Annotation of imach/src/imach.c, revision 1.295
1.295 ! brouard 1: /* $Id: imach.c,v 1.294 2019/05/16 14:54:33 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.295 ! brouard 4: Revision 1.294 2019/05/16 14:54:33 brouard
! 5: Summary: There was some wrong lines added
! 6:
1.294 brouard 7: Revision 1.293 2019/05/09 15:17:34 brouard
8: *** empty log message ***
9:
1.293 brouard 10: Revision 1.292 2019/05/09 14:17:20 brouard
11: Summary: Some updates
12:
1.292 brouard 13: Revision 1.291 2019/05/09 13:44:18 brouard
14: Summary: Before ncovmax
15:
1.291 brouard 16: Revision 1.290 2019/05/09 13:39:37 brouard
17: Summary: 0.99r18 unlimited number of individuals
18:
19: 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.
20:
1.290 brouard 21: Revision 1.289 2018/12/13 09:16:26 brouard
22: Summary: Bug for young ages (<-30) will be in r17
23:
1.289 brouard 24: Revision 1.288 2018/05/02 20:58:27 brouard
25: Summary: Some bugs fixed
26:
1.288 brouard 27: Revision 1.287 2018/05/01 17:57:25 brouard
28: Summary: Bug fixed by providing frequencies only for non missing covariates
29:
1.287 brouard 30: Revision 1.286 2018/04/27 14:27:04 brouard
31: Summary: some minor bugs
32:
1.286 brouard 33: Revision 1.285 2018/04/21 21:02:16 brouard
34: Summary: Some bugs fixed, valgrind tested
35:
1.285 brouard 36: Revision 1.284 2018/04/20 05:22:13 brouard
37: Summary: Computing mean and stdeviation of fixed quantitative variables
38:
1.284 brouard 39: Revision 1.283 2018/04/19 14:49:16 brouard
40: Summary: Some minor bugs fixed
41:
1.283 brouard 42: Revision 1.282 2018/02/27 22:50:02 brouard
43: *** empty log message ***
44:
1.282 brouard 45: Revision 1.281 2018/02/27 19:25:23 brouard
46: Summary: Adding second argument for quitting
47:
1.281 brouard 48: Revision 1.280 2018/02/21 07:58:13 brouard
49: Summary: 0.99r15
50:
51: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
52:
1.280 brouard 53: Revision 1.279 2017/07/20 13:35:01 brouard
54: Summary: temporary working
55:
1.279 brouard 56: Revision 1.278 2017/07/19 14:09:02 brouard
57: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
58:
1.278 brouard 59: Revision 1.277 2017/07/17 08:53:49 brouard
60: Summary: BOM files can be read now
61:
1.277 brouard 62: Revision 1.276 2017/06/30 15:48:31 brouard
63: Summary: Graphs improvements
64:
1.276 brouard 65: Revision 1.275 2017/06/30 13:39:33 brouard
66: Summary: Saito's color
67:
1.275 brouard 68: Revision 1.274 2017/06/29 09:47:08 brouard
69: Summary: Version 0.99r14
70:
1.274 brouard 71: Revision 1.273 2017/06/27 11:06:02 brouard
72: Summary: More documentation on projections
73:
1.273 brouard 74: Revision 1.272 2017/06/27 10:22:40 brouard
75: Summary: Color of backprojection changed from 6 to 5(yellow)
76:
1.272 brouard 77: Revision 1.271 2017/06/27 10:17:50 brouard
78: Summary: Some bug with rint
79:
1.271 brouard 80: Revision 1.270 2017/05/24 05:45:29 brouard
81: *** empty log message ***
82:
1.270 brouard 83: Revision 1.269 2017/05/23 08:39:25 brouard
84: Summary: Code into subroutine, cleanings
85:
1.269 brouard 86: Revision 1.268 2017/05/18 20:09:32 brouard
87: Summary: backprojection and confidence intervals of backprevalence
88:
1.268 brouard 89: Revision 1.267 2017/05/13 10:25:05 brouard
90: Summary: temporary save for backprojection
91:
1.267 brouard 92: Revision 1.266 2017/05/13 07:26:12 brouard
93: Summary: Version 0.99r13 (improvements and bugs fixed)
94:
1.266 brouard 95: Revision 1.265 2017/04/26 16:22:11 brouard
96: Summary: imach 0.99r13 Some bugs fixed
97:
1.265 brouard 98: Revision 1.264 2017/04/26 06:01:29 brouard
99: Summary: Labels in graphs
100:
1.264 brouard 101: Revision 1.263 2017/04/24 15:23:15 brouard
102: Summary: to save
103:
1.263 brouard 104: Revision 1.262 2017/04/18 16:48:12 brouard
105: *** empty log message ***
106:
1.262 brouard 107: Revision 1.261 2017/04/05 10:14:09 brouard
108: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
109:
1.261 brouard 110: Revision 1.260 2017/04/04 17:46:59 brouard
111: Summary: Gnuplot indexations fixed (humm)
112:
1.260 brouard 113: Revision 1.259 2017/04/04 13:01:16 brouard
114: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
115:
1.259 brouard 116: Revision 1.258 2017/04/03 10:17:47 brouard
117: Summary: Version 0.99r12
118:
119: Some cleanings, conformed with updated documentation.
120:
1.258 brouard 121: Revision 1.257 2017/03/29 16:53:30 brouard
122: Summary: Temp
123:
1.257 brouard 124: Revision 1.256 2017/03/27 05:50:23 brouard
125: Summary: Temporary
126:
1.256 brouard 127: Revision 1.255 2017/03/08 16:02:28 brouard
128: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
129:
1.255 brouard 130: Revision 1.254 2017/03/08 07:13:00 brouard
131: Summary: Fixing data parameter line
132:
1.254 brouard 133: Revision 1.253 2016/12/15 11:59:41 brouard
134: Summary: 0.99 in progress
135:
1.253 brouard 136: Revision 1.252 2016/09/15 21:15:37 brouard
137: *** empty log message ***
138:
1.252 brouard 139: Revision 1.251 2016/09/15 15:01:13 brouard
140: Summary: not working
141:
1.251 brouard 142: Revision 1.250 2016/09/08 16:07:27 brouard
143: Summary: continue
144:
1.250 brouard 145: Revision 1.249 2016/09/07 17:14:18 brouard
146: Summary: Starting values from frequencies
147:
1.249 brouard 148: Revision 1.248 2016/09/07 14:10:18 brouard
149: *** empty log message ***
150:
1.248 brouard 151: Revision 1.247 2016/09/02 11:11:21 brouard
152: *** empty log message ***
153:
1.247 brouard 154: Revision 1.246 2016/09/02 08:49:22 brouard
155: *** empty log message ***
156:
1.246 brouard 157: Revision 1.245 2016/09/02 07:25:01 brouard
158: *** empty log message ***
159:
1.245 brouard 160: Revision 1.244 2016/09/02 07:17:34 brouard
161: *** empty log message ***
162:
1.244 brouard 163: Revision 1.243 2016/09/02 06:45:35 brouard
164: *** empty log message ***
165:
1.243 brouard 166: Revision 1.242 2016/08/30 15:01:20 brouard
167: Summary: Fixing a lots
168:
1.242 brouard 169: Revision 1.241 2016/08/29 17:17:25 brouard
170: Summary: gnuplot problem in Back projection to fix
171:
1.241 brouard 172: Revision 1.240 2016/08/29 07:53:18 brouard
173: Summary: Better
174:
1.240 brouard 175: Revision 1.239 2016/08/26 15:51:03 brouard
176: Summary: Improvement in Powell output in order to copy and paste
177:
178: Author:
179:
1.239 brouard 180: Revision 1.238 2016/08/26 14:23:35 brouard
181: Summary: Starting tests of 0.99
182:
1.238 brouard 183: Revision 1.237 2016/08/26 09:20:19 brouard
184: Summary: to valgrind
185:
1.237 brouard 186: Revision 1.236 2016/08/25 10:50:18 brouard
187: *** empty log message ***
188:
1.236 brouard 189: Revision 1.235 2016/08/25 06:59:23 brouard
190: *** empty log message ***
191:
1.235 brouard 192: Revision 1.234 2016/08/23 16:51:20 brouard
193: *** empty log message ***
194:
1.234 brouard 195: Revision 1.233 2016/08/23 07:40:50 brouard
196: Summary: not working
197:
1.233 brouard 198: Revision 1.232 2016/08/22 14:20:21 brouard
199: Summary: not working
200:
1.232 brouard 201: Revision 1.231 2016/08/22 07:17:15 brouard
202: Summary: not working
203:
1.231 brouard 204: Revision 1.230 2016/08/22 06:55:53 brouard
205: Summary: Not working
206:
1.230 brouard 207: Revision 1.229 2016/07/23 09:45:53 brouard
208: Summary: Completing for func too
209:
1.229 brouard 210: Revision 1.228 2016/07/22 17:45:30 brouard
211: Summary: Fixing some arrays, still debugging
212:
1.227 brouard 213: Revision 1.226 2016/07/12 18:42:34 brouard
214: Summary: temp
215:
1.226 brouard 216: Revision 1.225 2016/07/12 08:40:03 brouard
217: Summary: saving but not running
218:
1.225 brouard 219: Revision 1.224 2016/07/01 13:16:01 brouard
220: Summary: Fixes
221:
1.224 brouard 222: Revision 1.223 2016/02/19 09:23:35 brouard
223: Summary: temporary
224:
1.223 brouard 225: Revision 1.222 2016/02/17 08:14:50 brouard
226: Summary: Probably last 0.98 stable version 0.98r6
227:
1.222 brouard 228: Revision 1.221 2016/02/15 23:35:36 brouard
229: Summary: minor bug
230:
1.220 brouard 231: Revision 1.219 2016/02/15 00:48:12 brouard
232: *** empty log message ***
233:
1.219 brouard 234: Revision 1.218 2016/02/12 11:29:23 brouard
235: Summary: 0.99 Back projections
236:
1.218 brouard 237: Revision 1.217 2015/12/23 17:18:31 brouard
238: Summary: Experimental backcast
239:
1.217 brouard 240: Revision 1.216 2015/12/18 17:32:11 brouard
241: Summary: 0.98r4 Warning and status=-2
242:
243: Version 0.98r4 is now:
244: - displaying an error when status is -1, date of interview unknown and date of death known;
245: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
246: Older changes concerning s=-2, dating from 2005 have been supersed.
247:
1.216 brouard 248: Revision 1.215 2015/12/16 08:52:24 brouard
249: Summary: 0.98r4 working
250:
1.215 brouard 251: Revision 1.214 2015/12/16 06:57:54 brouard
252: Summary: temporary not working
253:
1.214 brouard 254: Revision 1.213 2015/12/11 18:22:17 brouard
255: Summary: 0.98r4
256:
1.213 brouard 257: Revision 1.212 2015/11/21 12:47:24 brouard
258: Summary: minor typo
259:
1.212 brouard 260: Revision 1.211 2015/11/21 12:41:11 brouard
261: Summary: 0.98r3 with some graph of projected cross-sectional
262:
263: Author: Nicolas Brouard
264:
1.211 brouard 265: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 266: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 267: Summary: Adding ftolpl parameter
268: Author: N Brouard
269:
270: We had difficulties to get smoothed confidence intervals. It was due
271: to the period prevalence which wasn't computed accurately. The inner
272: parameter ftolpl is now an outer parameter of the .imach parameter
273: file after estepm. If ftolpl is small 1.e-4 and estepm too,
274: computation are long.
275:
1.209 brouard 276: Revision 1.208 2015/11/17 14:31:57 brouard
277: Summary: temporary
278:
1.208 brouard 279: Revision 1.207 2015/10/27 17:36:57 brouard
280: *** empty log message ***
281:
1.207 brouard 282: Revision 1.206 2015/10/24 07:14:11 brouard
283: *** empty log message ***
284:
1.206 brouard 285: Revision 1.205 2015/10/23 15:50:53 brouard
286: Summary: 0.98r3 some clarification for graphs on likelihood contributions
287:
1.205 brouard 288: Revision 1.204 2015/10/01 16:20:26 brouard
289: Summary: Some new graphs of contribution to likelihood
290:
1.204 brouard 291: Revision 1.203 2015/09/30 17:45:14 brouard
292: Summary: looking at better estimation of the hessian
293:
294: Also a better criteria for convergence to the period prevalence And
295: therefore adding the number of years needed to converge. (The
296: prevalence in any alive state shold sum to one
297:
1.203 brouard 298: Revision 1.202 2015/09/22 19:45:16 brouard
299: Summary: Adding some overall graph on contribution to likelihood. Might change
300:
1.202 brouard 301: Revision 1.201 2015/09/15 17:34:58 brouard
302: Summary: 0.98r0
303:
304: - Some new graphs like suvival functions
305: - Some bugs fixed like model=1+age+V2.
306:
1.201 brouard 307: Revision 1.200 2015/09/09 16:53:55 brouard
308: Summary: Big bug thanks to Flavia
309:
310: Even model=1+age+V2. did not work anymore
311:
1.200 brouard 312: Revision 1.199 2015/09/07 14:09:23 brouard
313: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
314:
1.199 brouard 315: Revision 1.198 2015/09/03 07:14:39 brouard
316: Summary: 0.98q5 Flavia
317:
1.198 brouard 318: Revision 1.197 2015/09/01 18:24:39 brouard
319: *** empty log message ***
320:
1.197 brouard 321: Revision 1.196 2015/08/18 23:17:52 brouard
322: Summary: 0.98q5
323:
1.196 brouard 324: Revision 1.195 2015/08/18 16:28:39 brouard
325: Summary: Adding a hack for testing purpose
326:
327: After reading the title, ftol and model lines, if the comment line has
328: a q, starting with #q, the answer at the end of the run is quit. It
329: permits to run test files in batch with ctest. The former workaround was
330: $ echo q | imach foo.imach
331:
1.195 brouard 332: Revision 1.194 2015/08/18 13:32:00 brouard
333: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
334:
1.194 brouard 335: Revision 1.193 2015/08/04 07:17:42 brouard
336: Summary: 0.98q4
337:
1.193 brouard 338: Revision 1.192 2015/07/16 16:49:02 brouard
339: Summary: Fixing some outputs
340:
1.192 brouard 341: Revision 1.191 2015/07/14 10:00:33 brouard
342: Summary: Some fixes
343:
1.191 brouard 344: Revision 1.190 2015/05/05 08:51:13 brouard
345: Summary: Adding digits in output parameters (7 digits instead of 6)
346:
347: Fix 1+age+.
348:
1.190 brouard 349: Revision 1.189 2015/04/30 14:45:16 brouard
350: Summary: 0.98q2
351:
1.189 brouard 352: Revision 1.188 2015/04/30 08:27:53 brouard
353: *** empty log message ***
354:
1.188 brouard 355: Revision 1.187 2015/04/29 09:11:15 brouard
356: *** empty log message ***
357:
1.187 brouard 358: Revision 1.186 2015/04/23 12:01:52 brouard
359: Summary: V1*age is working now, version 0.98q1
360:
361: Some codes had been disabled in order to simplify and Vn*age was
362: working in the optimization phase, ie, giving correct MLE parameters,
363: but, as usual, outputs were not correct and program core dumped.
364:
1.186 brouard 365: Revision 1.185 2015/03/11 13:26:42 brouard
366: Summary: Inclusion of compile and links command line for Intel Compiler
367:
1.185 brouard 368: Revision 1.184 2015/03/11 11:52:39 brouard
369: Summary: Back from Windows 8. Intel Compiler
370:
1.184 brouard 371: Revision 1.183 2015/03/10 20:34:32 brouard
372: Summary: 0.98q0, trying with directest, mnbrak fixed
373:
374: We use directest instead of original Powell test; probably no
375: incidence on the results, but better justifications;
376: We fixed Numerical Recipes mnbrak routine which was wrong and gave
377: wrong results.
378:
1.183 brouard 379: Revision 1.182 2015/02/12 08:19:57 brouard
380: Summary: Trying to keep directest which seems simpler and more general
381: Author: Nicolas Brouard
382:
1.182 brouard 383: Revision 1.181 2015/02/11 23:22:24 brouard
384: Summary: Comments on Powell added
385:
386: Author:
387:
1.181 brouard 388: Revision 1.180 2015/02/11 17:33:45 brouard
389: Summary: Finishing move from main to function (hpijx and prevalence_limit)
390:
1.180 brouard 391: Revision 1.179 2015/01/04 09:57:06 brouard
392: Summary: back to OS/X
393:
1.179 brouard 394: Revision 1.178 2015/01/04 09:35:48 brouard
395: *** empty log message ***
396:
1.178 brouard 397: Revision 1.177 2015/01/03 18:40:56 brouard
398: Summary: Still testing ilc32 on OSX
399:
1.177 brouard 400: Revision 1.176 2015/01/03 16:45:04 brouard
401: *** empty log message ***
402:
1.176 brouard 403: Revision 1.175 2015/01/03 16:33:42 brouard
404: *** empty log message ***
405:
1.175 brouard 406: Revision 1.174 2015/01/03 16:15:49 brouard
407: Summary: Still in cross-compilation
408:
1.174 brouard 409: Revision 1.173 2015/01/03 12:06:26 brouard
410: Summary: trying to detect cross-compilation
411:
1.173 brouard 412: Revision 1.172 2014/12/27 12:07:47 brouard
413: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
414:
1.172 brouard 415: Revision 1.171 2014/12/23 13:26:59 brouard
416: Summary: Back from Visual C
417:
418: Still problem with utsname.h on Windows
419:
1.171 brouard 420: Revision 1.170 2014/12/23 11:17:12 brouard
421: Summary: Cleaning some \%% back to %%
422:
423: The escape was mandatory for a specific compiler (which one?), but too many warnings.
424:
1.170 brouard 425: Revision 1.169 2014/12/22 23:08:31 brouard
426: Summary: 0.98p
427:
428: Outputs some informations on compiler used, OS etc. Testing on different platforms.
429:
1.169 brouard 430: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 431: Summary: update
1.169 brouard 432:
1.168 brouard 433: Revision 1.167 2014/12/22 13:50:56 brouard
434: Summary: Testing uname and compiler version and if compiled 32 or 64
435:
436: Testing on Linux 64
437:
1.167 brouard 438: Revision 1.166 2014/12/22 11:40:47 brouard
439: *** empty log message ***
440:
1.166 brouard 441: Revision 1.165 2014/12/16 11:20:36 brouard
442: Summary: After compiling on Visual C
443:
444: * imach.c (Module): Merging 1.61 to 1.162
445:
1.165 brouard 446: Revision 1.164 2014/12/16 10:52:11 brouard
447: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
448:
449: * imach.c (Module): Merging 1.61 to 1.162
450:
1.164 brouard 451: Revision 1.163 2014/12/16 10:30:11 brouard
452: * imach.c (Module): Merging 1.61 to 1.162
453:
1.163 brouard 454: Revision 1.162 2014/09/25 11:43:39 brouard
455: Summary: temporary backup 0.99!
456:
1.162 brouard 457: Revision 1.1 2014/09/16 11:06:58 brouard
458: Summary: With some code (wrong) for nlopt
459:
460: Author:
461:
462: Revision 1.161 2014/09/15 20:41:41 brouard
463: Summary: Problem with macro SQR on Intel compiler
464:
1.161 brouard 465: Revision 1.160 2014/09/02 09:24:05 brouard
466: *** empty log message ***
467:
1.160 brouard 468: Revision 1.159 2014/09/01 10:34:10 brouard
469: Summary: WIN32
470: Author: Brouard
471:
1.159 brouard 472: Revision 1.158 2014/08/27 17:11:51 brouard
473: *** empty log message ***
474:
1.158 brouard 475: Revision 1.157 2014/08/27 16:26:55 brouard
476: Summary: Preparing windows Visual studio version
477: Author: Brouard
478:
479: In order to compile on Visual studio, time.h is now correct and time_t
480: and tm struct should be used. difftime should be used but sometimes I
481: just make the differences in raw time format (time(&now).
