectancy with the same linear
5591: * hypothesis. A more precise result, taking into account a more precise
5592: * curvature will be obtained if estepm is as small as stepm. */
5593:
5594: /* For example we decided to compute the life expectancy with the smallest unit */
5595: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5596: nhstepm is the number of hstepm from age to agelim
5597: nstepm is the number of stepm from age to agelin.
1.270 brouard 5598: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5599: and note for a fixed period like estepm months */
5600: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5601: survival function given by stepm (the optimization length). Unfortunately it
5602: means that if the survival funtion is printed only each two years of age and if
5603: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5604: results. So we changed our mind and took the option of the best precision.
5605: */
5606: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5607:
5608: agelim=AGESUP;
5609: /* If stepm=6 months */
5610: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5611: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5612:
5613: /* nhstepm age range expressed in number of stepm */
5614: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5615: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5616: /* if (stepm >= YEARM) hstepm=1;*/
5617: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5618: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5619:
5620: for (age=bage; age<=fage; age ++){
5621: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5622: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5623: /* if (stepm >= YEARM) hstepm=1;*/
5624: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5625:
5626: /* If stepm=6 months */
5627: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5628: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5629:
1.235 brouard 5630: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5631:
5632: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5633:
5634: printf("%d|",(int)age);fflush(stdout);
5635: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5636:
5637: /* Computing expectancies */
5638: for(i=1; i<=nlstate;i++)
5639: for(j=1; j<=nlstate;j++)
5640: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5641: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5642:
5643: /* 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]);*/
5644:
5645: }
5646:
5647: fprintf(ficreseij,"%3.0f",age );
5648: for(i=1; i<=nlstate;i++){
5649: eip=0;
5650: for(j=1; j<=nlstate;j++){
5651: eip +=eij[i][j][(int)age];
5652: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5653: }
5654: fprintf(ficreseij,"%9.4f", eip );
5655: }
5656: fprintf(ficreseij,"\n");
5657:
5658: }
5659: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5660: printf("\n");
5661: fprintf(ficlog,"\n");
5662:
5663: }
5664:
1.235 brouard 5665: 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 5666:
5667: {
5668: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5669: to initial status i, ei. .
1.126 brouard 5670: */
5671: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5672: int nhstepma, nstepma; /* Decreasing with age */
5673: double age, agelim, hf;
5674: double ***p3matp, ***p3matm, ***varhe;
5675: double **dnewm,**doldm;
5676: double *xp, *xm;
5677: double **gp, **gm;
5678: double ***gradg, ***trgradg;
5679: int theta;
5680:
5681: double eip, vip;
5682:
5683: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5684: xp=vector(1,npar);
5685: xm=vector(1,npar);
5686: dnewm=matrix(1,nlstate*nlstate,1,npar);
5687: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5688:
5689: pstamp(ficresstdeij);
5690: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5691: fprintf(ficresstdeij,"# Age");
5692: for(i=1; i<=nlstate;i++){
5693: for(j=1; j<=nlstate;j++)
5694: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5695: fprintf(ficresstdeij," e%1d. ",i);
5696: }
5697: fprintf(ficresstdeij,"\n");
5698:
5699: pstamp(ficrescveij);
5700: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5701: fprintf(ficrescveij,"# Age");
5702: for(i=1; i<=nlstate;i++)
5703: for(j=1; j<=nlstate;j++){
5704: cptj= (j-1)*nlstate+i;
5705: for(i2=1; i2<=nlstate;i2++)
5706: for(j2=1; j2<=nlstate;j2++){
5707: cptj2= (j2-1)*nlstate+i2;
5708: if(cptj2 <= cptj)
5709: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5710: }
5711: }
5712: fprintf(ficrescveij,"\n");
5713:
5714: if(estepm < stepm){
5715: printf ("Problem %d lower than %d\n",estepm, stepm);
5716: }
5717: else hstepm=estepm;
5718: /* We compute the life expectancy from trapezoids spaced every estepm months
5719: * This is mainly to measure the difference between two models: for example
5720: * if stepm=24 months pijx are given only every 2 years and by summing them
5721: * we are calculating an estimate of the Life Expectancy assuming a linear
5722: * progression in between and thus overestimating or underestimating according
5723: * to the curvature of the survival function. If, for the same date, we
5724: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5725: * to compare the new estimate of Life expectancy with the same linear
5726: * hypothesis. A more precise result, taking into account a more precise
5727: * curvature will be obtained if estepm is as small as stepm. */
5728:
5729: /* For example we decided to compute the life expectancy with the smallest unit */
5730: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5731: nhstepm is the number of hstepm from age to agelim
5732: nstepm is the number of stepm from age to agelin.
5733: Look at hpijx to understand the reason of that which relies in memory size
5734: and note for a fixed period like estepm months */
5735: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5736: survival function given by stepm (the optimization length). Unfortunately it
5737: means that if the survival funtion is printed only each two years of age and if
5738: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5739: results. So we changed our mind and took the option of the best precision.
5740: */
5741: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5742:
5743: /* If stepm=6 months */
5744: /* nhstepm age range expressed in number of stepm */
5745: agelim=AGESUP;
5746: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5747: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5748: /* if (stepm >= YEARM) hstepm=1;*/
5749: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5750:
5751: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5752: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5753: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5754: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5755: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5756: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5757:
5758: for (age=bage; age<=fage; age ++){
5759: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5760: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5761: /* if (stepm >= YEARM) hstepm=1;*/
5762: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5763:
1.126 brouard 5764: /* If stepm=6 months */
5765: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5766: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5767:
5768: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5769:
1.126 brouard 5770: /* Computing Variances of health expectancies */
5771: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5772: decrease memory allocation */
5773: for(theta=1; theta <=npar; theta++){
5774: for(i=1; i<=npar; i++){
1.222 brouard 5775: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5776: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5777: }
1.235 brouard 5778: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5779: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5780:
1.126 brouard 5781: for(j=1; j<= nlstate; j++){
1.222 brouard 5782: for(i=1; i<=nlstate; i++){
5783: for(h=0; h<=nhstepm-1; h++){
5784: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5785: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5786: }
5787: }
1.126 brouard 5788: }
1.218 brouard 5789:
1.126 brouard 5790: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5791: for(h=0; h<=nhstepm-1; h++){
5792: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5793: }
1.126 brouard 5794: }/* End theta */
5795:
5796:
5797: for(h=0; h<=nhstepm-1; h++)
5798: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5799: for(theta=1; theta <=npar; theta++)
5800: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5801:
1.218 brouard 5802:
1.222 brouard 5803: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5804: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5805: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5806:
1.222 brouard 5807: printf("%d|",(int)age);fflush(stdout);
5808: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5809: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5810: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5811: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5812: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5813: for(ij=1;ij<=nlstate*nlstate;ij++)
5814: for(ji=1;ji<=nlstate*nlstate;ji++)
5815: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5816: }
5817: }
1.218 brouard 5818:
1.126 brouard 5819: /* Computing expectancies */
1.235 brouard 5820: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5821: for(i=1; i<=nlstate;i++)
5822: for(j=1; j<=nlstate;j++)
1.222 brouard 5823: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5824: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5825:
1.222 brouard 5826: /* 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 5827:
1.222 brouard 5828: }
1.269 brouard 5829:
5830: /* Standard deviation of expectancies ij */
1.126 brouard 5831: fprintf(ficresstdeij,"%3.0f",age );
5832: for(i=1; i<=nlstate;i++){
5833: eip=0.;
5834: vip=0.;
5835: for(j=1; j<=nlstate;j++){
1.222 brouard 5836: eip += eij[i][j][(int)age];
5837: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5838: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5839: 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 5840: }
5841: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5842: }
5843: fprintf(ficresstdeij,"\n");
1.218 brouard 5844:
1.269 brouard 5845: /* Variance of expectancies ij */
1.126 brouard 5846: fprintf(ficrescveij,"%3.0f",age );
5847: for(i=1; i<=nlstate;i++)
5848: for(j=1; j<=nlstate;j++){
1.222 brouard 5849: cptj= (j-1)*nlstate+i;
5850: for(i2=1; i2<=nlstate;i2++)
5851: for(j2=1; j2<=nlstate;j2++){
5852: cptj2= (j2-1)*nlstate+i2;
5853: if(cptj2 <= cptj)
5854: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5855: }
1.126 brouard 5856: }
5857: fprintf(ficrescveij,"\n");
1.218 brouard 5858:
1.126 brouard 5859: }
5860: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5861: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5862: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5863: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5864: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5865: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5866: printf("\n");
5867: fprintf(ficlog,"\n");
1.218 brouard 5868:
1.126 brouard 5869: free_vector(xm,1,npar);
5870: free_vector(xp,1,npar);
5871: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5872: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5873: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5874: }
1.218 brouard 5875:
1.126 brouard 5876: /************ Variance ******************/
1.235 brouard 5877: 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 5878: {
1.279 brouard 5879: /** Variance of health expectancies
5880: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5881: * double **newm;
5882: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5883: */
1.218 brouard 5884:
5885: /* int movingaverage(); */
5886: double **dnewm,**doldm;
5887: double **dnewmp,**doldmp;
5888: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 5889: int first=0;
1.218 brouard 5890: int k;
5891: double *xp;
1.279 brouard 5892: double **gp, **gm; /**< for var eij */
5893: double ***gradg, ***trgradg; /**< for var eij */
5894: double **gradgp, **trgradgp; /**< for var p point j */
5895: double *gpp, *gmp; /**< for var p point j */
5896: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5897: double ***p3mat;
5898: double age,agelim, hf;
5899: /* double ***mobaverage; */
5900: int theta;
5901: char digit[4];
5902: char digitp[25];
5903:
5904: char fileresprobmorprev[FILENAMELENGTH];
5905:
5906: if(popbased==1){
5907: if(mobilav!=0)
5908: strcpy(digitp,"-POPULBASED-MOBILAV_");
5909: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5910: }
5911: else
5912: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5913:
1.218 brouard 5914: /* if (mobilav!=0) { */
5915: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5916: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5917: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5918: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5919: /* } */
5920: /* } */
5921:
5922: strcpy(fileresprobmorprev,"PRMORPREV-");
5923: sprintf(digit,"%-d",ij);
5924: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5925: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5926: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5927: strcat(fileresprobmorprev,fileresu);
5928: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5929: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5930: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5931: }
5932: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5933: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5934: pstamp(ficresprobmorprev);
5935: 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 5936: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5937: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5938: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5939: }
5940: for(j=1;j<=cptcoveff;j++)
5941: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5942: fprintf(ficresprobmorprev,"\n");
5943:
1.218 brouard 5944: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5945: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5946: fprintf(ficresprobmorprev," p.%-d SE",j);
5947: for(i=1; i<=nlstate;i++)
5948: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5949: }
5950: fprintf(ficresprobmorprev,"\n");
5951:
5952: fprintf(ficgp,"\n# Routine varevsij");
5953: fprintf(ficgp,"\nunset title \n");
5954: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5955: 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");
5956: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5957:
1.218 brouard 5958: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5959: pstamp(ficresvij);
5960: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5961: if(popbased==1)
5962: 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);
5963: else
5964: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5965: fprintf(ficresvij,"# Age");
5966: for(i=1; i<=nlstate;i++)
5967: for(j=1; j<=nlstate;j++)
5968: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5969: fprintf(ficresvij,"\n");
5970:
5971: xp=vector(1,npar);
5972: dnewm=matrix(1,nlstate,1,npar);
5973: doldm=matrix(1,nlstate,1,nlstate);
5974: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5975: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5976:
5977: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5978: gpp=vector(nlstate+1,nlstate+ndeath);
5979: gmp=vector(nlstate+1,nlstate+ndeath);
5980: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5981:
1.218 brouard 5982: if(estepm < stepm){
5983: printf ("Problem %d lower than %d\n",estepm, stepm);
5984: }
5985: else hstepm=estepm;
5986: /* For example we decided to compute the life expectancy with the smallest unit */
5987: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5988: nhstepm is the number of hstepm from age to agelim
5989: nstepm is the number of stepm from age to agelim.
5990: Look at function hpijx to understand why because of memory size limitations,
5991: we decided (b) to get a life expectancy respecting the most precise curvature of the
5992: survival function given by stepm (the optimization length). Unfortunately it
5993: means that if the survival funtion is printed every two years of age and if
5994: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5995: results. So we changed our mind and took the option of the best precision.
5996: */
5997: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5998: agelim = AGESUP;
5999: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6000: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6001: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6002: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6003: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6004: gp=matrix(0,nhstepm,1,nlstate);
6005: gm=matrix(0,nhstepm,1,nlstate);
6006:
6007:
6008: for(theta=1; theta <=npar; theta++){
6009: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6010: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6011: }
1.279 brouard 6012: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6013: * returns into prlim .
1.288 brouard 6014: */
1.242 brouard 6015: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6016:
6017: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6018: if (popbased==1) {
6019: if(mobilav ==0){
6020: for(i=1; i<=nlstate;i++)
6021: prlim[i][i]=probs[(int)age][i][ij];
6022: }else{ /* mobilav */
6023: for(i=1; i<=nlstate;i++)
6024: prlim[i][i]=mobaverage[(int)age][i][ij];
6025: }
6026: }
1.295 brouard 6027: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6028: */
6029: 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 6030: /**< 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 6031: * at horizon h in state j including mortality.
6032: */
1.218 brouard 6033: for(j=1; j<= nlstate; j++){
6034: for(h=0; h<=nhstepm; h++){
6035: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6036: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6037: }
6038: }
1.279 brouard 6039: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6040: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6041: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6042: */
6043: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6044: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6045: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6046: }
6047:
6048: /* Again with minus shift */
1.218 brouard 6049:
6050: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6051: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6052:
1.242 brouard 6053: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6054:
6055: if (popbased==1) {
6056: if(mobilav ==0){
6057: for(i=1; i<=nlstate;i++)
6058: prlim[i][i]=probs[(int)age][i][ij];
6059: }else{ /* mobilav */
6060: for(i=1; i<=nlstate;i++)
6061: prlim[i][i]=mobaverage[(int)age][i][ij];
6062: }
6063: }
6064:
1.235 brouard 6065: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6066:
6067: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6068: for(h=0; h<=nhstepm; h++){
6069: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6070: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6071: }
6072: }
6073: /* This for computing probability of death (h=1 means
6074: computed over hstepm matrices product = hstepm*stepm months)
6075: as a weighted average of prlim.
6076: */
6077: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6078: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6079: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6080: }
1.279 brouard 6081: /* end shifting computations */
6082:
6083: /**< Computing gradient matrix at horizon h
6084: */
1.218 brouard 6085: for(j=1; j<= nlstate; j++) /* vareij */
6086: for(h=0; h<=nhstepm; h++){
6087: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6088: }
1.279 brouard 6089: /**< Gradient of overall mortality p.3 (or p.j)
6090: */
6091: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6092: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6093: }
6094:
6095: } /* End theta */
1.279 brouard 6096:
6097: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6098: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6099:
6100: for(h=0; h<=nhstepm; h++) /* veij */
6101: for(j=1; j<=nlstate;j++)
6102: for(theta=1; theta <=npar; theta++)
6103: trgradg[h][j][theta]=gradg[h][theta][j];
6104:
6105: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6106: for(theta=1; theta <=npar; theta++)
6107: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6108: /**< as well as its transposed matrix
6109: */
1.218 brouard 6110:
6111: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6112: for(i=1;i<=nlstate;i++)
6113: for(j=1;j<=nlstate;j++)
6114: vareij[i][j][(int)age] =0.;
1.279 brouard 6115:
6116: /* Computing trgradg by matcov by gradg at age and summing over h
6117: * and k (nhstepm) formula 15 of article
6118: * Lievre-Brouard-Heathcote
6119: */
6120:
1.218 brouard 6121: for(h=0;h<=nhstepm;h++){
6122: for(k=0;k<=nhstepm;k++){
6123: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6124: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6125: for(i=1;i<=nlstate;i++)
6126: for(j=1;j<=nlstate;j++)
6127: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6128: }
6129: }
6130:
1.279 brouard 6131: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6132: * p.j overall mortality formula 49 but computed directly because
6133: * we compute the grad (wix pijx) instead of grad (pijx),even if
6134: * wix is independent of theta.
6135: */
1.218 brouard 6136: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6137: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6138: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6139: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6140: varppt[j][i]=doldmp[j][i];
6141: /* end ppptj */
6142: /* x centered again */
6143:
1.242 brouard 6144: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6145:
6146: if (popbased==1) {
6147: if(mobilav ==0){
6148: for(i=1; i<=nlstate;i++)
6149: prlim[i][i]=probs[(int)age][i][ij];
6150: }else{ /* mobilav */
6151: for(i=1; i<=nlstate;i++)
6152: prlim[i][i]=mobaverage[(int)age][i][ij];
6153: }
6154: }
6155:
6156: /* This for computing probability of death (h=1 means
6157: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6158: as a weighted average of prlim.
6159: */
1.235 brouard 6160: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6161: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6162: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6163: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6164: }
6165: /* end probability of death */
6166:
6167: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6168: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6169: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6170: for(i=1; i<=nlstate;i++){
6171: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6172: }
6173: }
6174: fprintf(ficresprobmorprev,"\n");
6175:
6176: fprintf(ficresvij,"%.0f ",age );
6177: for(i=1; i<=nlstate;i++)
6178: for(j=1; j<=nlstate;j++){
6179: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6180: }
6181: fprintf(ficresvij,"\n");
6182: free_matrix(gp,0,nhstepm,1,nlstate);
6183: free_matrix(gm,0,nhstepm,1,nlstate);
6184: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6185: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6186: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6187: } /* End age */
6188: free_vector(gpp,nlstate+1,nlstate+ndeath);
6189: free_vector(gmp,nlstate+1,nlstate+ndeath);
6190: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6191: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6192: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6193: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6194: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6195: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6196: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6197: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6198: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6199: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6200: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6201: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6202: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6203: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6204: 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);
6205: /* 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 6206: */
1.218 brouard 6207: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6208: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6209:
1.218 brouard 6210: free_vector(xp,1,npar);
6211: free_matrix(doldm,1,nlstate,1,nlstate);
6212: free_matrix(dnewm,1,nlstate,1,npar);
6213: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6214: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6215: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6216: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6217: fclose(ficresprobmorprev);
6218: fflush(ficgp);
6219: fflush(fichtm);
6220: } /* end varevsij */
1.126 brouard 6221:
6222: /************ Variance of prevlim ******************/
1.269 brouard 6223: 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 6224: {
1.205 brouard 6225: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6226: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6227:
1.268 brouard 6228: double **dnewmpar,**doldm;
1.126 brouard 6229: int i, j, nhstepm, hstepm;
6230: double *xp;
6231: double *gp, *gm;
6232: double **gradg, **trgradg;
1.208 brouard 6233: double **mgm, **mgp;
1.126 brouard 6234: double age,agelim;
6235: int theta;
6236:
6237: pstamp(ficresvpl);
1.288 brouard 6238: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6239: fprintf(ficresvpl,"# Age ");
6240: if(nresult >=1)
6241: fprintf(ficresvpl," Result# ");
1.126 brouard 6242: for(i=1; i<=nlstate;i++)
6243: fprintf(ficresvpl," %1d-%1d",i,i);
6244: fprintf(ficresvpl,"\n");
6245:
6246: xp=vector(1,npar);
1.268 brouard 6247: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6248: doldm=matrix(1,nlstate,1,nlstate);
6249:
6250: hstepm=1*YEARM; /* Every year of age */
6251: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6252: agelim = AGESUP;
6253: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6254: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6255: if (stepm >= YEARM) hstepm=1;
6256: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6257: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6258: mgp=matrix(1,npar,1,nlstate);
6259: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6260: gp=vector(1,nlstate);
6261: gm=vector(1,nlstate);
6262:
6263: for(theta=1; theta <=npar; theta++){
6264: for(i=1; i<=npar; i++){ /* Computes gradient */
6265: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6266: }
1.288 brouard 6267: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6268: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6269: /* else */
6270: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6271: for(i=1;i<=nlstate;i++){
1.126 brouard 6272: gp[i] = prlim[i][i];
1.208 brouard 6273: mgp[theta][i] = prlim[i][i];
6274: }
1.126 brouard 6275: for(i=1; i<=npar; i++) /* Computes gradient */
6276: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6277: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6278: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6279: /* else */
6280: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6281: for(i=1;i<=nlstate;i++){
1.126 brouard 6282: gm[i] = prlim[i][i];
1.208 brouard 6283: mgm[theta][i] = prlim[i][i];
6284: }
1.126 brouard 6285: for(i=1;i<=nlstate;i++)
6286: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6287: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6288: } /* End theta */
6289:
6290: trgradg =matrix(1,nlstate,1,npar);
6291:
6292: for(j=1; j<=nlstate;j++)
6293: for(theta=1; theta <=npar; theta++)
6294: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6295: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6296: /* printf("\nmgm mgp %d ",(int)age); */
6297: /* for(j=1; j<=nlstate;j++){ */
6298: /* printf(" %d ",j); */
6299: /* for(theta=1; theta <=npar; theta++) */
6300: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6301: /* printf("\n "); */
6302: /* } */
6303: /* } */
6304: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6305: /* printf("\n gradg %d ",(int)age); */
6306: /* for(j=1; j<=nlstate;j++){ */
6307: /* printf("%d ",j); */
6308: /* for(theta=1; theta <=npar; theta++) */
6309: /* printf("%d %lf ",theta,gradg[theta][j]); */
6310: /* printf("\n "); */
6311: /* } */
6312: /* } */
1.126 brouard 6313:
6314: for(i=1;i<=nlstate;i++)
6315: varpl[i][(int)age] =0.;
1.209 brouard 6316: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6317: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6318: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6319: }else{
1.268 brouard 6320: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6321: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6322: }
1.126 brouard 6323: for(i=1;i<=nlstate;i++)
6324: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6325:
6326: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6327: if(nresult >=1)
6328: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6329: for(i=1; i<=nlstate;i++){
1.126 brouard 6330: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6331: /* for(j=1;j<=nlstate;j++) */
6332: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6333: }
1.126 brouard 6334: fprintf(ficresvpl,"\n");
6335: free_vector(gp,1,nlstate);
6336: free_vector(gm,1,nlstate);
1.208 brouard 6337: free_matrix(mgm,1,npar,1,nlstate);
6338: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6339: free_matrix(gradg,1,npar,1,nlstate);
6340: free_matrix(trgradg,1,nlstate,1,npar);
6341: } /* End age */
6342:
6343: free_vector(xp,1,npar);
6344: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6345: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6346:
6347: }
6348:
6349:
6350: /************ Variance of backprevalence limit ******************/
1.269 brouard 6351: 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 6352: {
6353: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6354: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6355:
6356: double **dnewmpar,**doldm;
6357: int i, j, nhstepm, hstepm;
6358: double *xp;
6359: double *gp, *gm;
6360: double **gradg, **trgradg;
6361: double **mgm, **mgp;
6362: double age,agelim;
6363: int theta;
6364:
6365: pstamp(ficresvbl);
6366: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6367: fprintf(ficresvbl,"# Age ");
6368: if(nresult >=1)
6369: fprintf(ficresvbl," Result# ");
6370: for(i=1; i<=nlstate;i++)
6371: fprintf(ficresvbl," %1d-%1d",i,i);
6372: fprintf(ficresvbl,"\n");
6373:
6374: xp=vector(1,npar);
6375: dnewmpar=matrix(1,nlstate,1,npar);
6376: doldm=matrix(1,nlstate,1,nlstate);
6377:
6378: hstepm=1*YEARM; /* Every year of age */
6379: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6380: agelim = AGEINF;
6381: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6382: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6383: if (stepm >= YEARM) hstepm=1;
6384: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6385: gradg=matrix(1,npar,1,nlstate);
6386: mgp=matrix(1,npar,1,nlstate);
6387: mgm=matrix(1,npar,1,nlstate);
6388: gp=vector(1,nlstate);
6389: gm=vector(1,nlstate);
6390:
6391: for(theta=1; theta <=npar; theta++){
6392: for(i=1; i<=npar; i++){ /* Computes gradient */
6393: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6394: }
6395: if(mobilavproj > 0 )
6396: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6397: else
6398: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6399: for(i=1;i<=nlstate;i++){
6400: gp[i] = bprlim[i][i];
6401: mgp[theta][i] = bprlim[i][i];
6402: }
6403: for(i=1; i<=npar; i++) /* Computes gradient */
6404: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6405: if(mobilavproj > 0 )
6406: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6407: else
6408: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6409: for(i=1;i<=nlstate;i++){
6410: gm[i] = bprlim[i][i];
6411: mgm[theta][i] = bprlim[i][i];
6412: }
6413: for(i=1;i<=nlstate;i++)
6414: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6415: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6416: } /* End theta */
6417:
6418: trgradg =matrix(1,nlstate,1,npar);
6419:
6420: for(j=1; j<=nlstate;j++)
6421: for(theta=1; theta <=npar; theta++)
6422: trgradg[j][theta]=gradg[theta][j];
6423: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6424: /* printf("\nmgm mgp %d ",(int)age); */
6425: /* for(j=1; j<=nlstate;j++){ */
6426: /* printf(" %d ",j); */
6427: /* for(theta=1; theta <=npar; theta++) */
6428: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6429: /* printf("\n "); */
6430: /* } */
6431: /* } */
6432: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6433: /* printf("\n gradg %d ",(int)age); */
6434: /* for(j=1; j<=nlstate;j++){ */
6435: /* printf("%d ",j); */
6436: /* for(theta=1; theta <=npar; theta++) */
6437: /* printf("%d %lf ",theta,gradg[theta][j]); */
6438: /* printf("\n "); */
6439: /* } */
6440: /* } */
6441:
6442: for(i=1;i<=nlstate;i++)
6443: varbpl[i][(int)age] =0.;
6444: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6445: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6446: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6447: }else{
6448: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6449: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6450: }
6451: for(i=1;i<=nlstate;i++)
6452: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6453:
6454: fprintf(ficresvbl,"%.0f ",age );
6455: if(nresult >=1)
6456: fprintf(ficresvbl,"%d ",nres );
6457: for(i=1; i<=nlstate;i++)
6458: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6459: fprintf(ficresvbl,"\n");
6460: free_vector(gp,1,nlstate);
6461: free_vector(gm,1,nlstate);
6462: free_matrix(mgm,1,npar,1,nlstate);
6463: free_matrix(mgp,1,npar,1,nlstate);
6464: free_matrix(gradg,1,npar,1,nlstate);
6465: free_matrix(trgradg,1,nlstate,1,npar);
6466: } /* End age */
6467:
6468: free_vector(xp,1,npar);
6469: free_matrix(doldm,1,nlstate,1,npar);
6470: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6471:
6472: }
6473:
6474: /************ Variance of one-step probabilities ******************/
6475: 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 6476: {
6477: int i, j=0, k1, l1, tj;
6478: int k2, l2, j1, z1;
6479: int k=0, l;
6480: int first=1, first1, first2;
6481: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6482: double **dnewm,**doldm;
6483: double *xp;
6484: double *gp, *gm;
6485: double **gradg, **trgradg;
6486: double **mu;
6487: double age, cov[NCOVMAX+1];
6488: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6489: int theta;
6490: char fileresprob[FILENAMELENGTH];
6491: char fileresprobcov[FILENAMELENGTH];
6492: char fileresprobcor[FILENAMELENGTH];
6493: double ***varpij;
6494:
6495: strcpy(fileresprob,"PROB_");
6496: strcat(fileresprob,fileres);
6497: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6498: printf("Problem with resultfile: %s\n", fileresprob);
6499: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6500: }
6501: strcpy(fileresprobcov,"PROBCOV_");
6502: strcat(fileresprobcov,fileresu);
6503: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6504: printf("Problem with resultfile: %s\n", fileresprobcov);
6505: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6506: }
6507: strcpy(fileresprobcor,"PROBCOR_");
6508: strcat(fileresprobcor,fileresu);
6509: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6510: printf("Problem with resultfile: %s\n", fileresprobcor);
6511: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6512: }
6513: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6514: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6515: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6516: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6517: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6518: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6519: pstamp(ficresprob);
6520: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6521: fprintf(ficresprob,"# Age");
6522: pstamp(ficresprobcov);
6523: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6524: fprintf(ficresprobcov,"# Age");
6525: pstamp(ficresprobcor);
6526: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6527: fprintf(ficresprobcor,"# Age");
1.126 brouard 6528:
6529:
1.222 brouard 6530: for(i=1; i<=nlstate;i++)
6531: for(j=1; j<=(nlstate+ndeath);j++){
6532: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6533: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6534: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6535: }
6536: /* fprintf(ficresprob,"\n");
6537: fprintf(ficresprobcov,"\n");
6538: fprintf(ficresprobcor,"\n");
6539: */
6540: xp=vector(1,npar);
6541: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6542: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6543: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6544: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6545: first=1;
6546: fprintf(ficgp,"\n# Routine varprob");
6547: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6548: fprintf(fichtm,"\n");
6549:
1.288 brouard 6550: 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 6551: 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);
6552: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6553: and drawn. It helps understanding how is the covariance between two incidences.\
6554: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6555: 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 6556: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6557: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6558: standard deviations wide on each axis. <br>\
6559: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6560: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6561: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6562:
1.222 brouard 6563: cov[1]=1;
6564: /* tj=cptcoveff; */
1.225 brouard 6565: tj = (int) pow(2,cptcoveff);
1.222 brouard 6566: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6567: j1=0;
1.224 brouard 6568: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6569: if (cptcovn>0) {
6570: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6571: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6572: fprintf(ficresprob, "**********\n#\n");
6573: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6574: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6575: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6576:
1.222 brouard 6577: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6578: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6579: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6580:
6581:
1.222 brouard 6582: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6583: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6584: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6585:
1.222 brouard 6586: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6587: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6588: fprintf(ficresprobcor, "**********\n#");
6589: if(invalidvarcomb[j1]){
6590: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6591: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6592: continue;
6593: }
6594: }
6595: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6596: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6597: gp=vector(1,(nlstate)*(nlstate+ndeath));
6598: gm=vector(1,(nlstate)*(nlstate+ndeath));
6599: for (age=bage; age<=fage; age ++){
6600: cov[2]=age;
6601: if(nagesqr==1)
6602: cov[3]= age*age;
6603: for (k=1; k<=cptcovn;k++) {
6604: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6605: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6606: * 1 1 1 1 1
6607: * 2 2 1 1 1
6608: * 3 1 2 1 1
6609: */
6610: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6611: }