482: Trying to suppress #ifdef LINUX
483: Add xdg-open for __linux in order to open default browser.
484:
1.157 brouard 485: Revision 1.156 2014/08/25 20:10:10 brouard
486: *** empty log message ***
487:
1.156 brouard 488: Revision 1.155 2014/08/25 18:32:34 brouard
489: Summary: New compile, minor changes
490: Author: Brouard
491:
1.155 brouard 492: Revision 1.154 2014/06/20 17:32:08 brouard
493: Summary: Outputs now all graphs of convergence to period prevalence
494:
1.154 brouard 495: Revision 1.153 2014/06/20 16:45:46 brouard
496: Summary: If 3 live state, convergence to period prevalence on same graph
497: Author: Brouard
498:
1.153 brouard 499: Revision 1.152 2014/06/18 17:54:09 brouard
500: Summary: open browser, use gnuplot on same dir than imach if not found in the path
501:
1.152 brouard 502: Revision 1.151 2014/06/18 16:43:30 brouard
503: *** empty log message ***
504:
1.151 brouard 505: Revision 1.150 2014/06/18 16:42:35 brouard
506: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
507: Author: brouard
508:
1.150 brouard 509: Revision 1.149 2014/06/18 15:51:14 brouard
510: Summary: Some fixes in parameter files errors
511: Author: Nicolas Brouard
512:
1.149 brouard 513: Revision 1.148 2014/06/17 17:38:48 brouard
514: Summary: Nothing new
515: Author: Brouard
516:
517: Just a new packaging for OS/X version 0.98nS
518:
1.148 brouard 519: Revision 1.147 2014/06/16 10:33:11 brouard
520: *** empty log message ***
521:
1.147 brouard 522: Revision 1.146 2014/06/16 10:20:28 brouard
523: Summary: Merge
524: Author: Brouard
525:
526: Merge, before building revised version.
527:
1.146 brouard 528: Revision 1.145 2014/06/10 21:23:15 brouard
529: Summary: Debugging with valgrind
530: Author: Nicolas Brouard
531:
532: Lot of changes in order to output the results with some covariates
533: After the Edimburgh REVES conference 2014, it seems mandatory to
534: improve the code.
535: No more memory valgrind error but a lot has to be done in order to
536: continue the work of splitting the code into subroutines.
537: Also, decodemodel has been improved. Tricode is still not
538: optimal. nbcode should be improved. Documentation has been added in
539: the source code.
540:
1.144 brouard 541: Revision 1.143 2014/01/26 09:45:38 brouard
542: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
543:
544: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
545: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
546:
1.143 brouard 547: Revision 1.142 2014/01/26 03:57:36 brouard
548: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
549:
550: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
551:
1.142 brouard 552: Revision 1.141 2014/01/26 02:42:01 brouard
553: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
554:
1.141 brouard 555: Revision 1.140 2011/09/02 10:37:54 brouard
556: Summary: times.h is ok with mingw32 now.
557:
1.140 brouard 558: Revision 1.139 2010/06/14 07:50:17 brouard
559: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
560: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
561:
1.139 brouard 562: Revision 1.138 2010/04/30 18:19:40 brouard
563: *** empty log message ***
564:
1.138 brouard 565: Revision 1.137 2010/04/29 18:11:38 brouard
566: (Module): Checking covariates for more complex models
567: than V1+V2. A lot of change to be done. Unstable.
568:
1.137 brouard 569: Revision 1.136 2010/04/26 20:30:53 brouard
570: (Module): merging some libgsl code. Fixing computation
571: of likelione (using inter/intrapolation if mle = 0) in order to
572: get same likelihood as if mle=1.
573: Some cleaning of code and comments added.
574:
1.136 brouard 575: Revision 1.135 2009/10/29 15:33:14 brouard
576: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
577:
1.135 brouard 578: Revision 1.134 2009/10/29 13:18:53 brouard
579: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
580:
1.134 brouard 581: Revision 1.133 2009/07/06 10:21:25 brouard
582: just nforces
583:
1.133 brouard 584: Revision 1.132 2009/07/06 08:22:05 brouard
585: Many tings
586:
1.132 brouard 587: Revision 1.131 2009/06/20 16:22:47 brouard
588: Some dimensions resccaled
589:
1.131 brouard 590: Revision 1.130 2009/05/26 06:44:34 brouard
591: (Module): Max Covariate is now set to 20 instead of 8. A
592: lot of cleaning with variables initialized to 0. Trying to make
593: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
594:
1.130 brouard 595: Revision 1.129 2007/08/31 13:49:27 lievre
596: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
597:
1.129 lievre 598: Revision 1.128 2006/06/30 13:02:05 brouard
599: (Module): Clarifications on computing e.j
600:
1.128 brouard 601: Revision 1.127 2006/04/28 18:11:50 brouard
602: (Module): Yes the sum of survivors was wrong since
603: imach-114 because nhstepm was no more computed in the age
604: loop. Now we define nhstepma in the age loop.
605: (Module): In order to speed up (in case of numerous covariates) we
606: compute health expectancies (without variances) in a first step
607: and then all the health expectancies with variances or standard
608: deviation (needs data from the Hessian matrices) which slows the
609: computation.
610: In the future we should be able to stop the program is only health
611: expectancies and graph are needed without standard deviations.
612:
1.127 brouard 613: Revision 1.126 2006/04/28 17:23:28 brouard
614: (Module): Yes the sum of survivors was wrong since
615: imach-114 because nhstepm was no more computed in the age
616: loop. Now we define nhstepma in the age loop.
617: Version 0.98h
618:
1.126 brouard 619: Revision 1.125 2006/04/04 15:20:31 lievre
620: Errors in calculation of health expectancies. Age was not initialized.
621: Forecasting file added.
622:
623: Revision 1.124 2006/03/22 17:13:53 lievre
624: Parameters are printed with %lf instead of %f (more numbers after the comma).
625: The log-likelihood is printed in the log file
626:
627: Revision 1.123 2006/03/20 10:52:43 brouard
628: * imach.c (Module): <title> changed, corresponds to .htm file
629: name. <head> headers where missing.
630:
631: * imach.c (Module): Weights can have a decimal point as for
632: English (a comma might work with a correct LC_NUMERIC environment,
633: otherwise the weight is truncated).
634: Modification of warning when the covariates values are not 0 or
635: 1.
636: Version 0.98g
637:
638: Revision 1.122 2006/03/20 09:45:41 brouard
639: (Module): Weights can have a decimal point as for
640: English (a comma might work with a correct LC_NUMERIC environment,
641: otherwise the weight is truncated).
642: Modification of warning when the covariates values are not 0 or
643: 1.
644: Version 0.98g
645:
646: Revision 1.121 2006/03/16 17:45:01 lievre
647: * imach.c (Module): Comments concerning covariates added
648:
649: * imach.c (Module): refinements in the computation of lli if
650: status=-2 in order to have more reliable computation if stepm is
651: not 1 month. Version 0.98f
652:
653: Revision 1.120 2006/03/16 15:10:38 lievre
654: (Module): refinements in the computation of lli if
655: status=-2 in order to have more reliable computation if stepm is
656: not 1 month. Version 0.98f
657:
658: Revision 1.119 2006/03/15 17:42:26 brouard
659: (Module): Bug if status = -2, the loglikelihood was
660: computed as likelihood omitting the logarithm. Version O.98e
661:
662: Revision 1.118 2006/03/14 18:20:07 brouard
663: (Module): varevsij Comments added explaining the second
664: table of variances if popbased=1 .
665: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
666: (Module): Function pstamp added
667: (Module): Version 0.98d
668:
669: Revision 1.117 2006/03/14 17:16:22 brouard
670: (Module): varevsij Comments added explaining the second
671: table of variances if popbased=1 .
672: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
673: (Module): Function pstamp added
674: (Module): Version 0.98d
675:
676: Revision 1.116 2006/03/06 10:29:27 brouard
677: (Module): Variance-covariance wrong links and
678: varian-covariance of ej. is needed (Saito).
679:
680: Revision 1.115 2006/02/27 12:17:45 brouard
681: (Module): One freematrix added in mlikeli! 0.98c
682:
683: Revision 1.114 2006/02/26 12:57:58 brouard
684: (Module): Some improvements in processing parameter
685: filename with strsep.
686:
687: Revision 1.113 2006/02/24 14:20:24 brouard
688: (Module): Memory leaks checks with valgrind and:
689: datafile was not closed, some imatrix were not freed and on matrix
690: allocation too.
691:
692: Revision 1.112 2006/01/30 09:55:26 brouard
693: (Module): Back to gnuplot.exe instead of wgnuplot.exe
694:
695: Revision 1.111 2006/01/25 20:38:18 brouard
696: (Module): Lots of cleaning and bugs added (Gompertz)
697: (Module): Comments can be added in data file. Missing date values
698: can be a simple dot '.'.
699:
700: Revision 1.110 2006/01/25 00:51:50 brouard
701: (Module): Lots of cleaning and bugs added (Gompertz)
702:
703: Revision 1.109 2006/01/24 19:37:15 brouard
704: (Module): Comments (lines starting with a #) are allowed in data.
705:
706: Revision 1.108 2006/01/19 18:05:42 lievre
707: Gnuplot problem appeared...
708: To be fixed
709:
710: Revision 1.107 2006/01/19 16:20:37 brouard
711: Test existence of gnuplot in imach path
712:
713: Revision 1.106 2006/01/19 13:24:36 brouard
714: Some cleaning and links added in html output
715:
716: Revision 1.105 2006/01/05 20:23:19 lievre
717: *** empty log message ***
718:
719: Revision 1.104 2005/09/30 16:11:43 lievre
720: (Module): sump fixed, loop imx fixed, and simplifications.
721: (Module): If the status is missing at the last wave but we know
722: that the person is alive, then we can code his/her status as -2
723: (instead of missing=-1 in earlier versions) and his/her
724: contributions to the likelihood is 1 - Prob of dying from last
725: health status (= 1-p13= p11+p12 in the easiest case of somebody in
726: the healthy state at last known wave). Version is 0.98
727:
728: Revision 1.103 2005/09/30 15:54:49 lievre
729: (Module): sump fixed, loop imx fixed, and simplifications.
730:
731: Revision 1.102 2004/09/15 17:31:30 brouard
732: Add the possibility to read data file including tab characters.
733:
734: Revision 1.101 2004/09/15 10:38:38 brouard
735: Fix on curr_time
736:
737: Revision 1.100 2004/07/12 18:29:06 brouard
738: Add version for Mac OS X. Just define UNIX in Makefile
739:
740: Revision 1.99 2004/06/05 08:57:40 brouard
741: *** empty log message ***
742:
743: Revision 1.98 2004/05/16 15:05:56 brouard
744: New version 0.97 . First attempt to estimate force of mortality
745: directly from the data i.e. without the need of knowing the health
746: state at each age, but using a Gompertz model: log u =a + b*age .
747: This is the basic analysis of mortality and should be done before any
748: other analysis, in order to test if the mortality estimated from the
749: cross-longitudinal survey is different from the mortality estimated
750: from other sources like vital statistic data.
751:
752: The same imach parameter file can be used but the option for mle should be -3.
753:
1.133 brouard 754: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 755: former routines in order to include the new code within the former code.
756:
757: The output is very simple: only an estimate of the intercept and of
758: the slope with 95% confident intervals.
759:
760: Current limitations:
761: A) Even if you enter covariates, i.e. with the
762: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
763: B) There is no computation of Life Expectancy nor Life Table.
764:
765: Revision 1.97 2004/02/20 13:25:42 lievre
766: Version 0.96d. Population forecasting command line is (temporarily)
767: suppressed.
768:
769: Revision 1.96 2003/07/15 15:38:55 brouard
770: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
771: rewritten within the same printf. Workaround: many printfs.
772:
773: Revision 1.95 2003/07/08 07:54:34 brouard
774: * imach.c (Repository):
775: (Repository): Using imachwizard code to output a more meaningful covariance
776: matrix (cov(a12,c31) instead of numbers.
777:
778: Revision 1.94 2003/06/27 13:00:02 brouard
779: Just cleaning
780:
781: Revision 1.93 2003/06/25 16:33:55 brouard
782: (Module): On windows (cygwin) function asctime_r doesn't
783: exist so I changed back to asctime which exists.
784: (Module): Version 0.96b
785:
786: Revision 1.92 2003/06/25 16:30:45 brouard
787: (Module): On windows (cygwin) function asctime_r doesn't
788: exist so I changed back to asctime which exists.
789:
790: Revision 1.91 2003/06/25 15:30:29 brouard
791: * imach.c (Repository): Duplicated warning errors corrected.
792: (Repository): Elapsed time after each iteration is now output. It
793: helps to forecast when convergence will be reached. Elapsed time
794: is stamped in powell. We created a new html file for the graphs
795: concerning matrix of covariance. It has extension -cov.htm.
796:
797: Revision 1.90 2003/06/24 12:34:15 brouard
798: (Module): Some bugs corrected for windows. Also, when
799: mle=-1 a template is output in file "or"mypar.txt with the design
800: of the covariance matrix to be input.
801:
802: Revision 1.89 2003/06/24 12:30:52 brouard
803: (Module): Some bugs corrected for windows. Also, when
804: mle=-1 a template is output in file "or"mypar.txt with the design
805: of the covariance matrix to be input.
806:
807: Revision 1.88 2003/06/23 17:54:56 brouard
808: * 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.
809:
810: Revision 1.87 2003/06/18 12:26:01 brouard
811: Version 0.96
812:
813: Revision 1.86 2003/06/17 20:04:08 brouard
814: (Module): Change position of html and gnuplot routines and added
815: routine fileappend.
816:
817: Revision 1.85 2003/06/17 13:12:43 brouard
818: * imach.c (Repository): Check when date of death was earlier that
819: current date of interview. It may happen when the death was just
820: prior to the death. In this case, dh was negative and likelihood
821: was wrong (infinity). We still send an "Error" but patch by
822: assuming that the date of death was just one stepm after the
823: interview.
824: (Repository): Because some people have very long ID (first column)
825: we changed int to long in num[] and we added a new lvector for
826: memory allocation. But we also truncated to 8 characters (left
827: truncation)
828: (Repository): No more line truncation errors.
829:
830: Revision 1.84 2003/06/13 21:44:43 brouard
831: * imach.c (Repository): Replace "freqsummary" at a correct
832: place. It differs from routine "prevalence" which may be called
833: many times. Probs is memory consuming and must be used with
834: parcimony.
835: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
836:
837: Revision 1.83 2003/06/10 13:39:11 lievre
838: *** empty log message ***
839:
840: Revision 1.82 2003/06/05 15:57:20 brouard
841: Add log in imach.c and fullversion number is now printed.
842:
843: */
844: /*
845: Interpolated Markov Chain
846:
847: Short summary of the programme:
848:
1.227 brouard 849: This program computes Healthy Life Expectancies or State-specific
850: (if states aren't health statuses) Expectancies from
851: cross-longitudinal data. Cross-longitudinal data consist in:
852:
853: -1- a first survey ("cross") where individuals from different ages
854: are interviewed on their health status or degree of disability (in
855: the case of a health survey which is our main interest)
856:
857: -2- at least a second wave of interviews ("longitudinal") which
858: measure each change (if any) in individual health status. Health
859: expectancies are computed from the time spent in each health state
860: according to a model. More health states you consider, more time is
861: necessary to reach the Maximum Likelihood of the parameters involved
862: in the model. The simplest model is the multinomial logistic model
863: where pij is the probability to be observed in state j at the second
864: wave conditional to be observed in state i at the first
865: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
866: etc , where 'age' is age and 'sex' is a covariate. If you want to
867: have a more complex model than "constant and age", you should modify
868: the program where the markup *Covariates have to be included here
869: again* invites you to do it. More covariates you add, slower the
1.126 brouard 870: convergence.
871:
872: The advantage of this computer programme, compared to a simple
873: multinomial logistic model, is clear when the delay between waves is not
874: identical for each individual. Also, if a individual missed an
875: intermediate interview, the information is lost, but taken into
876: account using an interpolation or extrapolation.
877:
878: hPijx is the probability to be observed in state i at age x+h
879: conditional to the observed state i at age x. The delay 'h' can be
880: split into an exact number (nh*stepm) of unobserved intermediate
881: states. This elementary transition (by month, quarter,
882: semester or year) is modelled as a multinomial logistic. The hPx
883: matrix is simply the matrix product of nh*stepm elementary matrices
884: and the contribution of each individual to the likelihood is simply
885: hPijx.
886:
887: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 888: of the life expectancies. It also computes the period (stable) prevalence.
889:
890: Back prevalence and projections:
1.227 brouard 891:
892: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
893: double agemaxpar, double ftolpl, int *ncvyearp, double
894: dateprev1,double dateprev2, int firstpass, int lastpass, int
895: mobilavproj)
896:
897: Computes the back prevalence limit for any combination of
898: covariate values k at any age between ageminpar and agemaxpar and
899: returns it in **bprlim. In the loops,
900:
901: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
902: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
903:
904: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 905: Computes for any combination of covariates k and any age between bage and fage
906: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
907: oldm=oldms;savm=savms;
1.227 brouard 908:
1.267 brouard 909: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 910: Computes the transition matrix starting at age 'age' over
911: 'nhstepm*hstepm*stepm' months (i.e. until
912: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 913: nhstepm*hstepm matrices.
914:
915: Returns p3mat[i][j][h] after calling
916: p3mat[i][j][h]=matprod2(newm,
917: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
918: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
919: oldm);
1.226 brouard 920:
921: Important routines
922:
923: - func (or funcone), computes logit (pij) distinguishing
924: o fixed variables (single or product dummies or quantitative);
925: o varying variables by:
926: (1) wave (single, product dummies, quantitative),
927: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
928: % fixed dummy (treated) or quantitative (not done because time-consuming);
929: % varying dummy (not done) or quantitative (not done);
930: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
931: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
932: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
933: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
934: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 935:
1.226 brouard 936:
937:
1.133 brouard 938: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
939: Institut national d'études démographiques, Paris.
1.126 brouard 940: This software have been partly granted by Euro-REVES, a concerted action
941: from the European Union.
942: It is copyrighted identically to a GNU software product, ie programme and
943: software can be distributed freely for non commercial use. Latest version
944: can be accessed at http://euroreves.ined.fr/imach .
945:
946: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
947: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
948:
949: **********************************************************************/
950: /*
951: main
952: read parameterfile
953: read datafile
954: concatwav
955: freqsummary
956: if (mle >= 1)
957: mlikeli
958: print results files
959: if mle==1
960: computes hessian
961: read end of parameter file: agemin, agemax, bage, fage, estepm
962: begin-prev-date,...
963: open gnuplot file
964: open html file
1.145 brouard 965: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
966: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
967: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
968: freexexit2 possible for memory heap.
969:
970: h Pij x | pij_nom ficrestpij
971: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
972: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
973: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
974:
975: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
976: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
977: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
978: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
979: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
980:
1.126 brouard 981: forecasting if prevfcast==1 prevforecast call prevalence()
982: health expectancies
983: Variance-covariance of DFLE
984: prevalence()
985: movingaverage()
986: varevsij()
987: if popbased==1 varevsij(,popbased)
988: total life expectancies
989: Variance of period (stable) prevalence
990: end
991: */
992:
1.187 brouard 993: /* #define DEBUG */
994: /* #define DEBUGBRENT */
1.203 brouard 995: /* #define DEBUGLINMIN */
996: /* #define DEBUGHESS */
997: #define DEBUGHESSIJ
1.224 brouard 998: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 999: #define POWELL /* Instead of NLOPT */
1.224 brouard 1000: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1001: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1002: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 1003:
1004: #include <math.h>
1005: #include <stdio.h>
1006: #include <stdlib.h>
1007: #include <string.h>
1.226 brouard 1008: #include <ctype.h>
1.159 brouard 1009:
1010: #ifdef _WIN32
1011: #include <io.h>
1.172 brouard 1012: #include <windows.h>
1013: #include <tchar.h>
1.159 brouard 1014: #else
1.126 brouard 1015: #include <unistd.h>
1.159 brouard 1016: #endif
1.126 brouard 1017:
1018: #include <limits.h>
1019: #include <sys/types.h>
1.171 brouard 1020:
1021: #if defined(__GNUC__)
1022: #include <sys/utsname.h> /* Doesn't work on Windows */
1023: #endif
1024:
1.126 brouard 1025: #include <sys/stat.h>
1026: #include <errno.h>
1.159 brouard 1027: /* extern int errno; */
1.126 brouard 1028:
1.157 brouard 1029: /* #ifdef LINUX */
1030: /* #include <time.h> */
1031: /* #include "timeval.h" */
1032: /* #else */
1033: /* #include <sys/time.h> */
1034: /* #endif */
1035:
1.126 brouard 1036: #include <time.h>
1037:
1.136 brouard 1038: #ifdef GSL
1039: #include <gsl/gsl_errno.h>
1040: #include <gsl/gsl_multimin.h>
1041: #endif
1042:
1.167 brouard 1043:
1.162 brouard 1044: #ifdef NLOPT
1045: #include <nlopt.h>
1046: typedef struct {
1047: double (* function)(double [] );
1048: } myfunc_data ;
1049: #endif
1050:
1.126 brouard 1051: /* #include <libintl.h> */
1052: /* #define _(String) gettext (String) */
1053:
1.251 brouard 1054: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1055:
1056: #define GNUPLOTPROGRAM "gnuplot"
1057: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1058: #define FILENAMELENGTH 132
1059:
1060: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1061: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1062:
1.144 brouard 1063: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1064: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1065:
1066: #define NINTERVMAX 8
1.144 brouard 1067: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1068: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.291 brouard 1069: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1070: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1071: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1072: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1073: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1074: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1075: /* #define AGESUP 130 */
1.288 brouard 1076: /* #define AGESUP 150 */
1077: #define AGESUP 200
1.268 brouard 1078: #define AGEINF 0
1.218 brouard 1079: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1080: #define AGEBASE 40
1.194 brouard 1081: #define AGEOVERFLOW 1.e20
1.164 brouard 1082: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1083: #ifdef _WIN32
1084: #define DIRSEPARATOR '\\'
1085: #define CHARSEPARATOR "\\"
1086: #define ODIRSEPARATOR '/'
1087: #else
1.126 brouard 1088: #define DIRSEPARATOR '/'
1089: #define CHARSEPARATOR "/"
1090: #define ODIRSEPARATOR '\\'
1091: #endif
1092:
1.295 ! brouard 1093: /* $Id: imach.c,v 1.294 2019/05/16 14:54:33 brouard Exp $ */
1.126 brouard 1094: /* $State: Exp $ */
1.196 brouard 1095: #include "version.h"
1096: char version[]=__IMACH_VERSION__;
1.283 brouard 1097: 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";
1.295 ! brouard 1098: char fullversion[]="$Revision: 1.294 $ $Date: 2019/05/16 14:54:33 $";
1.126 brouard 1099: char strstart[80];
1100: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1101: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1102: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1103: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1104: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1105: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1106: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1107: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1108: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1109: int cptcovprodnoage=0; /**< Number of covariate products without age */
1110: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1111: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1112: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1113: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1114: int nsd=0; /**< Total number of single dummy variables (output) */
1115: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1116: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1117: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1118: int ntveff=0; /**< ntveff number of effective time varying variables */
1119: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1120: int cptcov=0; /* Working variable */
1.290 brouard 1121: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1122: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1123: int npar=NPARMAX;
1124: int nlstate=2; /* Number of live states */
1125: int ndeath=1; /* Number of dead states */
1.130 brouard 1126: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1127: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1128: int popbased=0;
1129:
1130: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1131: int maxwav=0; /* Maxim number of waves */
1132: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1133: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1134: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1135: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1136: int mle=1, weightopt=0;
1.126 brouard 1137: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1138: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1139: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1140: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1141: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1142: int selected(int kvar); /* Is covariate kvar selected for printing results */
1143:
1.130 brouard 1144: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1145: double **matprod2(); /* test */
1.126 brouard 1146: double **oldm, **newm, **savm; /* Working pointers to matrices */
1147: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1148: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1149:
1.136 brouard 1150: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1151: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1152: FILE *ficlog, *ficrespow;
1.130 brouard 1153: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1154: double fretone; /* Only one call to likelihood */
1.130 brouard 1155: long ipmx=0; /* Number of contributions */
1.126 brouard 1156: double sw; /* Sum of weights */
1157: char filerespow[FILENAMELENGTH];
1158: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1159: FILE *ficresilk;
1160: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1161: FILE *ficresprobmorprev;
1162: FILE *fichtm, *fichtmcov; /* Html File */
1163: FILE *ficreseij;
1164: char filerese[FILENAMELENGTH];
1165: FILE *ficresstdeij;
1166: char fileresstde[FILENAMELENGTH];
1167: FILE *ficrescveij;
1168: char filerescve[FILENAMELENGTH];
1169: FILE *ficresvij;
1170: char fileresv[FILENAMELENGTH];
1.269 brouard 1171:
1.126 brouard 1172: char title[MAXLINE];
1.234 brouard 1173: char model[MAXLINE]; /**< The model line */
1.217 brouard 1174: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1175: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1176: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1177: char command[FILENAMELENGTH];
1178: int outcmd=0;
1179:
1.217 brouard 1180: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1181: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1182: char filelog[FILENAMELENGTH]; /* Log file */
1183: char filerest[FILENAMELENGTH];
1184: char fileregp[FILENAMELENGTH];
1185: char popfile[FILENAMELENGTH];
1186:
1187: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1188:
1.157 brouard 1189: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1190: /* struct timezone tzp; */
1191: /* extern int gettimeofday(); */
1192: struct tm tml, *gmtime(), *localtime();
1193:
1194: extern time_t time();
1195:
1196: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1197: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1198: struct tm tm;
1199:
1.126 brouard 1200: char strcurr[80], strfor[80];
1201:
1202: char *endptr;
1203: long lval;
1204: double dval;
1205:
1206: #define NR_END 1
1207: #define FREE_ARG char*
1208: #define FTOL 1.0e-10
1209:
1210: #define NRANSI
1.240 brouard 1211: #define ITMAX 200
1212: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1213:
1214: #define TOL 2.0e-4
1215:
1216: #define CGOLD 0.3819660
1217: #define ZEPS 1.0e-10
1218: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1219:
1220: #define GOLD 1.618034
1221: #define GLIMIT 100.0
1222: #define TINY 1.0e-20
1223:
1224: static double maxarg1,maxarg2;
1225: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1226: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1227:
1228: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1229: #define rint(a) floor(a+0.5)
1.166 brouard 1230: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1231: #define mytinydouble 1.0e-16
1.166 brouard 1232: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1233: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1234: /* static double dsqrarg; */
1235: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1236: static double sqrarg;
1237: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1238: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1239: int agegomp= AGEGOMP;
1240:
1241: int imx;
1242: int stepm=1;
1243: /* Stepm, step in month: minimum step interpolation*/
1244:
1245: int estepm;
1246: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1247:
1248: int m,nb;
1249: long *num;
1.197 brouard 1250: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1251: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1252: covariate for which somebody answered excluding
1253: undefined. Usually 2: 0 and 1. */
1254: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1255: covariate for which somebody answered including
1256: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1257: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1258: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1259: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1260: double *ageexmed,*agecens;
1261: double dateintmean=0;
1262:
1263: double *weight;
1264: int **s; /* Status */
1.141 brouard 1265: double *agedc;
1.145 brouard 1266: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1267: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1268: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1269: double **coqvar; /* Fixed quantitative covariate nqv */
1270: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1271: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1272: double idx;
1273: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1274: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1275: /*k 1 2 3 4 5 6 7 8 9 */
1276: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1277: /* Tndvar[k] 1 2 3 4 5 */
1278: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1279: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1280: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1281: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1282: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1283: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1284: /* Tprod[i]=k 4 7 */
1285: /* Tage[i]=k 5 8 */
1286: /* */
1287: /* Type */
1288: /* V 1 2 3 4 5 */
1289: /* F F V V V */
1290: /* D Q D D Q */
1291: /* */
1292: int *TvarsD;
1293: int *TvarsDind;
1294: int *TvarsQ;
1295: int *TvarsQind;
1296:
1.235 brouard 1297: #define MAXRESULTLINES 10
1298: int nresult=0;
1.258 brouard 1299: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1300: int TKresult[MAXRESULTLINES];
1.237 brouard 1301: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1302: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1303: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1304: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1305: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1306: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1307:
1.234 brouard 1308: /* 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 1309: 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 */
1310: 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 */
1311: 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 */
1312: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1313: 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 */
1314: 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 1315: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1316: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1317: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1318: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1319: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1320: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1321: 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 */
1322: 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 */
1323:
1.230 brouard 1324: int *Tvarsel; /**< Selected covariates for output */
1325: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1326: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1327: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1328: 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 1329: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1330: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1331: int *Tage;
1.227 brouard 1332: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1333: 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 1334: 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*/
1335: 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 1336: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1337: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1338: int **Tvard;
1339: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1340: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1341: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1342: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1343: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1344: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1345: double *lsurv, *lpop, *tpop;
1346:
1.231 brouard 1347: #define FD 1; /* Fixed dummy covariate */
1348: #define FQ 2; /* Fixed quantitative covariate */
1349: #define FP 3; /* Fixed product covariate */
1350: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1351: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1352: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1353: #define VD 10; /* Varying dummy covariate */
1354: #define VQ 11; /* Varying quantitative covariate */
1355: #define VP 12; /* Varying product covariate */
1356: #define VPDD 13; /* Varying product dummy*dummy covariate */
1357: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1358: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1359: #define APFD 16; /* Age product * fixed dummy covariate */
1360: #define APFQ 17; /* Age product * fixed quantitative covariate */
1361: #define APVD 18; /* Age product * varying dummy covariate */
1362: #define APVQ 19; /* Age product * varying quantitative covariate */
1363:
1364: #define FTYPE 1; /* Fixed covariate */
1365: #define VTYPE 2; /* Varying covariate (loop in wave) */
1366: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1367:
1368: struct kmodel{
1369: int maintype; /* main type */
1370: int subtype; /* subtype */
1371: };
1372: struct kmodel modell[NCOVMAX];
1373:
1.143 brouard 1374: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1375: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1376:
1377: /**************** split *************************/
1378: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1379: {
1380: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1381: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1382: */
1383: char *ss; /* pointer */
1.186 brouard 1384: int l1=0, l2=0; /* length counters */
1.126 brouard 1385:
1386: l1 = strlen(path ); /* length of path */
1387: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1388: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1389: if ( ss == NULL ) { /* no directory, so determine current directory */
1390: strcpy( name, path ); /* we got the fullname name because no directory */
1391: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1392: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1393: /* get current working directory */
1394: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1395: #ifdef WIN32
1396: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1397: #else
1398: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1399: #endif
1.126 brouard 1400: return( GLOCK_ERROR_GETCWD );
1401: }
1402: /* got dirc from getcwd*/
1403: printf(" DIRC = %s \n",dirc);
1.205 brouard 1404: } else { /* strip directory from path */
1.126 brouard 1405: ss++; /* after this, the filename */
1406: l2 = strlen( ss ); /* length of filename */
1407: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1408: strcpy( name, ss ); /* save file name */
1409: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1410: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1411: printf(" DIRC2 = %s \n",dirc);
1412: }
1413: /* We add a separator at the end of dirc if not exists */
1414: l1 = strlen( dirc ); /* length of directory */
1415: if( dirc[l1-1] != DIRSEPARATOR ){
1416: dirc[l1] = DIRSEPARATOR;
1417: dirc[l1+1] = 0;
1418: printf(" DIRC3 = %s \n",dirc);
1419: }
1420: ss = strrchr( name, '.' ); /* find last / */
1421: if (ss >0){
1422: ss++;
1423: strcpy(ext,ss); /* save extension */
1424: l1= strlen( name);
1425: l2= strlen(ss)+1;
1426: strncpy( finame, name, l1-l2);
1427: finame[l1-l2]= 0;
1428: }
1429:
1430: return( 0 ); /* we're done */
1431: }
1432:
1433:
1434: /******************************************/
1435:
1436: void replace_back_to_slash(char *s, char*t)
1437: {
1438: int i;
1439: int lg=0;
1440: i=0;
1441: lg=strlen(t);
1442: for(i=0; i<= lg; i++) {
1443: (s[i] = t[i]);
1444: if (t[i]== '\\') s[i]='/';
1445: }
1446: }
1447:
1.132 brouard 1448: char *trimbb(char *out, char *in)
1.137 brouard 1449: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1450: char *s;
1451: s=out;
1452: while (*in != '\0'){
1.137 brouard 1453: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1454: in++;
1455: }
1456: *out++ = *in++;
1457: }
1458: *out='\0';
1459: return s;
1460: }
1461:
1.187 brouard 1462: /* char *substrchaine(char *out, char *in, char *chain) */
1463: /* { */
1464: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1465: /* char *s, *t; */
1466: /* t=in;s=out; */
1467: /* while ((*in != *chain) && (*in != '\0')){ */
1468: /* *out++ = *in++; */
1469: /* } */
1470:
1471: /* /\* *in matches *chain *\/ */
1472: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1473: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1474: /* } */
1475: /* in--; chain--; */
1476: /* while ( (*in != '\0')){ */
1477: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1478: /* *out++ = *in++; */
1479: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1480: /* } */
1481: /* *out='\0'; */
1482: /* out=s; */
1483: /* return out; */
1484: /* } */
1485: char *substrchaine(char *out, char *in, char *chain)
1486: {
1487: /* Substract chain 'chain' from 'in', return and output 'out' */
1488: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1489:
1490: char *strloc;
1491:
1492: strcpy (out, in);
1493: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1494: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1495: if(strloc != NULL){
1496: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1497: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1498: /* strcpy (strloc, strloc +strlen(chain));*/
1499: }
1500: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1501: return out;
1502: }
1503:
1504:
1.145 brouard 1505: char *cutl(char *blocc, char *alocc, char *in, char occ)
1506: {
1.187 brouard 1507: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1508: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1509: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1510: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1511: */
1.160 brouard 1512: char *s, *t;
1.145 brouard 1513: t=in;s=in;
1514: while ((*in != occ) && (*in != '\0')){
1515: *alocc++ = *in++;
1516: }
1517: if( *in == occ){
1518: *(alocc)='\0';
1519: s=++in;
1520: }
1521:
1522: if (s == t) {/* occ not found */
1523: *(alocc-(in-s))='\0';
1524: in=s;
1525: }
1526: while ( *in != '\0'){
1527: *blocc++ = *in++;
1528: }
1529:
1530: *blocc='\0';
1531: return t;
1532: }
1.137 brouard 1533: char *cutv(char *blocc, char *alocc, char *in, char occ)
1534: {
1.187 brouard 1535: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1536: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1537: gives blocc="abcdef2ghi" and alocc="j".