6612: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6613: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6614: for (k=1; k<=cptcovprod;k++)
6615: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6616:
6617:
1.222 brouard 6618: for(theta=1; theta <=npar; theta++){
6619: for(i=1; i<=npar; i++)
6620: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6621:
1.222 brouard 6622: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6623:
1.222 brouard 6624: k=0;
6625: for(i=1; i<= (nlstate); i++){
6626: for(j=1; j<=(nlstate+ndeath);j++){
6627: k=k+1;
6628: gp[k]=pmmij[i][j];
6629: }
6630: }
1.220 brouard 6631:
1.222 brouard 6632: for(i=1; i<=npar; i++)
6633: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6634:
1.222 brouard 6635: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6636: k=0;
6637: for(i=1; i<=(nlstate); i++){
6638: for(j=1; j<=(nlstate+ndeath);j++){
6639: k=k+1;
6640: gm[k]=pmmij[i][j];
6641: }
6642: }
1.220 brouard 6643:
1.222 brouard 6644: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6645: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6646: }
1.126 brouard 6647:
1.222 brouard 6648: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6649: for(theta=1; theta <=npar; theta++)
6650: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6651:
1.222 brouard 6652: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6653: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6654:
1.222 brouard 6655: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6656:
1.222 brouard 6657: k=0;
6658: for(i=1; i<=(nlstate); i++){
6659: for(j=1; j<=(nlstate+ndeath);j++){
6660: k=k+1;
6661: mu[k][(int) age]=pmmij[i][j];
6662: }
6663: }
6664: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6665: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6666: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6667:
1.222 brouard 6668: /*printf("\n%d ",(int)age);
6669: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6670: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6671: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6672: }*/
1.220 brouard 6673:
1.222 brouard 6674: fprintf(ficresprob,"\n%d ",(int)age);
6675: fprintf(ficresprobcov,"\n%d ",(int)age);
6676: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6677:
1.222 brouard 6678: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6679: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6680: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6681: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6682: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6683: }
6684: i=0;
6685: for (k=1; k<=(nlstate);k++){
6686: for (l=1; l<=(nlstate+ndeath);l++){
6687: i++;
6688: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6689: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6690: for (j=1; j<=i;j++){
6691: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6692: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6693: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6694: }
6695: }
6696: }/* end of loop for state */
6697: } /* end of loop for age */
6698: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6699: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6700: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6701: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6702:
6703: /* Confidence intervalle of pij */
6704: /*
6705: fprintf(ficgp,"\nunset parametric;unset label");
6706: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6707: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6708: 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);
6709: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6710: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6711: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6712: */
6713:
6714: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6715: first1=1;first2=2;
6716: for (k2=1; k2<=(nlstate);k2++){
6717: for (l2=1; l2<=(nlstate+ndeath);l2++){
6718: if(l2==k2) continue;
6719: j=(k2-1)*(nlstate+ndeath)+l2;
6720: for (k1=1; k1<=(nlstate);k1++){
6721: for (l1=1; l1<=(nlstate+ndeath);l1++){
6722: if(l1==k1) continue;
6723: i=(k1-1)*(nlstate+ndeath)+l1;
6724: if(i<=j) continue;
6725: for (age=bage; age<=fage; age ++){
6726: if ((int)age %5==0){
6727: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6728: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6729: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6730: mu1=mu[i][(int) age]/stepm*YEARM ;
6731: mu2=mu[j][(int) age]/stepm*YEARM;
6732: c12=cv12/sqrt(v1*v2);
6733: /* Computing eigen value of matrix of covariance */
6734: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6735: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6736: if ((lc2 <0) || (lc1 <0) ){
6737: if(first2==1){
6738: first1=0;
6739: 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);
6740: }
6741: 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);
6742: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6743: /* lc2=fabs(lc2); */
6744: }
1.220 brouard 6745:
1.222 brouard 6746: /* Eigen vectors */
1.280 brouard 6747: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6748: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6749: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6750: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6751: }else
6752: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6753: /*v21=sqrt(1.-v11*v11); *//* error */
6754: v21=(lc1-v1)/cv12*v11;
6755: v12=-v21;
6756: v22=v11;
6757: tnalp=v21/v11;
6758: if(first1==1){
6759: first1=0;
6760: 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);
6761: }
6762: 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);
6763: /*printf(fignu*/
6764: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6765: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6766: if(first==1){
6767: first=0;
6768: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6769: fprintf(ficgp,"\nset parametric;unset label");
6770: 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);
6771: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6772: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6773: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6774: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6775: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6776: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6777: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6778: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6779: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6780: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6781: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6782: 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 6783: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6784: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6785: }else{
6786: first=0;
6787: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6788: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6789: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6790: 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 6791: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6792: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6793: }/* if first */
6794: } /* age mod 5 */
6795: } /* end loop age */
6796: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6797: first=1;
6798: } /*l12 */
6799: } /* k12 */
6800: } /*l1 */
6801: }/* k1 */
6802: } /* loop on combination of covariates j1 */
6803: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6804: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6805: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6806: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6807: free_vector(xp,1,npar);
6808: fclose(ficresprob);
6809: fclose(ficresprobcov);
6810: fclose(ficresprobcor);
6811: fflush(ficgp);
6812: fflush(fichtmcov);
6813: }
1.126 brouard 6814:
6815:
6816: /******************* Printing html file ***********/
1.201 brouard 6817: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6818: int lastpass, int stepm, int weightopt, char model[],\
6819: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 ! brouard 6820: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
! 6821: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
! 6822: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 6823: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6824:
6825: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6826: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6827: </ul>");
1.237 brouard 6828: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6829: </ul>", model);
1.214 brouard 6830: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6831: 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",
6832: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6833: 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 6834: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6835: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6836: fprintf(fichtm,"\
6837: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6838: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6839: fprintf(fichtm,"\
1.217 brouard 6840: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6841: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6842: fprintf(fichtm,"\
1.288 brouard 6843: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6844: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6845: fprintf(fichtm,"\
1.288 brouard 6846: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6847: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6848: fprintf(fichtm,"\
1.211 brouard 6849: - (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 6850: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6851: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6852: if(prevfcast==1){
6853: fprintf(fichtm,"\
6854: - Prevalence projections by age and states: \
1.201 brouard 6855: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6856: }
1.126 brouard 6857:
6858:
1.225 brouard 6859: m=pow(2,cptcoveff);
1.222 brouard 6860: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6861:
1.264 brouard 6862: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6863:
6864: jj1=0;
6865:
6866: fprintf(fichtm," \n<ul>");
6867: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6868: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6869: if(m != 1 && TKresult[nres]!= k1)
6870: continue;
6871: jj1++;
6872: if (cptcovn > 0) {
6873: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6874: for (cpt=1; cpt<=cptcoveff;cpt++){
6875: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6876: }
6877: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6878: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6879: }
6880: fprintf(fichtm,"\">");
6881:
6882: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6883: fprintf(fichtm,"************ Results for covariates");
6884: for (cpt=1; cpt<=cptcoveff;cpt++){
6885: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6886: }
6887: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6888: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6889: }
6890: if(invalidvarcomb[k1]){
6891: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6892: continue;
6893: }
6894: fprintf(fichtm,"</a></li>");
6895: } /* cptcovn >0 */
6896: }
6897: fprintf(fichtm," \n</ul>");
6898:
1.222 brouard 6899: jj1=0;
1.237 brouard 6900:
6901: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6902: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6903: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6904: continue;
1.220 brouard 6905:
1.222 brouard 6906: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6907: jj1++;
6908: if (cptcovn > 0) {
1.264 brouard 6909: fprintf(fichtm,"\n<p><a name=\"rescov");
6910: for (cpt=1; cpt<=cptcoveff;cpt++){
6911: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6912: }
6913: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6914: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6915: }
6916: fprintf(fichtm,"\"</a>");
6917:
1.222 brouard 6918: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6919: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6920: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6921: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6922: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6923: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6924: }
1.237 brouard 6925: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6926: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6927: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6928: }
6929:
1.230 brouard 6930: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6931: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6932: if(invalidvarcomb[k1]){
6933: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6934: printf("\nCombination (%d) ignored because no cases \n",k1);
6935: continue;
6936: }
6937: }
6938: /* aij, bij */
1.259 brouard 6939: 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 6940: <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 6941: /* Pij */
1.241 brouard 6942: 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> \
6943: <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 6944: /* Quasi-incidences */
6945: 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 6946: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6947: 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 6948: 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> \
6949: <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 6950: /* Survival functions (period) in state j */
6951: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 6952: 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 6953: <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 6954: }
6955: /* State specific survival functions (period) */
6956: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 6957: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
6958: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 6959: <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 6960: }
1.288 brouard 6961: /* Period (forward stable) prevalence in each health state */
1.222 brouard 6962: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6963: 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> \
6964: <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 6965: }
1.296 ! brouard 6966: if(prevbcast==1){
1.288 brouard 6967: /* Backward prevalence in each health state */
1.222 brouard 6968: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6969: 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 6970: <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 6971: }
1.217 brouard 6972: }
1.222 brouard 6973: if(prevfcast==1){
1.288 brouard 6974: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 6975: for(cpt=1; cpt<=nlstate;cpt++){
1.288 brouard 6976: 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><br> \
1.296 ! brouard 6977: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 6978: }
6979: }
1.296 ! brouard 6980: if(prevbcast==1){
1.268 brouard 6981: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6982: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6983: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6984: 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 \
6985: 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) \
6986: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6987: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 6988: }
6989: }
1.220 brouard 6990:
1.222 brouard 6991: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6992: 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> <br> \
6993: <img src=\"%s_%d-%d-%d.svg\">",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.222 brouard 6994: }
6995: /* } /\* end i1 *\/ */
6996: }/* End k1 */
6997: fprintf(fichtm,"</ul>");
1.126 brouard 6998:
1.222 brouard 6999: fprintf(fichtm,"\
1.126 brouard 7000: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7001: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7002: - 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 7003: But because parameters are usually highly correlated (a higher incidence of disability \
7004: and a higher incidence of recovery can give very close observed transition) it might \
7005: be very useful to look not only at linear confidence intervals estimated from the \
7006: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7007: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7008: covariance matrix of the one-step probabilities. \
7009: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7010:
1.222 brouard 7011: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7012: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7013: fprintf(fichtm,"\
1.126 brouard 7014: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7015: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7016:
1.222 brouard 7017: fprintf(fichtm,"\
1.126 brouard 7018: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7019: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7020: fprintf(fichtm,"\
1.126 brouard 7021: - 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): \
7022: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7023: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7024: fprintf(fichtm,"\
1.126 brouard 7025: - (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): \
7026: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7027: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7028: fprintf(fichtm,"\
1.288 brouard 7029: - 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 7030: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7031: fprintf(fichtm,"\
1.128 brouard 7032: - 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 7033: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7034: fprintf(fichtm,"\
1.288 brouard 7035: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7036: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7037:
7038: /* if(popforecast==1) fprintf(fichtm,"\n */
7039: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7040: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7041: /* <br>",fileres,fileres,fileres,fileres); */
7042: /* else */
7043: /* 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 7044: fflush(fichtm);
7045: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7046:
1.225 brouard 7047: m=pow(2,cptcoveff);
1.222 brouard 7048: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7049:
1.222 brouard 7050: jj1=0;
1.237 brouard 7051:
1.241 brouard 7052: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7053: for(k1=1; k1<=m;k1++){
1.253 brouard 7054: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7055: continue;
1.222 brouard 7056: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7057: jj1++;
1.126 brouard 7058: if (cptcovn > 0) {
7059: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7060: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7061: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7062: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7063: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7064: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7065: }
7066:
1.126 brouard 7067: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7068:
1.222 brouard 7069: if(invalidvarcomb[k1]){
7070: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7071: continue;
7072: }
1.126 brouard 7073: }
7074: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7075: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7076: prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d-%d.svg\"> %s_%d-%d-%d.svg</a>\n <br>\
1.258 brouard 7077: <img src=\"%s_%d-%d-%d.svg\">",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
1.126 brouard 7078: }
7079: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7080: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7081: true period expectancies (those weighted with period prevalences are also\
7082: drawn in addition to the population based expectancies computed using\
1.241 brouard 7083: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7084: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7085: /* } /\* end i1 *\/ */
7086: }/* End k1 */
1.241 brouard 7087: }/* End nres */
1.222 brouard 7088: fprintf(fichtm,"</ul>");
7089: fflush(fichtm);
1.126 brouard 7090: }
7091:
7092: /******************* Gnuplot file **************/
1.296 ! brouard 7093: 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 7094:
7095: char dirfileres[132],optfileres[132];
1.264 brouard 7096: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7097: 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 7098: int lv=0, vlv=0, kl=0;
1.130 brouard 7099: int ng=0;
1.201 brouard 7100: int vpopbased;
1.223 brouard 7101: int ioffset; /* variable offset for columns */
1.270 brouard 7102: int iyearc=1; /* variable column for year of projection */
7103: int iagec=1; /* variable column for age of projection */
1.235 brouard 7104: int nres=0; /* Index of resultline */
1.266 brouard 7105: int istart=1; /* For starting graphs in projections */
1.219 brouard 7106:
1.126 brouard 7107: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7108: /* printf("Problem with file %s",optionfilegnuplot); */
7109: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7110: /* } */
7111:
7112: /*#ifdef windows */
7113: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7114: /*#endif */
1.225 brouard 7115: m=pow(2,cptcoveff);
1.126 brouard 7116:
1.274 brouard 7117: /* diagram of the model */
7118: fprintf(ficgp,"\n#Diagram of the model \n");
7119: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7120: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7121: 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);
7122:
7123: 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);
7124: fprintf(ficgp,"\n#show arrow\nunset label\n");
7125: 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);
7126: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7127: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7128: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7129: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7130:
1.202 brouard 7131: /* Contribution to likelihood */
7132: /* Plot the probability implied in the likelihood */
1.223 brouard 7133: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7134: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7135: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7136: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7137: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7138: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7139: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7140: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7141: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7142: 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));
7143: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7144: 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));
7145: for (i=1; i<= nlstate ; i ++) {
7146: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7147: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7148: 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);
7149: for (j=2; j<= nlstate+ndeath ; j ++) {
7150: 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);
7151: }
7152: fprintf(ficgp,";\nset out; unset ylabel;\n");
7153: }
7154: /* 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 */
7155: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7156: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7157: fprintf(ficgp,"\nset out;unset log\n");
7158: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7159:
1.126 brouard 7160: strcpy(dirfileres,optionfilefiname);
7161: strcpy(optfileres,"vpl");
1.223 brouard 7162: /* 1eme*/
1.238 brouard 7163: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7164: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7165: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7166: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7167: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7168: continue;
7169: /* We are interested in selected combination by the resultline */
1.246 brouard 7170: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7171: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7172: strcpy(gplotlabel,"(");
1.238 brouard 7173: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7174: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7175: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7176: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7177: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7178: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7179: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7180: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7181: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7182: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7183: }
7184: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7185: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7186: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7187: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7188: }
7189: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7190: /* printf("\n#\n"); */
1.238 brouard 7191: fprintf(ficgp,"\n#\n");
7192: if(invalidvarcomb[k1]){
1.260 brouard 7193: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7194: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7195: continue;
7196: }
1.235 brouard 7197:
1.241 brouard 7198: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7199: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7200: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7201: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7202: 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);
7203: /* 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); */
7204: /* k1-1 error should be nres-1*/
1.238 brouard 7205: for (i=1; i<= nlstate ; i ++) {
7206: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7207: else fprintf(ficgp," %%*lf (%%*lf)");
7208: }
1.288 brouard 7209: 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 7210: for (i=1; i<= nlstate ; i ++) {
7211: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7212: else fprintf(ficgp," %%*lf (%%*lf)");
7213: }
1.260 brouard 7214: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7215: for (i=1; i<= nlstate ; i ++) {
7216: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7217: else fprintf(ficgp," %%*lf (%%*lf)");
7218: }
1.265 brouard 7219: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7220:
7221: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7222: if(cptcoveff ==0){
1.271 brouard 7223: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7224: }else{
7225: kl=0;
7226: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7227: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7228: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7229: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7230: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7231: vlv= nbcode[Tvaraff[k]][lv];
7232: kl++;
7233: /* 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 *\/ */
7234: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7235: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7236: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7237: if(k==cptcoveff){
7238: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7239: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7240: }else{
7241: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7242: kl++;
7243: }
7244: } /* end covariate */
7245: } /* end if no covariate */
7246:
1.296 ! brouard 7247: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7248: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7249: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7250: if(cptcoveff ==0){
1.245 brouard 7251: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7252: }else{
7253: kl=0;
7254: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7255: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7256: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7257: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7258: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7259: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7260: kl++;
1.238 brouard 7261: /* 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 *\/ */
7262: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7263: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7264: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7265: if(k==cptcoveff){
1.245 brouard 7266: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7267: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7268: }else{
7269: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7270: kl++;
7271: }
7272: } /* end covariate */
7273: } /* end if no covariate */
1.296 ! brouard 7274: if(prevbcast == 1){
1.268 brouard 7275: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7276: /* k1-1 error should be nres-1*/
7277: for (i=1; i<= nlstate ; i ++) {
7278: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7279: else fprintf(ficgp," %%*lf (%%*lf)");
7280: }
1.271 brouard 7281: 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 7282: for (i=1; i<= nlstate ; i ++) {
7283: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7284: else fprintf(ficgp," %%*lf (%%*lf)");
7285: }
1.276 brouard 7286: 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 7287: for (i=1; i<= nlstate ; i ++) {
7288: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7289: else fprintf(ficgp," %%*lf (%%*lf)");
7290: }
1.274 brouard 7291: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7292: } /* end if backprojcast */
1.296 ! brouard 7293: } /* end if prevbcast */
1.276 brouard 7294: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7295: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7296: } /* nres */
1.201 brouard 7297: } /* k1 */
7298: } /* cpt */
1.235 brouard 7299:
7300:
1.126 brouard 7301: /*2 eme*/
1.238 brouard 7302: for (k1=1; k1<= m ; k1 ++){
7303: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7304: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7305: continue;
7306: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7307: strcpy(gplotlabel,"(");
1.238 brouard 7308: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7309: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7310: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7311: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7312: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7313: vlv= nbcode[Tvaraff[k]][lv];
7314: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7315: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7316: }
1.237 brouard 7317: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7318: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7319: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7320: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7321: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7322: }
1.264 brouard 7323: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7324: fprintf(ficgp,"\n#\n");
1.223 brouard 7325: if(invalidvarcomb[k1]){
7326: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7327: continue;
7328: }
1.219 brouard 7329:
1.241 brouard 7330: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7331: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7332: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7333: if(vpopbased==0){
1.238 brouard 7334: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7335: }else
1.238 brouard 7336: fprintf(ficgp,"\nreplot ");
7337: for (i=1; i<= nlstate+1 ; i ++) {
7338: k=2*i;
1.261 brouard 7339: 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 7340: for (j=1; j<= nlstate+1 ; j ++) {
7341: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7342: else fprintf(ficgp," %%*lf (%%*lf)");
7343: }
7344: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7345: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7346: 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 7347: for (j=1; j<= nlstate+1 ; j ++) {
7348: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7349: else fprintf(ficgp," %%*lf (%%*lf)");
7350: }
7351: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7352: 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 7353: for (j=1; j<= nlstate+1 ; j ++) {
7354: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7355: else fprintf(ficgp," %%*lf (%%*lf)");
7356: }
7357: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7358: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7359: } /* state */
7360: } /* vpopbased */
1.264 brouard 7361: 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 7362: } /* end nres */
7363: } /* k1 end 2 eme*/
7364:
7365:
7366: /*3eme*/
7367: for (k1=1; k1<= m ; k1 ++){
7368: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7369: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7370: continue;
7371:
7372: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7373: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7374: strcpy(gplotlabel,"(");
1.238 brouard 7375: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7376: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7377: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7378: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7379: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7380: vlv= nbcode[Tvaraff[k]][lv];
7381: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7382: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7383: }
7384: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7385: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7386: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7387: }
1.264 brouard 7388: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7389: fprintf(ficgp,"\n#\n");
7390: if(invalidvarcomb[k1]){
7391: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7392: continue;
7393: }
7394:
7395: /* k=2+nlstate*(2*cpt-2); */
7396: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7397: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7398: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7399: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7400: 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 7401: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7402: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7403: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7404: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7405: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7406: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7407:
1.238 brouard 7408: */
7409: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7410: 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 7411: /* 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 7412:
1.238 brouard 7413: }
1.261 brouard 7414: 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 7415: }
1.264 brouard 7416: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7417: } /* end nres */
7418: } /* end kl 3eme */
1.126 brouard 7419:
1.223 brouard 7420: /* 4eme */
1.201 brouard 7421: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7422: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7423: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7424: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7425: continue;
1.238 brouard 7426: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7427: strcpy(gplotlabel,"(");
1.238 brouard 7428: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7429: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7430: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7431: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7432: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7433: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7434: vlv= nbcode[Tvaraff[k]][lv];
7435: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7436: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7437: }
7438: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7439: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7440: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7441: }
1.264 brouard 7442: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7443: fprintf(ficgp,"\n#\n");
7444: if(invalidvarcomb[k1]){
7445: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7446: continue;
1.223 brouard 7447: }
1.238 brouard 7448:
1.241 brouard 7449: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7450: 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 7451: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7452: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7453: k=3;
7454: for (i=1; i<= nlstate ; i ++){
7455: if(i==1){
7456: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7457: }else{
7458: fprintf(ficgp,", '' ");
7459: }
7460: l=(nlstate+ndeath)*(i-1)+1;
7461: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7462: for (j=2; j<= nlstate+ndeath ; j ++)
7463: fprintf(ficgp,"+$%d",k+l+j-1);
7464: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7465: } /* nlstate */
1.264 brouard 7466: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7467: } /* end cpt state*/
7468: } /* end nres */
7469: } /* end covariate k1 */
7470:
1.220 brouard 7471: /* 5eme */
1.201 brouard 7472: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7473: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7474: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7475: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7476: continue;
1.238 brouard 7477: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7478: strcpy(gplotlabel,"(");
1.238 brouard 7479: 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);
7480: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7481: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7482: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7483: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7484: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7485: vlv= nbcode[Tvaraff[k]][lv];
7486: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7487: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7488: }
7489: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7490: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7491: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7492: }
1.264 brouard 7493: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7494: fprintf(ficgp,"\n#\n");
7495: if(invalidvarcomb[k1]){
7496: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7497: continue;
7498: }
1.227 brouard 7499:
1.241 brouard 7500: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7501: 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 7502: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7503: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7504: k=3;
7505: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7506: if(j==1)
7507: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7508: else
7509: fprintf(ficgp,", '' ");
7510: l=(nlstate+ndeath)*(cpt-1) +j;
7511: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7512: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7513: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7514: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7515: } /* nlstate */
7516: fprintf(ficgp,", '' ");
7517: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7518: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7519: l=(nlstate+ndeath)*(cpt-1) +j;
7520: if(j < nlstate)
7521: fprintf(ficgp,"$%d +",k+l);
7522: else
7523: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7524: }
1.264 brouard 7525: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7526: } /* end cpt state*/
7527: } /* end covariate */
7528: } /* end nres */
1.227 brouard 7529:
1.220 brouard 7530: /* 6eme */
1.202 brouard 7531: /* CV preval stable (period) for each covariate */