1538: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1539: */
1540: char *s, *t;
1541: t=in;s=in;
1542: while (*in != '\0'){
1543: while( *in == occ){
1544: *blocc++ = *in++;
1545: s=in;
1546: }
1547: *blocc++ = *in++;
1548: }
1549: if (s == t) /* occ not found */
1550: *(blocc-(in-s))='\0';
1551: else
1552: *(blocc-(in-s)-1)='\0';
1553: in=s;
1554: while ( *in != '\0'){
1555: *alocc++ = *in++;
1556: }
1557:
1558: *alocc='\0';
1559: return s;
1560: }
1561:
1.126 brouard 1562: int nbocc(char *s, char occ)
1563: {
1564: int i,j=0;
1565: int lg=20;
1566: i=0;
1567: lg=strlen(s);
1568: for(i=0; i<= lg; i++) {
1.234 brouard 1569: if (s[i] == occ ) j++;
1.126 brouard 1570: }
1571: return j;
1572: }
1573:
1.137 brouard 1574: /* void cutv(char *u,char *v, char*t, char occ) */
1575: /* { */
1576: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1577: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1578: /* gives u="abcdef2ghi" and v="j" *\/ */
1579: /* int i,lg,j,p=0; */
1580: /* i=0; */
1581: /* lg=strlen(t); */
1582: /* for(j=0; j<=lg-1; j++) { */
1583: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1584: /* } */
1.126 brouard 1585:
1.137 brouard 1586: /* for(j=0; j<p; j++) { */
1587: /* (u[j] = t[j]); */
1588: /* } */
1589: /* u[p]='\0'; */
1.126 brouard 1590:
1.137 brouard 1591: /* for(j=0; j<= lg; j++) { */
1592: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1593: /* } */
1594: /* } */
1.126 brouard 1595:
1.160 brouard 1596: #ifdef _WIN32
1597: char * strsep(char **pp, const char *delim)
1598: {
1599: char *p, *q;
1600:
1601: if ((p = *pp) == NULL)
1602: return 0;
1603: if ((q = strpbrk (p, delim)) != NULL)
1604: {
1605: *pp = q + 1;
1606: *q = '\0';
1607: }
1608: else
1609: *pp = 0;
1610: return p;
1611: }
1612: #endif
1613:
1.126 brouard 1614: /********************** nrerror ********************/
1615:
1616: void nrerror(char error_text[])
1617: {
1618: fprintf(stderr,"ERREUR ...\n");
1619: fprintf(stderr,"%s\n",error_text);
1620: exit(EXIT_FAILURE);
1621: }
1622: /*********************** vector *******************/
1623: double *vector(int nl, int nh)
1624: {
1625: double *v;
1626: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1627: if (!v) nrerror("allocation failure in vector");
1628: return v-nl+NR_END;
1629: }
1630:
1631: /************************ free vector ******************/
1632: void free_vector(double*v, int nl, int nh)
1633: {
1634: free((FREE_ARG)(v+nl-NR_END));
1635: }
1636:
1637: /************************ivector *******************************/
1638: int *ivector(long nl,long nh)
1639: {
1640: int *v;
1641: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1642: if (!v) nrerror("allocation failure in ivector");
1643: return v-nl+NR_END;
1644: }
1645:
1646: /******************free ivector **************************/
1647: void free_ivector(int *v, long nl, long nh)
1648: {
1649: free((FREE_ARG)(v+nl-NR_END));
1650: }
1651:
1652: /************************lvector *******************************/
1653: long *lvector(long nl,long nh)
1654: {
1655: long *v;
1656: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1657: if (!v) nrerror("allocation failure in ivector");
1658: return v-nl+NR_END;
1659: }
1660:
1661: /******************free lvector **************************/
1662: void free_lvector(long *v, long nl, long nh)
1663: {
1664: free((FREE_ARG)(v+nl-NR_END));
1665: }
1666:
1667: /******************* imatrix *******************************/
1668: int **imatrix(long nrl, long nrh, long ncl, long nch)
1669: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1670: {
1671: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1672: int **m;
1673:
1674: /* allocate pointers to rows */
1675: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1676: if (!m) nrerror("allocation failure 1 in matrix()");
1677: m += NR_END;
1678: m -= nrl;
1679:
1680:
1681: /* allocate rows and set pointers to them */
1682: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1683: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1684: m[nrl] += NR_END;
1685: m[nrl] -= ncl;
1686:
1687: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1688:
1689: /* return pointer to array of pointers to rows */
1690: return m;
1691: }
1692:
1693: /****************** free_imatrix *************************/
1694: void free_imatrix(m,nrl,nrh,ncl,nch)
1695: int **m;
1696: long nch,ncl,nrh,nrl;
1697: /* free an int matrix allocated by imatrix() */
1698: {
1699: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1700: free((FREE_ARG) (m+nrl-NR_END));
1701: }
1702:
1703: /******************* matrix *******************************/
1704: double **matrix(long nrl, long nrh, long ncl, long nch)
1705: {
1706: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1707: double **m;
1708:
1709: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1710: if (!m) nrerror("allocation failure 1 in matrix()");
1711: m += NR_END;
1712: m -= nrl;
1713:
1714: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1715: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1716: m[nrl] += NR_END;
1717: m[nrl] -= ncl;
1718:
1719: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1720: return m;
1.145 brouard 1721: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1722: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1723: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1724: */
1725: }
1726:
1727: /*************************free matrix ************************/
1728: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1729: {
1730: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1731: free((FREE_ARG)(m+nrl-NR_END));
1732: }
1733:
1734: /******************* ma3x *******************************/
1735: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1736: {
1737: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1738: double ***m;
1739:
1740: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1741: if (!m) nrerror("allocation failure 1 in matrix()");
1742: m += NR_END;
1743: m -= nrl;
1744:
1745: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1746: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1747: m[nrl] += NR_END;
1748: m[nrl] -= ncl;
1749:
1750: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1751:
1752: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1753: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1754: m[nrl][ncl] += NR_END;
1755: m[nrl][ncl] -= nll;
1756: for (j=ncl+1; j<=nch; j++)
1757: m[nrl][j]=m[nrl][j-1]+nlay;
1758:
1759: for (i=nrl+1; i<=nrh; i++) {
1760: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1761: for (j=ncl+1; j<=nch; j++)
1762: m[i][j]=m[i][j-1]+nlay;
1763: }
1764: return m;
1765: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1766: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1767: */
1768: }
1769:
1770: /*************************free ma3x ************************/
1771: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1772: {
1773: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1774: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1775: free((FREE_ARG)(m+nrl-NR_END));
1776: }
1777:
1778: /*************** function subdirf ***********/
1779: char *subdirf(char fileres[])
1780: {
1781: /* Caution optionfilefiname is hidden */
1782: strcpy(tmpout,optionfilefiname);
1783: strcat(tmpout,"/"); /* Add to the right */
1784: strcat(tmpout,fileres);
1785: return tmpout;
1786: }
1787:
1788: /*************** function subdirf2 ***********/
1789: char *subdirf2(char fileres[], char *preop)
1790: {
1791:
1792: /* Caution optionfilefiname is hidden */
1793: strcpy(tmpout,optionfilefiname);
1794: strcat(tmpout,"/");
1795: strcat(tmpout,preop);
1796: strcat(tmpout,fileres);
1797: return tmpout;
1798: }
1799:
1800: /*************** function subdirf3 ***********/
1801: char *subdirf3(char fileres[], char *preop, char *preop2)
1802: {
1803:
1804: /* Caution optionfilefiname is hidden */
1805: strcpy(tmpout,optionfilefiname);
1806: strcat(tmpout,"/");
1807: strcat(tmpout,preop);
1808: strcat(tmpout,preop2);
1809: strcat(tmpout,fileres);
1810: return tmpout;
1811: }
1.213 brouard 1812:
1813: /*************** function subdirfext ***********/
1814: char *subdirfext(char fileres[], char *preop, char *postop)
1815: {
1816:
1817: strcpy(tmpout,preop);
1818: strcat(tmpout,fileres);
1819: strcat(tmpout,postop);
1820: return tmpout;
1821: }
1.126 brouard 1822:
1.213 brouard 1823: /*************** function subdirfext3 ***********/
1824: char *subdirfext3(char fileres[], char *preop, char *postop)
1825: {
1826:
1827: /* Caution optionfilefiname is hidden */
1828: strcpy(tmpout,optionfilefiname);
1829: strcat(tmpout,"/");
1830: strcat(tmpout,preop);
1831: strcat(tmpout,fileres);
1832: strcat(tmpout,postop);
1833: return tmpout;
1834: }
1835:
1.162 brouard 1836: char *asc_diff_time(long time_sec, char ascdiff[])
1837: {
1838: long sec_left, days, hours, minutes;
1839: days = (time_sec) / (60*60*24);
1840: sec_left = (time_sec) % (60*60*24);
1841: hours = (sec_left) / (60*60) ;
1842: sec_left = (sec_left) %(60*60);
1843: minutes = (sec_left) /60;
1844: sec_left = (sec_left) % (60);
1845: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1846: return ascdiff;
1847: }
1848:
1.126 brouard 1849: /***************** f1dim *************************/
1850: extern int ncom;
1851: extern double *pcom,*xicom;
1852: extern double (*nrfunc)(double []);
1853:
1854: double f1dim(double x)
1855: {
1856: int j;
1857: double f;
1858: double *xt;
1859:
1860: xt=vector(1,ncom);
1861: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1862: f=(*nrfunc)(xt);
1863: free_vector(xt,1,ncom);
1864: return f;
1865: }
1866:
1867: /*****************brent *************************/
1868: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1869: {
1870: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1871: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1872: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1873: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1874: * returned function value.
1875: */
1.126 brouard 1876: int iter;
1877: double a,b,d,etemp;
1.159 brouard 1878: double fu=0,fv,fw,fx;
1.164 brouard 1879: double ftemp=0.;
1.126 brouard 1880: double p,q,r,tol1,tol2,u,v,w,x,xm;
1881: double e=0.0;
1882:
1883: a=(ax < cx ? ax : cx);
1884: b=(ax > cx ? ax : cx);
1885: x=w=v=bx;
1886: fw=fv=fx=(*f)(x);
1887: for (iter=1;iter<=ITMAX;iter++) {
1888: xm=0.5*(a+b);
1889: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1890: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1891: printf(".");fflush(stdout);
1892: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1893: #ifdef DEBUGBRENT
1.126 brouard 1894: 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);
1895: 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);
1896: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1897: #endif
1898: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1899: *xmin=x;
1900: return fx;
1901: }
1902: ftemp=fu;
1903: if (fabs(e) > tol1) {
1904: r=(x-w)*(fx-fv);
1905: q=(x-v)*(fx-fw);
1906: p=(x-v)*q-(x-w)*r;
1907: q=2.0*(q-r);
1908: if (q > 0.0) p = -p;
1909: q=fabs(q);
1910: etemp=e;
1911: e=d;
1912: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1913: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1914: else {
1.224 brouard 1915: d=p/q;
1916: u=x+d;
1917: if (u-a < tol2 || b-u < tol2)
1918: d=SIGN(tol1,xm-x);
1.126 brouard 1919: }
1920: } else {
1921: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1922: }
1923: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1924: fu=(*f)(u);
1925: if (fu <= fx) {
1926: if (u >= x) a=x; else b=x;
1927: SHFT(v,w,x,u)
1.183 brouard 1928: SHFT(fv,fw,fx,fu)
1929: } else {
1930: if (u < x) a=u; else b=u;
1931: if (fu <= fw || w == x) {
1.224 brouard 1932: v=w;
1933: w=u;
1934: fv=fw;
1935: fw=fu;
1.183 brouard 1936: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1937: v=u;
1938: fv=fu;
1.183 brouard 1939: }
1940: }
1.126 brouard 1941: }
1942: nrerror("Too many iterations in brent");
1943: *xmin=x;
1944: return fx;
1945: }
1946:
1947: /****************** mnbrak ***********************/
1948:
1949: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1950: double (*func)(double))
1.183 brouard 1951: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1952: the downhill direction (defined by the function as evaluated at the initial points) and returns
1953: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1954: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1955: */
1.126 brouard 1956: double ulim,u,r,q, dum;
1957: double fu;
1.187 brouard 1958:
1959: double scale=10.;
1960: int iterscale=0;
1961:
1962: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1963: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1964:
1965:
1966: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1967: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1968: /* *bx = *ax - (*ax - *bx)/scale; */
1969: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1970: /* } */
1971:
1.126 brouard 1972: if (*fb > *fa) {
1973: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1974: SHFT(dum,*fb,*fa,dum)
1975: }
1.126 brouard 1976: *cx=(*bx)+GOLD*(*bx-*ax);
1977: *fc=(*func)(*cx);
1.183 brouard 1978: #ifdef DEBUG
1.224 brouard 1979: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1980: 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 1981: #endif
1.224 brouard 1982: 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 1983: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1984: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1985: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1986: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1987: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1988: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1989: fu=(*func)(u);
1.163 brouard 1990: #ifdef DEBUG
1991: /* f(x)=A(x-u)**2+f(u) */
1992: double A, fparabu;
1993: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1994: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1995: 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);
1996: 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 1997: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1998: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1999: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2000: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2001: #endif
1.184 brouard 2002: #ifdef MNBRAKORIGINAL
1.183 brouard 2003: #else
1.191 brouard 2004: /* if (fu > *fc) { */
2005: /* #ifdef DEBUG */
2006: /* printf("mnbrak4 fu > fc \n"); */
2007: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2008: /* #endif */
2009: /* /\* 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 *\\/ *\/ */
2010: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2011: /* dum=u; /\* Shifting c and u *\/ */
2012: /* u = *cx; */
2013: /* *cx = dum; */
2014: /* dum = fu; */
2015: /* fu = *fc; */
2016: /* *fc =dum; */
2017: /* } else { /\* end *\/ */
2018: /* #ifdef DEBUG */
2019: /* printf("mnbrak3 fu < fc \n"); */
2020: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2021: /* #endif */
2022: /* dum=u; /\* Shifting c and u *\/ */
2023: /* u = *cx; */
2024: /* *cx = dum; */
2025: /* dum = fu; */
2026: /* fu = *fc; */
2027: /* *fc =dum; */
2028: /* } */
1.224 brouard 2029: #ifdef DEBUGMNBRAK
2030: double A, fparabu;
2031: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2032: fparabu= *fa - A*(*ax-u)*(*ax-u);
2033: 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);
2034: 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 2035: #endif
1.191 brouard 2036: dum=u; /* Shifting c and u */
2037: u = *cx;
2038: *cx = dum;
2039: dum = fu;
2040: fu = *fc;
2041: *fc =dum;
1.183 brouard 2042: #endif
1.162 brouard 2043: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2044: #ifdef DEBUG
1.224 brouard 2045: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2046: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2047: #endif
1.126 brouard 2048: fu=(*func)(u);
2049: if (fu < *fc) {
1.183 brouard 2050: #ifdef DEBUG
1.224 brouard 2051: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2052: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2053: #endif
2054: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2055: SHFT(*fb,*fc,fu,(*func)(u))
2056: #ifdef DEBUG
2057: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2058: #endif
2059: }
1.162 brouard 2060: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2061: #ifdef DEBUG
1.224 brouard 2062: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2063: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2064: #endif
1.126 brouard 2065: u=ulim;
2066: fu=(*func)(u);
1.183 brouard 2067: } else { /* u could be left to b (if r > q parabola has a maximum) */
2068: #ifdef DEBUG
1.224 brouard 2069: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2070: 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 2071: #endif
1.126 brouard 2072: u=(*cx)+GOLD*(*cx-*bx);
2073: fu=(*func)(u);
1.224 brouard 2074: #ifdef DEBUG
2075: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2076: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2077: #endif
1.183 brouard 2078: } /* end tests */
1.126 brouard 2079: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2080: SHFT(*fa,*fb,*fc,fu)
2081: #ifdef DEBUG
1.224 brouard 2082: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2083: 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 2084: #endif
2085: } /* 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 2086: }
2087:
2088: /*************** linmin ************************/
1.162 brouard 2089: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2090: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2091: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2092: the value of func at the returned location p . This is actually all accomplished by calling the
2093: routines mnbrak and brent .*/
1.126 brouard 2094: int ncom;
2095: double *pcom,*xicom;
2096: double (*nrfunc)(double []);
2097:
1.224 brouard 2098: #ifdef LINMINORIGINAL
1.126 brouard 2099: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2100: #else
2101: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2102: #endif
1.126 brouard 2103: {
2104: double brent(double ax, double bx, double cx,
2105: double (*f)(double), double tol, double *xmin);
2106: double f1dim(double x);
2107: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2108: double *fc, double (*func)(double));
2109: int j;
2110: double xx,xmin,bx,ax;
2111: double fx,fb,fa;
1.187 brouard 2112:
1.203 brouard 2113: #ifdef LINMINORIGINAL
2114: #else
2115: double scale=10., axs, xxs; /* Scale added for infinity */
2116: #endif
2117:
1.126 brouard 2118: ncom=n;
2119: pcom=vector(1,n);
2120: xicom=vector(1,n);
2121: nrfunc=func;
2122: for (j=1;j<=n;j++) {
2123: pcom[j]=p[j];
1.202 brouard 2124: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2125: }
1.187 brouard 2126:
1.203 brouard 2127: #ifdef LINMINORIGINAL
2128: xx=1.;
2129: #else
2130: axs=0.0;
2131: xxs=1.;
2132: do{
2133: xx= xxs;
2134: #endif
1.187 brouard 2135: ax=0.;
2136: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2137: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2138: /* 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)) */
2139: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2140: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2141: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2142: /* 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 2143: #ifdef LINMINORIGINAL
2144: #else
2145: if (fx != fx){
1.224 brouard 2146: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2147: printf("|");
2148: fprintf(ficlog,"|");
1.203 brouard 2149: #ifdef DEBUGLINMIN
1.224 brouard 2150: 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 2151: #endif
2152: }
1.224 brouard 2153: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2154: #endif
2155:
1.191 brouard 2156: #ifdef DEBUGLINMIN
2157: 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 2158: 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 2159: #endif
1.224 brouard 2160: #ifdef LINMINORIGINAL
2161: #else
2162: if(fb == fx){ /* Flat function in the direction */
2163: xmin=xx;
2164: *flat=1;
2165: }else{
2166: *flat=0;
2167: #endif
2168: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2169: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2170: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2171: /* fmin = f(p[j] + xmin * xi[j]) */
2172: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2173: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2174: #ifdef DEBUG
1.224 brouard 2175: 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);
2176: 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);
2177: #endif
2178: #ifdef LINMINORIGINAL
2179: #else
2180: }
1.126 brouard 2181: #endif
1.191 brouard 2182: #ifdef DEBUGLINMIN
2183: printf("linmin end ");
1.202 brouard 2184: fprintf(ficlog,"linmin end ");
1.191 brouard 2185: #endif
1.126 brouard 2186: for (j=1;j<=n;j++) {
1.203 brouard 2187: #ifdef LINMINORIGINAL
2188: xi[j] *= xmin;
2189: #else
2190: #ifdef DEBUGLINMIN
2191: if(xxs <1.0)
2192: printf(" before xi[%d]=%12.8f", j,xi[j]);
2193: #endif
2194: 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) */
2195: #ifdef DEBUGLINMIN
2196: if(xxs <1.0)
2197: 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 );
2198: #endif
2199: #endif
1.187 brouard 2200: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2201: }
1.191 brouard 2202: #ifdef DEBUGLINMIN
1.203 brouard 2203: printf("\n");
1.191 brouard 2204: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2205: 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 2206: for (j=1;j<=n;j++) {
1.202 brouard 2207: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2208: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2209: if(j % ncovmodel == 0){
1.191 brouard 2210: printf("\n");
1.202 brouard 2211: fprintf(ficlog,"\n");
2212: }
1.191 brouard 2213: }
1.203 brouard 2214: #else
1.191 brouard 2215: #endif
1.126 brouard 2216: free_vector(xicom,1,n);
2217: free_vector(pcom,1,n);
2218: }
2219:
2220:
2221: /*************** powell ************************/
1.162 brouard 2222: /*
2223: Minimization of a function func of n variables. Input consists of an initial starting point
2224: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2225: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2226: such that failure to decrease by more than this amount on one iteration signals doneness. On
2227: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2228: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2229: */
1.224 brouard 2230: #ifdef LINMINORIGINAL
2231: #else
2232: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2233: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2234: #endif
1.126 brouard 2235: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2236: double (*func)(double []))
2237: {
1.224 brouard 2238: #ifdef LINMINORIGINAL
2239: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2240: double (*func)(double []));
1.224 brouard 2241: #else
1.241 brouard 2242: void linmin(double p[], double xi[], int n, double *fret,
2243: double (*func)(double []),int *flat);
1.224 brouard 2244: #endif
1.239 brouard 2245: int i,ibig,j,jk,k;
1.126 brouard 2246: double del,t,*pt,*ptt,*xit;
1.181 brouard 2247: double directest;
1.126 brouard 2248: double fp,fptt;
2249: double *xits;
2250: int niterf, itmp;
1.224 brouard 2251: #ifdef LINMINORIGINAL
2252: #else
2253:
2254: flatdir=ivector(1,n);
2255: for (j=1;j<=n;j++) flatdir[j]=0;
2256: #endif
1.126 brouard 2257:
2258: pt=vector(1,n);
2259: ptt=vector(1,n);
2260: xit=vector(1,n);
2261: xits=vector(1,n);
2262: *fret=(*func)(p);
2263: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2264: rcurr_time = time(NULL);
1.126 brouard 2265: for (*iter=1;;++(*iter)) {
1.187 brouard 2266: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2267: ibig=0;
2268: del=0.0;
1.157 brouard 2269: rlast_time=rcurr_time;
2270: /* (void) gettimeofday(&curr_time,&tzp); */
2271: rcurr_time = time(NULL);
2272: curr_time = *localtime(&rcurr_time);
2273: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2274: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2275: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2276: for (i=1;i<=n;i++) {
1.126 brouard 2277: fprintf(ficrespow," %.12lf", p[i]);
2278: }
1.239 brouard 2279: fprintf(ficrespow,"\n");fflush(ficrespow);
2280: printf("\n#model= 1 + age ");
2281: fprintf(ficlog,"\n#model= 1 + age ");
2282: if(nagesqr==1){
1.241 brouard 2283: printf(" + age*age ");
2284: fprintf(ficlog," + age*age ");
1.239 brouard 2285: }
2286: for(j=1;j <=ncovmodel-2;j++){
2287: if(Typevar[j]==0) {
2288: printf(" + V%d ",Tvar[j]);
2289: fprintf(ficlog," + V%d ",Tvar[j]);
2290: }else if(Typevar[j]==1) {
2291: printf(" + V%d*age ",Tvar[j]);
2292: fprintf(ficlog," + V%d*age ",Tvar[j]);
2293: }else if(Typevar[j]==2) {
2294: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2295: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2296: }
2297: }
1.126 brouard 2298: printf("\n");
1.239 brouard 2299: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2300: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2301: fprintf(ficlog,"\n");
1.239 brouard 2302: for(i=1,jk=1; i <=nlstate; i++){
2303: for(k=1; k <=(nlstate+ndeath); k++){
2304: if (k != i) {
2305: printf("%d%d ",i,k);
2306: fprintf(ficlog,"%d%d ",i,k);
2307: for(j=1; j <=ncovmodel; j++){
2308: printf("%12.7f ",p[jk]);
2309: fprintf(ficlog,"%12.7f ",p[jk]);
2310: jk++;
2311: }
2312: printf("\n");
2313: fprintf(ficlog,"\n");
2314: }
2315: }
2316: }
1.241 brouard 2317: if(*iter <=3 && *iter >1){
1.157 brouard 2318: tml = *localtime(&rcurr_time);
2319: strcpy(strcurr,asctime(&tml));
2320: rforecast_time=rcurr_time;
1.126 brouard 2321: itmp = strlen(strcurr);
2322: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2323: strcurr[itmp-1]='\0';
1.162 brouard 2324: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2325: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2326: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2327: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2328: forecast_time = *localtime(&rforecast_time);
2329: strcpy(strfor,asctime(&forecast_time));
2330: itmp = strlen(strfor);
2331: if(strfor[itmp-1]=='\n')
2332: strfor[itmp-1]='\0';
2333: 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);
2334: 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 2335: }
2336: }
1.187 brouard 2337: for (i=1;i<=n;i++) { /* For each direction i */
2338: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2339: fptt=(*fret);
2340: #ifdef DEBUG
1.203 brouard 2341: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2342: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2343: #endif
1.203 brouard 2344: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2345: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2346: #ifdef LINMINORIGINAL
1.188 brouard 2347: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2348: #else
2349: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2350: flatdir[i]=flat; /* Function is vanishing in that direction i */
2351: #endif
2352: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2353: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2354: /* because that direction will be replaced unless the gain del is small */
2355: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2356: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2357: /* with the new direction. */
2358: del=fabs(fptt-(*fret));
2359: ibig=i;
1.126 brouard 2360: }
2361: #ifdef DEBUG
2362: printf("%d %.12e",i,(*fret));
2363: fprintf(ficlog,"%d %.12e",i,(*fret));
2364: for (j=1;j<=n;j++) {
1.224 brouard 2365: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2366: printf(" x(%d)=%.12e",j,xit[j]);
2367: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2368: }
2369: for(j=1;j<=n;j++) {
1.225 brouard 2370: printf(" p(%d)=%.12e",j,p[j]);
2371: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2372: }
2373: printf("\n");
2374: fprintf(ficlog,"\n");
2375: #endif
1.187 brouard 2376: } /* end loop on each direction i */
2377: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2378: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2379: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2380: for(j=1;j<=n;j++) {
1.225 brouard 2381: if(flatdir[j] >0){