1.237 brouard 7532: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7533: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7534: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7535: continue;
1.255 brouard 7536: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7537: strcpy(gplotlabel,"(");
1.288 brouard 7538: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7539: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7540: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7541: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7542: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7543: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7544: vlv= nbcode[Tvaraff[k]][lv];
7545: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7546: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7547: }
1.237 brouard 7548: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7549: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7550: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7551: }
1.264 brouard 7552: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7553: fprintf(ficgp,"\n#\n");
1.223 brouard 7554: if(invalidvarcomb[k1]){
1.227 brouard 7555: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7556: continue;
1.223 brouard 7557: }
1.227 brouard 7558:
1.241 brouard 7559: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7560: 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 7561: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7562: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7563: k=3; /* Offset */
1.255 brouard 7564: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7565: if(i==1)
7566: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7567: else
7568: fprintf(ficgp,", '' ");
1.255 brouard 7569: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7570: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7571: for (j=2; j<= nlstate ; j ++)
7572: fprintf(ficgp,"+$%d",k+l+j-1);
7573: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7574: } /* nlstate */
1.264 brouard 7575: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7576: } /* end cpt state*/
7577: } /* end covariate */
1.227 brouard 7578:
7579:
1.220 brouard 7580: /* 7eme */
1.296 ! brouard 7581: if(prevbcast == 1){
1.288 brouard 7582: /* CV backward prevalence for each covariate */
1.237 brouard 7583: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7584: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7585: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7586: continue;
1.268 brouard 7587: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7588: strcpy(gplotlabel,"(");
1.288 brouard 7589: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7590: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7591: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7592: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7593: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7594: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7595: vlv= nbcode[Tvaraff[k]][lv];
7596: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7597: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7598: }
1.237 brouard 7599: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7600: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7601: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7602: }
1.264 brouard 7603: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7604: fprintf(ficgp,"\n#\n");
7605: if(invalidvarcomb[k1]){
7606: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7607: continue;
7608: }
7609:
1.241 brouard 7610: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7611: 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 7612: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7613: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7614: k=3; /* Offset */
1.268 brouard 7615: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7616: if(i==1)
7617: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7618: else
7619: fprintf(ficgp,", '' ");
7620: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7621: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7622: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7623: /* 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 7624: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7625: /* for (j=2; j<= nlstate ; j ++) */
7626: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7627: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7628: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7629: } /* nlstate */
1.264 brouard 7630: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7631: } /* end cpt state*/
7632: } /* end covariate */
1.296 ! brouard 7633: } /* End if prevbcast */
1.218 brouard 7634:
1.223 brouard 7635: /* 8eme */
1.218 brouard 7636: if(prevfcast==1){
1.288 brouard 7637: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7638:
1.237 brouard 7639: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7640: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7641: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7642: continue;
1.211 brouard 7643: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7644: strcpy(gplotlabel,"(");
1.288 brouard 7645: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7646: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7647: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7648: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7649: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7650: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7651: vlv= nbcode[Tvaraff[k]][lv];
7652: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7653: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7654: }
1.237 brouard 7655: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7656: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7657: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7658: }
1.264 brouard 7659: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7660: fprintf(ficgp,"\n#\n");
7661: if(invalidvarcomb[k1]){
7662: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7663: continue;
7664: }
7665:
7666: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7667: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7668: 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 7669: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7670: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7671:
7672: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7673: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7674: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7675: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7676: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7677: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7678: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7679: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7680: if(i==istart){
1.227 brouard 7681: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7682: }else{
7683: fprintf(ficgp,",\\\n '' ");
7684: }
7685: if(cptcoveff ==0){ /* No covariate */
7686: ioffset=2; /* Age is in 2 */
7687: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7688: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7689: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7690: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7691: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7692: if(i==nlstate+1){
1.270 brouard 7693: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7694: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7695: fprintf(ficgp,",\\\n '' ");
7696: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7697: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7698: offyear, \
1.268 brouard 7699: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7700: }else
1.227 brouard 7701: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7702: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7703: }else{ /* more than 2 covariates */
1.270 brouard 7704: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7705: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7706: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7707: iyearc=ioffset-1;
7708: iagec=ioffset;
1.227 brouard 7709: fprintf(ficgp," u %d:(",ioffset);
7710: kl=0;
7711: strcpy(gplotcondition,"(");
7712: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7713: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7714: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7715: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7716: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7717: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7718: kl++;
7719: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7720: kl++;
7721: if(k <cptcoveff && cptcoveff>1)
7722: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7723: }
7724: strcpy(gplotcondition+strlen(gplotcondition),")");
7725: /* 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 *\/ */
7726: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7727: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7728: /* '' 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*/
7729: if(i==nlstate+1){
1.270 brouard 7730: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7731: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7732: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7733: fprintf(ficgp," u %d:(",iagec);
7734: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7735: iyearc, iagec, offyear, \
7736: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7737: /* '' 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 7738: }else{
7739: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7740: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7741: }
7742: } /* end if covariate */
7743: } /* nlstate */
1.264 brouard 7744: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7745: } /* end cpt state*/
7746: } /* end covariate */
7747: } /* End if prevfcast */
1.227 brouard 7748:
1.296 ! brouard 7749: if(prevbcast==1){
1.268 brouard 7750: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7751:
7752: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7753: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7754: if(m != 1 && TKresult[nres]!= k1)
7755: continue;
7756: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7757: strcpy(gplotlabel,"(");
7758: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7759: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7760: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7761: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7762: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7763: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7764: vlv= nbcode[Tvaraff[k]][lv];
7765: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7766: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7767: }
7768: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7769: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7770: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7771: }
7772: strcpy(gplotlabel+strlen(gplotlabel),")");
7773: fprintf(ficgp,"\n#\n");
7774: if(invalidvarcomb[k1]){
7775: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7776: continue;
7777: }
7778:
7779: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7780: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7781: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7782: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7783: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7784:
7785: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7786: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7787: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7788: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7789: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7790: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7791: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7792: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7793: if(i==istart){
7794: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7795: }else{
7796: fprintf(ficgp,",\\\n '' ");
7797: }
7798: if(cptcoveff ==0){ /* No covariate */
7799: ioffset=2; /* Age is in 2 */
7800: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7801: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7802: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7803: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7804: fprintf(ficgp," u %d:(", ioffset);
7805: if(i==nlstate+1){
1.270 brouard 7806: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7807: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7808: fprintf(ficgp,",\\\n '' ");
7809: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7810: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7811: offbyear, \
7812: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7813: }else
7814: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7815: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7816: }else{ /* more than 2 covariates */
1.270 brouard 7817: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7818: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7819: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7820: iyearc=ioffset-1;
7821: iagec=ioffset;
1.268 brouard 7822: fprintf(ficgp," u %d:(",ioffset);
7823: kl=0;
7824: strcpy(gplotcondition,"(");
7825: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7826: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7827: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7828: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7829: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7830: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7831: kl++;
7832: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7833: kl++;
7834: if(k <cptcoveff && cptcoveff>1)
7835: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7836: }
7837: strcpy(gplotcondition+strlen(gplotcondition),")");
7838: /* 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 *\/ */
7839: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7840: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7841: /* '' 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*/
7842: if(i==nlstate+1){
1.270 brouard 7843: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7844: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7845: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7846: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7847: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7848: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7849: iyearc,iagec,offbyear, \
7850: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7851: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7852: }else{
7853: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7854: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7855: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7856: }
7857: } /* end if covariate */
7858: } /* nlstate */
7859: fprintf(ficgp,"\nset out; unset label;\n");
7860: } /* end cpt state*/
7861: } /* end covariate */
1.296 ! brouard 7862: } /* End if prevbcast */
1.268 brouard 7863:
1.227 brouard 7864:
1.238 brouard 7865: /* 9eme writing MLE parameters */
7866: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7867: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7868: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7869: for(k=1; k <=(nlstate+ndeath); k++){
7870: if (k != i) {
1.227 brouard 7871: fprintf(ficgp,"# current state %d\n",k);
7872: for(j=1; j <=ncovmodel; j++){
7873: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7874: jk++;
7875: }
7876: fprintf(ficgp,"\n");
1.126 brouard 7877: }
7878: }
1.223 brouard 7879: }
1.187 brouard 7880: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7881:
1.145 brouard 7882: /*goto avoid;*/
1.238 brouard 7883: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7884: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7885: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7886: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7887: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7888: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7889: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7890: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7891: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7892: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7893: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7894: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7895: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7896: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7897: fprintf(ficgp,"#\n");
1.223 brouard 7898: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7899: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7900: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7901: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7902: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7903: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7904: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7905: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7906: continue;
1.264 brouard 7907: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7908: strcpy(gplotlabel,"(");
1.276 brouard 7909: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7910: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7911: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7912: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7913: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7914: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7915: vlv= nbcode[Tvaraff[k]][lv];
7916: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7917: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7918: }
1.237 brouard 7919: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7920: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7921: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7922: }
1.264 brouard 7923: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7924: fprintf(ficgp,"\n#\n");
1.264 brouard 7925: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7926: fprintf(ficgp,"\nset key outside ");
7927: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7928: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7929: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7930: if (ng==1){
7931: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7932: fprintf(ficgp,"\nunset log y");
7933: }else if (ng==2){
7934: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7935: fprintf(ficgp,"\nset log y");
7936: }else if (ng==3){
7937: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7938: fprintf(ficgp,"\nset log y");
7939: }else
7940: fprintf(ficgp,"\nunset title ");
7941: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7942: i=1;
7943: for(k2=1; k2<=nlstate; k2++) {
7944: k3=i;
7945: for(k=1; k<=(nlstate+ndeath); k++) {
7946: if (k != k2){
7947: switch( ng) {
7948: case 1:
7949: if(nagesqr==0)
7950: fprintf(ficgp," p%d+p%d*x",i,i+1);
7951: else /* nagesqr =1 */
7952: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7953: break;
7954: case 2: /* ng=2 */
7955: if(nagesqr==0)
7956: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7957: else /* nagesqr =1 */
7958: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7959: break;
7960: case 3:
7961: if(nagesqr==0)
7962: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7963: else /* nagesqr =1 */
7964: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7965: break;
7966: }
7967: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7968: ijp=1; /* product no age */
7969: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7970: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7971: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7972: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7973: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7974: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7975: if(DummyV[j]==0){
7976: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7977: }else{ /* quantitative */
7978: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7979: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7980: }
7981: ij++;
1.237 brouard 7982: }
1.268 brouard 7983: }
7984: }else if(cptcovprod >0){
7985: if(j==Tprod[ijp]) { /* */
7986: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7987: if(ijp <=cptcovprod) { /* Product */
7988: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7989: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7990: /* 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)]); */
7991: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7992: }else{ /* Vn is dummy and Vm is quanti */
7993: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7994: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7995: }
7996: }else{ /* Vn*Vm Vn is quanti */
7997: if(DummyV[Tvard[ijp][2]]==0){
7998: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7999: }else{ /* Both quanti */
8000: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8001: }
1.237 brouard 8002: }
1.268 brouard 8003: ijp++;
1.237 brouard 8004: }
1.268 brouard 8005: } /* end Tprod */
1.237 brouard 8006: } else{ /* simple covariate */
1.264 brouard 8007: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8008: if(Dummy[j]==0){
8009: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8010: }else{ /* quantitative */
8011: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8012: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8013: }
1.237 brouard 8014: } /* end simple */
8015: } /* end j */
1.223 brouard 8016: }else{
8017: i=i-ncovmodel;
8018: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8019: fprintf(ficgp," (1.");
8020: }
1.227 brouard 8021:
1.223 brouard 8022: if(ng != 1){
8023: fprintf(ficgp,")/(1");
1.227 brouard 8024:
1.264 brouard 8025: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8026: if(nagesqr==0)
1.264 brouard 8027: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8028: else /* nagesqr =1 */
1.264 brouard 8029: 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 8030:
1.223 brouard 8031: ij=1;
8032: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8033: if(cptcovage >0){
8034: if((j-2)==Tage[ij]) { /* Bug valgrind */
8035: if(ij <=cptcovage) { /* Bug valgrind */
8036: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8037: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8038: ij++;
8039: }
8040: }
8041: }else
8042: 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 8043: }
8044: fprintf(ficgp,")");
8045: }
8046: fprintf(ficgp,")");
8047: if(ng ==2)
1.276 brouard 8048: 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 8049: else /* ng= 3 */
1.276 brouard 8050: 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 8051: }else{ /* end ng <> 1 */
8052: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8053: 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 8054: }
8055: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8056: fprintf(ficgp,",");
8057: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8058: fprintf(ficgp,",");
8059: i=i+ncovmodel;
8060: } /* end k */
8061: } /* end k2 */
1.276 brouard 8062: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8063: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8064: } /* end k1 */
1.223 brouard 8065: } /* end ng */
8066: /* avoid: */
8067: fflush(ficgp);
1.126 brouard 8068: } /* end gnuplot */
8069:
8070:
8071: /*************** Moving average **************/
1.219 brouard 8072: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8073: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8074:
1.222 brouard 8075: int i, cpt, cptcod;
8076: int modcovmax =1;
8077: int mobilavrange, mob;
8078: int iage=0;
1.288 brouard 8079: int firstA1=0, firstA2=0;
1.222 brouard 8080:
1.266 brouard 8081: double sum=0., sumr=0.;
1.222 brouard 8082: double age;
1.266 brouard 8083: double *sumnewp, *sumnewm, *sumnewmr;
8084: double *agemingood, *agemaxgood;
8085: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8086:
8087:
1.278 brouard 8088: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8089: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8090:
8091: sumnewp = vector(1,ncovcombmax);
8092: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8093: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8094: agemingood = vector(1,ncovcombmax);
1.266 brouard 8095: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8096: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8097: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8098:
8099: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8100: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8101: sumnewp[cptcod]=0.;
1.266 brouard 8102: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8103: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8104: }
8105: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8106:
1.266 brouard 8107: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8108: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8109: else mobilavrange=mobilav;
8110: for (age=bage; age<=fage; age++)
8111: for (i=1; i<=nlstate;i++)
8112: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8113: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8114: /* We keep the original values on the extreme ages bage, fage and for
8115: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8116: we use a 5 terms etc. until the borders are no more concerned.
8117: */
8118: for (mob=3;mob <=mobilavrange;mob=mob+2){
8119: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8120: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8121: sumnewm[cptcod]=0.;
8122: for (i=1; i<=nlstate;i++){
1.222 brouard 8123: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8124: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8125: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8126: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8127: }
8128: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8129: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8130: } /* end i */
8131: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8132: } /* end cptcod */
1.222 brouard 8133: }/* end age */
8134: }/* end mob */
1.266 brouard 8135: }else{
8136: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8137: return -1;
1.266 brouard 8138: }
8139:
8140: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8141: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8142: if(invalidvarcomb[cptcod]){
8143: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8144: continue;
8145: }
1.219 brouard 8146:
1.266 brouard 8147: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8148: sumnewm[cptcod]=0.;
8149: sumnewmr[cptcod]=0.;
8150: for (i=1; i<=nlstate;i++){
8151: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8152: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8153: }
8154: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8155: agemingoodr[cptcod]=age;
8156: }
8157: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8158: agemingood[cptcod]=age;
8159: }
8160: } /* age */
8161: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8162: sumnewm[cptcod]=0.;
1.266 brouard 8163: sumnewmr[cptcod]=0.;
1.222 brouard 8164: for (i=1; i<=nlstate;i++){
8165: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8166: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8167: }
8168: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8169: agemaxgoodr[cptcod]=age;
1.222 brouard 8170: }
8171: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8172: agemaxgood[cptcod]=age;
8173: }
8174: } /* age */
8175: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8176: /* but they will change */
1.288 brouard 8177: firstA1=0;firstA2=0;
1.266 brouard 8178: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8179: sumnewm[cptcod]=0.;
8180: sumnewmr[cptcod]=0.;
8181: for (i=1; i<=nlstate;i++){
8182: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8183: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8184: }
8185: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8186: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8187: agemaxgoodr[cptcod]=age; /* age min */
8188: for (i=1; i<=nlstate;i++)
8189: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8190: }else{ /* bad we change the value with the values of good ages */
8191: for (i=1; i<=nlstate;i++){
8192: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8193: } /* i */
8194: } /* end bad */
8195: }else{
8196: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8197: agemaxgood[cptcod]=age;
8198: }else{ /* bad we change the value with the values of good ages */
8199: for (i=1; i<=nlstate;i++){
8200: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8201: } /* i */
8202: } /* end bad */
8203: }/* end else */
8204: sum=0.;sumr=0.;
8205: for (i=1; i<=nlstate;i++){
8206: sum+=mobaverage[(int)age][i][cptcod];
8207: sumr+=probs[(int)age][i][cptcod];
8208: }
8209: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8210: if(!firstA1){
8211: firstA1=1;
8212: 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);
8213: }
8214: 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 8215: } /* end bad */
8216: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8217: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8218: if(!firstA2){
8219: firstA2=1;
8220: 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);
8221: }
8222: 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 8223: } /* end bad */
8224: }/* age */
1.266 brouard 8225:
8226: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8227: sumnewm[cptcod]=0.;
1.266 brouard 8228: sumnewmr[cptcod]=0.;
1.222 brouard 8229: for (i=1; i<=nlstate;i++){
8230: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8231: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8232: }
8233: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8234: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8235: agemingoodr[cptcod]=age;
8236: for (i=1; i<=nlstate;i++)
8237: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8238: }else{ /* bad we change the value with the values of good ages */
8239: for (i=1; i<=nlstate;i++){
8240: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8241: } /* i */
8242: } /* end bad */
8243: }else{
8244: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8245: agemingood[cptcod]=age;
8246: }else{ /* bad */
8247: for (i=1; i<=nlstate;i++){
8248: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8249: } /* i */
8250: } /* end bad */
8251: }/* end else */
8252: sum=0.;sumr=0.;
8253: for (i=1; i<=nlstate;i++){
8254: sum+=mobaverage[(int)age][i][cptcod];
8255: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8256: }
1.266 brouard 8257: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8258: 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 8259: } /* end bad */
8260: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8261: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8262: 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 8263: } /* end bad */
8264: }/* age */
1.266 brouard 8265:
1.222 brouard 8266:
8267: for (age=bage; age<=fage; age++){
1.235 brouard 8268: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8269: sumnewp[cptcod]=0.;
8270: sumnewm[cptcod]=0.;
8271: for (i=1; i<=nlstate;i++){
8272: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8273: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8274: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8275: }
8276: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8277: }
8278: /* printf("\n"); */
8279: /* } */
1.266 brouard 8280:
1.222 brouard 8281: /* brutal averaging */
1.266 brouard 8282: /* for (i=1; i<=nlstate;i++){ */
8283: /* for (age=1; age<=bage; age++){ */
8284: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8285: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8286: /* } */
8287: /* for (age=fage; age<=AGESUP; age++){ */
8288: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8289: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8290: /* } */
8291: /* } /\* end i status *\/ */
8292: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8293: /* for (age=1; age<=AGESUP; age++){ */
8294: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8295: /* mobaverage[(int)age][i][cptcod]=0.; */
8296: /* } */
8297: /* } */
1.222 brouard 8298: }/* end cptcod */
1.266 brouard 8299: free_vector(agemaxgoodr,1, ncovcombmax);
8300: free_vector(agemaxgood,1, ncovcombmax);
8301: free_vector(agemingood,1, ncovcombmax);
8302: free_vector(agemingoodr,1, ncovcombmax);
8303: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8304: free_vector(sumnewm,1, ncovcombmax);
8305: free_vector(sumnewp,1, ncovcombmax);
8306: return 0;
8307: }/* End movingaverage */
1.218 brouard 8308:
1.126 brouard 8309:
1.296 ! brouard 8310: int date2dmy(double date,double *day, double *month, double *year){
! 8311: double yp=0., yp1=0., yp2=0.;
! 8312:
! 8313: yp1=modf(date,&yp);/* extracts integral of date in yp and
! 8314: fractional in yp1 */
! 8315: *year=yp;
! 8316: yp2=modf((yp1*12),&yp);
! 8317: *month=yp;
! 8318: yp1=modf((yp2*30.5),&yp);
! 8319: *day=yp;
! 8320: if(*day==0) *day=1;
! 8321: if(*month==0) *month=1;
! 8322: return;
! 8323: }
! 8324:
1.126 brouard 8325: /************** Forecasting ******************/
1.296 ! brouard 8326: /* 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)*/
! 8327: 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){
! 8328: /* dateintemean, mean date of interviews
! 8329: dateprojd, year, month, day of starting projection
! 8330: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8331: agemin, agemax range of age
8332: dateprev1 dateprev2 range of dates during which prevalence is computed
8333: */
1.296 ! brouard 8334: /* double anprojd, mprojd, jprojd; */
! 8335: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8336: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8337: double agec; /* generic age */
1.296 ! brouard 8338: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8339: double *popeffectif,*popcount;
8340: double ***p3mat;
1.218 brouard 8341: /* double ***mobaverage; */
1.126 brouard 8342: char fileresf[FILENAMELENGTH];
8343:
8344: agelim=AGESUP;
1.211 brouard 8345: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8346: in each health status at the date of interview (if between dateprev1 and dateprev2).
8347: We still use firstpass and lastpass as another selection.
8348: */
1.214 brouard 8349: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8350: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8351:
1.201 brouard 8352: strcpy(fileresf,"F_");
8353: strcat(fileresf,fileresu);
1.126 brouard 8354: if((ficresf=fopen(fileresf,"w"))==NULL) {
8355: printf("Problem with forecast resultfile: %s\n", fileresf);
8356: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8357: }
1.235 brouard 8358: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8359: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8360:
1.225 brouard 8361: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8362:
8363:
8364: stepsize=(int) (stepm+YEARM-1)/YEARM;
8365: if (stepm<=12) stepsize=1;
8366: if(estepm < stepm){
8367: printf ("Problem %d lower than %d\n",estepm, stepm);
8368: }
1.270 brouard 8369: else{
8370: hstepm=estepm;
8371: }
8372: if(estepm > stepm){ /* Yes every two year */
8373: stepsize=2;
8374: }
1.296 ! brouard 8375: hstepm=hstepm/stepm;
1.126 brouard 8376:
1.296 ! brouard 8377:
! 8378: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
! 8379: /* fractional in yp1 *\/ */
! 8380: /* aintmean=yp; */
! 8381: /* yp2=modf((yp1*12),&yp); */
! 8382: /* mintmean=yp; */
! 8383: /* yp1=modf((yp2*30.5),&yp); */
! 8384: /* jintmean=yp; */
! 8385: /* if(jintmean==0) jintmean=1; */
! 8386: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8387:
1.296 ! brouard 8388:
! 8389: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
! 8390: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
! 8391: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8392: i1=pow(2,cptcoveff);
1.126 brouard 8393: if (cptcovn < 1){i1=1;}
8394:
1.296 ! brouard 8395: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8396:
8397: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8398:
1.126 brouard 8399: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8400: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8401: for(k=1; k<=i1;k++){
1.253 brouard 8402: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8403: continue;
1.227 brouard 8404: if(invalidvarcomb[k]){
8405: printf("\nCombination (%d) projection ignored because no cases \n",k);
8406: continue;
8407: }
8408: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8409: for(j=1;j<=cptcoveff;j++) {
8410: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8411: }
1.235 brouard 8412: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8413: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8414: }
1.227 brouard 8415: fprintf(ficresf," yearproj age");
8416: for(j=1; j<=nlstate+ndeath;j++){
8417: for(i=1; i<=nlstate;i++)
8418: fprintf(ficresf," p%d%d",i,j);
8419: fprintf(ficresf," wp.%d",j);
8420: }
1.296 ! brouard 8421: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8422: fprintf(ficresf,"\n");
1.296 ! brouard 8423: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8424: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8425: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8426: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8427: nhstepm = nhstepm/hstepm;
8428: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8429: oldm=oldms;savm=savms;
1.268 brouard 8430: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8431: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8432: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8433: for (h=0; h<=nhstepm; h++){
8434: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8435: break;
8436: }
8437: }
8438: fprintf(ficresf,"\n");
8439: for(j=1;j<=cptcoveff;j++)
8440: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 ! brouard 8441: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8442:
8443: for(j=1; j<=nlstate+ndeath;j++) {
8444: ppij=0.;
8445: for(i=1; i<=nlstate;i++) {
1.278 brouard 8446: if (mobilav>=1)
8447: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8448: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8449: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8450: }
1.268 brouard 8451: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8452: } /* end i */
8453: fprintf(ficresf," %.3f", ppij);
8454: }/* end j */
1.227 brouard 8455: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8456: } /* end agec */
1.266 brouard 8457: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8458: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8459: } /* end yearp */
8460: } /* end k */
1.219 brouard 8461:
1.126 brouard 8462: fclose(ficresf);
1.215 brouard 8463: printf("End of Computing forecasting \n");
8464: fprintf(ficlog,"End of Computing forecasting\n");
8465:
1.126 brouard 8466: }
8467:
1.269 brouard 8468: /************** Back Forecasting ******************/
1.296 ! brouard 8469: /* 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){ */
! 8470: 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){
! 8471: /* back1, year, month, day of starting backprojection
1.267 brouard 8472: agemin, agemax range of age
8473: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8474: anback2 year of end of backprojection (same day and month as back1).
8475: prevacurrent and prev are prevalences.
1.267 brouard 8476: */
8477: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8478: double agec; /* generic age */
1.296 ! brouard 8479: double agelim, ppij, ppi, yp,yp1,yp2,jintmean,mintmean,aintmean;
1.267 brouard 8480: double *popeffectif,*popcount;
8481: double ***p3mat;
8482: /* double ***mobaverage; */
8483: char fileresfb[FILENAMELENGTH];
8484:
1.268 brouard 8485: agelim=AGEINF;
1.267 brouard 8486: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8487: in each health status at the date of interview (if between dateprev1 and dateprev2).
8488: We still use firstpass and lastpass as another selection.