2382: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2383: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2384: }
2385: /* printf("\n"); */
2386: /* fprintf(ficlog,"\n"); */
2387: }
1.243 brouard 2388: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2389: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2390: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2391: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2392: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2393: /* decreased of more than 3.84 */
2394: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2395: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2396: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2397:
1.188 brouard 2398: /* Starting the program with initial values given by a former maximization will simply change */
2399: /* the scales of the directions and the directions, because the are reset to canonical directions */
2400: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2401: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2402: #ifdef DEBUG
2403: int k[2],l;
2404: k[0]=1;
2405: k[1]=-1;
2406: printf("Max: %.12e",(*func)(p));
2407: fprintf(ficlog,"Max: %.12e",(*func)(p));
2408: for (j=1;j<=n;j++) {
2409: printf(" %.12e",p[j]);
2410: fprintf(ficlog," %.12e",p[j]);
2411: }
2412: printf("\n");
2413: fprintf(ficlog,"\n");
2414: for(l=0;l<=1;l++) {
2415: for (j=1;j<=n;j++) {
2416: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2417: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2418: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2419: }
2420: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2421: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2422: }
2423: #endif
2424:
1.224 brouard 2425: #ifdef LINMINORIGINAL
2426: #else
2427: free_ivector(flatdir,1,n);
2428: #endif
1.126 brouard 2429: free_vector(xit,1,n);
2430: free_vector(xits,1,n);
2431: free_vector(ptt,1,n);
2432: free_vector(pt,1,n);
2433: return;
1.192 brouard 2434: } /* enough precision */
1.240 brouard 2435: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2436: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2437: ptt[j]=2.0*p[j]-pt[j];
2438: xit[j]=p[j]-pt[j];
2439: pt[j]=p[j];
2440: }
1.181 brouard 2441: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2442: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2443: if (*iter <=4) {
1.225 brouard 2444: #else
2445: #endif
1.224 brouard 2446: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2447: #else
1.161 brouard 2448: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2449: #endif
1.162 brouard 2450: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2451: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2452: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2453: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2454: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2455: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2456: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2457: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2458: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2459: /* Even if f3 <f1, directest can be negative and t >0 */
2460: /* mu² and del² are equal when f3=f1 */
2461: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2462: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2463: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2464: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2465: #ifdef NRCORIGINAL
2466: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2467: #else
2468: 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 2469: t= t- del*SQR(fp-fptt);
1.183 brouard 2470: #endif
1.202 brouard 2471: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2472: #ifdef DEBUG
1.181 brouard 2473: 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);
2474: 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 2475: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2476: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2477: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2478: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2479: 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);
2480: 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);
2481: #endif
1.183 brouard 2482: #ifdef POWELLORIGINAL
2483: if (t < 0.0) { /* Then we use it for new direction */
2484: #else
1.182 brouard 2485: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2486: 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 2487: 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 2488: 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 2489: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2490: }
1.181 brouard 2491: if (directest < 0.0) { /* Then we use it for new direction */
2492: #endif
1.191 brouard 2493: #ifdef DEBUGLINMIN
1.234 brouard 2494: printf("Before linmin in direction P%d-P0\n",n);
2495: for (j=1;j<=n;j++) {
2496: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2497: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2498: if(j % ncovmodel == 0){
2499: printf("\n");
2500: fprintf(ficlog,"\n");
2501: }
2502: }
1.224 brouard 2503: #endif
2504: #ifdef LINMINORIGINAL
1.234 brouard 2505: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2506: #else
1.234 brouard 2507: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2508: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2509: #endif
1.234 brouard 2510:
1.191 brouard 2511: #ifdef DEBUGLINMIN
1.234 brouard 2512: for (j=1;j<=n;j++) {
2513: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2514: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2515: if(j % ncovmodel == 0){
2516: printf("\n");
2517: fprintf(ficlog,"\n");
2518: }
2519: }
1.224 brouard 2520: #endif
1.234 brouard 2521: for (j=1;j<=n;j++) {
2522: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2523: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2524: }
1.224 brouard 2525: #ifdef LINMINORIGINAL
2526: #else
1.234 brouard 2527: for (j=1, flatd=0;j<=n;j++) {
2528: if(flatdir[j]>0)
2529: flatd++;
2530: }
2531: if(flatd >0){
1.255 brouard 2532: printf("%d flat directions: ",flatd);
2533: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2534: for (j=1;j<=n;j++) {
2535: if(flatdir[j]>0){
2536: printf("%d ",j);
2537: fprintf(ficlog,"%d ",j);
2538: }
2539: }
2540: printf("\n");
2541: fprintf(ficlog,"\n");
2542: }
1.191 brouard 2543: #endif
1.234 brouard 2544: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2545: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2546:
1.126 brouard 2547: #ifdef DEBUG
1.234 brouard 2548: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2549: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2550: for(j=1;j<=n;j++){
2551: printf(" %lf",xit[j]);
2552: fprintf(ficlog," %lf",xit[j]);
2553: }
2554: printf("\n");
2555: fprintf(ficlog,"\n");
1.126 brouard 2556: #endif
1.192 brouard 2557: } /* end of t or directest negative */
1.224 brouard 2558: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2559: #else
1.234 brouard 2560: } /* end if (fptt < fp) */
1.192 brouard 2561: #endif
1.225 brouard 2562: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2563: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2564: #else
1.224 brouard 2565: #endif
1.234 brouard 2566: } /* loop iteration */
1.126 brouard 2567: }
1.234 brouard 2568:
1.126 brouard 2569: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2570:
1.235 brouard 2571: 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 2572: {
1.279 brouard 2573: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2574: * (and selected quantitative values in nres)
2575: * by left multiplying the unit
2576: * matrix by transitions matrix until convergence is reached with precision ftolpl
2577: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2578: * Wx is row vector: population in state 1, population in state 2, population dead
2579: * or prevalence in state 1, prevalence in state 2, 0
2580: * newm is the matrix after multiplications, its rows are identical at a factor.
2581: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2582: * Output is prlim.
2583: * Initial matrix pimij
2584: */
1.206 brouard 2585: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2586: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2587: /* 0, 0 , 1} */
2588: /*
2589: * and after some iteration: */
2590: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2591: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2592: /* 0, 0 , 1} */
2593: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2594: /* {0.51571254859325999, 0.4842874514067399, */
2595: /* 0.51326036147820708, 0.48673963852179264} */
2596: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2597:
1.126 brouard 2598: int i, ii,j,k;
1.209 brouard 2599: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2600: /* double **matprod2(); */ /* test */
1.218 brouard 2601: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2602: double **newm;
1.209 brouard 2603: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2604: int ncvloop=0;
1.288 brouard 2605: int first=0;
1.169 brouard 2606:
1.209 brouard 2607: min=vector(1,nlstate);
2608: max=vector(1,nlstate);
2609: meandiff=vector(1,nlstate);
2610:
1.218 brouard 2611: /* Starting with matrix unity */
1.126 brouard 2612: for (ii=1;ii<=nlstate+ndeath;ii++)
2613: for (j=1;j<=nlstate+ndeath;j++){
2614: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2615: }
1.169 brouard 2616:
2617: cov[1]=1.;
2618:
2619: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2620: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2621: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2622: ncvloop++;
1.126 brouard 2623: newm=savm;
2624: /* Covariates have to be included here again */
1.138 brouard 2625: cov[2]=agefin;
1.187 brouard 2626: if(nagesqr==1)
2627: cov[3]= agefin*agefin;;
1.234 brouard 2628: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2629: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2630: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2631: /* 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 2632: }
2633: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2634: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2635: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2636: /* 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 2637: }
1.237 brouard 2638: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2639: if(Dummy[Tvar[Tage[k]]]){
2640: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2641: } else{
1.235 brouard 2642: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2643: }
1.235 brouard 2644: /* 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 2645: }
1.237 brouard 2646: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2647: /* 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 2648: if(Dummy[Tvard[k][1]==0]){
2649: if(Dummy[Tvard[k][2]==0]){
2650: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2651: }else{
2652: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2653: }
2654: }else{
2655: if(Dummy[Tvard[k][2]==0]){
2656: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2657: }else{
2658: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2659: }
2660: }
1.234 brouard 2661: }
1.138 brouard 2662: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2663: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2664: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2665: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2666: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2667: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2668: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2669:
1.126 brouard 2670: savm=oldm;
2671: oldm=newm;
1.209 brouard 2672:
2673: for(j=1; j<=nlstate; j++){
2674: max[j]=0.;
2675: min[j]=1.;
2676: }
2677: for(i=1;i<=nlstate;i++){
2678: sumnew=0;
2679: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2680: for(j=1; j<=nlstate; j++){
2681: prlim[i][j]= newm[i][j]/(1-sumnew);
2682: max[j]=FMAX(max[j],prlim[i][j]);
2683: min[j]=FMIN(min[j],prlim[i][j]);
2684: }
2685: }
2686:
1.126 brouard 2687: maxmax=0.;
1.209 brouard 2688: for(j=1; j<=nlstate; j++){
2689: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2690: maxmax=FMAX(maxmax,meandiff[j]);
2691: /* 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 2692: } /* j loop */
1.203 brouard 2693: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2694: /* 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 2695: if(maxmax < ftolpl){
1.209 brouard 2696: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2697: free_vector(min,1,nlstate);
2698: free_vector(max,1,nlstate);
2699: free_vector(meandiff,1,nlstate);
1.126 brouard 2700: return prlim;
2701: }
1.288 brouard 2702: } /* agefin loop */
1.208 brouard 2703: /* After some age loop it doesn't converge */
1.288 brouard 2704: if(!first){
2705: first=1;
2706: 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);
2707: }
2708: 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);
2709:
1.209 brouard 2710: /* 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); */
2711: free_vector(min,1,nlstate);
2712: free_vector(max,1,nlstate);
2713: free_vector(meandiff,1,nlstate);
1.208 brouard 2714:
1.169 brouard 2715: return prlim; /* should not reach here */
1.126 brouard 2716: }
2717:
1.217 brouard 2718:
2719: /**** Back Prevalence limit (stable or period prevalence) ****************/
2720:
1.218 brouard 2721: /* 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) */
2722: /* 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 2723: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2724: {
1.264 brouard 2725: /* 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 2726: matrix by transitions matrix until convergence is reached with precision ftolpl */
2727: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2728: /* Wx is row vector: population in state 1, population in state 2, population dead */
2729: /* or prevalence in state 1, prevalence in state 2, 0 */
2730: /* newm is the matrix after multiplications, its rows are identical at a factor */
2731: /* Initial matrix pimij */
2732: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2733: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2734: /* 0, 0 , 1} */
2735: /*
2736: * and after some iteration: */
2737: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2738: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2739: /* 0, 0 , 1} */
2740: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2741: /* {0.51571254859325999, 0.4842874514067399, */
2742: /* 0.51326036147820708, 0.48673963852179264} */
2743: /* If we start from prlim again, prlim tends to a constant matrix */
2744:
2745: int i, ii,j,k;
1.247 brouard 2746: int first=0;
1.217 brouard 2747: double *min, *max, *meandiff, maxmax,sumnew=0.;
2748: /* double **matprod2(); */ /* test */
2749: double **out, cov[NCOVMAX+1], **bmij();
2750: double **newm;
1.218 brouard 2751: double **dnewm, **doldm, **dsavm; /* for use */
2752: double **oldm, **savm; /* for use */
2753:
1.217 brouard 2754: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2755: int ncvloop=0;
2756:
2757: min=vector(1,nlstate);
2758: max=vector(1,nlstate);
2759: meandiff=vector(1,nlstate);
2760:
1.266 brouard 2761: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2762: oldm=oldms; savm=savms;
2763:
2764: /* Starting with matrix unity */
2765: for (ii=1;ii<=nlstate+ndeath;ii++)
2766: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2767: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2768: }
2769:
2770: cov[1]=1.;
2771:
2772: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2773: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2774: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2775: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2776: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2777: ncvloop++;
1.218 brouard 2778: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2779: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2780: /* Covariates have to be included here again */
2781: cov[2]=agefin;
2782: if(nagesqr==1)
2783: cov[3]= agefin*agefin;;
1.242 brouard 2784: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2785: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2786: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2787: /* 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 2788: }
2789: /* for (k=1; k<=cptcovn;k++) { */
2790: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2791: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2792: /* /\* 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])]); *\/ */
2793: /* } */
2794: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2795: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2796: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2797: /* 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]); */
2798: }
2799: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2800: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2801: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2802: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2803: for (k=1; k<=cptcovage;k++){ /* For product with age */
2804: if(Dummy[Tvar[Tage[k]]]){
2805: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2806: } else{
2807: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2808: }
2809: /* 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]); */
2810: }
2811: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2812: /* 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]); */
2813: if(Dummy[Tvard[k][1]==0]){
2814: if(Dummy[Tvard[k][2]==0]){
2815: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2816: }else{
2817: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2818: }
2819: }else{
2820: if(Dummy[Tvard[k][2]==0]){
2821: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2822: }else{
2823: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2824: }
2825: }
1.217 brouard 2826: }
2827:
2828: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2829: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2830: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2831: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2832: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2833: /* ij should be linked to the correct index of cov */
2834: /* age and covariate values ij are in 'cov', but we need to pass
2835: * ij for the observed prevalence at age and status and covariate
2836: * number: prevacurrent[(int)agefin][ii][ij]
2837: */
2838: /* 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 *\/ */
2839: /* 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 *\/ */
2840: 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 2841: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2842: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2843: /* for(i=1; i<=nlstate+ndeath; i++) { */
2844: /* printf("%d newm= ",i); */
2845: /* for(j=1;j<=nlstate+ndeath;j++) { */
2846: /* printf("%f ",newm[i][j]); */
2847: /* } */
2848: /* printf("oldm * "); */
2849: /* for(j=1;j<=nlstate+ndeath;j++) { */
2850: /* printf("%f ",oldm[i][j]); */
2851: /* } */
1.268 brouard 2852: /* printf(" bmmij "); */
1.266 brouard 2853: /* for(j=1;j<=nlstate+ndeath;j++) { */
2854: /* printf("%f ",pmmij[i][j]); */
2855: /* } */
2856: /* printf("\n"); */
2857: /* } */
2858: /* } */
1.217 brouard 2859: savm=oldm;
2860: oldm=newm;
1.266 brouard 2861:
1.217 brouard 2862: for(j=1; j<=nlstate; j++){
2863: max[j]=0.;
2864: min[j]=1.;
2865: }
2866: for(j=1; j<=nlstate; j++){
2867: for(i=1;i<=nlstate;i++){
1.234 brouard 2868: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2869: bprlim[i][j]= newm[i][j];
2870: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2871: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2872: }
2873: }
1.218 brouard 2874:
1.217 brouard 2875: maxmax=0.;
2876: for(i=1; i<=nlstate; i++){
2877: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2878: maxmax=FMAX(maxmax,meandiff[i]);
2879: /* 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 2880: } /* i loop */
1.217 brouard 2881: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2882: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2883: if(maxmax < ftolpl){
1.220 brouard 2884: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2885: free_vector(min,1,nlstate);
2886: free_vector(max,1,nlstate);
2887: free_vector(meandiff,1,nlstate);
2888: return bprlim;
2889: }
1.288 brouard 2890: } /* agefin loop */
1.217 brouard 2891: /* After some age loop it doesn't converge */
1.288 brouard 2892: if(!first){
1.247 brouard 2893: first=1;
2894: 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\
2895: 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);
2896: }
2897: 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 2898: 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);
2899: /* 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); */
2900: free_vector(min,1,nlstate);
2901: free_vector(max,1,nlstate);
2902: free_vector(meandiff,1,nlstate);
2903:
2904: return bprlim; /* should not reach here */
2905: }
2906:
1.126 brouard 2907: /*************** transition probabilities ***************/
2908:
2909: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2910: {
1.138 brouard 2911: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2912: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2913: model to the ncovmodel covariates (including constant and age).
2914: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2915: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2916: ncth covariate in the global vector x is given by the formula:
2917: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2918: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2919: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2920: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2921: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2922: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2923: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2924: */
2925: double s1, lnpijopii;
1.126 brouard 2926: /*double t34;*/
1.164 brouard 2927: int i,j, nc, ii, jj;
1.126 brouard 2928:
1.223 brouard 2929: for(i=1; i<= nlstate; i++){
2930: for(j=1; j<i;j++){
2931: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2932: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2933: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2934: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2935: }
2936: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2937: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2938: }
2939: for(j=i+1; j<=nlstate+ndeath;j++){
2940: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2941: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2942: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2943: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2944: }
2945: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2946: }
2947: }
1.218 brouard 2948:
1.223 brouard 2949: for(i=1; i<= nlstate; i++){
2950: s1=0;
2951: for(j=1; j<i; j++){
2952: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2953: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2954: }
2955: for(j=i+1; j<=nlstate+ndeath; j++){
2956: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2957: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2958: }
2959: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2960: ps[i][i]=1./(s1+1.);
2961: /* Computing other pijs */
2962: for(j=1; j<i; j++)
2963: ps[i][j]= exp(ps[i][j])*ps[i][i];
2964: for(j=i+1; j<=nlstate+ndeath; j++)
2965: ps[i][j]= exp(ps[i][j])*ps[i][i];
2966: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2967: } /* end i */
1.218 brouard 2968:
1.223 brouard 2969: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2970: for(jj=1; jj<= nlstate+ndeath; jj++){
2971: ps[ii][jj]=0;
2972: ps[ii][ii]=1;
2973: }
2974: }
1.294 brouard 2975:
2976:
1.223 brouard 2977: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2978: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2979: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2980: /* } */
2981: /* printf("\n "); */
2982: /* } */
2983: /* printf("\n ");printf("%lf ",cov[2]);*/
2984: /*
2985: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2986: goto end;*/
1.266 brouard 2987: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2988: }
2989:
1.218 brouard 2990: /*************** backward transition probabilities ***************/
2991:
2992: /* 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 ) */
2993: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2994: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2995: {
1.266 brouard 2996: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2997: * 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 2998: */
1.218 brouard 2999: int i, ii, j,k;
1.222 brouard 3000:
3001: double **out, **pmij();
3002: double sumnew=0.;
1.218 brouard 3003: double agefin;
1.292 brouard 3004: 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 3005: double **dnewm, **dsavm, **doldm;
3006: double **bbmij;
3007:
1.218 brouard 3008: doldm=ddoldms; /* global pointers */
1.222 brouard 3009: dnewm=ddnewms;
3010: dsavm=ddsavms;
3011:
3012: agefin=cov[2];
1.268 brouard 3013: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3014: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3015: the observed prevalence (with this covariate ij) at beginning of transition */
3016: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3017:
3018: /* P_x */
1.266 brouard 3019: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3020: /* outputs pmmij which is a stochastic matrix in row */
3021:
3022: /* Diag(w_x) */
1.292 brouard 3023: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3024: sumnew=0.;
1.269 brouard 3025: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3026: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 3027: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3028: sumnew+=prevacurrent[(int)agefin][ii][ij];
3029: }
3030: if(sumnew >0.01){ /* At least some value in the prevalence */
3031: for (ii=1;ii<=nlstate+ndeath;ii++){
3032: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3033: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3034: }
3035: }else{
3036: for (ii=1;ii<=nlstate+ndeath;ii++){
3037: for (j=1;j<=nlstate+ndeath;j++)
3038: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3039: }
3040: /* if(sumnew <0.9){ */
3041: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3042: /* } */
3043: }
3044: k3=0.0; /* We put the last diagonal to 0 */
3045: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3046: doldm[ii][ii]= k3;
3047: }
3048: /* End doldm, At the end doldm is diag[(w_i)] */
3049:
1.292 brouard 3050: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3051: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3052:
1.292 brouard 3053: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3054: /* 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 3055: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3056: sumnew=0.;
1.222 brouard 3057: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3058: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3059: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3060: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3061: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3062: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3063: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3064: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3065: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3066: /* }else */
1.268 brouard 3067: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3068: } /*End ii */
3069: } /* 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 */
3070:
1.292 brouard 3071: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3072: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3073: /* end bmij */
1.266 brouard 3074: return ps; /*pointer is unchanged */
1.218 brouard 3075: }
1.217 brouard 3076: /*************** transition probabilities ***************/
3077:
1.218 brouard 3078: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3079: {
3080: /* According to parameters values stored in x and the covariate's values stored in cov,
3081: computes the probability to be observed in state j being in state i by appying the
3082: model to the ncovmodel covariates (including constant and age).