8489: */
8490: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8491: /* firstpass, lastpass, stepm, weightopt, model); */
8492:
8493: /*Do we need to compute prevalence again?*/
8494:
8495: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8496:
8497: strcpy(fileresfb,"FB_");
8498: strcat(fileresfb,fileresu);
8499: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8500: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8501: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8502: }
8503: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8504: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8505:
8506: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8507:
8508:
8509: stepsize=(int) (stepm+YEARM-1)/YEARM;
8510: if (stepm<=12) stepsize=1;
8511: if(estepm < stepm){
8512: printf ("Problem %d lower than %d\n",estepm, stepm);
8513: }
1.270 brouard 8514: else{
8515: hstepm=estepm;
8516: }
8517: if(estepm >= stepm){ /* Yes every two year */
8518: stepsize=2;
8519: }
1.267 brouard 8520:
8521: hstepm=hstepm/stepm;
1.296 ! brouard 8522: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
! 8523: /* fractional in yp1 *\/ */
! 8524: /* aintmean=yp; */
! 8525: /* yp2=modf((yp1*12),&yp); */
! 8526: /* mintmean=yp; */
! 8527: /* yp1=modf((yp2*30.5),&yp); */
! 8528: /* jintmean=yp; */
! 8529: /* if(jintmean==0) jintmean=1; */
! 8530: /* if(mintmean==0) jintmean=1; */
1.267 brouard 8531:
8532: i1=pow(2,cptcoveff);
8533: if (cptcovn < 1){i1=1;}
8534:
1.296 ! brouard 8535: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
! 8536: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8537:
8538: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8539:
8540: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8541: for(k=1; k<=i1;k++){
8542: if(i1 != 1 && TKresult[nres]!= k)
8543: continue;
8544: if(invalidvarcomb[k]){
8545: printf("\nCombination (%d) projection ignored because no cases \n",k);
8546: continue;
8547: }
1.268 brouard 8548: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8549: for(j=1;j<=cptcoveff;j++) {
8550: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8551: }
8552: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8553: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8554: }
8555: fprintf(ficresfb," yearbproj age");
8556: for(j=1; j<=nlstate+ndeath;j++){
8557: for(i=1; i<=nlstate;i++)
1.268 brouard 8558: fprintf(ficresfb," b%d%d",i,j);
8559: fprintf(ficresfb," b.%d",j);
1.267 brouard 8560: }
1.296 ! brouard 8561: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 8562: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8563: fprintf(ficresfb,"\n");
1.296 ! brouard 8564: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 8565: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8566: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8567: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8568: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8569: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8570: nhstepm = nhstepm/hstepm;
8571: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8572: oldm=oldms;savm=savms;
1.268 brouard 8573: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8574: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8575: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8576: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8577: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8578: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8579: for (h=0; h<=nhstepm; h++){
1.268 brouard 8580: if (h*hstepm/YEARM*stepm ==-yearp) {
8581: break;
8582: }
8583: }
8584: fprintf(ficresfb,"\n");
8585: for(j=1;j<=cptcoveff;j++)
8586: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 ! brouard 8587: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 8588: for(i=1; i<=nlstate+ndeath;i++) {
8589: ppij=0.;ppi=0.;
8590: for(j=1; j<=nlstate;j++) {
8591: /* if (mobilav==1) */
1.269 brouard 8592: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8593: ppi=ppi+prevacurrent[(int)agec][j][k];
8594: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8595: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8596: /* else { */
8597: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8598: /* } */
1.268 brouard 8599: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8600: } /* end j */
8601: if(ppi <0.99){
8602: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8603: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8604: }
8605: fprintf(ficresfb," %.3f", ppij);
8606: }/* end j */
1.267 brouard 8607: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8608: } /* end agec */
8609: } /* end yearp */
8610: } /* end k */
1.217 brouard 8611:
1.267 brouard 8612: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8613:
1.267 brouard 8614: fclose(ficresfb);
8615: printf("End of Computing Back forecasting \n");
8616: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8617:
1.267 brouard 8618: }
1.217 brouard 8619:
1.269 brouard 8620: /* Variance of prevalence limit: varprlim */
8621: 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 8622: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8623:
8624: char fileresvpl[FILENAMELENGTH];
8625: FILE *ficresvpl;
8626: double **oldm, **savm;
8627: double **varpl; /* Variances of prevalence limits by age */
8628: int i1, k, nres, j ;
8629:
8630: strcpy(fileresvpl,"VPL_");
8631: strcat(fileresvpl,fileresu);
8632: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8633: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8634: exit(0);
8635: }
1.288 brouard 8636: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8637: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8638:
8639: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8640: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8641:
8642: i1=pow(2,cptcoveff);
8643: if (cptcovn < 1){i1=1;}
8644:
8645: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8646: for(k=1; k<=i1;k++){
8647: if(i1 != 1 && TKresult[nres]!= k)
8648: continue;
8649: fprintf(ficresvpl,"\n#****** ");
8650: printf("\n#****** ");
8651: fprintf(ficlog,"\n#****** ");
8652: for(j=1;j<=cptcoveff;j++) {
8653: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8654: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8655: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8656: }
8657: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8658: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8659: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8660: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8661: }
8662: fprintf(ficresvpl,"******\n");
8663: printf("******\n");
8664: fprintf(ficlog,"******\n");
8665:
8666: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8667: oldm=oldms;savm=savms;
8668: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8669: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8670: /*}*/
8671: }
8672:
8673: fclose(ficresvpl);
1.288 brouard 8674: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8675: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8676:
8677: }
8678: /* Variance of back prevalence: varbprlim */
8679: 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){
8680: /*------- Variance of back (stable) prevalence------*/
8681:
8682: char fileresvbl[FILENAMELENGTH];
8683: FILE *ficresvbl;
8684:
8685: double **oldm, **savm;
8686: double **varbpl; /* Variances of back prevalence limits by age */
8687: int i1, k, nres, j ;
8688:
8689: strcpy(fileresvbl,"VBL_");
8690: strcat(fileresvbl,fileresu);
8691: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8692: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8693: exit(0);
8694: }
8695: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8696: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8697:
8698:
8699: i1=pow(2,cptcoveff);
8700: if (cptcovn < 1){i1=1;}
8701:
8702: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8703: for(k=1; k<=i1;k++){
8704: if(i1 != 1 && TKresult[nres]!= k)
8705: continue;
8706: fprintf(ficresvbl,"\n#****** ");
8707: printf("\n#****** ");
8708: fprintf(ficlog,"\n#****** ");
8709: for(j=1;j<=cptcoveff;j++) {
8710: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8711: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8712: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8713: }
8714: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8715: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8716: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8717: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8718: }
8719: fprintf(ficresvbl,"******\n");
8720: printf("******\n");
8721: fprintf(ficlog,"******\n");
8722:
8723: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8724: oldm=oldms;savm=savms;
8725:
8726: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8727: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8728: /*}*/
8729: }
8730:
8731: fclose(ficresvbl);
8732: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8733: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8734:
8735: } /* End of varbprlim */
8736:
1.126 brouard 8737: /************** Forecasting *****not tested NB*************/
1.227 brouard 8738: /* 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 8739:
1.227 brouard 8740: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8741: /* int *popage; */
8742: /* double calagedatem, agelim, kk1, kk2; */
8743: /* double *popeffectif,*popcount; */
8744: /* double ***p3mat,***tabpop,***tabpopprev; */
8745: /* /\* double ***mobaverage; *\/ */
8746: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8747:
1.227 brouard 8748: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8749: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8750: /* agelim=AGESUP; */
8751: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8752:
1.227 brouard 8753: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8754:
8755:
1.227 brouard 8756: /* strcpy(filerespop,"POP_"); */
8757: /* strcat(filerespop,fileresu); */
8758: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8759: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8760: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8761: /* } */
8762: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8763: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8764:
1.227 brouard 8765: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8766:
1.227 brouard 8767: /* /\* if (mobilav!=0) { *\/ */
8768: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8769: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8770: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8771: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8772: /* /\* } *\/ */
8773: /* /\* } *\/ */
1.126 brouard 8774:
1.227 brouard 8775: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8776: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8777:
1.227 brouard 8778: /* agelim=AGESUP; */
1.126 brouard 8779:
1.227 brouard 8780: /* hstepm=1; */
8781: /* hstepm=hstepm/stepm; */
1.218 brouard 8782:
1.227 brouard 8783: /* if (popforecast==1) { */
8784: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8785: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8786: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8787: /* } */
8788: /* popage=ivector(0,AGESUP); */
8789: /* popeffectif=vector(0,AGESUP); */
8790: /* popcount=vector(0,AGESUP); */
1.126 brouard 8791:
1.227 brouard 8792: /* i=1; */
8793: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8794:
1.227 brouard 8795: /* imx=i; */
8796: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8797: /* } */
1.218 brouard 8798:
1.227 brouard 8799: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8800: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8801: /* k=k+1; */
8802: /* fprintf(ficrespop,"\n#******"); */
8803: /* for(j=1;j<=cptcoveff;j++) { */
8804: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8805: /* } */
8806: /* fprintf(ficrespop,"******\n"); */
8807: /* fprintf(ficrespop,"# Age"); */
8808: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8809: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8810:
1.227 brouard 8811: /* for (cpt=0; cpt<=0;cpt++) { */
8812: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8813:
1.227 brouard 8814: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8815: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8816: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8817:
1.227 brouard 8818: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8819: /* oldm=oldms;savm=savms; */
8820: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8821:
1.227 brouard 8822: /* for (h=0; h<=nhstepm; h++){ */
8823: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8824: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8825: /* } */
8826: /* for(j=1; j<=nlstate+ndeath;j++) { */
8827: /* kk1=0.;kk2=0; */
8828: /* for(i=1; i<=nlstate;i++) { */
8829: /* if (mobilav==1) */
8830: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8831: /* else { */
8832: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8833: /* } */
8834: /* } */
8835: /* if (h==(int)(calagedatem+12*cpt)){ */
8836: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8837: /* /\*fprintf(ficrespop," %.3f", kk1); */
8838: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8839: /* } */
8840: /* } */
8841: /* for(i=1; i<=nlstate;i++){ */
8842: /* kk1=0.; */
8843: /* for(j=1; j<=nlstate;j++){ */
8844: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8845: /* } */
8846: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8847: /* } */
1.218 brouard 8848:
1.227 brouard 8849: /* if (h==(int)(calagedatem+12*cpt)) */
8850: /* for(j=1; j<=nlstate;j++) */
8851: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8852: /* } */
8853: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8854: /* } */
8855: /* } */
1.218 brouard 8856:
1.227 brouard 8857: /* /\******\/ */
1.218 brouard 8858:
1.227 brouard 8859: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8860: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8861: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8862: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8863: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8864:
1.227 brouard 8865: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8866: /* oldm=oldms;savm=savms; */
8867: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8868: /* for (h=0; h<=nhstepm; h++){ */
8869: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8870: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8871: /* } */
8872: /* for(j=1; j<=nlstate+ndeath;j++) { */
8873: /* kk1=0.;kk2=0; */
8874: /* for(i=1; i<=nlstate;i++) { */
8875: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8876: /* } */
8877: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8878: /* } */
8879: /* } */
8880: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8881: /* } */
8882: /* } */
8883: /* } */
8884: /* } */
1.218 brouard 8885:
1.227 brouard 8886: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8887:
1.227 brouard 8888: /* if (popforecast==1) { */
8889: /* free_ivector(popage,0,AGESUP); */
8890: /* free_vector(popeffectif,0,AGESUP); */
8891: /* free_vector(popcount,0,AGESUP); */
8892: /* } */
8893: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8894: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8895: /* fclose(ficrespop); */
8896: /* } /\* End of popforecast *\/ */
1.218 brouard 8897:
1.126 brouard 8898: int fileappend(FILE *fichier, char *optionfich)
8899: {
8900: if((fichier=fopen(optionfich,"a"))==NULL) {
8901: printf("Problem with file: %s\n", optionfich);
8902: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8903: return (0);
8904: }
8905: fflush(fichier);
8906: return (1);
8907: }
8908:
8909:
8910: /**************** function prwizard **********************/
8911: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8912: {
8913:
8914: /* Wizard to print covariance matrix template */
8915:
1.164 brouard 8916: char ca[32], cb[32];
8917: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8918: int numlinepar;
8919:
8920: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8921: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8922: for(i=1; i <=nlstate; i++){
8923: jj=0;
8924: for(j=1; j <=nlstate+ndeath; j++){
8925: if(j==i) continue;
8926: jj++;
8927: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8928: printf("%1d%1d",i,j);
8929: fprintf(ficparo,"%1d%1d",i,j);
8930: for(k=1; k<=ncovmodel;k++){
8931: /* printf(" %lf",param[i][j][k]); */
8932: /* fprintf(ficparo," %lf",param[i][j][k]); */
8933: printf(" 0.");
8934: fprintf(ficparo," 0.");
8935: }
8936: printf("\n");
8937: fprintf(ficparo,"\n");
8938: }
8939: }
8940: printf("# Scales (for hessian or gradient estimation)\n");
8941: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8942: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8943: for(i=1; i <=nlstate; i++){
8944: jj=0;
8945: for(j=1; j <=nlstate+ndeath; j++){
8946: if(j==i) continue;
8947: jj++;
8948: fprintf(ficparo,"%1d%1d",i,j);
8949: printf("%1d%1d",i,j);
8950: fflush(stdout);
8951: for(k=1; k<=ncovmodel;k++){
8952: /* printf(" %le",delti3[i][j][k]); */
8953: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8954: printf(" 0.");
8955: fprintf(ficparo," 0.");
8956: }
8957: numlinepar++;
8958: printf("\n");
8959: fprintf(ficparo,"\n");
8960: }
8961: }
8962: printf("# Covariance matrix\n");
8963: /* # 121 Var(a12)\n\ */
8964: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8965: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8966: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8967: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8968: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8969: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8970: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8971: fflush(stdout);
8972: fprintf(ficparo,"# Covariance matrix\n");
8973: /* # 121 Var(a12)\n\ */
8974: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8975: /* # ...\n\ */
8976: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8977:
8978: for(itimes=1;itimes<=2;itimes++){
8979: jj=0;
8980: for(i=1; i <=nlstate; i++){
8981: for(j=1; j <=nlstate+ndeath; j++){
8982: if(j==i) continue;
8983: for(k=1; k<=ncovmodel;k++){
8984: jj++;
8985: ca[0]= k+'a'-1;ca[1]='\0';
8986: if(itimes==1){
8987: printf("#%1d%1d%d",i,j,k);
8988: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8989: }else{
8990: printf("%1d%1d%d",i,j,k);
8991: fprintf(ficparo,"%1d%1d%d",i,j,k);
8992: /* printf(" %.5le",matcov[i][j]); */
8993: }
8994: ll=0;
8995: for(li=1;li <=nlstate; li++){
8996: for(lj=1;lj <=nlstate+ndeath; lj++){
8997: if(lj==li) continue;
8998: for(lk=1;lk<=ncovmodel;lk++){
8999: ll++;
9000: if(ll<=jj){
9001: cb[0]= lk +'a'-1;cb[1]='\0';
9002: if(ll<jj){
9003: if(itimes==1){
9004: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9005: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9006: }else{
9007: printf(" 0.");
9008: fprintf(ficparo," 0.");
9009: }
9010: }else{
9011: if(itimes==1){
9012: printf(" Var(%s%1d%1d)",ca,i,j);
9013: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9014: }else{
9015: printf(" 0.");
9016: fprintf(ficparo," 0.");
9017: }
9018: }
9019: }
9020: } /* end lk */
9021: } /* end lj */
9022: } /* end li */
9023: printf("\n");
9024: fprintf(ficparo,"\n");
9025: numlinepar++;
9026: } /* end k*/
9027: } /*end j */
9028: } /* end i */
9029: } /* end itimes */
9030:
9031: } /* end of prwizard */
9032: /******************* Gompertz Likelihood ******************************/
9033: double gompertz(double x[])
9034: {
9035: double A,B,L=0.0,sump=0.,num=0.;
9036: int i,n=0; /* n is the size of the sample */
9037:
1.220 brouard 9038: for (i=1;i<=imx ; i++) {
1.126 brouard 9039: sump=sump+weight[i];
9040: /* sump=sump+1;*/
9041: num=num+1;
9042: }
9043:
9044:
9045: /* for (i=0; i<=imx; i++)
9046: 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]);*/
9047:
9048: for (i=1;i<=imx ; i++)
9049: {
9050: if (cens[i] == 1 && wav[i]>1)
9051: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9052:
9053: if (cens[i] == 0 && wav[i]>1)
9054: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
9055: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
9056:
9057: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9058: if (wav[i] > 1 ) { /* ??? */
9059: L=L+A*weight[i];
9060: /* 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]);*/
9061: }
9062: }
9063:
9064: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9065:
9066: return -2*L*num/sump;
9067: }
9068:
1.136 brouard 9069: #ifdef GSL
9070: /******************* Gompertz_f Likelihood ******************************/
9071: double gompertz_f(const gsl_vector *v, void *params)
9072: {
9073: double A,B,LL=0.0,sump=0.,num=0.;
9074: double *x= (double *) v->data;
9075: int i,n=0; /* n is the size of the sample */
9076:
9077: for (i=0;i<=imx-1 ; i++) {
9078: sump=sump+weight[i];
9079: /* sump=sump+1;*/
9080: num=num+1;
9081: }
9082:
9083:
9084: /* for (i=0; i<=imx; i++)
9085: 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]);*/
9086: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9087: for (i=1;i<=imx ; i++)
9088: {
9089: if (cens[i] == 1 && wav[i]>1)
9090: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9091:
9092: if (cens[i] == 0 && wav[i]>1)
9093: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9094: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9095:
9096: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9097: if (wav[i] > 1 ) { /* ??? */
9098: LL=LL+A*weight[i];
9099: /* 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]);*/
9100: }
9101: }
9102:
9103: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9104: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9105:
9106: return -2*LL*num/sump;
9107: }
9108: #endif
9109:
1.126 brouard 9110: /******************* Printing html file ***********/
1.201 brouard 9111: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9112: int lastpass, int stepm, int weightopt, char model[],\
9113: int imx, double p[],double **matcov,double agemortsup){
9114: int i,k;
9115:
9116: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9117: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9118: for (i=1;i<=2;i++)
9119: 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 9120: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9121: fprintf(fichtm,"</ul>");
9122:
9123: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9124:
9125: 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>");
9126:
9127: for (k=agegomp;k<(agemortsup-2);k++)
9128: 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]);
9129:
9130:
9131: fflush(fichtm);
9132: }
9133:
9134: /******************* Gnuplot file **************/
1.201 brouard 9135: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9136:
9137: char dirfileres[132],optfileres[132];
1.164 brouard 9138:
1.126 brouard 9139: int ng;
9140:
9141:
9142: /*#ifdef windows */
9143: fprintf(ficgp,"cd \"%s\" \n",pathc);
9144: /*#endif */
9145:
9146:
9147: strcpy(dirfileres,optionfilefiname);
9148: strcpy(optfileres,"vpl");
1.199 brouard 9149: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9150: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9151: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9152: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9153: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9154:
9155: }
9156:
1.136 brouard 9157: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9158: {
1.126 brouard 9159:
1.136 brouard 9160: /*-------- data file ----------*/
9161: FILE *fic;
9162: char dummy[]=" ";
1.240 brouard 9163: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9164: int lstra;
1.136 brouard 9165: int linei, month, year,iout;
9166: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9167: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9168: char *stratrunc;
1.223 brouard 9169:
1.240 brouard 9170: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9171: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9172:
1.240 brouard 9173: for(v=1; v <=ncovcol;v++){
9174: DummyV[v]=0;
9175: FixedV[v]=0;
9176: }
9177: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9178: DummyV[v]=1;
9179: FixedV[v]=0;
9180: }
9181: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9182: DummyV[v]=0;
9183: FixedV[v]=1;
9184: }
9185: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9186: DummyV[v]=1;
9187: FixedV[v]=1;
9188: }
9189: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9190: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9191: 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]);
9192: }
1.126 brouard 9193:
1.136 brouard 9194: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9195: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9196: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9197: }
1.126 brouard 9198:
1.136 brouard 9199: i=1;
9200: linei=0;
9201: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9202: linei=linei+1;
9203: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9204: if(line[j] == '\t')
9205: line[j] = ' ';
9206: }
9207: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9208: ;
9209: };
9210: line[j+1]=0; /* Trims blanks at end of line */
9211: if(line[0]=='#'){
9212: fprintf(ficlog,"Comment line\n%s\n",line);
9213: printf("Comment line\n%s\n",line);
9214: continue;
9215: }
9216: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9217: strcpy(line, linetmp);
1.223 brouard 9218:
9219: /* Loops on waves */
9220: for (j=maxwav;j>=1;j--){
9221: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9222: cutv(stra, strb, line, ' ');
9223: if(strb[0]=='.') { /* Missing value */
9224: lval=-1;
9225: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9226: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9227: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9228: 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);
9229: 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);
9230: return 1;
9231: }
9232: }else{
9233: errno=0;
9234: /* what_kind_of_number(strb); */
9235: dval=strtod(strb,&endptr);
9236: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9237: /* if(strb != endptr && *endptr == '\0') */
9238: /* dval=dlval; */
9239: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9240: if( strb[0]=='\0' || (*endptr != '\0')){
9241: 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);
9242: 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);
9243: return 1;
9244: }
9245: cotqvar[j][iv][i]=dval;
9246: cotvar[j][ntv+iv][i]=dval;
9247: }
9248: strcpy(line,stra);
1.223 brouard 9249: }/* end loop ntqv */
1.225 brouard 9250:
1.223 brouard 9251: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9252: cutv(stra, strb, line, ' ');
9253: if(strb[0]=='.') { /* Missing value */
9254: lval=-1;
9255: }else{
9256: errno=0;
9257: lval=strtol(strb,&endptr,10);
9258: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9259: if( strb[0]=='\0' || (*endptr != '\0')){
9260: 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);
9261: 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);
9262: return 1;
9263: }
9264: }
9265: if(lval <-1 || lval >1){
9266: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9267: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9268: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9269: For example, for multinomial values like 1, 2 and 3,\n \
9270: build V1=0 V2=0 for the reference value (1),\n \
9271: V1=1 V2=0 for (2) \n \
1.223 brouard 9272: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9273: output of IMaCh is often meaningless.\n \
1.223 brouard 9274: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9275: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9276: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9277: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9278: For example, for multinomial values like 1, 2 and 3,\n \
9279: build V1=0 V2=0 for the reference value (1),\n \
9280: V1=1 V2=0 for (2) \n \
1.223 brouard 9281: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9282: output of IMaCh is often meaningless.\n \
1.223 brouard 9283: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9284: return 1;
9285: }
9286: cotvar[j][iv][i]=(double)(lval);
9287: strcpy(line,stra);
1.223 brouard 9288: }/* end loop ntv */
1.225 brouard 9289:
1.223 brouard 9290: /* Statuses at wave */
1.137 brouard 9291: cutv(stra, strb, line, ' ');
1.223 brouard 9292: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9293: lval=-1;
1.136 brouard 9294: }else{
1.238 brouard 9295: errno=0;
9296: lval=strtol(strb,&endptr,10);
9297: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9298: if( strb[0]=='\0' || (*endptr != '\0')){
9299: 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);
9300: 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);
9301: return 1;
9302: }
1.136 brouard 9303: }
1.225 brouard 9304:
1.136 brouard 9305: s[j][i]=lval;
1.225 brouard 9306:
1.223 brouard 9307: /* Date of Interview */
1.136 brouard 9308: strcpy(line,stra);
9309: cutv(stra, strb,line,' ');
1.169 brouard 9310: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9311: }
1.169 brouard 9312: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9313: month=99;
9314: year=9999;
1.136 brouard 9315: }else{
1.225 brouard 9316: 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);
9317: 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);
9318: return 1;
1.136 brouard 9319: }
9320: anint[j][i]= (double) year;
9321: mint[j][i]= (double)month;
9322: strcpy(line,stra);
1.223 brouard 9323: } /* End loop on waves */
1.225 brouard 9324:
1.223 brouard 9325: /* Date of death */
1.136 brouard 9326: cutv(stra, strb,line,' ');
1.169 brouard 9327: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9328: }
1.169 brouard 9329: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9330: month=99;
9331: year=9999;
9332: }else{
1.141 brouard 9333: 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 9334: 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);
9335: return 1;
1.136 brouard 9336: }
9337: andc[i]=(double) year;
9338: moisdc[i]=(double) month;
9339: strcpy(line,stra);
9340:
1.223 brouard 9341: /* Date of birth */
1.136 brouard 9342: cutv(stra, strb,line,' ');
1.169 brouard 9343: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9344: }
1.169 brouard 9345: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9346: month=99;
9347: year=9999;
9348: }else{
1.141 brouard 9349: 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);
9350: 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 9351: return 1;
1.136 brouard 9352: }
9353: if (year==9999) {
1.141 brouard 9354: 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);
9355: 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 9356: return 1;
9357:
1.136 brouard 9358: }
9359: annais[i]=(double)(year);
9360: moisnais[i]=(double)(month);
9361: strcpy(line,stra);
1.225 brouard 9362:
1.223 brouard 9363: /* Sample weight */
1.136 brouard 9364: cutv(stra, strb,line,' ');
9365: errno=0;
9366: dval=strtod(strb,&endptr);
9367: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9368: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9369: 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 9370: fflush(ficlog);
9371: return 1;
9372: }
9373: weight[i]=dval;
9374: strcpy(line,stra);
1.225 brouard 9375:
1.223 brouard 9376: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9377: cutv(stra, strb, line, ' ');
9378: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9379: lval=-1;
1.223 brouard 9380: }else{
1.225 brouard 9381: errno=0;
9382: /* what_kind_of_number(strb); */
9383: dval=strtod(strb,&endptr);
9384: /* if(strb != endptr && *endptr == '\0') */
9385: /* dval=dlval; */
9386: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9387: if( strb[0]=='\0' || (*endptr != '\0')){
9388: 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);
9389: 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);
9390: return 1;
9391: }
9392: coqvar[iv][i]=dval;
1.226 brouard 9393: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9394: }
9395: strcpy(line,stra);
9396: }/* end loop nqv */
1.136 brouard 9397:
1.223 brouard 9398: /* Covariate values */
1.136 brouard 9399: for (j=ncovcol;j>=1;j--){
9400: cutv(stra, strb,line,' ');
1.223 brouard 9401: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9402: lval=-1;
1.136 brouard 9403: }else{
1.225 brouard 9404: errno=0;
9405: lval=strtol(strb,&endptr,10);
9406: if( strb[0]=='\0' || (*endptr != '\0')){
9407: 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);
9408: 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);
9409: return 1;
9410: }
1.136 brouard 9411: }
9412: if(lval <-1 || lval >1){
1.225 brouard 9413: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9414: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9415: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9416: For example, for multinomial values like 1, 2 and 3,\n \
9417: build V1=0 V2=0 for the reference value (1),\n \
9418: V1=1 V2=0 for (2) \n \
1.136 brouard 9419: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9420: output of IMaCh is often meaningless.\n \
1.136 brouard 9421: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9422: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9423: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9424: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9425: For example, for multinomial values like 1, 2 and 3,\n \
9426: build V1=0 V2=0 for the reference value (1),\n \
9427: V1=1 V2=0 for (2) \n \
1.136 brouard 9428: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9429: output of IMaCh is often meaningless.\n \
1.136 brouard 9430: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9431: return 1;
1.136 brouard 9432: }
9433: covar[j][i]=(double)(lval);
9434: strcpy(line,stra);
9435: }
9436: lstra=strlen(stra);
1.225 brouard 9437:
1.136 brouard 9438: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9439: stratrunc = &(stra[lstra-9]);
9440: num[i]=atol(stratrunc);
9441: }
9442: else
9443: num[i]=atol(stra);
9444: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9445: 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;}*/
9446:
9447: i=i+1;
9448: } /* End loop reading data */
1.225 brouard 9449:
1.136 brouard 9450: *imax=i-1; /* Number of individuals */
9451: fclose(fic);
1.225 brouard 9452:
1.136 brouard 9453: return (0);
1.164 brouard 9454: /* endread: */
1.225 brouard 9455: printf("Exiting readdata: ");
9456: fclose(fic);
9457: return (1);
1.223 brouard 9458: }
1.126 brouard 9459:
1.234 brouard 9460: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9461: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9462: while (*p2 == ' ')
1.234 brouard 9463: p2++;
9464: /* while ((*p1++ = *p2++) !=0) */
9465: /* ; */
9466: /* do */
9467: /* while (*p2 == ' ') */
9468: /* p2++; */
9469: /* while (*p1++ == *p2++); */
9470: *stri=p2;
1.145 brouard 9471: }
9472:
1.235 brouard 9473: int decoderesult ( char resultline[], int nres)
1.230 brouard 9474: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9475: {
1.235 brouard 9476: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9477: char resultsav[MAXLINE];
1.234 brouard 9478: int resultmodel[MAXLINE];
9479: int modelresult[MAXLINE];
1.230 brouard 9480: char stra[80], strb[80], strc[80], strd[80],stre[80];
9481:
1.234 brouard 9482: removefirstspace(&resultline);
1.233 brouard 9483: printf("decoderesult:%s\n",resultline);
1.230 brouard 9484:
9485: if (strstr(resultline,"v") !=0){
9486: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9487: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9488: return 1;
9489: }
9490: trimbb(resultsav, resultline);
9491: if (strlen(resultsav) >1){
9492: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9493: }
1.253 brouard 9494: if(j == 0){ /* Resultline but no = */
9495: TKresult[nres]=0; /* Combination for the nresult and the model */
9496: return (0);
9497: }
9498:
1.234 brouard 9499: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9500: printf("ERROR: the number of variable in the resultline, %d, differs from the number of variable used in the model line, %d.\n",j, cptcovs);
9501: fprintf(ficlog,"ERROR: the number of variable in the resultline, %d, differs from the number of variable used in the model line, %d.\n",j, cptcovs);
9502: }
9503: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9504: if(nbocc(resultsav,'=') >1){
9505: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9506: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9507: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9508: }else
9509: cutl(strc,strd,resultsav,'=');
1.230 brouard 9510: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9511:
1.230 brouard 9512: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9513: Tvarsel[k]=atoi(strc);
9514: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9515: /* cptcovsel++; */
9516: if (nbocc(stra,'=') >0)
9517: strcpy(resultsav,stra); /* and analyzes it */
9518: }
1.235 brouard 9519: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9520: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9521: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9522: match=0;
1.236 brouard 9523: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9524: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9525: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9526: match=1;
9527: break;
9528: }
9529: }
9530: if(match == 0){
9531: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9532: }
9533: }
9534: }
1.235 brouard 9535: /* Checking for missing or useless values in comparison of current model needs */
9536: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9537: match=0;
1.235 brouard 9538: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9539: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9540: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9541: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9542: ++match;
9543: }
9544: }
9545: }
9546: if(match == 0){
9547: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9548: }else if(match > 1){
9549: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9550: }
9551: }
1.235 brouard 9552:
1.234 brouard 9553: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9554: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9555: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9556: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9557: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9558: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9559: /* 1 0 0 0 */
9560: /* 2 1 0 0 */
9561: /* 3 0 1 0 */
9562: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9563: /* 5 0 0 1 */
9564: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9565: /* 7 0 1 1 */
9566: /* 8 1 1 1 */
1.237 brouard 9567: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9568: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9569: /* V5*age V5 known which value for nres? */
9570: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9571: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9572: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9573: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9574: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9575: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9576: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9577: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9578: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9579: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9580: k4++;;
9581: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9582: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9583: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9584: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9585: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9586: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9587: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9588: k4q++;;
9589: }
9590: }
1.234 brouard 9591:
1.235 brouard 9592: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9593: return (0);
9594: }
1.235 brouard 9595:
1.230 brouard 9596: int decodemodel( char model[], int lastobs)
9597: /**< This routine decodes the model and returns:
1.224 brouard 9598: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9599: * - nagesqr = 1 if age*age in the model, otherwise 0.