3083: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3084: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3085: ncth covariate in the global vector x is given by the formula:
3086: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3087: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3088: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3089: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3090: Outputs ps[i][j] the probability to be observed in j being in j according to
3091: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3092: */
3093: double s1, lnpijopii;
3094: /*double t34;*/
3095: int i,j, nc, ii, jj;
3096:
1.234 brouard 3097: for(i=1; i<= nlstate; i++){
3098: for(j=1; j<i;j++){
3099: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3100: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3101: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3102: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3103: }
3104: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3105: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3106: }
3107: for(j=i+1; j<=nlstate+ndeath;j++){
3108: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3109: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3110: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3111: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3112: }
3113: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3114: }
3115: }
3116:
3117: for(i=1; i<= nlstate; i++){
3118: s1=0;
3119: for(j=1; j<i; j++){
3120: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3121: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3122: }
3123: for(j=i+1; j<=nlstate+ndeath; j++){
3124: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3125: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3126: }
3127: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3128: ps[i][i]=1./(s1+1.);
3129: /* Computing other pijs */
3130: for(j=1; j<i; j++)
3131: ps[i][j]= exp(ps[i][j])*ps[i][i];
3132: for(j=i+1; j<=nlstate+ndeath; j++)
3133: ps[i][j]= exp(ps[i][j])*ps[i][i];
3134: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3135: } /* end i */
3136:
3137: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3138: for(jj=1; jj<= nlstate+ndeath; jj++){
3139: ps[ii][jj]=0;
3140: ps[ii][ii]=1;
3141: }
3142: }
3143: /* Added for backcast */ /* Transposed matrix too */
3144: for(jj=1; jj<= nlstate+ndeath; jj++){
3145: s1=0.;
3146: for(ii=1; ii<= nlstate+ndeath; ii++){
3147: s1+=ps[ii][jj];
3148: }
3149: for(ii=1; ii<= nlstate; ii++){
3150: ps[ii][jj]=ps[ii][jj]/s1;
3151: }
3152: }
3153: /* Transposition */
3154: for(jj=1; jj<= nlstate+ndeath; jj++){
3155: for(ii=jj; ii<= nlstate+ndeath; ii++){
3156: s1=ps[ii][jj];
3157: ps[ii][jj]=ps[jj][ii];
3158: ps[jj][ii]=s1;
3159: }
3160: }
3161: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3162: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3163: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3164: /* } */
3165: /* printf("\n "); */
3166: /* } */
3167: /* printf("\n ");printf("%lf ",cov[2]);*/
3168: /*
3169: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3170: goto end;*/
3171: return ps;
1.217 brouard 3172: }
3173:
3174:
1.126 brouard 3175: /**************** Product of 2 matrices ******************/
3176:
1.145 brouard 3177: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3178: {
3179: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3180: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3181: /* in, b, out are matrice of pointers which should have been initialized
3182: before: only the contents of out is modified. The function returns
3183: a pointer to pointers identical to out */
1.145 brouard 3184: int i, j, k;
1.126 brouard 3185: for(i=nrl; i<= nrh; i++)
1.145 brouard 3186: for(k=ncolol; k<=ncoloh; k++){
3187: out[i][k]=0.;
3188: for(j=ncl; j<=nch; j++)
3189: out[i][k] +=in[i][j]*b[j][k];
3190: }
1.126 brouard 3191: return out;
3192: }
3193:
3194:
3195: /************* Higher Matrix Product ***************/
3196:
1.235 brouard 3197: 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 3198: {
1.218 brouard 3199: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3200: 'nhstepm*hstepm*stepm' months (i.e. until
3201: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3202: nhstepm*hstepm matrices.
3203: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3204: (typically every 2 years instead of every month which is too big
3205: for the memory).
3206: Model is determined by parameters x and covariates have to be
3207: included manually here.
3208:
3209: */
3210:
3211: int i, j, d, h, k;
1.131 brouard 3212: double **out, cov[NCOVMAX+1];
1.126 brouard 3213: double **newm;
1.187 brouard 3214: double agexact;
1.214 brouard 3215: double agebegin, ageend;
1.126 brouard 3216:
3217: /* Hstepm could be zero and should return the unit matrix */
3218: for (i=1;i<=nlstate+ndeath;i++)
3219: for (j=1;j<=nlstate+ndeath;j++){
3220: oldm[i][j]=(i==j ? 1.0 : 0.0);
3221: po[i][j][0]=(i==j ? 1.0 : 0.0);
3222: }
3223: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3224: for(h=1; h <=nhstepm; h++){
3225: for(d=1; d <=hstepm; d++){
3226: newm=savm;
3227: /* Covariates have to be included here again */
3228: cov[1]=1.;
1.214 brouard 3229: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3230: cov[2]=agexact;
3231: if(nagesqr==1)
1.227 brouard 3232: cov[3]= agexact*agexact;
1.235 brouard 3233: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3234: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3235: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3236: /* 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)); */
3237: }
3238: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3239: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3240: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3241: /* 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]); */
3242: }
3243: for (k=1; k<=cptcovage;k++){
3244: if(Dummy[Tvar[Tage[k]]]){
3245: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3246: } else{
3247: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3248: }
3249: /* 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]); */
3250: }
3251: for (k=1; k<=cptcovprod;k++){ /* */
3252: /* 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]); */
3253: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3254: }
3255: /* for (k=1; k<=cptcovn;k++) */
3256: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3257: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3258: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3259: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3260: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3261:
3262:
1.126 brouard 3263: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3264: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3265: /* right multiplication of oldm by the current matrix */
1.126 brouard 3266: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3267: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3268: /* if((int)age == 70){ */
3269: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3270: /* for(i=1; i<=nlstate+ndeath; i++) { */
3271: /* printf("%d pmmij ",i); */
3272: /* for(j=1;j<=nlstate+ndeath;j++) { */
3273: /* printf("%f ",pmmij[i][j]); */
3274: /* } */
3275: /* printf(" oldm "); */
3276: /* for(j=1;j<=nlstate+ndeath;j++) { */
3277: /* printf("%f ",oldm[i][j]); */
3278: /* } */
3279: /* printf("\n"); */
3280: /* } */
3281: /* } */
1.126 brouard 3282: savm=oldm;
3283: oldm=newm;
3284: }
3285: for(i=1; i<=nlstate+ndeath; i++)
3286: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3287: po[i][j][h]=newm[i][j];
3288: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3289: }
1.128 brouard 3290: /*printf("h=%d ",h);*/
1.126 brouard 3291: } /* end h */
1.267 brouard 3292: /* printf("\n H=%d \n",h); */
1.126 brouard 3293: return po;
3294: }
3295:
1.217 brouard 3296: /************* Higher Back Matrix Product ***************/
1.218 brouard 3297: /* 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 3298: 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 3299: {
1.266 brouard 3300: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3301: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3302: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3303: nhstepm*hstepm matrices.
3304: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3305: (typically every 2 years instead of every month which is too big
1.217 brouard 3306: for the memory).
1.218 brouard 3307: Model is determined by parameters x and covariates have to be
1.266 brouard 3308: included manually here. Then we use a call to bmij(x and cov)
3309: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3310: */
1.217 brouard 3311:
3312: int i, j, d, h, k;
1.266 brouard 3313: double **out, cov[NCOVMAX+1], **bmij();
3314: double **newm, ***newmm;
1.217 brouard 3315: double agexact;
3316: double agebegin, ageend;
1.222 brouard 3317: double **oldm, **savm;
1.217 brouard 3318:
1.266 brouard 3319: newmm=po; /* To be saved */
3320: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3321: /* Hstepm could be zero and should return the unit matrix */
3322: for (i=1;i<=nlstate+ndeath;i++)
3323: for (j=1;j<=nlstate+ndeath;j++){
3324: oldm[i][j]=(i==j ? 1.0 : 0.0);
3325: po[i][j][0]=(i==j ? 1.0 : 0.0);
3326: }
3327: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3328: for(h=1; h <=nhstepm; h++){
3329: for(d=1; d <=hstepm; d++){
3330: newm=savm;
3331: /* Covariates have to be included here again */
3332: cov[1]=1.;
1.271 brouard 3333: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3334: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3335: cov[2]=agexact;
3336: if(nagesqr==1)
1.222 brouard 3337: cov[3]= agexact*agexact;
1.266 brouard 3338: for (k=1; k<=cptcovn;k++){
3339: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3340: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3341: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3342: /* 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)); */
3343: }
1.267 brouard 3344: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3345: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3346: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3347: /* 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]); */
3348: }
3349: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3350: if(Dummy[Tvar[Tage[k]]]){
3351: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3352: } else{
3353: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3354: }
3355: /* 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]); */
3356: }
3357: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3358: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3359: }
1.217 brouard 3360: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3361: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3362:
1.218 brouard 3363: /* Careful transposed matrix */
1.266 brouard 3364: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3365: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3366: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3367: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3368: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3369: /* if((int)age == 70){ */
3370: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3371: /* for(i=1; i<=nlstate+ndeath; i++) { */
3372: /* printf("%d pmmij ",i); */
3373: /* for(j=1;j<=nlstate+ndeath;j++) { */
3374: /* printf("%f ",pmmij[i][j]); */
3375: /* } */
3376: /* printf(" oldm "); */
3377: /* for(j=1;j<=nlstate+ndeath;j++) { */
3378: /* printf("%f ",oldm[i][j]); */
3379: /* } */
3380: /* printf("\n"); */
3381: /* } */
3382: /* } */
3383: savm=oldm;
3384: oldm=newm;
3385: }
3386: for(i=1; i<=nlstate+ndeath; i++)
3387: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3388: po[i][j][h]=newm[i][j];
1.268 brouard 3389: /* if(h==nhstepm) */
3390: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3391: }
1.268 brouard 3392: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3393: } /* end h */
1.268 brouard 3394: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3395: return po;
3396: }
3397:
3398:
1.162 brouard 3399: #ifdef NLOPT
3400: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3401: double fret;
3402: double *xt;
3403: int j;
3404: myfunc_data *d2 = (myfunc_data *) pd;
3405: /* xt = (p1-1); */
3406: xt=vector(1,n);
3407: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3408:
3409: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3410: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3411: printf("Function = %.12lf ",fret);
3412: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3413: printf("\n");
3414: free_vector(xt,1,n);
3415: return fret;
3416: }
3417: #endif
1.126 brouard 3418:
3419: /*************** log-likelihood *************/
3420: double func( double *x)
3421: {
1.226 brouard 3422: int i, ii, j, k, mi, d, kk;
3423: int ioffset=0;
3424: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3425: double **out;
3426: double lli; /* Individual log likelihood */
3427: int s1, s2;
1.228 brouard 3428: 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 3429: double bbh, survp;
3430: long ipmx;
3431: double agexact;
3432: /*extern weight */
3433: /* We are differentiating ll according to initial status */
3434: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3435: /*for(i=1;i<imx;i++)
3436: printf(" %d\n",s[4][i]);
3437: */
1.162 brouard 3438:
1.226 brouard 3439: ++countcallfunc;
1.162 brouard 3440:
1.226 brouard 3441: cov[1]=1.;
1.126 brouard 3442:
1.226 brouard 3443: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3444: ioffset=0;
1.226 brouard 3445: if(mle==1){
3446: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3447: /* Computes the values of the ncovmodel covariates of the model
3448: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3449: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3450: to be observed in j being in i according to the model.
3451: */
1.243 brouard 3452: ioffset=2+nagesqr ;
1.233 brouard 3453: /* Fixed */
1.234 brouard 3454: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3455: 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)*/
3456: }
1.226 brouard 3457: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3458: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3459: has been calculated etc */
3460: /* For an individual i, wav[i] gives the number of effective waves */
3461: /* We compute the contribution to Likelihood of each effective transition
3462: mw[mi][i] is real wave of the mi th effectve wave */
3463: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3464: s2=s[mw[mi+1][i]][i];
3465: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3466: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3467: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3468: */
3469: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3470: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3471: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3472: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3473: }
3474: for (ii=1;ii<=nlstate+ndeath;ii++)
3475: for (j=1;j<=nlstate+ndeath;j++){
3476: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3477: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3478: }
3479: for(d=0; d<dh[mi][i]; d++){
3480: newm=savm;
3481: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3482: cov[2]=agexact;
3483: if(nagesqr==1)
3484: cov[3]= agexact*agexact; /* Should be changed here */
3485: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3486: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3487: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3488: else
3489: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3490: }
3491: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3492: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3493: savm=oldm;
3494: oldm=newm;
3495: } /* end mult */
3496:
3497: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3498: /* But now since version 0.9 we anticipate for bias at large stepm.
3499: * If stepm is larger than one month (smallest stepm) and if the exact delay
3500: * (in months) between two waves is not a multiple of stepm, we rounded to
3501: * the nearest (and in case of equal distance, to the lowest) interval but now
3502: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3503: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3504: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3505: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3506: * -stepm/2 to stepm/2 .
3507: * For stepm=1 the results are the same as for previous versions of Imach.
3508: * For stepm > 1 the results are less biased than in previous versions.
3509: */
1.234 brouard 3510: s1=s[mw[mi][i]][i];
3511: s2=s[mw[mi+1][i]][i];
3512: bbh=(double)bh[mi][i]/(double)stepm;
3513: /* bias bh is positive if real duration
3514: * is higher than the multiple of stepm and negative otherwise.
3515: */
3516: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3517: if( s2 > nlstate){
3518: /* i.e. if s2 is a death state and if the date of death is known
3519: then the contribution to the likelihood is the probability to
3520: die between last step unit time and current step unit time,
3521: which is also equal to probability to die before dh
3522: minus probability to die before dh-stepm .
3523: In version up to 0.92 likelihood was computed
3524: as if date of death was unknown. Death was treated as any other
3525: health state: the date of the interview describes the actual state
3526: and not the date of a change in health state. The former idea was
3527: to consider that at each interview the state was recorded
3528: (healthy, disable or death) and IMaCh was corrected; but when we
3529: introduced the exact date of death then we should have modified
3530: the contribution of an exact death to the likelihood. This new
3531: contribution is smaller and very dependent of the step unit
3532: stepm. It is no more the probability to die between last interview
3533: and month of death but the probability to survive from last
3534: interview up to one month before death multiplied by the
3535: probability to die within a month. Thanks to Chris
3536: Jackson for correcting this bug. Former versions increased
3537: mortality artificially. The bad side is that we add another loop
3538: which slows down the processing. The difference can be up to 10%
3539: lower mortality.
3540: */
3541: /* If, at the beginning of the maximization mostly, the
3542: cumulative probability or probability to be dead is
3543: constant (ie = 1) over time d, the difference is equal to
3544: 0. out[s1][3] = savm[s1][3]: probability, being at state
3545: s1 at precedent wave, to be dead a month before current
3546: wave is equal to probability, being at state s1 at
3547: precedent wave, to be dead at mont of the current
3548: wave. Then the observed probability (that this person died)
3549: is null according to current estimated parameter. In fact,
3550: it should be very low but not zero otherwise the log go to
3551: infinity.
3552: */
1.183 brouard 3553: /* #ifdef INFINITYORIGINAL */
3554: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3555: /* #else */
3556: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3557: /* lli=log(mytinydouble); */
3558: /* else */
3559: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3560: /* #endif */
1.226 brouard 3561: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3562:
1.226 brouard 3563: } else if ( s2==-1 ) { /* alive */
3564: for (j=1,survp=0. ; j<=nlstate; j++)
3565: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3566: /*survp += out[s1][j]; */
3567: lli= log(survp);
3568: }
3569: else if (s2==-4) {
3570: for (j=3,survp=0. ; j<=nlstate; j++)
3571: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3572: lli= log(survp);
3573: }
3574: else if (s2==-5) {
3575: for (j=1,survp=0. ; j<=2; j++)
3576: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3577: lli= log(survp);
3578: }
3579: else{
3580: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3581: /* 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 */
3582: }
3583: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3584: /*if(lli ==000.0)*/
3585: /*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); */
3586: ipmx +=1;
3587: sw += weight[i];
3588: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3589: /* if (lli < log(mytinydouble)){ */
3590: /* 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); */
3591: /* 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]); */
3592: /* } */
3593: } /* end of wave */
3594: } /* end of individual */
3595: } else if(mle==2){
3596: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3597: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3598: for(mi=1; mi<= wav[i]-1; mi++){
3599: for (ii=1;ii<=nlstate+ndeath;ii++)
3600: for (j=1;j<=nlstate+ndeath;j++){
3601: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3602: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3603: }
3604: for(d=0; d<=dh[mi][i]; d++){
3605: newm=savm;
3606: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3607: cov[2]=agexact;
3608: if(nagesqr==1)
3609: cov[3]= agexact*agexact;
3610: for (kk=1; kk<=cptcovage;kk++) {
3611: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3612: }
3613: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3614: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3615: savm=oldm;
3616: oldm=newm;
3617: } /* end mult */
3618:
3619: s1=s[mw[mi][i]][i];
3620: s2=s[mw[mi+1][i]][i];
3621: bbh=(double)bh[mi][i]/(double)stepm;
3622: 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 */
3623: ipmx +=1;
3624: sw += weight[i];
3625: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3626: } /* end of wave */
3627: } /* end of individual */
3628: } else if(mle==3){ /* exponential inter-extrapolation */
3629: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3630: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3631: for(mi=1; mi<= wav[i]-1; mi++){
3632: for (ii=1;ii<=nlstate+ndeath;ii++)
3633: for (j=1;j<=nlstate+ndeath;j++){
3634: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3635: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3636: }
3637: for(d=0; d<dh[mi][i]; d++){
3638: newm=savm;
3639: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3640: cov[2]=agexact;
3641: if(nagesqr==1)
3642: cov[3]= agexact*agexact;
3643: for (kk=1; kk<=cptcovage;kk++) {
3644: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3645: }
3646: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3647: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3648: savm=oldm;
3649: oldm=newm;
3650: } /* end mult */
3651:
3652: s1=s[mw[mi][i]][i];
3653: s2=s[mw[mi+1][i]][i];
3654: bbh=(double)bh[mi][i]/(double)stepm;
3655: 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 */
3656: ipmx +=1;
3657: sw += weight[i];
3658: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3659: } /* end of wave */
3660: } /* end of individual */
3661: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3662: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3663: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3664: for(mi=1; mi<= wav[i]-1; mi++){
3665: for (ii=1;ii<=nlstate+ndeath;ii++)
3666: for (j=1;j<=nlstate+ndeath;j++){
3667: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3668: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3669: }
3670: for(d=0; d<dh[mi][i]; d++){
3671: newm=savm;
3672: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3673: cov[2]=agexact;
3674: if(nagesqr==1)
3675: cov[3]= agexact*agexact;
3676: for (kk=1; kk<=cptcovage;kk++) {
3677: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3678: }
1.126 brouard 3679:
1.226 brouard 3680: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3681: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3682: savm=oldm;
3683: oldm=newm;
3684: } /* end mult */
3685:
3686: s1=s[mw[mi][i]][i];
3687: s2=s[mw[mi+1][i]][i];
3688: if( s2 > nlstate){
3689: lli=log(out[s1][s2] - savm[s1][s2]);
3690: } else if ( s2==-1 ) { /* alive */
3691: for (j=1,survp=0. ; j<=nlstate; j++)
3692: survp += out[s1][j];
3693: lli= log(survp);
3694: }else{
3695: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3696: }
3697: ipmx +=1;
3698: sw += weight[i];
3699: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3700: /* 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 3701: } /* end of wave */
3702: } /* end of individual */
3703: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3704: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3705: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3706: for(mi=1; mi<= wav[i]-1; mi++){
3707: for (ii=1;ii<=nlstate+ndeath;ii++)
3708: for (j=1;j<=nlstate+ndeath;j++){
3709: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3710: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3711: }
3712: for(d=0; d<dh[mi][i]; d++){
3713: newm=savm;
3714: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3715: cov[2]=agexact;
3716: if(nagesqr==1)
3717: cov[3]= agexact*agexact;
3718: for (kk=1; kk<=cptcovage;kk++) {
3719: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3720: }
1.126 brouard 3721:
1.226 brouard 3722: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3723: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3724: savm=oldm;
3725: oldm=newm;
3726: } /* end mult */
3727:
3728: s1=s[mw[mi][i]][i];
3729: s2=s[mw[mi+1][i]][i];
3730: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3731: ipmx +=1;
3732: sw += weight[i];
3733: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3734: /*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]);*/
3735: } /* end of wave */
3736: } /* end of individual */
3737: } /* End of if */
3738: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3739: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3740: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3741: return -l;
1.126 brouard 3742: }
3743:
3744: /*************** log-likelihood *************/
3745: double funcone( double *x)
3746: {
1.228 brouard 3747: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3748: int i, ii, j, k, mi, d, kk;
1.228 brouard 3749: int ioffset=0;
1.131 brouard 3750: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3751: double **out;
3752: double lli; /* Individual log likelihood */
3753: double llt;
3754: int s1, s2;
1.228 brouard 3755: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3756:
1.126 brouard 3757: double bbh, survp;
1.187 brouard 3758: double agexact;
1.214 brouard 3759: double agebegin, ageend;
1.126 brouard 3760: /*extern weight */
3761: /* We are differentiating ll according to initial status */
3762: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3763: /*for(i=1;i<imx;i++)
3764: printf(" %d\n",s[4][i]);
3765: */
3766: cov[1]=1.;
3767:
3768: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3769: ioffset=0;
3770: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3771: /* ioffset=2+nagesqr+cptcovage; */
3772: ioffset=2+nagesqr;
1.232 brouard 3773: /* Fixed */
1.224 brouard 3774: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3775: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3776: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3777: 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)*/
3778: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3779: /* cov[2+6]=covar[Tvar[6]][i]; */
3780: /* cov[2+6]=covar[2][i]; V2 */
3781: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3782: /* cov[2+7]=covar[Tvar[7]][i]; */
3783: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3784: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3785: /* cov[2+9]=covar[Tvar[9]][i]; */
3786: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3787: }
1.232 brouard 3788: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3789: /* 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?)*\/ */
3790: /* } */
1.231 brouard 3791: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3792: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3793: /* } */
1.225 brouard 3794:
1.233 brouard 3795:
3796: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3797: /* Wave varying (but not age varying) */
3798: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3799: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3800: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3801: }
1.232 brouard 3802: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3803: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3804: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3805: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3806: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3807: /* 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 3808: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3809: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3810: /* /\* 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]); *\/ */
3811: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3812: /* } */
1.126 brouard 3813: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3814: for (j=1;j<=nlstate+ndeath;j++){
3815: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3816: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3817: }
1.214 brouard 3818:
3819: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3820: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3821: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3822: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3823: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3824: and mw[mi+1][i]. dh depends on stepm.*/
3825: newm=savm;
1.247 brouard 3826: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3827: cov[2]=agexact;
3828: if(nagesqr==1)
3829: cov[3]= agexact*agexact;
3830: for (kk=1; kk<=cptcovage;kk++) {
3831: if(!FixedV[Tvar[Tage[kk]]])
3832: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3833: else
3834: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3835: }
3836: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3837: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3838: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3839: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3840: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3841: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3842: savm=oldm;
3843: oldm=newm;
1.126 brouard 3844: } /* end mult */
3845:
3846: s1=s[mw[mi][i]][i];
3847: s2=s[mw[mi+1][i]][i];
1.217 brouard 3848: /* if(s2==-1){ */
1.268 brouard 3849: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3850: /* /\* exit(1); *\/ */
3851: /* } */
1.126 brouard 3852: bbh=(double)bh[mi][i]/(double)stepm;
3853: /* bias is positive if real duration
3854: * is higher than the multiple of stepm and negative otherwise.
3855: */
3856: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3857: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3858: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3859: for (j=1,survp=0. ; j<=nlstate; j++)
3860: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3861: lli= log(survp);
1.126 brouard 3862: }else if (mle==1){
1.242 brouard 3863: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3864: } else if(mle==2){
1.242 brouard 3865: 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 3866: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3867: 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 3868: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3869: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3870: } else{ /* mle=0 back to 1 */
1.242 brouard 3871: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3872: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3873: } /* End of if */
3874: ipmx +=1;
3875: sw += weight[i];
3876: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3877: /*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 3878: if(globpr){
1.246 brouard 3879: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3880: %11.6f %11.6f %11.6f ", \
1.242 brouard 3881: 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 3882: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3883: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3884: llt +=ll[k]*gipmx/gsw;
3885: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3886: }
3887: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3888: }
1.232 brouard 3889: } /* end of wave */
3890: } /* end of individual */
3891: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3892: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3893: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3894: if(globpr==0){ /* First time we count the contributions and weights */
3895: gipmx=ipmx;
3896: gsw=sw;
3897: }
3898: return -l;
1.126 brouard 3899: }
3900:
3901:
3902: /*************** function likelione ***********/
1.292 brouard 3903: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 3904: {
3905: /* This routine should help understanding what is done with
3906: the selection of individuals/waves and
3907: to check the exact contribution to the likelihood.
3908: Plotting could be done.
3909: */
3910: int k;
3911:
3912: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3913: strcpy(fileresilk,"ILK_");
1.202 brouard 3914: strcat(fileresilk,fileresu);
1.126 brouard 3915: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3916: printf("Problem with resultfile: %s\n", fileresilk);
3917: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3918: }
1.214 brouard 3919: 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");
3920: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3921: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3922: for(k=1; k<=nlstate; k++)
3923: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3924: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3925: }
3926:
1.292 brouard 3927: *fretone=(*func)(p);
1.126 brouard 3928: if(*globpri !=0){
3929: fclose(ficresilk);
1.205 brouard 3930: if (mle ==0)
3931: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3932: else if(mle >=1)
3933: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3934: 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 3935: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3936:
3937: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3938: 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 3939: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3940: }
1.207 brouard 3941: 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 3942: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3943: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3944: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3945: fflush(fichtm);
1.205 brouard 3946: }
1.126 brouard 3947: return;
3948: }
3949:
3950:
3951: /*********** Maximum Likelihood Estimation ***************/
3952:
3953: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3954: {
1.165 brouard 3955: int i,j, iter=0;
1.126 brouard 3956: double **xi;
3957: double fret;
3958: double fretone; /* Only one call to likelihood */
3959: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3960:
3961: #ifdef NLOPT
3962: int creturn;
3963: nlopt_opt opt;
3964: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3965: double *lb;
3966: double minf; /* the minimum objective value, upon return */
3967: double * p1; /* Shifted parameters from 0 instead of 1 */
3968: myfunc_data dinst, *d = &dinst;
3969: #endif
3970:
3971:
1.126 brouard 3972: xi=matrix(1,npar,1,npar);
3973: for (i=1;i<=npar;i++)
3974: for (j=1;j<=npar;j++)
3975: xi[i][j]=(i==j ? 1.0 : 0.0);
3976: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3977: strcpy(filerespow,"POW_");
1.126 brouard 3978: strcat(filerespow,fileres);
3979: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3980: printf("Problem with resultfile: %s\n", filerespow);
3981: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3982: }
3983: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3984: for (i=1;i<=nlstate;i++)
3985: for(j=1;j<=nlstate+ndeath;j++)
3986: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3987: fprintf(ficrespow,"\n");
1.162 brouard 3988: #ifdef POWELL
1.126 brouard 3989: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3990: #endif
1.126 brouard 3991:
1.162 brouard 3992: #ifdef NLOPT
3993: #ifdef NEWUOA
3994: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3995: #else
3996: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3997: #endif
3998: lb=vector(0,npar-1);
3999: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4000: nlopt_set_lower_bounds(opt, lb);
4001: nlopt_set_initial_step1(opt, 0.1);
4002:
4003: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4004: d->function = func;
4005: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4006: nlopt_set_min_objective(opt, myfunc, d);
4007: nlopt_set_xtol_rel(opt, ftol);
4008: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4009: printf("nlopt failed! %d\n",creturn);
4010: }
4011: else {
4012: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4013: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4014: iter=1; /* not equal */
4015: }
4016: nlopt_destroy(opt);
4017: #endif
1.126 brouard 4018: free_matrix(xi,1,npar,1,npar);
4019: fclose(ficrespow);
1.203 brouard 4020: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4021: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4022: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4023:
4024: }
4025:
4026: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4027: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4028: {
4029: double **a,**y,*x,pd;
1.203 brouard 4030: /* double **hess; */
1.164 brouard 4031: int i, j;
1.126 brouard 4032: int *indx;
4033:
4034: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4035: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4036: void lubksb(double **a, int npar, int *indx, double b[]) ;
4037: void ludcmp(double **a, int npar, int *indx, double *d) ;
4038: double gompertz(double p[]);
1.203 brouard 4039: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4040:
4041: printf("\nCalculation of the hessian matrix. Wait...\n");
4042: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4043: for (i=1;i<=npar;i++){
1.203 brouard 4044: printf("%d-",i);fflush(stdout);
4045: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4046:
4047: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4048:
4049: /* printf(" %f ",p[i]);
4050: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4051: }
4052:
4053: for (i=1;i<=npar;i++) {
4054: for (j=1;j<=npar;j++) {
4055: if (j>i) {
1.203 brouard 4056: printf(".%d-%d",i,j);fflush(stdout);
4057: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4058: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4059:
4060: hess[j][i]=hess[i][j];
4061: /*printf(" %lf ",hess[i][j]);*/
4062: }
4063: }
4064: }
4065: printf("\n");
4066: fprintf(ficlog,"\n");
4067:
4068: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4069: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4070:
4071: a=matrix(1,npar,1,npar);
4072: y=matrix(1,npar,1,npar);
4073: x=vector(1,npar);
4074: indx=ivector(1,npar);
4075: for (i=1;i<=npar;i++)
4076: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4077: ludcmp(a,npar,indx,&pd);
4078:
4079: for (j=1;j<=npar;j++) {
4080: for (i=1;i<=npar;i++) x[i]=0;
4081: x[j]=1;
4082: lubksb(a,npar,indx,x);
4083: for (i=1;i<=npar;i++){
4084: matcov[i][j]=x[i];
4085: }
4086: }
4087:
4088: printf("\n#Hessian matrix#\n");
4089: fprintf(ficlog,"\n#Hessian matrix#\n");
4090: for (i=1;i<=npar;i++) {
4091: for (j=1;j<=npar;j++) {
1.203 brouard 4092: printf("%.6e ",hess[i][j]);
4093: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4094: }
4095: printf("\n");
4096: fprintf(ficlog,"\n");
4097: }
4098:
1.203 brouard 4099: /* printf("\n#Covariance matrix#\n"); */
4100: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4101: /* for (i=1;i<=npar;i++) { */
4102: /* for (j=1;j<=npar;j++) { */
4103: /* printf("%.6e ",matcov[i][j]); */
4104: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4105: /* } */
4106: /* printf("\n"); */
4107: /* fprintf(ficlog,"\n"); */
4108: /* } */
4109:
1.126 brouard 4110: /* Recompute Inverse */
1.203 brouard 4111: /* for (i=1;i<=npar;i++) */
4112: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4113: /* ludcmp(a,npar,indx,&pd); */
4114:
4115: /* printf("\n#Hessian matrix recomputed#\n"); */
4116:
4117: /* for (j=1;j<=npar;j++) { */
4118: /* for (i=1;i<=npar;i++) x[i]=0; */
4119: /* x[j]=1; */
4120: /* lubksb(a,npar,indx,x); */
4121: /* for (i=1;i<=npar;i++){ */
4122: /* y[i][j]=x[i]; */
4123: /* printf("%.3e ",y[i][j]); */
4124: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4125: /* } */
4126: /* printf("\n"); */
4127: /* fprintf(ficlog,"\n"); */
4128: /* } */
4129:
4130: /* Verifying the inverse matrix */
4131: #ifdef DEBUGHESS
4132: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4133:
1.203 brouard 4134: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4135: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4136:
4137: for (j=1;j<=npar;j++) {
4138: for (i=1;i<=npar;i++){
1.203 brouard 4139: printf("%.2f ",y[i][j]);
4140: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4141: }
4142: printf("\n");
4143: fprintf(ficlog,"\n");
4144: }
1.203 brouard 4145: #endif
1.126 brouard 4146:
4147: free_matrix(a,1,npar,1,npar);
4148: free_matrix(y,1,npar,1,npar);
4149: free_vector(x,1,npar);
4150: free_ivector(indx,1,npar);
1.203 brouard 4151: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4152:
4153:
4154: }
4155:
4156: /*************** hessian matrix ****************/
4157: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4158: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4159: int i;
4160: int l=1, lmax=20;
1.203 brouard 4161: double k1,k2, res, fx;
1.132 brouard 4162: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4163: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4164: int k=0,kmax=10;
4165: double l1;
4166:
4167: fx=func(x);
4168: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4169: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4170: l1=pow(10,l);
4171: delts=delt;
4172: for(k=1 ; k <kmax; k=k+1){
4173: delt = delta*(l1*k);
4174: p2[theta]=x[theta] +delt;
1.145 brouard 4175: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4176: p2[theta]=x[theta]-delt;
4177: k2=func(p2)-fx;
4178: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4179: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4180:
1.203 brouard 4181: #ifdef DEBUGHESSII
1.126 brouard 4182: 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);
4183: 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);
4184: #endif
4185: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4186: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4187: k=kmax;
4188: }
4189: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4190: k=kmax; l=lmax*10;
1.126 brouard 4191: }
4192: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4193: delts=delt;
4194: }
1.203 brouard 4195: } /* End loop k */
1.126 brouard 4196: }
4197: delti[theta]=delts;
4198: return res;
4199:
4200: }
4201:
1.203 brouard 4202: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4203: {
4204: int i;
1.164 brouard 4205: int l=1, lmax=20;
1.126 brouard 4206: double k1,k2,k3,k4,res,fx;
1.132 brouard 4207: double p2[MAXPARM+1];
1.203 brouard 4208: int k, kmax=1;
4209: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4210:
4211: int firstime=0;
1.203 brouard 4212:
1.126 brouard 4213: fx=func(x);
1.203 brouard 4214: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4215: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4216: p2[thetai]=x[thetai]+delti[thetai]*k;
4217: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4218: k1=func(p2)-fx;
4219:
1.203 brouard 4220: p2[thetai]=x[thetai]+delti[thetai]*k;
4221: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4222: k2=func(p2)-fx;
4223:
1.203 brouard 4224: p2[thetai]=x[thetai]-delti[thetai]*k;
4225: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4226: k3=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: k4=func(p2)-fx;
1.203 brouard 4231: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4232: if(k1*k2*k3*k4 <0.){
1.208 brouard 4233: firstime=1;
1.203 brouard 4234: kmax=kmax+10;
1.208 brouard 4235: }
4236: if(kmax >=10 || firstime ==1){
1.246 brouard 4237: 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);
4238: 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 4239: 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);
4240: 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);
4241: }
4242: #ifdef DEBUGHESSIJ
4243: v1=hess[thetai][thetai];
4244: v2=hess[thetaj][thetaj];
4245: cv12=res;
4246: /* Computing eigen value of Hessian matrix */
4247: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4248: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4249: if ((lc2 <0) || (lc1 <0) ){
4250: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4251: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4252: 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);
4253: 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);
4254: }
1.126 brouard 4255: #endif
4256: }
4257: return res;
4258: }
4259:
1.203 brouard 4260: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4261: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4262: /* { */
4263: /* int i; */
4264: /* int l=1, lmax=20; */
4265: /* double k1,k2,k3,k4,res,fx; */
4266: /* double p2[MAXPARM+1]; */
4267: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4268: /* int k=0,kmax=10; */
4269: /* double l1; */
4270:
4271: /* fx=func(x); */
4272: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4273: /* l1=pow(10,l); */
4274: /* delts=delt; */
4275: /* for(k=1 ; k <kmax; k=k+1){ */
4276: /* delt = delti*(l1*k); */
4277: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4278: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4279: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4280: /* k1=func(p2)-fx; */
4281:
4282: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4283: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4284: /* k2=func(p2)-fx; */
4285:
4286: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4287: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4288: /* k3=func(p2)-fx; */
4289:
4290: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4291: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4292: /* k4=func(p2)-fx; */
4293: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4294: /* #ifdef DEBUGHESSIJ */
4295: /* 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); */
4296: /* 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); */
4297: /* #endif */
4298: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4299: /* k=kmax; */
4300: /* } */
4301: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4302: /* k=kmax; l=lmax*10; */
4303: /* } */
4304: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4305: /* delts=delt; */
4306: /* } */
4307: /* } /\* End loop k *\/ */
4308: /* } */
4309: /* delti[theta]=delts; */
4310: /* return res; */
4311: /* } */
4312:
4313:
1.126 brouard 4314: /************** Inverse of matrix **************/
4315: void ludcmp(double **a, int n, int *indx, double *d)
4316: {
4317: int i,imax,j,k;
4318: double big,dum,sum,temp;
4319: double *vv;
4320:
4321: vv=vector(1,n);
4322: *d=1.0;
4323: for (i=1;i<=n;i++) {
4324: big=0.0;
4325: for (j=1;j<=n;j++)
4326: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4327: if (big == 0.0){
4328: printf(" Singular Hessian matrix at row %d:\n",i);
4329: for (j=1;j<=n;j++) {
4330: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4331: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4332: }
4333: fflush(ficlog);
4334: fclose(ficlog);
4335: nrerror("Singular matrix in routine ludcmp");
4336: }
1.126 brouard 4337: vv[i]=1.0/big;
4338: }
4339: for (j=1;j<=n;j++) {
4340: for (i=1;i<j;i++) {
4341: sum=a[i][j];
4342: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4343: a[i][j]=sum;
4344: }
4345: big=0.0;
4346: for (i=j;i<=n;i++) {
4347: sum=a[i][j];
4348: for (k=1;k<j;k++)
4349: sum -= a[i][k]*a[k][j];
4350: a[i][j]=sum;
4351: if ( (dum=vv[i]*fabs(sum)) >= big) {
4352: big=dum;
4353: imax=i;
4354: }
4355: }
4356: if (j != imax) {
4357: for (k=1;k<=n;k++) {
4358: dum=a[imax][k];
4359: a[imax][k]=a[j][k];
4360: a[j][k]=dum;
4361: }
4362: *d = -(*d);
4363: vv[imax]=vv[j];
4364: }
4365: indx[j]=imax;
4366: if (a[j][j] == 0.0) a[j][j]=TINY;
4367: if (j != n) {
4368: dum=1.0/(a[j][j]);
4369: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4370: }
4371: }
4372: free_vector(vv,1,n); /* Doesn't work */
4373: ;
4374: }
4375:
4376: void lubksb(double **a, int n, int *indx, double b[])
4377: {
4378: int i,ii=0,ip,j;
4379: double sum;
4380:
4381: for (i=1;i<=n;i++) {
4382: ip=indx[i];
4383: sum=b[ip];
4384: b[ip]=b[i];
4385: if (ii)
4386: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4387: else if (sum) ii=i;
4388: b[i]=sum;
4389: }
4390: for (i=n;i>=1;i--) {
4391: sum=b[i];
4392: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4393: b[i]=sum/a[i][i];
4394: }
4395: }
4396:
4397: void pstamp(FILE *fichier)
4398: {
1.196 brouard 4399: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4400: }
4401:
1.253 brouard 4402:
4403:
1.126 brouard 4404: /************ Frequencies ********************/
1.251 brouard 4405: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4406: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4407: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4408: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4409:
1.265 brouard 4410: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4411: int iind=0, iage=0;
4412: int mi; /* Effective wave */
4413: int first;
4414: double ***freq; /* Frequencies */
1.268 brouard 4415: 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 */
4416: 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 4417: double *meanq, *stdq, *idq;
1.226 brouard 4418: double **meanqt;
4419: double *pp, **prop, *posprop, *pospropt;
4420: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4421: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4422: double agebegin, ageend;
4423:
4424: pp=vector(1,nlstate);
1.251 brouard 4425: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4426: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4427: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4428: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4429: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4430: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4431: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4432: meanqt=matrix(1,lastpass,1,nqtveff);
4433: strcpy(fileresp,"P_");
4434: strcat(fileresp,fileresu);
4435: /*strcat(fileresphtm,fileresu);*/
4436: if((ficresp=fopen(fileresp,"w"))==NULL) {
4437: printf("Problem with prevalence resultfile: %s\n", fileresp);
4438: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4439: exit(0);
4440: }
1.240 brouard 4441:
1.226 brouard 4442: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4443: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4444: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4445: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4446: fflush(ficlog);
4447: exit(70);
4448: }
4449: else{
4450: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4451: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4452: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4453: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4454: }
1.237 brouard 4455: 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 4456:
1.226 brouard 4457: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4458: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4459: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4460: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4461: fflush(ficlog);
4462: exit(70);
1.240 brouard 4463: } else{
1.226 brouard 4464: 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 4465: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4466: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4467: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4468: }
1.240 brouard 4469: 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);
4470:
1.253 brouard 4471: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4472: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4473: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4474: j1=0;
1.126 brouard 4475:
1.227 brouard 4476: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4477: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4478: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4479:
4480:
1.226 brouard 4481: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4482: reference=low_education V1=0,V2=0
4483: med_educ V1=1 V2=0,
4484: high_educ V1=0 V2=1
4485: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4486: */
1.249 brouard 4487: dateintsum=0;
4488: k2cpt=0;
4489:
1.253 brouard 4490: if(cptcoveff == 0 )
1.265 brouard 4491: nl=1; /* Constant and age model only */
1.253 brouard 4492: else
4493: nl=2;
1.265 brouard 4494:
4495: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4496: /* Loop on nj=1 or 2 if dummy covariates j!=0
4497: * Loop on j1(1 to 2**cptcoveff) covariate combination
4498: * freq[s1][s2][iage] =0.