9600: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9601: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9602: * - cptcovage number of covariates with age*products =2
9603: * - cptcovs number of simple covariates
9604: * - 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
9605: * which is a new column after the 9 (ncovcol) variables.
9606: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9607: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9608: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9609: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9610: */
1.136 brouard 9611: {
1.238 brouard 9612: int i, j, k, ks, v;
1.227 brouard 9613: int j1, k1, k2, k3, k4;
1.136 brouard 9614: char modelsav[80];
1.145 brouard 9615: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9616: char *strpt;
1.136 brouard 9617:
1.145 brouard 9618: /*removespace(model);*/
1.136 brouard 9619: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9620: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9621: if (strstr(model,"AGE") !=0){
1.192 brouard 9622: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9623: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9624: return 1;
9625: }
1.141 brouard 9626: if (strstr(model,"v") !=0){
9627: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9628: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9629: return 1;
9630: }
1.187 brouard 9631: strcpy(modelsav,model);
9632: if ((strpt=strstr(model,"age*age")) !=0){
9633: printf(" strpt=%s, model=%s\n",strpt, model);
9634: if(strpt != model){
1.234 brouard 9635: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9636: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9637: corresponding column of parameters.\n",model);
1.234 brouard 9638: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9639: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9640: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9641: return 1;
1.225 brouard 9642: }
1.187 brouard 9643: nagesqr=1;
9644: if (strstr(model,"+age*age") !=0)
1.234 brouard 9645: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9646: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9647: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9648: else
1.234 brouard 9649: substrchaine(modelsav, model, "age*age");
1.187 brouard 9650: }else
9651: nagesqr=0;
9652: if (strlen(modelsav) >1){
9653: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9654: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9655: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9656: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9657: * cst, age and age*age
9658: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9659: /* including age products which are counted in cptcovage.
9660: * but the covariates which are products must be treated
9661: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9662: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9663: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9664:
9665:
1.187 brouard 9666: /* Design
9667: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9668: * < ncovcol=8 >
9669: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9670: * k= 1 2 3 4 5 6 7 8
9671: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9672: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9673: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9674: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9675: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9676: * Tage[++cptcovage]=k
9677: * if products, new covar are created after ncovcol with k1
9678: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9679: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9680: * 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
9681: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9682: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9683: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9684: * < ncovcol=8 >
9685: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9686: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9687: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9688: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9689: * p Tprod[1]@2={ 6, 5}
9690: *p Tvard[1][1]@4= {7, 8, 5, 6}
9691: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9692: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9693: *How to reorganize?
9694: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9695: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9696: * {2, 1, 4, 8, 5, 6, 3, 7}
9697: * Struct []
9698: */
1.225 brouard 9699:
1.187 brouard 9700: /* This loop fills the array Tvar from the string 'model'.*/
9701: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9702: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9703: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9704: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9705: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9706: /* k=1 Tvar[1]=2 (from V2) */
9707: /* k=5 Tvar[5] */
9708: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9709: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9710: /* } */
1.198 brouard 9711: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9712: /*
9713: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9714: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9715: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9716: }
1.187 brouard 9717: cptcovage=0;
9718: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9719: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9720: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9721: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9722: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9723: /*scanf("%d",i);*/
9724: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9725: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9726: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9727: /* covar is not filled and then is empty */
9728: cptcovprod--;
9729: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9730: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9731: Typevar[k]=1; /* 1 for age product */
9732: cptcovage++; /* Sums the number of covariates which include age as a product */
9733: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9734: /*printf("stre=%s ", stre);*/
9735: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9736: cptcovprod--;
9737: cutl(stre,strb,strc,'V');
9738: Tvar[k]=atoi(stre);
9739: Typevar[k]=1; /* 1 for age product */
9740: cptcovage++;
9741: Tage[cptcovage]=k;
9742: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9743: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9744: cptcovn++;
9745: cptcovprodnoage++;k1++;
9746: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9747: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9748: because this model-covariate is a construction we invent a new column
9749: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9750: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9751: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9752: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9753: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9754: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9755: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9756: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9757: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9758: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9759: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9760: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9761: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9762: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9763: for (i=1; i<=lastobs;i++){
9764: /* Computes the new covariate which is a product of
9765: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9766: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9767: }
9768: } /* End age is not in the model */
9769: } /* End if model includes a product */
9770: else { /* no more sum */
9771: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9772: /* scanf("%d",i);*/
9773: cutl(strd,strc,strb,'V');
9774: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9775: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9776: Tvar[k]=atoi(strd);
9777: Typevar[k]=0; /* 0 for simple covariates */
9778: }
9779: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9780: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9781: scanf("%d",i);*/
1.187 brouard 9782: } /* end of loop + on total covariates */
9783: } /* end if strlen(modelsave == 0) age*age might exist */
9784: } /* end if strlen(model == 0) */
1.136 brouard 9785:
9786: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9787: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9788:
1.136 brouard 9789: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9790: printf("cptcovprod=%d ", cptcovprod);
9791: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9792: scanf("%d ",i);*/
9793:
9794:
1.230 brouard 9795: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9796: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9797: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9798: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9799: k = 1 2 3 4 5 6 7 8 9
9800: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9801: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9802: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9803: Dummy[k] 1 0 0 0 3 1 1 2 3
9804: Tmodelind[combination of covar]=k;
1.225 brouard 9805: */
9806: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9807: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9808: /* 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 9809: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9810: printf("Model=%s\n\
9811: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9812: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9813: 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);
9814: fprintf(ficlog,"Model=%s\n\
9815: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9816: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9817: 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 9818: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9819: 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 */
9820: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9821: Fixed[k]= 0;
9822: Dummy[k]= 0;
1.225 brouard 9823: ncoveff++;
1.232 brouard 9824: ncovf++;
1.234 brouard 9825: nsd++;
9826: modell[k].maintype= FTYPE;
9827: TvarsD[nsd]=Tvar[k];
9828: TvarsDind[nsd]=k;
9829: TvarF[ncovf]=Tvar[k];
9830: TvarFind[ncovf]=k;
9831: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9832: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9833: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9834: Fixed[k]= 0;
9835: Dummy[k]= 0;
9836: ncoveff++;
9837: ncovf++;
9838: modell[k].maintype= FTYPE;
9839: TvarF[ncovf]=Tvar[k];
9840: TvarFind[ncovf]=k;
1.230 brouard 9841: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9842: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9843: }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 9844: Fixed[k]= 0;
9845: Dummy[k]= 1;
1.230 brouard 9846: nqfveff++;
1.234 brouard 9847: modell[k].maintype= FTYPE;
9848: modell[k].subtype= FQ;
9849: nsq++;
9850: TvarsQ[nsq]=Tvar[k];
9851: TvarsQind[nsq]=k;
1.232 brouard 9852: ncovf++;
1.234 brouard 9853: TvarF[ncovf]=Tvar[k];
9854: TvarFind[ncovf]=k;
1.231 brouard 9855: 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 9856: 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 9857: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9858: Fixed[k]= 1;
9859: Dummy[k]= 0;
1.225 brouard 9860: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9861: modell[k].maintype= VTYPE;
9862: modell[k].subtype= VD;
9863: nsd++;
9864: TvarsD[nsd]=Tvar[k];
9865: TvarsDind[nsd]=k;
9866: ncovv++; /* Only simple time varying variables */
9867: TvarV[ncovv]=Tvar[k];
1.242 brouard 9868: 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 9869: 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 */
9870: 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 9871: 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);
9872: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9873: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9874: Fixed[k]= 1;
9875: Dummy[k]= 1;
9876: nqtveff++;
9877: modell[k].maintype= VTYPE;
9878: modell[k].subtype= VQ;
9879: ncovv++; /* Only simple time varying variables */
9880: nsq++;
9881: TvarsQ[nsq]=Tvar[k];
9882: TvarsQind[nsq]=k;
9883: TvarV[ncovv]=Tvar[k];
1.242 brouard 9884: 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 9885: 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 */
9886: 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 9887: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9888: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9889: 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 9890: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9891: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9892: ncova++;
9893: TvarA[ncova]=Tvar[k];
9894: TvarAind[ncova]=k;
1.231 brouard 9895: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9896: Fixed[k]= 2;
9897: Dummy[k]= 2;
9898: modell[k].maintype= ATYPE;
9899: modell[k].subtype= APFD;
9900: /* ncoveff++; */
1.227 brouard 9901: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9902: Fixed[k]= 2;
9903: Dummy[k]= 3;
9904: modell[k].maintype= ATYPE;
9905: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9906: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9907: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9908: Fixed[k]= 3;
9909: Dummy[k]= 2;
9910: modell[k].maintype= ATYPE;
9911: modell[k].subtype= APVD; /* Product age * varying dummy */
9912: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9913: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9914: Fixed[k]= 3;
9915: Dummy[k]= 3;
9916: modell[k].maintype= ATYPE;
9917: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9918: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9919: }
9920: }else if (Typevar[k] == 2) { /* product without age */
9921: k1=Tposprod[k];
9922: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9923: if(Tvard[k1][2] <=ncovcol){
9924: Fixed[k]= 1;
9925: Dummy[k]= 0;
9926: modell[k].maintype= FTYPE;
9927: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9928: ncovf++; /* Fixed variables without age */
9929: TvarF[ncovf]=Tvar[k];
9930: TvarFind[ncovf]=k;
9931: }else if(Tvard[k1][2] <=ncovcol+nqv){
9932: Fixed[k]= 0; /* or 2 ?*/
9933: Dummy[k]= 1;
9934: modell[k].maintype= FTYPE;
9935: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9936: ncovf++; /* Varying variables without age */
9937: TvarF[ncovf]=Tvar[k];
9938: TvarFind[ncovf]=k;
9939: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9940: Fixed[k]= 1;
9941: Dummy[k]= 0;
9942: modell[k].maintype= VTYPE;
9943: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9944: ncovv++; /* Varying variables without age */
9945: TvarV[ncovv]=Tvar[k];
9946: TvarVind[ncovv]=k;
9947: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9948: Fixed[k]= 1;
9949: Dummy[k]= 1;
9950: modell[k].maintype= VTYPE;
9951: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9952: ncovv++; /* Varying variables without age */
9953: TvarV[ncovv]=Tvar[k];
9954: TvarVind[ncovv]=k;
9955: }
1.227 brouard 9956: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9957: if(Tvard[k1][2] <=ncovcol){
9958: Fixed[k]= 0; /* or 2 ?*/
9959: Dummy[k]= 1;
9960: modell[k].maintype= FTYPE;
9961: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9962: ncovf++; /* Fixed variables without age */
9963: TvarF[ncovf]=Tvar[k];
9964: TvarFind[ncovf]=k;
9965: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9966: Fixed[k]= 1;
9967: Dummy[k]= 1;
9968: modell[k].maintype= VTYPE;
9969: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9970: ncovv++; /* Varying variables without age */
9971: TvarV[ncovv]=Tvar[k];
9972: TvarVind[ncovv]=k;
9973: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9974: Fixed[k]= 1;
9975: Dummy[k]= 1;
9976: modell[k].maintype= VTYPE;
9977: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9978: ncovv++; /* Varying variables without age */
9979: TvarV[ncovv]=Tvar[k];
9980: TvarVind[ncovv]=k;
9981: ncovv++; /* Varying variables without age */
9982: TvarV[ncovv]=Tvar[k];
9983: TvarVind[ncovv]=k;
9984: }
1.227 brouard 9985: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9986: if(Tvard[k1][2] <=ncovcol){
9987: Fixed[k]= 1;
9988: Dummy[k]= 1;
9989: modell[k].maintype= VTYPE;
9990: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9991: ncovv++; /* Varying variables without age */
9992: TvarV[ncovv]=Tvar[k];
9993: TvarVind[ncovv]=k;
9994: }else if(Tvard[k1][2] <=ncovcol+nqv){
9995: Fixed[k]= 1;
9996: Dummy[k]= 1;
9997: modell[k].maintype= VTYPE;
9998: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9999: ncovv++; /* Varying variables without age */
10000: TvarV[ncovv]=Tvar[k];
10001: TvarVind[ncovv]=k;
10002: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10003: Fixed[k]= 1;
10004: Dummy[k]= 0;
10005: modell[k].maintype= VTYPE;
10006: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10007: ncovv++; /* Varying variables without age */
10008: TvarV[ncovv]=Tvar[k];
10009: TvarVind[ncovv]=k;
10010: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10011: Fixed[k]= 1;
10012: Dummy[k]= 1;
10013: modell[k].maintype= VTYPE;
10014: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10015: ncovv++; /* Varying variables without age */
10016: TvarV[ncovv]=Tvar[k];
10017: TvarVind[ncovv]=k;
10018: }
1.227 brouard 10019: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10020: if(Tvard[k1][2] <=ncovcol){
10021: Fixed[k]= 1;
10022: Dummy[k]= 1;
10023: modell[k].maintype= VTYPE;
10024: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10025: ncovv++; /* Varying variables without age */
10026: TvarV[ncovv]=Tvar[k];
10027: TvarVind[ncovv]=k;
10028: }else if(Tvard[k1][2] <=ncovcol+nqv){
10029: Fixed[k]= 1;
10030: Dummy[k]= 1;
10031: modell[k].maintype= VTYPE;
10032: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10033: ncovv++; /* Varying variables without age */
10034: TvarV[ncovv]=Tvar[k];
10035: TvarVind[ncovv]=k;
10036: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10037: Fixed[k]= 1;
10038: Dummy[k]= 1;
10039: modell[k].maintype= VTYPE;
10040: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10041: ncovv++; /* Varying variables without age */
10042: TvarV[ncovv]=Tvar[k];
10043: TvarVind[ncovv]=k;
10044: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10045: Fixed[k]= 1;
10046: Dummy[k]= 1;
10047: modell[k].maintype= VTYPE;
10048: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10049: ncovv++; /* Varying variables without age */
10050: TvarV[ncovv]=Tvar[k];
10051: TvarVind[ncovv]=k;
10052: }
1.227 brouard 10053: }else{
1.240 brouard 10054: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10055: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10056: } /*end k1*/
1.225 brouard 10057: }else{
1.226 brouard 10058: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10059: 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 10060: }
1.227 brouard 10061: 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 10062: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10063: 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]);
10064: }
10065: /* Searching for doublons in the model */
10066: for(k1=1; k1<= cptcovt;k1++){
10067: for(k2=1; k2 <k1;k2++){
1.285 brouard 10068: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10069: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10070: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10071: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10072: 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]);
10073: 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 10074: return(1);
10075: }
10076: }else if (Typevar[k1] ==2){
10077: k3=Tposprod[k1];
10078: k4=Tposprod[k2];
10079: 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])) ){
10080: 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]]);
10081: 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);
10082: return(1);
10083: }
10084: }
1.227 brouard 10085: }
10086: }
1.225 brouard 10087: }
10088: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10089: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10090: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10091: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10092: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10093: /*endread:*/
1.225 brouard 10094: printf("Exiting decodemodel: ");
10095: return (1);
1.136 brouard 10096: }
10097:
1.169 brouard 10098: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10099: {/* Check ages at death */
1.136 brouard 10100: int i, m;
1.218 brouard 10101: int firstone=0;
10102:
1.136 brouard 10103: for (i=1; i<=imx; i++) {
10104: for(m=2; (m<= maxwav); m++) {
10105: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10106: anint[m][i]=9999;
1.216 brouard 10107: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10108: s[m][i]=-1;
1.136 brouard 10109: }
10110: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10111: *nberr = *nberr + 1;
1.218 brouard 10112: if(firstone == 0){
10113: firstone=1;
1.260 brouard 10114: 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 10115: }
1.262 brouard 10116: 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 10117: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10118: }
10119: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10120: (*nberr)++;
1.259 brouard 10121: 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 10122: 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 10123: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10124: }
10125: }
10126: }
10127:
10128: for (i=1; i<=imx; i++) {
10129: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10130: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10131: 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 10132: if (s[m][i] >= nlstate+1) {
1.169 brouard 10133: if(agedc[i]>0){
10134: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10135: agev[m][i]=agedc[i];
1.214 brouard 10136: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10137: }else {
1.136 brouard 10138: if ((int)andc[i]!=9999){
10139: nbwarn++;
10140: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10141: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10142: agev[m][i]=-1;
10143: }
10144: }
1.169 brouard 10145: } /* agedc > 0 */
1.214 brouard 10146: } /* end if */
1.136 brouard 10147: else if(s[m][i] !=9){ /* Standard case, age in fractional
10148: years but with the precision of a month */
10149: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10150: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10151: agev[m][i]=1;
10152: else if(agev[m][i] < *agemin){
10153: *agemin=agev[m][i];
10154: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10155: }
10156: else if(agev[m][i] >*agemax){
10157: *agemax=agev[m][i];
1.156 brouard 10158: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10159: }
10160: /*agev[m][i]=anint[m][i]-annais[i];*/
10161: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10162: } /* en if 9*/
1.136 brouard 10163: else { /* =9 */
1.214 brouard 10164: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10165: agev[m][i]=1;
10166: s[m][i]=-1;
10167: }
10168: }
1.214 brouard 10169: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10170: agev[m][i]=1;
1.214 brouard 10171: else{
10172: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10173: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10174: agev[m][i]=0;
10175: }
10176: } /* End for lastpass */
10177: }
1.136 brouard 10178:
10179: for (i=1; i<=imx; i++) {
10180: for(m=firstpass; (m<=lastpass); m++){
10181: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10182: (*nberr)++;
1.136 brouard 10183: 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);
10184: 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);
10185: return 1;
10186: }
10187: }
10188: }
10189:
10190: /*for (i=1; i<=imx; i++){
10191: for (m=firstpass; (m<lastpass); m++){
10192: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10193: }
10194:
10195: }*/
10196:
10197:
1.139 brouard 10198: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10199: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10200:
10201: return (0);
1.164 brouard 10202: /* endread:*/
1.136 brouard 10203: printf("Exiting calandcheckages: ");
10204: return (1);
10205: }
10206:
1.172 brouard 10207: #if defined(_MSC_VER)
10208: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10209: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10210: //#include "stdafx.h"
10211: //#include <stdio.h>
10212: //#include <tchar.h>
10213: //#include <windows.h>
10214: //#include <iostream>
10215: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10216:
10217: LPFN_ISWOW64PROCESS fnIsWow64Process;
10218:
10219: BOOL IsWow64()
10220: {
10221: BOOL bIsWow64 = FALSE;
10222:
10223: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10224: // (HANDLE, PBOOL);
10225:
10226: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10227:
10228: HMODULE module = GetModuleHandle(_T("kernel32"));
10229: const char funcName[] = "IsWow64Process";
10230: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10231: GetProcAddress(module, funcName);
10232:
10233: if (NULL != fnIsWow64Process)
10234: {
10235: if (!fnIsWow64Process(GetCurrentProcess(),
10236: &bIsWow64))
10237: //throw std::exception("Unknown error");
10238: printf("Unknown error\n");
10239: }
10240: return bIsWow64 != FALSE;
10241: }
10242: #endif
1.177 brouard 10243:
1.191 brouard 10244: void syscompilerinfo(int logged)
1.292 brouard 10245: {
10246: #include <stdint.h>
10247:
10248: /* #include "syscompilerinfo.h"*/
1.185 brouard 10249: /* command line Intel compiler 32bit windows, XP compatible:*/
10250: /* /GS /W3 /Gy
10251: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10252: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10253: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10254: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10255: */
10256: /* 64 bits */
1.185 brouard 10257: /*
10258: /GS /W3 /Gy
10259: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10260: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10261: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10262: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10263: /* Optimization are useless and O3 is slower than O2 */
10264: /*
10265: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10266: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10267: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10268: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10269: */
1.186 brouard 10270: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10271: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10272: /PDB:"visual studio
10273: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10274: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10275: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10276: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10277: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10278: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10279: uiAccess='false'"
10280: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10281: /NOLOGO /TLBID:1
10282: */
1.292 brouard 10283:
10284:
1.177 brouard 10285: #if defined __INTEL_COMPILER
1.178 brouard 10286: #if defined(__GNUC__)
10287: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10288: #endif
1.177 brouard 10289: #elif defined(__GNUC__)
1.179 brouard 10290: #ifndef __APPLE__
1.174 brouard 10291: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10292: #endif
1.177 brouard 10293: struct utsname sysInfo;
1.178 brouard 10294: int cross = CROSS;
10295: if (cross){
10296: printf("Cross-");
1.191 brouard 10297: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10298: }
1.174 brouard 10299: #endif
10300:
1.191 brouard 10301: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10302: #if defined(__clang__)
1.191 brouard 10303: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10304: #endif
10305: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10306: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10307: #endif
10308: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10309: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10310: #endif
10311: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10312: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10313: #endif
10314: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10315: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10316: #endif
10317: #if defined(_MSC_VER)
1.191 brouard 10318: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10319: #endif
10320: #if defined(__PGI)
1.191 brouard 10321: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10322: #endif
10323: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10324: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10325: #endif
1.191 brouard 10326: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10327:
1.167 brouard 10328: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10329: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10330: // Windows (x64 and x86)
1.191 brouard 10331: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10332: #elif __unix__ // all unices, not all compilers
10333: // Unix
1.191 brouard 10334: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10335: #elif __linux__
10336: // linux
1.191 brouard 10337: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10338: #elif __APPLE__
1.174 brouard 10339: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10340: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10341: #endif
10342:
10343: /* __MINGW32__ */
10344: /* __CYGWIN__ */
10345: /* __MINGW64__ */
10346: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10347: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10348: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10349: /* _WIN64 // Defined for applications for Win64. */
10350: /* _M_X64 // Defined for compilations that target x64 processors. */
10351: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10352:
1.167 brouard 10353: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10354: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10355: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10356: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10357: #else
1.191 brouard 10358: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10359: #endif
10360:
1.169 brouard 10361: #if defined(__GNUC__)
10362: # if defined(__GNUC_PATCHLEVEL__)
10363: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10364: + __GNUC_MINOR__ * 100 \
10365: + __GNUC_PATCHLEVEL__)
10366: # else
10367: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10368: + __GNUC_MINOR__ * 100)
10369: # endif
1.174 brouard 10370: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10371: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10372:
10373: if (uname(&sysInfo) != -1) {
10374: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10375: 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 10376: }
10377: else
10378: perror("uname() error");
1.179 brouard 10379: //#ifndef __INTEL_COMPILER
10380: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10381: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10382: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10383: #endif
1.169 brouard 10384: #endif
1.172 brouard 10385:
1.286 brouard 10386: // void main ()
1.172 brouard 10387: // {
1.169 brouard 10388: #if defined(_MSC_VER)
1.174 brouard 10389: if (IsWow64()){
1.191 brouard 10390: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10391: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10392: }
10393: else{
1.191 brouard 10394: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10395: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10396: }
1.172 brouard 10397: // printf("\nPress Enter to continue...");
10398: // getchar();
10399: // }
10400:
1.169 brouard 10401: #endif
10402:
1.167 brouard 10403:
1.219 brouard 10404: }
1.136 brouard 10405:
1.219 brouard 10406: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10407: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10408: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10409: /* double ftolpl = 1.e-10; */
1.180 brouard 10410: double age, agebase, agelim;
1.203 brouard 10411: double tot;
1.180 brouard 10412:
1.202 brouard 10413: strcpy(filerespl,"PL_");
10414: strcat(filerespl,fileresu);
10415: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10416: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10417: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10418: }
1.288 brouard 10419: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10420: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10421: pstamp(ficrespl);
1.288 brouard 10422: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10423: fprintf(ficrespl,"#Age ");
10424: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10425: fprintf(ficrespl,"\n");
1.180 brouard 10426:
1.219 brouard 10427: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10428:
1.219 brouard 10429: agebase=ageminpar;
10430: agelim=agemaxpar;
1.180 brouard 10431:
1.227 brouard 10432: /* i1=pow(2,ncoveff); */
1.234 brouard 10433: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10434: if (cptcovn < 1){i1=1;}
1.180 brouard 10435:
1.238 brouard 10436: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10437: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10438: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10439: continue;
1.235 brouard 10440:
1.238 brouard 10441: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10442: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10443: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10444: /* k=k+1; */
10445: /* to clean */
10446: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10447: fprintf(ficrespl,"#******");
10448: printf("#******");
10449: fprintf(ficlog,"#******");
10450: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10451: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10452: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10453: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10454: }
10455: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10456: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10457: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10458: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10459: }
10460: fprintf(ficrespl,"******\n");
10461: printf("******\n");
10462: fprintf(ficlog,"******\n");
10463: if(invalidvarcomb[k]){
10464: printf("\nCombination (%d) ignored because no case \n",k);
10465: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10466: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10467: continue;
10468: }
1.219 brouard 10469:
1.238 brouard 10470: fprintf(ficrespl,"#Age ");
10471: for(j=1;j<=cptcoveff;j++) {
10472: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10473: }
10474: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10475: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10476:
1.238 brouard 10477: for (age=agebase; age<=agelim; age++){
10478: /* for (age=agebase; age<=agebase; age++){ */
10479: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10480: fprintf(ficrespl,"%.0f ",age );
10481: for(j=1;j<=cptcoveff;j++)
10482: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10483: tot=0.;
10484: for(i=1; i<=nlstate;i++){
10485: tot += prlim[i][i];
10486: fprintf(ficrespl," %.5f", prlim[i][i]);
10487: }
10488: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10489: } /* Age */
10490: /* was end of cptcod */
10491: } /* cptcov */
10492: } /* nres */
1.219 brouard 10493: return 0;
1.180 brouard 10494: }
10495:
1.218 brouard 10496: 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 10497: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10498:
10499: /* Computes the back prevalence limit for any combination of covariate values
10500: * at any age between ageminpar and agemaxpar
10501: */
1.235 brouard 10502: int i, j, k, i1, nres=0 ;
1.217 brouard 10503: /* double ftolpl = 1.e-10; */
10504: double age, agebase, agelim;
10505: double tot;
1.218 brouard 10506: /* double ***mobaverage; */
10507: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10508:
10509: strcpy(fileresplb,"PLB_");
10510: strcat(fileresplb,fileresu);
10511: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10512: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10513: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10514: }
1.288 brouard 10515: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10516: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10517: pstamp(ficresplb);
1.288 brouard 10518: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10519: fprintf(ficresplb,"#Age ");
10520: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10521: fprintf(ficresplb,"\n");
10522:
1.218 brouard 10523:
10524: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10525:
10526: agebase=ageminpar;
10527: agelim=agemaxpar;
10528:
10529:
1.227 brouard 10530: i1=pow(2,cptcoveff);
1.218 brouard 10531: if (cptcovn < 1){i1=1;}
1.227 brouard 10532:
1.238 brouard 10533: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10534: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10535: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10536: continue;
10537: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10538: fprintf(ficresplb,"#******");
10539: printf("#******");
10540: fprintf(ficlog,"#******");
10541: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10542: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10543: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10544: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10545: }
10546: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10547: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10548: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10549: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10550: }
10551: fprintf(ficresplb,"******\n");
10552: printf("******\n");
10553: fprintf(ficlog,"******\n");
10554: if(invalidvarcomb[k]){
10555: printf("\nCombination (%d) ignored because no cases \n",k);
10556: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10557: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10558: continue;
10559: }
1.218 brouard 10560:
1.238 brouard 10561: fprintf(ficresplb,"#Age ");
10562: for(j=1;j<=cptcoveff;j++) {
10563: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10564: }
10565: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10566: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10567:
10568:
1.238 brouard 10569: for (age=agebase; age<=agelim; age++){
10570: /* for (age=agebase; age<=agebase; age++){ */
10571: if(mobilavproj > 0){
10572: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10573: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10574: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10575: }else if (mobilavproj == 0){
10576: 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);
10577: 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);
10578: exit(1);
10579: }else{
10580: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10581: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10582: /* printf("TOTOT\n"); */
10583: /* exit(1); */
1.238 brouard 10584: }
10585: fprintf(ficresplb,"%.0f ",age );
10586: for(j=1;j<=cptcoveff;j++)
10587: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10588: tot=0.;
10589: for(i=1; i<=nlstate;i++){
10590: tot += bprlim[i][i];
10591: fprintf(ficresplb," %.5f", bprlim[i][i]);
10592: }
10593: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10594: } /* Age */
10595: /* was end of cptcod */
1.255 brouard 10596: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10597: } /* end of any combination */
10598: } /* end of nres */
1.218 brouard 10599: /* hBijx(p, bage, fage); */
10600: /* fclose(ficrespijb); */
10601:
10602: return 0;
1.217 brouard 10603: }
1.218 brouard 10604:
1.180 brouard 10605: int hPijx(double *p, int bage, int fage){
10606: /*------------- h Pij x at various ages ------------*/
10607:
10608: int stepsize;
10609: int agelim;
10610: int hstepm;
10611: int nhstepm;
1.235 brouard 10612: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10613:
10614: double agedeb;
10615: double ***p3mat;
10616:
1.201 brouard 10617: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10618: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10619: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10620: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10621: }
10622: printf("Computing pij: result on file '%s' \n", filerespij);
10623: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10624:
10625: stepsize=(int) (stepm+YEARM-1)/YEARM;
10626: /*if (stepm<=24) stepsize=2;*/
10627:
10628: agelim=AGESUP;
10629: hstepm=stepsize*YEARM; /* Every year of age */
10630: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10631:
1.180 brouard 10632: /* hstepm=1; aff par mois*/
10633: pstamp(ficrespij);
10634: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10635: i1= pow(2,cptcoveff);
1.218 brouard 10636: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10637: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10638: /* k=k+1; */
1.235 brouard 10639: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10640: for(k=1; k<=i1;k++){
1.253 brouard 10641: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10642: continue;
1.183 brouard 10643: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10644: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10645: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10646: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10647: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10648: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10649: }
1.183 brouard 10650: fprintf(ficrespij,"******\n");
10651:
10652: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10653: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10654: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10655:
10656: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10657:
1.183 brouard 10658: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10659: oldm=oldms;savm=savms;
1.235 brouard 10660: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10661: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10662: for(i=1; i<=nlstate;i++)
10663: for(j=1; j<=nlstate+ndeath;j++)
10664: fprintf(ficrespij," %1d-%1d",i,j);
10665: fprintf(ficrespij,"\n");
10666: for (h=0; h<=nhstepm; h++){
10667: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10668: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10669: for(i=1; i<=nlstate;i++)
10670: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10671: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10672: fprintf(ficrespij,"\n");
10673: }
1.183 brouard 10674: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10675: fprintf(ficrespij,"\n");
10676: }
1.180 brouard 10677: /*}*/
10678: }
1.218 brouard 10679: return 0;
1.180 brouard 10680: }
1.218 brouard 10681:
10682: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10683: /*------------- h Bij x at various ages ------------*/
10684:
10685: int stepsize;
1.218 brouard 10686: /* int agelim; */
10687: int ageminl;
1.217 brouard 10688: int hstepm;
10689: int nhstepm;
1.238 brouard 10690: int h, i, i1, j, k, nres;
1.218 brouard 10691:
1.217 brouard 10692: double agedeb;
10693: double ***p3mat;
1.218 brouard 10694:
10695: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10696: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10697: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10698: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10699: }
10700: printf("Computing pij back: result on file '%s' \n", filerespijb);
10701: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10702:
10703: stepsize=(int) (stepm+YEARM-1)/YEARM;
10704: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10705:
1.218 brouard 10706: /* agelim=AGESUP; */
1.289 brouard 10707: ageminl=AGEINF; /* was 30 */
1.218 brouard 10708: hstepm=stepsize*YEARM; /* Every year of age */
10709: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10710:
10711: /* hstepm=1; aff par mois*/
10712: pstamp(ficrespijb);
1.255 brouard 10713: 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 10714: i1= pow(2,cptcoveff);
1.218 brouard 10715: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10716: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10717: /* k=k+1; */
1.238 brouard 10718: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10719: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10720: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10721: continue;
10722: fprintf(ficrespijb,"\n#****** ");
10723: for(j=1;j<=cptcoveff;j++)
10724: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10725: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10726: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10727: }
10728: fprintf(ficrespijb,"******\n");
1.264 brouard 10729: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10730: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10731: continue;
10732: }
10733:
10734: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10735: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10736: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10737: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10738: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10739:
10740: /* nhstepm=nhstepm*YEARM; aff par mois*/
10741:
1.266 brouard 10742: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10743: /* and memory limitations if stepm is small */
10744:
1.238 brouard 10745: /* oldm=oldms;savm=savms; */
10746: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10747: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10748: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10749: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10750: for(i=1; i<=nlstate;i++)
10751: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10752: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10753: fprintf(ficrespijb,"\n");
1.238 brouard 10754: for (h=0; h<=nhstepm; h++){
10755: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10756: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10757: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10758: for(i=1; i<=nlstate;i++)
10759: for(j=1; j<=nlstate+ndeath;j++)
10760: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10761: fprintf(ficrespijb,"\n");
10762: }
10763: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10764: fprintf(ficrespijb,"\n");
10765: } /* end age deb */
10766: } /* end combination */
10767: } /* end nres */
1.218 brouard 10768: return 0;
10769: } /* hBijx */
1.217 brouard 10770:
1.180 brouard 10771:
1.136 brouard 10772: /***********************************************/
10773: /**************** Main Program *****************/
10774: /***********************************************/
10775:
10776: int main(int argc, char *argv[])
10777: {
10778: #ifdef GSL
10779: const gsl_multimin_fminimizer_type *T;
10780: size_t iteri = 0, it;
10781: int rval = GSL_CONTINUE;
10782: int status = GSL_SUCCESS;
10783: double ssval;
10784: #endif
10785: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 10786: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
10787: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 10788: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10789: int jj, ll, li, lj, lk;
1.136 brouard 10790: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10791: int num_filled;
1.136 brouard 10792: int itimes;
10793: int NDIM=2;
10794: int vpopbased=0;
1.235 brouard 10795: int nres=0;
1.258 brouard 10796: int endishere=0;
1.277 brouard 10797: int noffset=0;
1.274 brouard 10798: int ncurrv=0; /* Temporary variable */
10799:
1.164 brouard 10800: char ca[32], cb[32];
1.136 brouard 10801: /* FILE *fichtm; *//* Html File */
10802: /* FILE *ficgp;*/ /*Gnuplot File */
10803: struct stat info;
1.191 brouard 10804: double agedeb=0.;
1.194 brouard 10805:
10806: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10807: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10808:
1.165 brouard 10809: double fret;
1.191 brouard 10810: double dum=0.; /* Dummy variable */
1.136 brouard 10811: double ***p3mat;
1.218 brouard 10812: /* double ***mobaverage; */
1.164 brouard 10813:
10814: char line[MAXLINE];
1.197 brouard 10815: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10816:
1.234 brouard 10817: char modeltemp[MAXLINE];
1.230 brouard 10818: char resultline[MAXLINE];
10819:
1.136 brouard 10820: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10821: char *tok, *val; /* pathtot */
1.290 brouard 10822: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 10823: int c, h , cpt, c2;
1.191 brouard 10824: int jl=0;
10825: int i1, j1, jk, stepsize=0;
1.194 brouard 10826: int count=0;
10827:
1.164 brouard 10828: int *tab;
1.136 brouard 10829: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 ! brouard 10830: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
! 10831: /* double anprojf, mprojf, jprojf; */
! 10832: /* double jintmean,mintmean,aintmean; */
! 10833: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
! 10834: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
! 10835: double yrfproj= 10.0; /* Number of years of forward projections */
! 10836: double yrbproj= 10.0; /* Number of years of backward projections */
! 10837: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 10838: int mobilav=0,popforecast=0;
1.191 brouard 10839: int hstepm=0, nhstepm=0;
1.136 brouard 10840: int agemortsup;
10841: float sumlpop=0.;
10842: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10843: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10844:
1.191 brouard 10845: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10846: double ftolpl=FTOL;
10847: double **prlim;
1.217 brouard 10848: double **bprlim;
1.136 brouard 10849: double ***param; /* Matrix of parameters */
1.251 brouard 10850: double ***paramstart; /* Matrix of starting parameter values */
10851: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10852: double **matcov; /* Matrix of covariance */
1.203 brouard 10853: double **hess; /* Hessian matrix */
1.136 brouard 10854: double ***delti3; /* Scale */
10855: double *delti; /* Scale */
10856: double ***eij, ***vareij;
10857: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10858:
1.136 brouard 10859: double *epj, vepp;
1.164 brouard 10860:
1.273 brouard 10861: double dateprev1, dateprev2;
1.296 ! brouard 10862: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
! 10863: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
! 10864:
1.217 brouard 10865:
1.136 brouard 10866: double **ximort;
1.145 brouard 10867: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10868: int *dcwave;
10869:
1.164 brouard 10870: char z[1]="c";
1.136 brouard 10871:
10872: /*char *strt;*/
10873: char strtend[80];
1.126 brouard 10874:
1.164 brouard 10875:
1.126 brouard 10876: /* setlocale (LC_ALL, ""); */
10877: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10878: /* textdomain (PACKAGE); */
10879: /* setlocale (LC_CTYPE, ""); */
10880: /* setlocale (LC_MESSAGES, ""); */
10881:
10882: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10883: rstart_time = time(NULL);
10884: /* (void) gettimeofday(&start_time,&tzp);*/
10885: start_time = *localtime(&rstart_time);
1.126 brouard 10886: curr_time=start_time;
1.157 brouard 10887: /*tml = *localtime(&start_time.tm_sec);*/
10888: /* strcpy(strstart,asctime(&tml)); */
10889: strcpy(strstart,asctime(&start_time));
1.126 brouard 10890:
10891: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10892: /* tp.tm_sec = tp.tm_sec +86400; */
10893: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10894: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10895: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10896: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10897: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10898: /* strt=asctime(&tmg); */
10899: /* printf("Time(after) =%s",strstart); */
10900: /* (void) time (&time_value);
10901: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10902: * tm = *localtime(&time_value);
10903: * strstart=asctime(&tm);
10904: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10905: */
10906:
10907: nberr=0; /* Number of errors and warnings */
10908: nbwarn=0;
1.184 brouard 10909: #ifdef WIN32
10910: _getcwd(pathcd, size);
10911: #else
1.126 brouard 10912: getcwd(pathcd, size);
1.184 brouard 10913: #endif
1.191 brouard 10914: syscompilerinfo(0);
1.196 brouard 10915: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10916: if(argc <=1){
10917: printf("\nEnter the parameter file name: ");
1.205 brouard 10918: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10919: printf("ERROR Empty parameter file name\n");
10920: goto end;
10921: }
1.126 brouard 10922: i=strlen(pathr);
10923: if(pathr[i-1]=='\n')
10924: pathr[i-1]='\0';
1.156 brouard 10925: i=strlen(pathr);
1.205 brouard 10926: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10927: pathr[i-1]='\0';
1.205 brouard 10928: }
10929: i=strlen(pathr);
10930: if( i==0 ){
10931: printf("ERROR Empty parameter file name\n");
10932: goto end;
10933: }
10934: for (tok = pathr; tok != NULL; ){
1.126 brouard 10935: printf("Pathr |%s|\n",pathr);
10936: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10937: printf("val= |%s| pathr=%s\n",val,pathr);
10938: strcpy (pathtot, val);
10939: if(pathr[0] == '\0') break; /* Dirty */
10940: }
10941: }
1.281 brouard 10942: else if (argc<=2){
10943: strcpy(pathtot,argv[1]);
10944: }
1.126 brouard 10945: else{
10946: strcpy(pathtot,argv[1]);
1.281 brouard 10947: strcpy(z,argv[2]);
10948: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10949: }
10950: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10951: /*cygwin_split_path(pathtot,path,optionfile);
10952: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10953: /* cutv(path,optionfile,pathtot,'\\');*/
10954:
10955: /* Split argv[0], imach program to get pathimach */
10956: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10957: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10958: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10959: /* strcpy(pathimach,argv[0]); */
10960: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10961: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10962: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10963: #ifdef WIN32
10964: _chdir(path); /* Can be a relative path */
10965: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10966: #else
1.126 brouard 10967: chdir(path); /* Can be a relative path */
1.184 brouard 10968: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10969: #endif
10970: printf("Current directory %s!\n",pathcd);
1.126 brouard 10971: strcpy(command,"mkdir ");
10972: strcat(command,optionfilefiname);
10973: if((outcmd=system(command)) != 0){
1.169 brouard 10974: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10975: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10976: /* fclose(ficlog); */
10977: /* exit(1); */
10978: }
10979: /* if((imk=mkdir(optionfilefiname))<0){ */
10980: /* perror("mkdir"); */
10981: /* } */
10982:
10983: /*-------- arguments in the command line --------*/
10984:
1.186 brouard 10985: /* Main Log file */
1.126 brouard 10986: strcat(filelog, optionfilefiname);
10987: strcat(filelog,".log"); /* */
10988: if((ficlog=fopen(filelog,"w"))==NULL) {
10989: printf("Problem with logfile %s\n",filelog);
10990: goto end;
10991: }
10992: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10993: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10994: fprintf(ficlog,"\nEnter the parameter file name: \n");
10995: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10996: path=%s \n\
10997: optionfile=%s\n\
10998: optionfilext=%s\n\
1.156 brouard 10999: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11000:
1.197 brouard 11001: syscompilerinfo(1);
1.167 brouard 11002:
1.126 brouard 11003: printf("Local time (at start):%s",strstart);
11004: fprintf(ficlog,"Local time (at start): %s",strstart);
11005: fflush(ficlog);
11006: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11007: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11008:
11009: /* */
11010: strcpy(fileres,"r");
11011: strcat(fileres, optionfilefiname);
1.201 brouard 11012: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11013: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11014: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11015:
1.186 brouard 11016: /* Main ---------arguments file --------*/
1.126 brouard 11017:
11018: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11019: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11020: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11021: fflush(ficlog);
1.149 brouard 11022: /* goto end; */
11023: exit(70);
1.126 brouard 11024: }
11025:
11026: strcpy(filereso,"o");
1.201 brouard 11027: strcat(filereso,fileresu);
1.126 brouard 11028: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11029: printf("Problem with Output resultfile: %s\n", filereso);
11030: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11031: fflush(ficlog);
11032: goto end;
11033: }
1.278 brouard 11034: /*-------- Rewriting parameter file ----------*/
11035: strcpy(rfileres,"r"); /* "Rparameterfile */
11036: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11037: strcat(rfileres,"."); /* */
11038: strcat(rfileres,optionfilext); /* Other files have txt extension */
11039: if((ficres =fopen(rfileres,"w"))==NULL) {
11040: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11041: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11042: fflush(ficlog);
11043: goto end;
11044: }
11045: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11046:
1.278 brouard 11047:
1.126 brouard 11048: /* Reads comments: lines beginning with '#' */
11049: numlinepar=0;
1.277 brouard 11050: /* Is it a BOM UTF-8 Windows file? */
11051: /* First parameter line */
1.197 brouard 11052: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11053: noffset=0;
11054: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11055: {
11056: noffset=noffset+3;
11057: printf("# File is an UTF8 Bom.\n"); // 0xBF
11058: }
11059: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
11060: {
11061: noffset=noffset+2;
11062: printf("# File is an UTF16BE BOM file\n");
11063: }
11064: else if( line[0] == 0 && line[1] == 0)
11065: {
11066: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11067: noffset=noffset+4;
11068: printf("# File is an UTF16BE BOM file\n");
11069: }
11070: } else{
11071: ;/*printf(" Not a BOM file\n");*/
11072: }
11073:
1.197 brouard 11074: /* If line starts with a # it is a comment */
1.277 brouard 11075: if (line[noffset] == '#') {
1.197 brouard 11076: numlinepar++;
11077: fputs(line,stdout);
11078: fputs(line,ficparo);
1.278 brouard 11079: fputs(line,ficres);
1.197 brouard 11080: fputs(line,ficlog);
11081: continue;
11082: }else
11083: break;
11084: }
11085: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11086: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11087: if (num_filled != 5) {
11088: printf("Should be 5 parameters\n");
1.283 brouard 11089: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11090: }
1.126 brouard 11091: numlinepar++;
1.197 brouard 11092: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11093: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11094: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11095: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11096: }
11097: /* Second parameter line */
11098: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11099: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11100: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11101: if (line[0] == '#') {
11102: numlinepar++;
1.283 brouard 11103: printf("%s",line);
11104: fprintf(ficres,"%s",line);
11105: fprintf(ficparo,"%s",line);
11106: fprintf(ficlog,"%s",line);
1.197 brouard 11107: continue;
11108: }else
11109: break;
11110: }
1.223 brouard 11111: 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", \
11112: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11113: if (num_filled != 11) {
11114: 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 11115: printf("but line=%s\n",line);
1.283 brouard 11116: 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");
11117: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11118: }
1.286 brouard 11119: if( lastpass > maxwav){
11120: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11121: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11122: fflush(ficlog);
11123: goto end;
11124: }
11125: 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 11126: 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 11127: 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 11128: 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 11129: }
1.203 brouard 11130: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11131: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11132: /* Third parameter line */
11133: while(fgets(line, MAXLINE, ficpar)) {
11134: /* If line starts with a # it is a comment */
11135: if (line[0] == '#') {
11136: numlinepar++;
1.283 brouard 11137: printf("%s",line);
11138: fprintf(ficres,"%s",line);
11139: fprintf(ficparo,"%s",line);
11140: fprintf(ficlog,"%s",line);
1.197 brouard 11141: continue;
11142: }else
11143: break;
11144: }
1.201 brouard 11145: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11146: if (num_filled != 1){
11147: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11148: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11149: model[0]='\0';
11150: goto end;
11151: }
11152: else{
11153: if (model[0]=='+'){
11154: for(i=1; i<=strlen(model);i++)
11155: modeltemp[i-1]=model[i];
1.201 brouard 11156: strcpy(model,modeltemp);
1.197 brouard 11157: }
11158: }
1.199 brouard 11159: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11160: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11161: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11162: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11163: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11164: }
11165: /* 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); */
11166: /* numlinepar=numlinepar+3; /\* In general *\/ */
11167: /* 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 11168: /* 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); */
11169: /* 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 11170: fflush(ficlog);
1.190 brouard 11171: /* if(model[0]=='#'|| model[0]== '\0'){ */
11172: if(model[0]=='#'){
1.279 brouard 11173: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11174: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11175: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11176: if(mle != -1){
1.279 brouard 11177: 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 11178: exit(1);
11179: }
11180: }
1.126 brouard 11181: while((c=getc(ficpar))=='#' && c!= EOF){
11182: ungetc(c,ficpar);
11183: fgets(line, MAXLINE, ficpar);
11184: numlinepar++;
1.195 brouard 11185: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11186: z[0]=line[1];
11187: }
11188: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11189: fputs(line, stdout);
11190: //puts(line);
1.126 brouard 11191: fputs(line,ficparo);
11192: fputs(line,ficlog);
11193: }
11194: ungetc(c,ficpar);
11195:
11196:
1.290 brouard 11197: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11198: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11199: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11200: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11201: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11202: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11203: v1+v2*age+v2*v3 makes cptcovn = 3
11204: */
11205: if (strlen(model)>1)
1.187 brouard 11206: 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 11207: else
1.187 brouard 11208: ncovmodel=2; /* Constant and age */
1.133 brouard 11209: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11210: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11211: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11212: 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);
11213: 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);
11214: fflush(stdout);
11215: fclose (ficlog);
11216: goto end;
11217: }
1.126 brouard 11218: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11219: delti=delti3[1][1];
11220: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11221: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11222: /* We could also provide initial parameters values giving by simple logistic regression
11223: * only one way, that is without matrix product. We will have nlstate maximizations */
11224: /* for(i=1;i<nlstate;i++){ */
11225: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11226: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11227: /* } */
1.126 brouard 11228: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11229: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11230: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11231: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11232: fclose (ficparo);
11233: fclose (ficlog);
11234: goto end;
11235: exit(0);
1.220 brouard 11236: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11237: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11238: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11239: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11240: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11241: matcov=matrix(1,npar,1,npar);
1.203 brouard 11242: hess=matrix(1,npar,1,npar);
1.220 brouard 11243: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11244: /* Read guessed parameters */
1.126 brouard 11245: /* Reads comments: lines beginning with '#' */
11246: while((c=getc(ficpar))=='#' && c!= EOF){
11247: ungetc(c,ficpar);
11248: fgets(line, MAXLINE, ficpar);
11249: numlinepar++;
1.141 brouard 11250: fputs(line,stdout);
1.126 brouard 11251: fputs(line,ficparo);
11252: fputs(line,ficlog);
11253: }
11254: ungetc(c,ficpar);
11255:
11256: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11257: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11258: for(i=1; i <=nlstate; i++){
1.234 brouard 11259: j=0;
1.126 brouard 11260: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11261: if(jj==i) continue;
11262: j++;
1.292 brouard 11263: while((c=getc(ficpar))=='#' && c!= EOF){
11264: ungetc(c,ficpar);
11265: fgets(line, MAXLINE, ficpar);
11266: numlinepar++;
11267: fputs(line,stdout);
11268: fputs(line,ficparo);
11269: fputs(line,ficlog);
11270: }
11271: ungetc(c,ficpar);
1.234 brouard 11272: fscanf(ficpar,"%1d%1d",&i1,&j1);
11273: if ((i1 != i) || (j1 != jj)){
11274: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11275: It might be a problem of design; if ncovcol and the model are correct\n \
11276: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11277: exit(1);
11278: }
11279: fprintf(ficparo,"%1d%1d",i1,j1);
11280: if(mle==1)
11281: printf("%1d%1d",i,jj);
11282: fprintf(ficlog,"%1d%1d",i,jj);
11283: for(k=1; k<=ncovmodel;k++){
11284: fscanf(ficpar," %lf",¶m[i][j][k]);
11285: if(mle==1){
11286: printf(" %lf",param[i][j][k]);
11287: fprintf(ficlog," %lf",param[i][j][k]);
11288: }
11289: else
11290: fprintf(ficlog," %lf",param[i][j][k]);
11291: fprintf(ficparo," %lf",param[i][j][k]);
11292: }
11293: fscanf(ficpar,"\n");
11294: numlinepar++;
11295: if(mle==1)
11296: printf("\n");
11297: fprintf(ficlog,"\n");
11298: fprintf(ficparo,"\n");
1.126 brouard 11299: }
11300: }
11301: fflush(ficlog);
1.234 brouard 11302:
1.251 brouard 11303: /* Reads parameters values */
1.126 brouard 11304: p=param[1][1];
1.251 brouard 11305: pstart=paramstart[1][1];
1.126 brouard 11306:
11307: /* Reads comments: lines beginning with '#' */
11308: while((c=getc(ficpar))=='#' && c!= EOF){
11309: ungetc(c,ficpar);
11310: fgets(line, MAXLINE, ficpar);
11311: numlinepar++;
1.141 brouard 11312: fputs(line,stdout);
1.126 brouard 11313: fputs(line,ficparo);
11314: fputs(line,ficlog);
11315: }
11316: ungetc(c,ficpar);
11317:
11318: for(i=1; i <=nlstate; i++){
11319: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11320: fscanf(ficpar,"%1d%1d",&i1,&j1);
11321: if ( (i1-i) * (j1-j) != 0){
11322: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11323: exit(1);
11324: }
11325: printf("%1d%1d",i,j);
11326: fprintf(ficparo,"%1d%1d",i1,j1);
11327: fprintf(ficlog,"%1d%1d",i1,j1);
11328: for(k=1; k<=ncovmodel;k++){
11329: fscanf(ficpar,"%le",&delti3[i][j][k]);
11330: printf(" %le",delti3[i][j][k]);
11331: fprintf(ficparo," %le",delti3[i][j][k]);
11332: fprintf(ficlog," %le",delti3[i][j][k]);
11333: }
11334: fscanf(ficpar,"\n");
11335: numlinepar++;
11336: printf("\n");
11337: fprintf(ficparo,"\n");
11338: fprintf(ficlog,"\n");
1.126 brouard 11339: }
11340: }
11341: fflush(ficlog);
1.234 brouard 11342:
1.145 brouard 11343: /* Reads covariance matrix */
1.126 brouard 11344: delti=delti3[1][1];
1.220 brouard 11345:
11346:
1.126 brouard 11347: /* 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 11348:
1.126 brouard 11349: /* Reads comments: lines beginning with '#' */
11350: while((c=getc(ficpar))=='#' && c!= EOF){
11351: ungetc(c,ficpar);
11352: fgets(line, MAXLINE, ficpar);
11353: numlinepar++;
1.141 brouard 11354: fputs(line,stdout);
1.126 brouard 11355: fputs(line,ficparo);
11356: fputs(line,ficlog);
11357: }
11358: ungetc(c,ficpar);
1.220 brouard 11359:
1.126 brouard 11360: matcov=matrix(1,npar,1,npar);
1.203 brouard 11361: hess=matrix(1,npar,1,npar);
1.131 brouard 11362: for(i=1; i <=npar; i++)
11363: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11364:
1.194 brouard 11365: /* Scans npar lines */
1.126 brouard 11366: for(i=1; i <=npar; i++){
1.226 brouard 11367: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11368: if(count != 3){
1.226 brouard 11369: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11370: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11371: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11372: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11373: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11374: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11375: exit(1);
1.220 brouard 11376: }else{
1.226 brouard 11377: if(mle==1)
11378: printf("%1d%1d%d",i1,j1,jk);
11379: }
11380: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11381: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11382: for(j=1; j <=i; j++){
1.226 brouard 11383: fscanf(ficpar," %le",&matcov[i][j]);
11384: if(mle==1){
11385: printf(" %.5le",matcov[i][j]);
11386: }
11387: fprintf(ficlog," %.5le",matcov[i][j]);
11388: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11389: }
11390: fscanf(ficpar,"\n");
11391: numlinepar++;
11392: if(mle==1)
1.220 brouard 11393: printf("\n");
1.126 brouard 11394: fprintf(ficlog,"\n");
11395: fprintf(ficparo,"\n");
11396: }
1.194 brouard 11397: /* End of read covariance matrix npar lines */
1.126 brouard 11398: for(i=1; i <=npar; i++)
11399: for(j=i+1;j<=npar;j++)
1.226 brouard 11400: matcov[i][j]=matcov[j][i];
1.126 brouard 11401:
11402: if(mle==1)
11403: printf("\n");
11404: fprintf(ficlog,"\n");
11405:
11406: fflush(ficlog);
11407:
11408: } /* End of mle != -3 */
1.218 brouard 11409:
1.186 brouard 11410: /* Main data
11411: */
1.290 brouard 11412: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11413: /* num=lvector(1,n); */
11414: /* moisnais=vector(1,n); */
11415: /* annais=vector(1,n); */
11416: /* moisdc=vector(1,n); */
11417: /* andc=vector(1,n); */
11418: /* weight=vector(1,n); */
11419: /* agedc=vector(1,n); */
11420: /* cod=ivector(1,n); */
11421: /* for(i=1;i<=n;i++){ */
11422: num=lvector(firstobs,lastobs);
11423: moisnais=vector(firstobs,lastobs);
11424: annais=vector(firstobs,lastobs);
11425: moisdc=vector(firstobs,lastobs);
11426: andc=vector(firstobs,lastobs);
11427: weight=vector(firstobs,lastobs);
11428: agedc=vector(firstobs,lastobs);
11429: cod=ivector(firstobs,lastobs);
11430: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11431: num[i]=0;
11432: moisnais[i]=0;
11433: annais[i]=0;
11434: moisdc[i]=0;
11435: andc[i]=0;
11436: agedc[i]=0;
11437: cod[i]=0;
11438: weight[i]=1.0; /* Equal weights, 1 by default */
11439: }
1.290 brouard 11440: mint=matrix(1,maxwav,firstobs,lastobs);
11441: anint=matrix(1,maxwav,firstobs,lastobs);
11442: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11443: tab=ivector(1,NCOVMAX);
1.144 brouard 11444: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11445: 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 11446:
1.136 brouard 11447: /* Reads data from file datafile */
11448: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11449: goto end;
11450:
11451: /* Calculation of the number of parameters from char model */
1.234 brouard 11452: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11453: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11454: k=3 V4 Tvar[k=3]= 4 (from V4)
11455: k=2 V1 Tvar[k=2]= 1 (from V1)
11456: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11457: */
11458:
11459: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11460: TvarsDind=ivector(1,NCOVMAX); /* */
11461: TvarsD=ivector(1,NCOVMAX); /* */
11462: TvarsQind=ivector(1,NCOVMAX); /* */
11463: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11464: TvarF=ivector(1,NCOVMAX); /* */
11465: TvarFind=ivector(1,NCOVMAX); /* */
11466: TvarV=ivector(1,NCOVMAX); /* */
11467: TvarVind=ivector(1,NCOVMAX); /* */
11468: TvarA=ivector(1,NCOVMAX); /* */
11469: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11470: TvarFD=ivector(1,NCOVMAX); /* */
11471: TvarFDind=ivector(1,NCOVMAX); /* */
11472: TvarFQ=ivector(1,NCOVMAX); /* */
11473: TvarFQind=ivector(1,NCOVMAX); /* */
11474: TvarVD=ivector(1,NCOVMAX); /* */
11475: TvarVDind=ivector(1,NCOVMAX); /* */
11476: TvarVQ=ivector(1,NCOVMAX); /* */
11477: TvarVQind=ivector(1,NCOVMAX); /* */
11478:
1.230 brouard 11479: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11480: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11481: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11482: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11483: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11484: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11485: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11486: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11487: */
11488: /* For model-covariate k tells which data-covariate to use but
11489: because this model-covariate is a construction we invent a new column
11490: ncovcol + k1
11491: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11492: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11493: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11494: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11495: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11496: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11497: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11498: */
1.145 brouard 11499: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11500: 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 11501: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11502: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11503: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11504: 4 covariates (3 plus signs)
11505: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11506: */
1.230 brouard 11507: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11508: * individual dummy, fixed or varying:
11509: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11510: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11511: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11512: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11513: * Tmodelind[1]@9={9,0,3,2,}*/
11514: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11515: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11516: * individual quantitative, fixed or varying:
11517: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11518: * 3, 1, 0, 0, 0, 0, 0, 0},
11519: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11520: /* Main decodemodel */
11521:
1.187 brouard 11522:
1.223 brouard 11523: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11524: goto end;
11525:
1.137 brouard 11526: if((double)(lastobs-imx)/(double)imx > 1.10){
11527: nbwarn++;
11528: 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);
11529: 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);
11530: }
1.136 brouard 11531: /* if(mle==1){*/
1.137 brouard 11532: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11533: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11534: }
11535:
11536: /*-calculation of age at interview from date of interview and age at death -*/
11537: agev=matrix(1,maxwav,1,imx);
11538:
11539: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11540: goto end;
11541:
1.126 brouard 11542:
1.136 brouard 11543: agegomp=(int)agemin;
1.290 brouard 11544: free_vector(moisnais,firstobs,lastobs);
11545: free_vector(annais,firstobs,lastobs);
1.126 brouard 11546: /* free_matrix(mint,1,maxwav,1,n);
11547: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11548: /* free_vector(moisdc,1,n); */
11549: /* free_vector(andc,1,n); */
1.145 brouard 11550: /* */
11551:
1.126 brouard 11552: wav=ivector(1,imx);
1.214 brouard 11553: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11554: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11555: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11556: 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.*/
11557: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11558: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11559:
11560: /* Concatenates waves */
1.214 brouard 11561: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11562: Death is a valid wave (if date is known).
11563: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11564: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11565: and mw[mi+1][i]. dh depends on stepm.
11566: */
11567:
1.126 brouard 11568: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11569: /* Concatenates waves */
1.145 brouard 11570:
1.290 brouard 11571: free_vector(moisdc,firstobs,lastobs);
11572: free_vector(andc,firstobs,lastobs);
1.215 brouard 11573:
1.126 brouard 11574: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11575: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11576: ncodemax[1]=1;
1.145 brouard 11577: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11578: cptcoveff=0;
1.220 brouard 11579: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11580: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11581: }
11582:
11583: ncovcombmax=pow(2,cptcoveff);
11584: invalidvarcomb=ivector(1, ncovcombmax);
11585: for(i=1;i<ncovcombmax;i++)
11586: invalidvarcomb[i]=0;
11587:
1.211 brouard 11588: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11589: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11590: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11591:
1.200 brouard 11592: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11593: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11594: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11595: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11596: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11597: * (currently 0 or 1) in the data.
11598: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11599: * corresponding modality (h,j).
11600: */
11601:
1.145 brouard 11602: h=0;
11603: /*if (cptcovn > 0) */
1.126 brouard 11604: m=pow(2,cptcoveff);
11605:
1.144 brouard 11606: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11607: * For k=4 covariates, h goes from 1 to m=2**k
11608: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11609: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11610: * h\k 1 2 3 4
1.143 brouard 11611: *______________________________
11612: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11613: * 2 2 1 1 1
11614: * 3 i=2 1 2 1 1
11615: * 4 2 2 1 1
11616: * 5 i=3 1 i=2 1 2 1
11617: * 6 2 1 2 1
11618: * 7 i=4 1 2 2 1
11619: * 8 2 2 2 1
1.197 brouard 11620: * 9 i=5 1 i=3 1 i=2 1 2
11621: * 10 2 1 1 2
11622: * 11 i=6 1 2 1 2
11623: * 12 2 2 1 2
11624: * 13 i=7 1 i=4 1 2 2
11625: * 14 2 1 2 2
11626: * 15 i=8 1 2 2 2
11627: * 16 2 2 2 2
1.143 brouard 11628: */
1.212 brouard 11629: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11630: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11631: * and the value of each covariate?
11632: * V1=1, V2=1, V3=2, V4=1 ?
11633: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11634: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11635: * In order to get the real value in the data, we use nbcode
11636: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11637: * We are keeping this crazy system in order to be able (in the future?)
11638: * to have more than 2 values (0 or 1) for a covariate.
11639: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11640: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11641: * bbbbbbbb
11642: * 76543210
11643: * h-1 00000101 (6-1=5)
1.219 brouard 11644: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11645: * &
11646: * 1 00000001 (1)
1.219 brouard 11647: * 00000000 = 1 & ((h-1) >> (k-1))
11648: * +1= 00000001 =1
1.211 brouard 11649: *
11650: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11651: * h' 1101 =2^3+2^2+0x2^1+2^0
11652: * >>k' 11
11653: * & 00000001
11654: * = 00000001
11655: * +1 = 00000010=2 = codtabm(14,3)
11656: * Reverse h=6 and m=16?
11657: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11658: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11659: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11660: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11661: * V3=decodtabm(14,3,2**4)=2
11662: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11663: *(h-1) >> (j-1) 0011 =13 >> 2
11664: * &1 000000001
11665: * = 000000001
11666: * +1= 000000010 =2
11667: * 2211
11668: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11669: * V3=2
1.220 brouard 11670: * codtabm and decodtabm are identical
1.211 brouard 11671: */
11672:
1.145 brouard 11673:
11674: free_ivector(Ndum,-1,NCOVMAX);
11675:
11676:
1.126 brouard 11677:
1.186 brouard 11678: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11679: strcpy(optionfilegnuplot,optionfilefiname);
11680: if(mle==-3)
1.201 brouard 11681: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11682: strcat(optionfilegnuplot,".gp");
11683:
11684: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11685: printf("Problem with file %s",optionfilegnuplot);
11686: }
11687: else{
1.204 brouard 11688: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11689: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11690: //fprintf(ficgp,"set missing 'NaNq'\n");
11691: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11692: }
11693: /* fclose(ficgp);*/
1.186 brouard 11694:
11695:
11696: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11697:
11698: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11699: if(mle==-3)
1.201 brouard 11700: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11701: strcat(optionfilehtm,".htm");
11702: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11703: printf("Problem with %s \n",optionfilehtm);
11704: exit(0);
1.126 brouard 11705: }
11706:
11707: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11708: strcat(optionfilehtmcov,"-cov.htm");
11709: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11710: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11711: }
11712: else{
11713: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11714: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11715: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11716: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11717: }
11718:
1.213 brouard 11719: fprintf(fichtm,"<html><head>\n<head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<title>IMaCh %s</title></head>\n <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n<font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>-EUROREVES-Institut de longévité-2013-2016-Japan Society for the Promotion of Sciences 日本学術振興会 (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \
1.204 brouard 11720: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11721: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11722: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11723: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11724: \n\
11725: <hr size=\"2\" color=\"#EC5E5E\">\
11726: <ul><li><h4>Parameter files</h4>\n\
11727: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11728: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11729: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11730: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11731: - Date and time at start: %s</ul>\n",\
11732: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11733: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11734: fileres,fileres,\
11735: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11736: fflush(fichtm);
11737:
11738: strcpy(pathr,path);
11739: strcat(pathr,optionfilefiname);
1.184 brouard 11740: #ifdef WIN32
11741: _chdir(optionfilefiname); /* Move to directory named optionfile */
11742: #else
1.126 brouard 11743: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11744: #endif
11745:
1.126 brouard 11746:
1.220 brouard 11747: /* Calculates basic frequencies. Computes observed prevalence at single age
11748: and for any valid combination of covariates
1.126 brouard 11749: and prints on file fileres'p'. */
1.251 brouard 11750: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11751: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11752:
11753: fprintf(fichtm,"\n");
1.286 brouard 11754: 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 11755: ftol, stepm);
11756: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11757: ncurrv=1;
11758: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11759: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11760: ncurrv=i;
11761: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11762: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 11763: ncurrv=i;
11764: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11765: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 11766: ncurrv=i;
11767: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11768: 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", \
11769: nlstate, ndeath, maxwav, mle, weightopt);
11770:
11771: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11772: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11773:
11774:
11775: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11776: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11777: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11778: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11779: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11780: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11781: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11782: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11783: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11784:
1.126 brouard 11785: /* For Powell, parameters are in a vector p[] starting at p[1]
11786: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11787: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11788:
11789: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11790: /* For mortality only */
1.126 brouard 11791: if (mle==-3){
1.136 brouard 11792: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11793: for(i=1;i<=NDIM;i++)
11794: for(j=1;j<=NDIM;j++)
11795: ximort[i][j]=0.;
1.186 brouard 11796: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 11797: cens=ivector(firstobs,lastobs);
11798: ageexmed=vector(firstobs,lastobs);
11799: agecens=vector(firstobs,lastobs);
11800: dcwave=ivector(firstobs,lastobs);
1.223 brouard 11801:
1.126 brouard 11802: for (i=1; i<=imx; i++){
11803: dcwave[i]=-1;
11804: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11805: if (s[m][i]>nlstate) {
11806: dcwave[i]=m;
11807: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11808: break;
11809: }
1.126 brouard 11810: }
1.226 brouard 11811:
1.126 brouard 11812: for (i=1; i<=imx; i++) {
11813: if (wav[i]>0){
1.226 brouard 11814: ageexmed[i]=agev[mw[1][i]][i];
11815: j=wav[i];
11816: agecens[i]=1.;
11817:
11818: if (ageexmed[i]> 1 && wav[i] > 0){
11819: agecens[i]=agev[mw[j][i]][i];
11820: cens[i]= 1;
11821: }else if (ageexmed[i]< 1)
11822: cens[i]= -1;
11823: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11824: cens[i]=0 ;
1.126 brouard 11825: }
11826: else cens[i]=-1;
11827: }
11828:
11829: for (i=1;i<=NDIM;i++) {
11830: for (j=1;j<=NDIM;j++)
1.226 brouard 11831: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11832: }
11833:
1.145 brouard 11834: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11835: /*printf("%lf %lf", p[1], p[2]);*/
11836:
11837:
1.136 brouard 11838: #ifdef GSL
11839: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11840: #else
1.126 brouard 11841: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11842: #endif
1.201 brouard 11843: strcpy(filerespow,"POW-MORT_");
11844: strcat(filerespow,fileresu);
1.126 brouard 11845: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11846: printf("Problem with resultfile: %s\n", filerespow);
11847: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11848: }
1.136 brouard 11849: #ifdef GSL
11850: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11851: #else
1.126 brouard 11852: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11853: #endif
1.126 brouard 11854: /* for (i=1;i<=nlstate;i++)
11855: for(j=1;j<=nlstate+ndeath;j++)
11856: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11857: */
11858: fprintf(ficrespow,"\n");
1.136 brouard 11859: #ifdef GSL
11860: /* gsl starts here */
11861: T = gsl_multimin_fminimizer_nmsimplex;
11862: gsl_multimin_fminimizer *sfm = NULL;
11863: gsl_vector *ss, *x;
11864: gsl_multimin_function minex_func;
11865:
11866: /* Initial vertex size vector */
11867: ss = gsl_vector_alloc (NDIM);
11868:
11869: if (ss == NULL){
11870: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11871: }
11872: /* Set all step sizes to 1 */
11873: gsl_vector_set_all (ss, 0.001);
11874:
11875: /* Starting point */
1.126 brouard 11876:
1.136 brouard 11877: x = gsl_vector_alloc (NDIM);
11878:
11879: if (x == NULL){
11880: gsl_vector_free(ss);
11881: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11882: }
11883:
11884: /* Initialize method and iterate */
11885: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11886: /* gsl_vector_set(x, 0, 0.0268); */
11887: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11888: gsl_vector_set(x, 0, p[1]);
11889: gsl_vector_set(x, 1, p[2]);
11890:
11891: minex_func.f = &gompertz_f;
11892: minex_func.n = NDIM;
11893: minex_func.params = (void *)&p; /* ??? */
11894:
11895: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11896: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11897:
11898: printf("Iterations beginning .....\n\n");
11899: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11900:
11901: iteri=0;
11902: while (rval == GSL_CONTINUE){
11903: iteri++;
11904: status = gsl_multimin_fminimizer_iterate(sfm);
11905:
11906: if (status) printf("error: %s\n", gsl_strerror (status));
11907: fflush(0);
11908:
11909: if (status)
11910: break;
11911:
11912: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11913: ssval = gsl_multimin_fminimizer_size (sfm);
11914:
11915: if (rval == GSL_SUCCESS)
11916: printf ("converged to a local maximum at\n");
11917:
11918: printf("%5d ", iteri);
11919: for (it = 0; it < NDIM; it++){
11920: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11921: }
11922: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11923: }
11924:
11925: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11926:
11927: gsl_vector_free(x); /* initial values */
11928: gsl_vector_free(ss); /* inital step size */
11929: for (it=0; it<NDIM; it++){
11930: p[it+1]=gsl_vector_get(sfm->x,it);
11931: fprintf(ficrespow," %.12lf", p[it]);
11932: }
11933: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11934: #endif
11935: #ifdef POWELL
11936: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11937: #endif
1.126 brouard 11938: fclose(ficrespow);
11939:
1.203 brouard 11940: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11941:
11942: for(i=1; i <=NDIM; i++)
11943: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11944: matcov[i][j]=matcov[j][i];
1.126 brouard 11945:
11946: printf("\nCovariance matrix\n ");
1.203 brouard 11947: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11948: for(i=1; i <=NDIM; i++) {
11949: for(j=1;j<=NDIM;j++){
1.220 brouard 11950: printf("%f ",matcov[i][j]);
11951: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11952: }
1.203 brouard 11953: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11954: }
11955:
11956: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11957: for (i=1;i<=NDIM;i++) {
1.126 brouard 11958: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11959: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11960: }
1.126 brouard 11961: lsurv=vector(1,AGESUP);
11962: lpop=vector(1,AGESUP);
11963: tpop=vector(1,AGESUP);
11964: lsurv[agegomp]=100000;
11965:
11966: for (k=agegomp;k<=AGESUP;k++) {
11967: agemortsup=k;
11968: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11969: }
11970:
11971: for (k=agegomp;k<agemortsup;k++)
11972: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11973:
11974: for (k=agegomp;k<agemortsup;k++){
11975: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11976: sumlpop=sumlpop+lpop[k];
11977: }
11978:
11979: tpop[agegomp]=sumlpop;
11980: for (k=agegomp;k<(agemortsup-3);k++){
11981: /* tpop[k+1]=2;*/
11982: tpop[k+1]=tpop[k]-lpop[k];
11983: }
11984:
11985:
11986: printf("\nAge lx qx dx Lx Tx e(x)\n");
11987: for (k=agegomp;k<(agemortsup-2);k++)
11988: 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]);
11989:
11990:
11991: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11992: ageminpar=50;
11993: agemaxpar=100;
1.194 brouard 11994: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11995: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11996: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11997: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11998: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11999: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12000: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12001: }else{
12002: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12003: 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 12004: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12005: }
1.201 brouard 12006: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12007: stepm, weightopt,\
12008: model,imx,p,matcov,agemortsup);
12009:
12010: free_vector(lsurv,1,AGESUP);
12011: free_vector(lpop,1,AGESUP);
12012: free_vector(tpop,1,AGESUP);
1.220 brouard 12013: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12014: free_ivector(dcwave,firstobs,lastobs);
12015: free_vector(agecens,firstobs,lastobs);
12016: free_vector(ageexmed,firstobs,lastobs);
12017: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12018: #ifdef GSL
1.136 brouard 12019: #endif
1.186 brouard 12020: } /* Endof if mle==-3 mortality only */
1.205 brouard 12021: /* Standard */
12022: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12023: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12024: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12025: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12026: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12027: for (k=1; k<=npar;k++)
12028: printf(" %d %8.5f",k,p[k]);
12029: printf("\n");
1.205 brouard 12030: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12031: /* mlikeli uses func not funcone */
1.247 brouard 12032: /* for(i=1;i<nlstate;i++){ */
12033: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12034: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12035: /* } */
1.205 brouard 12036: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12037: }
12038: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12039: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12040: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12041: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12042: }
12043: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12044: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12045: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12046: for (k=1; k<=npar;k++)
12047: printf(" %d %8.5f",k,p[k]);
12048: printf("\n");
12049:
12050: /*--------- results files --------------*/
1.283 brouard 12051: /* 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 12052:
12053:
12054: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12055: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12056: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12057: for(i=1,jk=1; i <=nlstate; i++){
12058: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12059: if (k != i) {
12060: printf("%d%d ",i,k);
12061: fprintf(ficlog,"%d%d ",i,k);
12062: fprintf(ficres,"%1d%1d ",i,k);
12063: for(j=1; j <=ncovmodel; j++){
12064: printf("%12.7f ",p[jk]);
12065: fprintf(ficlog,"%12.7f ",p[jk]);
12066: fprintf(ficres,"%12.7f ",p[jk]);
12067: jk++;
12068: }
12069: printf("\n");
12070: fprintf(ficlog,"\n");
12071: fprintf(ficres,"\n");
12072: }
1.126 brouard 12073: }
12074: }
1.203 brouard 12075: if(mle != 0){
12076: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12077: ftolhess=ftol; /* Usually correct */
1.203 brouard 12078: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12079: 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");
12080: 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");
12081: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12082: for(k=1; k <=(nlstate+ndeath); k++){
12083: if (k != i) {
12084: printf("%d%d ",i,k);
12085: fprintf(ficlog,"%d%d ",i,k);
12086: for(j=1; j <=ncovmodel; j++){
12087: printf("%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
12088: fprintf(ficlog,"%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
12089: jk++;
12090: }
12091: printf("\n");
12092: fprintf(ficlog,"\n");
12093: }
12094: }
1.193 brouard 12095: }
1.203 brouard 12096: } /* end of hesscov and Wald tests */
1.225 brouard 12097:
1.203 brouard 12098: /* */
1.126 brouard 12099: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12100: printf("# Scales (for hessian or gradient estimation)\n");
12101: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12102: for(i=1,jk=1; i <=nlstate; i++){
12103: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12104: if (j!=i) {
12105: fprintf(ficres,"%1d%1d",i,j);
12106: printf("%1d%1d",i,j);
12107: fprintf(ficlog,"%1d%1d",i,j);
12108: for(k=1; k<=ncovmodel;k++){
12109: printf(" %.5e",delti[jk]);
12110: fprintf(ficlog," %.5e",delti[jk]);
12111: fprintf(ficres," %.5e",delti[jk]);
12112: jk++;
12113: }
12114: printf("\n");
12115: fprintf(ficlog,"\n");
12116: fprintf(ficres,"\n");
12117: }
1.126 brouard 12118: }
12119: }
12120:
12121: 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 12122: if(mle >= 1) /* To big for the screen */
1.126 brouard 12123: 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");
12124: 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");
12125: /* # 121 Var(a12)\n\ */
12126: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12127: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12128: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12129: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12130: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12131: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12132: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12133:
12134:
12135: /* Just to have a covariance matrix which will be more understandable
12136: even is we still don't want to manage dictionary of variables
12137: */
12138: for(itimes=1;itimes<=2;itimes++){
12139: jj=0;
12140: for(i=1; i <=nlstate; i++){
1.225 brouard 12141: for(j=1; j <=nlstate+ndeath; j++){
12142: if(j==i) continue;
12143: for(k=1; k<=ncovmodel;k++){
12144: jj++;
12145: ca[0]= k+'a'-1;ca[1]='\0';
12146: if(itimes==1){
12147: if(mle>=1)
12148: printf("#%1d%1d%d",i,j,k);
12149: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12150: fprintf(ficres,"#%1d%1d%d",i,j,k);
12151: }else{
12152: if(mle>=1)
12153: printf("%1d%1d%d",i,j,k);
12154: fprintf(ficlog,"%1d%1d%d",i,j,k);
12155: fprintf(ficres,"%1d%1d%d",i,j,k);
12156: }
12157: ll=0;
12158: for(li=1;li <=nlstate; li++){
12159: for(lj=1;lj <=nlstate+ndeath; lj++){
12160: if(lj==li) continue;
12161: for(lk=1;lk<=ncovmodel;lk++){
12162: ll++;
12163: if(ll<=jj){
12164: cb[0]= lk +'a'-1;cb[1]='\0';
12165: if(ll<jj){
12166: if(itimes==1){
12167: if(mle>=1)
12168: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12169: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12170: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12171: }else{
12172: if(mle>=1)
12173: printf(" %.5e",matcov[jj][ll]);
12174: fprintf(ficlog," %.5e",matcov[jj][ll]);
12175: fprintf(ficres," %.5e",matcov[jj][ll]);
12176: }
12177: }else{
12178: if(itimes==1){
12179: if(mle>=1)
12180: printf(" Var(%s%1d%1d)",ca,i,j);
12181: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12182: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12183: }else{
12184: if(mle>=1)
12185: printf(" %.7e",matcov[jj][ll]);
12186: fprintf(ficlog," %.7e",matcov[jj][ll]);
12187: fprintf(ficres," %.7e",matcov[jj][ll]);
12188: }
12189: }
12190: }
12191: } /* end lk */
12192: } /* end lj */
12193: } /* end li */
12194: if(mle>=1)
12195: printf("\n");
12196: fprintf(ficlog,"\n");
12197: fprintf(ficres,"\n");
12198: numlinepar++;
12199: } /* end k*/
12200: } /*end j */
1.126 brouard 12201: } /* end i */
12202: } /* end itimes */
12203:
12204: fflush(ficlog);
12205: fflush(ficres);
1.225 brouard 12206: while(fgets(line, MAXLINE, ficpar)) {
12207: /* If line starts with a # it is a comment */
12208: if (line[0] == '#') {
12209: numlinepar++;
12210: fputs(line,stdout);
12211: fputs(line,ficparo);
12212: fputs(line,ficlog);
12213: continue;
12214: }else
12215: break;
12216: }
12217:
1.209 brouard 12218: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12219: /* ungetc(c,ficpar); */
12220: /* fgets(line, MAXLINE, ficpar); */
12221: /* fputs(line,stdout); */
12222: /* fputs(line,ficparo); */
12223: /* } */
12224: /* ungetc(c,ficpar); */
1.126 brouard 12225:
12226: estepm=0;
1.209 brouard 12227: 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 12228:
12229: if (num_filled != 6) {
12230: 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);
12231: 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);
12232: goto end;
12233: }
12234: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12235: }
12236: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12237: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12238:
1.209 brouard 12239: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12240: if (estepm==0 || estepm < stepm) estepm=stepm;
12241: if (fage <= 2) {
12242: bage = ageminpar;
12243: fage = agemaxpar;
12244: }
12245:
12246: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12247: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12248: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12249:
1.186 brouard 12250: /* Other stuffs, more or less useful */
1.254 brouard 12251: while(fgets(line, MAXLINE, ficpar)) {
12252: /* If line starts with a # it is a comment */
12253: if (line[0] == '#') {
12254: numlinepar++;
12255: fputs(line,stdout);
12256: fputs(line,ficparo);
12257: fputs(line,ficlog);
12258: continue;
12259: }else
12260: break;
12261: }
12262:
12263: 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){
12264:
12265: if (num_filled != 7) {
12266: 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);
12267: 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);
12268: goto end;
12269: }
12270: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12271: 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);
12272: 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);
12273: 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 12274: }
1.254 brouard 12275:
12276: while(fgets(line, MAXLINE, ficpar)) {
12277: /* If line starts with a # it is a comment */
12278: if (line[0] == '#') {
12279: numlinepar++;
12280: fputs(line,stdout);
12281: fputs(line,ficparo);
12282: fputs(line,ficlog);
12283: continue;
12284: }else
12285: break;
1.126 brouard 12286: }
12287:
12288:
12289: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12290: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12291:
1.254 brouard 12292: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12293: if (num_filled != 1) {
12294: 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);
12295: 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);
12296: goto end;
12297: }
12298: printf("pop_based=%d\n",popbased);
12299: fprintf(ficlog,"pop_based=%d\n",popbased);
12300: fprintf(ficparo,"pop_based=%d\n",popbased);
12301: fprintf(ficres,"pop_based=%d\n",popbased);
12302: }
12303:
1.258 brouard 12304: /* Results */
12305: nresult=0;
12306: do{
12307: if(!fgets(line, MAXLINE, ficpar)){
12308: endishere=1;
12309: parameterline=14;
12310: }else if (line[0] == '#') {
12311: /* If line starts with a # it is a comment */
1.254 brouard 12312: numlinepar++;
12313: fputs(line,stdout);
12314: fputs(line,ficparo);
12315: fputs(line,ficlog);
12316: continue;
1.258 brouard 12317: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12318: parameterline=11;
1.296 ! brouard 12319: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12320: parameterline=12;
12321: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12322: parameterline=13;
12323: else{
12324: parameterline=14;
1.254 brouard 12325: }
1.258 brouard 12326: switch (parameterline){
12327: case 11:
1.296 ! brouard 12328: 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)){
! 12329: 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 12330: 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);
12331: 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);
12332: 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);
12333: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12334: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12335: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 ! brouard 12336: prvforecast = 1;
! 12337: }
! 12338: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
! 12339: printf(" Num_filled=%d, yearsfproj=%lf, mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
! 12340: prvforecast = 2;
! 12341: }
! 12342: else {
! 12343: 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);
! 12344: 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);
! 12345: goto end;
1.258 brouard 12346: }
1.254 brouard 12347: break;
1.258 brouard 12348: case 12:
1.296 ! brouard 12349: 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)){
! 12350: 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);
! 12351: 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);
! 12352: 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);
! 12353: 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);
! 12354: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 12355: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12356: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 ! brouard 12357: prvbackcast = 1;
! 12358: }
! 12359: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
! 12360: printf(" Num_filled=%d, yearsbproj=%lf, mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
! 12361: prvbackcast = 2;
! 12362: }
! 12363: else {
! 12364: 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);
! 12365: 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);
! 12366: goto end;
1.258 brouard 12367: }
1.230 brouard 12368: break;
1.296 ! brouard 12369: /* /\*fscanf(ficpar,"backcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&backcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj);*\/ */
! 12370: /* if((num_filled=sscanf(line,"backcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&backcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj)) !=EOF){ */
! 12371: /* if (num_filled != 8) { */
! 12372: /* printf("Error: Not 8 (data)parameters in line but %d, for example:backcast=1 starting-back-date=1/1/1990 final-back-date=1/1/1970 mobil_average=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line); */
! 12373: /* fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:backcast=1 starting-back-date=1/1/1990 final-back-date=1/1/1970 mobil_average=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line); */
! 12374: /* goto end; */
! 12375: /* } */
! 12376: /* printf("backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj); */
! 12377: /* fprintf(ficparo,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj); */
! 12378: /* fprintf(ficlog,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj); */
! 12379: /* fprintf(ficres,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj); */
! 12380: /* /\* day and month of proj2 are not used but only year anproj2.*\/ */
! 12381: /* dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.; */
! 12382: /* dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.; */
! 12383: /* } */
! 12384: /* break; */
1.258 brouard 12385: case 13:
12386: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12387: if (num_filled == 0){
12388: resultline[0]='\0';
12389: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12390: fprintf(ficlog,"Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12391: break;
12392: } else if (num_filled != 1){
12393: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12394: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12395: }
12396: nresult++; /* Sum of resultlines */
12397: printf("Result %d: result=%s\n",nresult, resultline);
12398: if(nresult > MAXRESULTLINES){
12399: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12400: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12401: goto end;
12402: }
12403: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12404: fprintf(ficparo,"result: %s\n",resultline);
12405: fprintf(ficres,"result: %s\n",resultline);
12406: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12407: break;
1.258 brouard 12408: case 14:
1.259 brouard 12409: if(ncovmodel >2 && nresult==0 ){
12410: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12411: goto end;
12412: }
1.259 brouard 12413: break;
1.258 brouard 12414: default:
12415: nresult=1;
12416: decoderesult(".",nresult ); /* No covariate */
12417: }
12418: } /* End switch parameterline */
12419: }while(endishere==0); /* End do */
1.126 brouard 12420:
1.230 brouard 12421: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12422: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12423:
12424: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12425: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12426: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12427: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12428: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12429: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12430: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12431: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12432: }else{
1.270 brouard 12433: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 ! brouard 12434: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
! 12435: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
! 12436: if(prvforecast==1){
! 12437: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
! 12438: jprojd=jproj1;
! 12439: mprojd=mproj1;
! 12440: anprojd=anproj1;
! 12441: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
! 12442: jprojf=jproj2;
! 12443: mprojf=mproj2;
! 12444: anprojf=anproj2;
! 12445: } else if(prvforecast == 2){
! 12446: dateprojd=dateintmean;
! 12447: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
! 12448: dateprojf=dateintmean+yrfproj;
! 12449: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
! 12450: }
! 12451: if(prvbackcast==1){
! 12452: datebackd=(jback1+12*mback1+365*anback1)/365;
! 12453: jbackd=jback1;
! 12454: mbackd=mback1;
! 12455: anbackd=anback1;
! 12456: datebackf=(jback2+12*mback2+365*anback2)/365;
! 12457: jbackf=jback2;
! 12458: mbackf=mback2;
! 12459: anbackf=anback2;
! 12460: } else if(prvbackcast == 2){
! 12461: datebackd=dateintmean;
! 12462: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
! 12463: datebackf=dateintmean-yrbproj;
! 12464: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
! 12465: }
! 12466:
! 12467: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 12468: }
12469: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 ! brouard 12470: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
! 12471: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 12472:
1.225 brouard 12473: /*------------ free_vector -------------*/
12474: /* chdir(path); */
1.220 brouard 12475:
1.215 brouard 12476: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12477: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12478: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12479: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12480: free_lvector(num,firstobs,lastobs);
12481: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12482: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12483: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12484: fclose(ficparo);
12485: fclose(ficres);
1.220 brouard 12486:
12487:
1.186 brouard 12488: /* Other results (useful)*/
1.220 brouard 12489:
12490:
1.126 brouard 12491: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12492: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12493: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12494: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12495: fclose(ficrespl);
12496:
12497: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12498: /*#include "hpijx.h"*/
12499: hPijx(p, bage, fage);
1.145 brouard 12500: fclose(ficrespij);
1.227 brouard 12501:
1.220 brouard 12502: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12503: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12504: k=1;
1.126 brouard 12505: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12506:
1.269 brouard 12507: /* Prevalence for each covariate combination in probs[age][status][cov] */
12508: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12509: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12510: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12511: for(k=1;k<=ncovcombmax;k++)
12512: probs[i][j][k]=0.;
1.269 brouard 12513: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12514: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12515: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12516: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12517: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12518: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12519: for(k=1;k<=ncovcombmax;k++)
12520: mobaverages[i][j][k]=0.;
1.219 brouard 12521: mobaverage=mobaverages;
12522: if (mobilav!=0) {
1.235 brouard 12523: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12524: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12525: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12526: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12527: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12528: }
1.269 brouard 12529: } else if (mobilavproj !=0) {
1.235 brouard 12530: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12531: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12532: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12533: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12534: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12535: }
1.269 brouard 12536: }else{
12537: printf("Internal error moving average\n");
12538: fflush(stdout);
12539: exit(1);
1.219 brouard 12540: }
12541: }/* end if moving average */
1.227 brouard 12542:
1.126 brouard 12543: /*---------- Forecasting ------------------*/
1.296 ! brouard 12544: if(prevfcast==1){
! 12545: /* /\* if(stepm ==1){*\/ */
! 12546: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
! 12547: /*This done previously after freqsummary.*/
! 12548: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
! 12549: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
! 12550:
! 12551: /* } else if (prvforecast==2){ */
! 12552: /* /\* if(stepm ==1){*\/ */
! 12553: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
! 12554: /* } */
! 12555: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
! 12556: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 12557: }
1.269 brouard 12558:
1.296 ! brouard 12559: /* Prevbcasting */
! 12560: if(prevbcast==1){
1.219 brouard 12561: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12562: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12563: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12564:
12565: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12566:
12567: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12568:
1.219 brouard 12569: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12570: fclose(ficresplb);
12571:
1.222 brouard 12572: hBijx(p, bage, fage, mobaverage);
12573: fclose(ficrespijb);
1.219 brouard 12574:
1.296 ! brouard 12575: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
! 12576: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
! 12577: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
! 12578: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
! 12579: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
! 12580: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
! 12581:
! 12582:
1.269 brouard 12583: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12584:
12585:
1.269 brouard 12586: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12587: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12588: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12589: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 ! brouard 12590: } /* end Prevbcasting */
1.268 brouard 12591:
1.186 brouard 12592:
12593: /* ------ Other prevalence ratios------------ */
1.126 brouard 12594:
1.215 brouard 12595: free_ivector(wav,1,imx);
12596: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12597: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12598: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12599:
12600:
1.127 brouard 12601: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12602:
1.201 brouard 12603: strcpy(filerese,"E_");
12604: strcat(filerese,fileresu);
1.126 brouard 12605: if((ficreseij=fopen(filerese,"w"))==NULL) {
12606: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12607: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12608: }
1.208 brouard 12609: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12610: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12611:
12612: pstamp(ficreseij);
1.219 brouard 12613:
1.235 brouard 12614: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12615: if (cptcovn < 1){i1=1;}
12616:
12617: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12618: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12619: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12620: continue;
1.219 brouard 12621: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12622: printf("\n#****** ");
1.225 brouard 12623: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12624: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12625: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12626: }
12627: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12628: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12629: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12630: }
12631: fprintf(ficreseij,"******\n");
1.235 brouard 12632: printf("******\n");
1.219 brouard 12633:
12634: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12635: oldm=oldms;savm=savms;
1.235 brouard 12636: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12637:
1.219 brouard 12638: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12639: }
12640: fclose(ficreseij);
1.208 brouard 12641: printf("done evsij\n");fflush(stdout);
12642: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12643:
1.218 brouard 12644:
1.227 brouard 12645: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12646:
1.201 brouard 12647: strcpy(filerest,"T_");
12648: strcat(filerest,fileresu);
1.127 brouard 12649: if((ficrest=fopen(filerest,"w"))==NULL) {
12650: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12651: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12652: }
1.208 brouard 12653: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12654: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12655: strcpy(fileresstde,"STDE_");
12656: strcat(fileresstde,fileresu);
1.126 brouard 12657: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12658: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12659: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12660: }
1.227 brouard 12661: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12662: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12663:
1.201 brouard 12664: strcpy(filerescve,"CVE_");
12665: strcat(filerescve,fileresu);
1.126 brouard 12666: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12667: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12668: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12669: }
1.227 brouard 12670: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12671: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12672:
1.201 brouard 12673: strcpy(fileresv,"V_");
12674: strcat(fileresv,fileresu);
1.126 brouard 12675: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12676: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12677: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12678: }
1.227 brouard 12679: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12680: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12681:
1.235 brouard 12682: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12683: if (cptcovn < 1){i1=1;}
12684:
12685: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12686: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12687: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12688: continue;
1.242 brouard 12689: printf("\n#****** Result for:");
12690: fprintf(ficrest,"\n#****** Result for:");
12691: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12692: for(j=1;j<=cptcoveff;j++){
12693: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12694: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12695: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12696: }
1.235 brouard 12697: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12698: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12699: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12700: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12701: }
1.208 brouard 12702: fprintf(ficrest,"******\n");
1.227 brouard 12703: fprintf(ficlog,"******\n");
12704: printf("******\n");
1.208 brouard 12705:
12706: fprintf(ficresstdeij,"\n#****** ");
12707: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12708: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12709: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12710: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12711: }
1.235 brouard 12712: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12713: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12714: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12715: }
1.208 brouard 12716: fprintf(ficresstdeij,"******\n");
12717: fprintf(ficrescveij,"******\n");
12718:
12719: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12720: /* pstamp(ficresvij); */
1.225 brouard 12721: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12722: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12723: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12724: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12725: }
1.208 brouard 12726: fprintf(ficresvij,"******\n");
12727:
12728: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12729: oldm=oldms;savm=savms;
1.235 brouard 12730: printf(" cvevsij ");
12731: fprintf(ficlog, " cvevsij ");
12732: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12733: printf(" end cvevsij \n ");
12734: fprintf(ficlog, " end cvevsij \n ");
12735:
12736: /*
12737: */
12738: /* goto endfree; */
12739:
12740: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12741: pstamp(ficrest);
12742:
1.269 brouard 12743: epj=vector(1,nlstate+1);
1.208 brouard 12744: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12745: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12746: cptcod= 0; /* To be deleted */
12747: printf("varevsij vpopbased=%d \n",vpopbased);
12748: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12749: 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 12750: 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 ");
12751: if(vpopbased==1)
12752: 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);
12753: else
1.288 brouard 12754: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12755: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12756: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12757: fprintf(ficrest,"\n");
12758: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 12759: printf("Computing age specific forward period (stable) prevalences in each health state \n");
12760: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12761: for(age=bage; age <=fage ;age++){
1.235 brouard 12762: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12763: if (vpopbased==1) {
12764: if(mobilav ==0){
12765: for(i=1; i<=nlstate;i++)
12766: prlim[i][i]=probs[(int)age][i][k];
12767: }else{ /* mobilav */
12768: for(i=1; i<=nlstate;i++)
12769: prlim[i][i]=mobaverage[(int)age][i][k];
12770: }
12771: }
1.219 brouard 12772:
1.227 brouard 12773: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12774: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12775: /* printf(" age %4.0f ",age); */
12776: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12777: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12778: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12779: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12780: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12781: }
12782: epj[nlstate+1] +=epj[j];
12783: }
12784: /* printf(" age %4.0f \n",age); */
1.219 brouard 12785:
1.227 brouard 12786: for(i=1, vepp=0.;i <=nlstate;i++)
12787: for(j=1;j <=nlstate;j++)
12788: vepp += vareij[i][j][(int)age];
12789: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12790: for(j=1;j <=nlstate;j++){
12791: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12792: }
12793: fprintf(ficrest,"\n");
12794: }
1.208 brouard 12795: } /* End vpopbased */
1.269 brouard 12796: free_vector(epj,1,nlstate+1);
1.208 brouard 12797: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12798: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12799: printf("done selection\n");fflush(stdout);
12800: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12801:
1.235 brouard 12802: } /* End k selection */
1.227 brouard 12803:
12804: printf("done State-specific expectancies\n");fflush(stdout);
12805: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12806:
1.288 brouard 12807: /* variance-covariance of forward period prevalence*/
1.269 brouard 12808: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12809:
1.227 brouard 12810:
1.290 brouard 12811: free_vector(weight,firstobs,lastobs);
1.227 brouard 12812: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 12813: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
12814: free_matrix(anint,1,maxwav,firstobs,lastobs);
12815: free_matrix(mint,1,maxwav,firstobs,lastobs);
12816: free_ivector(cod,firstobs,lastobs);
1.227 brouard 12817: free_ivector(tab,1,NCOVMAX);
12818: fclose(ficresstdeij);
12819: fclose(ficrescveij);
12820: fclose(ficresvij);
12821: fclose(ficrest);
12822: fclose(ficpar);
12823:
12824:
1.126 brouard 12825: /*---------- End : free ----------------*/
1.219 brouard 12826: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12827: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12828: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12829: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12830: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12831: } /* mle==-3 arrives here for freeing */
1.227 brouard 12832: /* endfree:*/
12833: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12834: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12835: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 12836: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
12837: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
12838: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
12839: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 12840: free_matrix(matcov,1,npar,1,npar);
12841: free_matrix(hess,1,npar,1,npar);
12842: /*free_vector(delti,1,npar);*/
12843: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12844: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12845: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12846: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12847:
12848: free_ivector(ncodemax,1,NCOVMAX);
12849: free_ivector(ncodemaxwundef,1,NCOVMAX);
12850: free_ivector(Dummy,-1,NCOVMAX);
12851: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12852: free_ivector(DummyV,1,NCOVMAX);
12853: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12854: free_ivector(Typevar,-1,NCOVMAX);
12855: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12856: free_ivector(TvarsQ,1,NCOVMAX);
12857: free_ivector(TvarsQind,1,NCOVMAX);
12858: free_ivector(TvarsD,1,NCOVMAX);
12859: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12860: free_ivector(TvarFD,1,NCOVMAX);
12861: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12862: free_ivector(TvarF,1,NCOVMAX);
12863: free_ivector(TvarFind,1,NCOVMAX);
12864: free_ivector(TvarV,1,NCOVMAX);
12865: free_ivector(TvarVind,1,NCOVMAX);
12866: free_ivector(TvarA,1,NCOVMAX);
12867: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12868: free_ivector(TvarFQ,1,NCOVMAX);
12869: free_ivector(TvarFQind,1,NCOVMAX);
12870: free_ivector(TvarVD,1,NCOVMAX);
12871: free_ivector(TvarVDind,1,NCOVMAX);
12872: free_ivector(TvarVQ,1,NCOVMAX);
12873: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12874: free_ivector(Tvarsel,1,NCOVMAX);
12875: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12876: free_ivector(Tposprod,1,NCOVMAX);
12877: free_ivector(Tprod,1,NCOVMAX);
12878: free_ivector(Tvaraff,1,NCOVMAX);
12879: free_ivector(invalidvarcomb,1,ncovcombmax);
12880: free_ivector(Tage,1,NCOVMAX);
12881: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12882: free_ivector(TmodelInvind,1,NCOVMAX);
12883: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12884:
12885: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12886: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12887: fflush(fichtm);
12888: fflush(ficgp);
12889:
1.227 brouard 12890:
1.126 brouard 12891: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12892: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12893: 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 12894: }else{
12895: printf("End of Imach\n");
12896: fprintf(ficlog,"End of Imach\n");
12897: }
12898: printf("See log file on %s\n",filelog);
12899: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12900: /*(void) gettimeofday(&end_time,&tzp);*/
12901: rend_time = time(NULL);
12902: end_time = *localtime(&rend_time);
12903: /* tml = *localtime(&end_time.tm_sec); */
12904: strcpy(strtend,asctime(&end_time));
1.126 brouard 12905: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12906: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12907: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12908:
1.157 brouard 12909: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12910: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12911: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12912: /* printf("Total time was %d uSec.\n", total_usecs);*/
12913: /* if(fileappend(fichtm,optionfilehtm)){ */
12914: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12915: fclose(fichtm);
12916: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12917: fclose(fichtmcov);
12918: fclose(ficgp);
12919: fclose(ficlog);
12920: /*------ End -----------*/
1.227 brouard 12921:
1.281 brouard 12922:
12923: /* Executes gnuplot */
1.227 brouard 12924:
12925: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12926: #ifdef WIN32
1.227 brouard 12927: if (_chdir(pathcd) != 0)
12928: printf("Can't move to directory %s!\n",path);
12929: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12930: #else
1.227 brouard 12931: if(chdir(pathcd) != 0)
12932: printf("Can't move to directory %s!\n", path);
12933: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12934: #endif
1.126 brouard 12935: printf("Current directory %s!\n",pathcd);
12936: /*strcat(plotcmd,CHARSEPARATOR);*/
12937: sprintf(plotcmd,"gnuplot");
1.157 brouard 12938: #ifdef _WIN32
1.126 brouard 12939: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12940: #endif
12941: if(!stat(plotcmd,&info)){
1.158 brouard 12942: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12943: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12944: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12945: }else
12946: strcpy(pplotcmd,plotcmd);
1.157 brouard 12947: #ifdef __unix
1.126 brouard 12948: strcpy(plotcmd,GNUPLOTPROGRAM);
12949: if(!stat(plotcmd,&info)){
1.158 brouard 12950: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12951: }else
12952: strcpy(pplotcmd,plotcmd);
12953: #endif
12954: }else
12955: strcpy(pplotcmd,plotcmd);
12956:
12957: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12958: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 12959: strcpy(pplotcmd,plotcmd);
1.227 brouard 12960:
1.126 brouard 12961: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 12962: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12963: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12964: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 12965: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 12966: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 12967: strcpy(plotcmd,pplotcmd);
12968: }
1.126 brouard 12969: }
1.158 brouard 12970: printf(" Successful, please wait...");
1.126 brouard 12971: while (z[0] != 'q') {
12972: /* chdir(path); */
1.154 brouard 12973: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12974: scanf("%s",z);
12975: /* if (z[0] == 'c') system("./imach"); */
12976: if (z[0] == 'e') {
1.158 brouard 12977: #ifdef __APPLE__
1.152 brouard 12978: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12979: #elif __linux
12980: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12981: #else
1.152 brouard 12982: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12983: #endif
12984: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12985: system(pplotcmd);
1.126 brouard 12986: }
12987: else if (z[0] == 'g') system(plotcmd);
12988: else if (z[0] == 'q') exit(0);
12989: }
1.227 brouard 12990: end:
1.126 brouard 12991: while (z[0] != 'q') {
1.195 brouard 12992: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12993: scanf("%s",z);
12994: }
1.283 brouard 12995: printf("End\n");
1.282 brouard 12996: exit(0);
1.126 brouard 12997: }
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