4499: * Loop on iind
4500: * ++freq[s1][s2][iage] weighted
4501: * end iind
4502: * if covariate and j!0
4503: * headers Variable on one line
4504: * endif cov j!=0
4505: * header of frequency table by age
4506: * Loop on age
4507: * pp[s1]+=freq[s1][s2][iage] weighted
4508: * pos+=freq[s1][s2][iage] weighted
4509: * Loop on s1 initial state
4510: * fprintf(ficresp
4511: * end s1
4512: * end age
4513: * if j!=0 computes starting values
4514: * end compute starting values
4515: * end j1
4516: * end nl
4517: */
1.253 brouard 4518: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4519: if(nj==1)
4520: j=0; /* First pass for the constant */
1.265 brouard 4521: else{
1.253 brouard 4522: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4523: }
1.251 brouard 4524: first=1;
1.265 brouard 4525: 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 4526: posproptt=0.;
4527: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4528: scanf("%d", i);*/
4529: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4530: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4531: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4532: freq[i][s2][m]=0;
1.251 brouard 4533:
4534: for (i=1; i<=nlstate; i++) {
1.240 brouard 4535: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4536: prop[i][m]=0;
4537: posprop[i]=0;
4538: pospropt[i]=0;
4539: }
1.283 brouard 4540: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4541: idq[z1]=0.;
4542: meanq[z1]=0.;
4543: stdq[z1]=0.;
1.283 brouard 4544: }
4545: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4546: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4547: /* meanqt[m][z1]=0.; */
4548: /* } */
4549: /* } */
1.251 brouard 4550: /* dateintsum=0; */
4551: /* k2cpt=0; */
4552:
1.265 brouard 4553: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4554: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4555: bool=1;
4556: if(j !=0){
4557: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4558: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4559: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4560: /* if(Tvaraff[z1] ==-20){ */
4561: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4562: /* }else if(Tvaraff[z1] ==-10){ */
4563: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4564: /* }else */
4565: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4566: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4567: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4568: /* 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",
4569: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4570: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4571: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4572: } /* Onlyf fixed */
4573: } /* end z1 */
4574: } /* cptcovn > 0 */
4575: } /* end any */
4576: }/* end j==0 */
1.265 brouard 4577: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4578: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4579: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4580: m=mw[mi][iind];
4581: if(j!=0){
4582: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4583: for (z1=1; z1<=cptcoveff; z1++) {
4584: if( Fixed[Tmodelind[z1]]==1){
4585: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4586: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4587: value is -1, we don't select. It differs from the
4588: constant and age model which counts them. */
4589: bool=0; /* not selected */
4590: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4591: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4592: bool=0;
4593: }
4594: }
4595: }
4596: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4597: } /* end j==0 */
4598: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4599: if(bool==1){ /*Selected */
1.251 brouard 4600: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4601: and mw[mi+1][iind]. dh depends on stepm. */
4602: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4603: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4604: if(m >=firstpass && m <=lastpass){
4605: k2=anint[m][iind]+(mint[m][iind]/12.);
4606: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4607: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4608: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4609: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4610: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4611: if (m<lastpass) {
4612: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4613: /* 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]); */
4614: if(s[m][iind]==-1)
4615: 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.));
4616: 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 4617: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4618: idq[z1]=idq[z1]+weight[iind];
4619: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4620: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4621: }
1.251 brouard 4622: /* if((int)agev[m][iind] == 55) */
4623: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4624: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4625: 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 4626: }
1.251 brouard 4627: } /* end if between passes */
4628: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4629: dateintsum=dateintsum+k2; /* on all covariates ?*/
4630: k2cpt++;
4631: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4632: }
1.251 brouard 4633: }else{
4634: bool=1;
4635: }/* end bool 2 */
4636: } /* end m */
1.284 brouard 4637: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4638: /* idq[z1]=idq[z1]+weight[iind]; */
4639: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4640: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4641: /* } */
1.251 brouard 4642: } /* end bool */
4643: } /* end iind = 1 to imx */
4644: /* prop[s][age] is feeded for any initial and valid live state as well as
4645: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4646:
4647:
4648: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4649: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4650: pstamp(ficresp);
1.251 brouard 4651: if (cptcoveff>0 && j!=0){
1.265 brouard 4652: pstamp(ficresp);
1.251 brouard 4653: printf( "\n#********** Variable ");
4654: fprintf(ficresp, "\n#********** Variable ");
4655: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4656: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4657: fprintf(ficlog, "\n#********** Variable ");
4658: for (z1=1; z1<=cptcoveff; z1++){
4659: if(!FixedV[Tvaraff[z1]]){
4660: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4661: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4662: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4663: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4664: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4665: }else{
1.251 brouard 4666: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4667: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4668: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4669: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4670: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4671: }
4672: }
4673: printf( "**********\n#");
4674: fprintf(ficresp, "**********\n#");
4675: fprintf(ficresphtm, "**********</h3>\n");
4676: fprintf(ficresphtmfr, "**********</h3>\n");
4677: fprintf(ficlog, "**********\n");
4678: }
1.284 brouard 4679: /*
4680: Printing means of quantitative variables if any
4681: */
4682: for (z1=1; z1<= nqfveff; z1++) {
1.285 brouard 4683: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4684: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4685: if(weightopt==1){
4686: printf(" Weighted mean and standard deviation of");
4687: fprintf(ficlog," Weighted mean and standard deviation of");
4688: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4689: }
1.285 brouard 4690: 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]));
4691: 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]));
4692: 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 4693: }
4694: /* for (z1=1; z1<= nqtveff; z1++) { */
4695: /* for(m=1;m<=lastpass;m++){ */
4696: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4697: /* } */
4698: /* } */
1.283 brouard 4699:
1.251 brouard 4700: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4701: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4702: fprintf(ficresp, " Age");
4703: 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 4704: for(i=1; i<=nlstate;i++) {
1.265 brouard 4705: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4706: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4707: }
1.265 brouard 4708: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4709: fprintf(ficresphtm, "\n");
4710:
4711: /* Header of frequency table by age */
4712: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4713: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4714: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4715: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4716: if(s2!=0 && m!=0)
4717: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4718: }
1.226 brouard 4719: }
1.251 brouard 4720: fprintf(ficresphtmfr, "\n");
4721:
4722: /* For each age */
4723: for(iage=iagemin; iage <= iagemax+3; iage++){
4724: fprintf(ficresphtm,"<tr>");
4725: if(iage==iagemax+1){
4726: fprintf(ficlog,"1");
4727: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4728: }else if(iage==iagemax+2){
4729: fprintf(ficlog,"0");
4730: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4731: }else if(iage==iagemax+3){
4732: fprintf(ficlog,"Total");
4733: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4734: }else{
1.240 brouard 4735: if(first==1){
1.251 brouard 4736: first=0;
4737: printf("See log file for details...\n");
4738: }
4739: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4740: fprintf(ficlog,"Age %d", iage);
4741: }
1.265 brouard 4742: for(s1=1; s1 <=nlstate ; s1++){
4743: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4744: pp[s1] += freq[s1][m][iage];
1.251 brouard 4745: }
1.265 brouard 4746: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4747: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4748: pos += freq[s1][m][iage];
4749: if(pp[s1]>=1.e-10){
1.251 brouard 4750: if(first==1){
1.265 brouard 4751: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4752: }
1.265 brouard 4753: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4754: }else{
4755: if(first==1)
1.265 brouard 4756: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4757: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4758: }
4759: }
4760:
1.265 brouard 4761: for(s1=1; s1 <=nlstate ; s1++){
4762: /* posprop[s1]=0; */
4763: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4764: pp[s1] += freq[s1][m][iage];
4765: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4766:
4767: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4768: pos += pp[s1]; /* pos is the total number of transitions until this age */
4769: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4770: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4771: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4772: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4773: }
4774:
4775: /* Writing ficresp */
4776: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4777: if( iage <= iagemax){
4778: fprintf(ficresp," %d",iage);
4779: }
4780: }else if( nj==2){
4781: if( iage <= iagemax){
4782: fprintf(ficresp," %d",iage);
4783: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4784: }
1.240 brouard 4785: }
1.265 brouard 4786: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4787: if(pos>=1.e-5){
1.251 brouard 4788: if(first==1)
1.265 brouard 4789: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4790: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4791: }else{
4792: if(first==1)
1.265 brouard 4793: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4794: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4795: }
4796: if( iage <= iagemax){
4797: if(pos>=1.e-5){
1.265 brouard 4798: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4799: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4800: }else if( nj==2){
4801: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4802: }
4803: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4804: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4805: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4806: } else{
4807: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4808: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4809: }
1.240 brouard 4810: }
1.265 brouard 4811: pospropt[s1] +=posprop[s1];
4812: } /* end loop s1 */
1.251 brouard 4813: /* pospropt=0.; */
1.265 brouard 4814: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4815: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4816: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4817: if(first==1){
1.265 brouard 4818: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4819: }
1.265 brouard 4820: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4821: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4822: }
1.265 brouard 4823: if(s1!=0 && m!=0)
4824: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4825: }
1.265 brouard 4826: } /* end loop s1 */
1.251 brouard 4827: posproptt=0.;
1.265 brouard 4828: for(s1=1; s1 <=nlstate; s1++){
4829: posproptt += pospropt[s1];
1.251 brouard 4830: }
4831: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4832: fprintf(ficresphtm,"</tr>\n");
4833: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4834: if(iage <= iagemax)
4835: fprintf(ficresp,"\n");
1.240 brouard 4836: }
1.251 brouard 4837: if(first==1)
4838: printf("Others in log...\n");
4839: fprintf(ficlog,"\n");
4840: } /* end loop age iage */
1.265 brouard 4841:
1.251 brouard 4842: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4843: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4844: if(posproptt < 1.e-5){
1.265 brouard 4845: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4846: }else{
1.265 brouard 4847: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4848: }
1.226 brouard 4849: }
1.251 brouard 4850: fprintf(ficresphtm,"</tr>\n");
4851: fprintf(ficresphtm,"</table>\n");
4852: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4853: if(posproptt < 1.e-5){
1.251 brouard 4854: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4855: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4856: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4857: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4858: invalidvarcomb[j1]=1;
1.226 brouard 4859: }else{
1.251 brouard 4860: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4861: invalidvarcomb[j1]=0;
1.226 brouard 4862: }
1.251 brouard 4863: fprintf(ficresphtmfr,"</table>\n");
4864: fprintf(ficlog,"\n");
4865: if(j!=0){
4866: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4867: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4868: for(k=1; k <=(nlstate+ndeath); k++){
4869: if (k != i) {
1.265 brouard 4870: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4871: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4872: if(j1==1){ /* All dummy covariates to zero */
4873: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4874: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4875: printf("%d%d ",i,k);
4876: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4877: 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]));
4878: 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]));
4879: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4880: }
1.253 brouard 4881: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4882: for(iage=iagemin; iage <= iagemax+3; iage++){
4883: x[iage]= (double)iage;
4884: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4885: /* 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 4886: }
1.268 brouard 4887: /* Some are not finite, but linreg will ignore these ages */
4888: no=0;
1.253 brouard 4889: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4890: pstart[s1]=b;
4891: pstart[s1-1]=a;
1.252 brouard 4892: }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 */
4893: 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]);
4894: 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 4895: 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 4896: printf("%d%d ",i,k);
4897: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4898: 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 4899: }else{ /* Other cases, like quantitative fixed or varying covariates */
4900: ;
4901: }
4902: /* printf("%12.7f )", param[i][jj][k]); */
4903: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4904: s1++;
1.251 brouard 4905: } /* end jj */
4906: } /* end k!= i */
4907: } /* end k */
1.265 brouard 4908: } /* end i, s1 */
1.251 brouard 4909: } /* end j !=0 */
4910: } /* end selected combination of covariate j1 */
4911: if(j==0){ /* We can estimate starting values from the occurences in each case */
4912: printf("#Freqsummary: Starting values for the constants:\n");
4913: fprintf(ficlog,"\n");
1.265 brouard 4914: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4915: for(k=1; k <=(nlstate+ndeath); k++){
4916: if (k != i) {
4917: printf("%d%d ",i,k);
4918: fprintf(ficlog,"%d%d ",i,k);
4919: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4920: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4921: if(jj==1){ /* Age has to be done */
1.265 brouard 4922: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4923: 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]));
4924: 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 4925: }
4926: /* printf("%12.7f )", param[i][jj][k]); */
4927: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4928: s1++;
1.250 brouard 4929: }
1.251 brouard 4930: printf("\n");
4931: fprintf(ficlog,"\n");
1.250 brouard 4932: }
4933: }
1.284 brouard 4934: } /* end of state i */
1.251 brouard 4935: printf("#Freqsummary\n");
4936: fprintf(ficlog,"\n");
1.265 brouard 4937: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4938: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4939: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4940: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4941: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4942: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4943: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4944: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4945: /* } */
4946: }
1.265 brouard 4947: } /* end loop s1 */
1.251 brouard 4948:
4949: printf("\n");
4950: fprintf(ficlog,"\n");
4951: } /* end j=0 */
1.249 brouard 4952: } /* end j */
1.252 brouard 4953:
1.253 brouard 4954: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4955: for(i=1, jk=1; i <=nlstate; i++){
4956: for(j=1; j <=nlstate+ndeath; j++){
4957: if(j!=i){
4958: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4959: printf("%1d%1d",i,j);
4960: fprintf(ficparo,"%1d%1d",i,j);
4961: for(k=1; k<=ncovmodel;k++){
4962: /* printf(" %lf",param[i][j][k]); */
4963: /* fprintf(ficparo," %lf",param[i][j][k]); */
4964: p[jk]=pstart[jk];
4965: printf(" %f ",pstart[jk]);
4966: fprintf(ficparo," %f ",pstart[jk]);
4967: jk++;
4968: }
4969: printf("\n");
4970: fprintf(ficparo,"\n");
4971: }
4972: }
4973: }
4974: } /* end mle=-2 */
1.226 brouard 4975: dateintmean=dateintsum/k2cpt;
1.240 brouard 4976:
1.226 brouard 4977: fclose(ficresp);
4978: fclose(ficresphtm);
4979: fclose(ficresphtmfr);
1.283 brouard 4980: free_vector(idq,1,nqfveff);
1.226 brouard 4981: free_vector(meanq,1,nqfveff);
1.284 brouard 4982: free_vector(stdq,1,nqfveff);
1.226 brouard 4983: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4984: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4985: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4986: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4987: free_vector(pospropt,1,nlstate);
4988: free_vector(posprop,1,nlstate);
1.251 brouard 4989: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4990: free_vector(pp,1,nlstate);
4991: /* End of freqsummary */
4992: }
1.126 brouard 4993:
1.268 brouard 4994: /* Simple linear regression */
4995: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4996:
4997: /* y=a+bx regression */
4998: double sumx = 0.0; /* sum of x */
4999: double sumx2 = 0.0; /* sum of x**2 */
5000: double sumxy = 0.0; /* sum of x * y */
5001: double sumy = 0.0; /* sum of y */
5002: double sumy2 = 0.0; /* sum of y**2 */
5003: double sume2 = 0.0; /* sum of square or residuals */
5004: double yhat;
5005:
5006: double denom=0;
5007: int i;
5008: int ne=*no;
5009:
5010: for ( i=ifi, ne=0;i<=ila;i++) {
5011: if(!isfinite(x[i]) || !isfinite(y[i])){
5012: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5013: continue;
5014: }
5015: ne=ne+1;
5016: sumx += x[i];
5017: sumx2 += x[i]*x[i];
5018: sumxy += x[i] * y[i];
5019: sumy += y[i];
5020: sumy2 += y[i]*y[i];
5021: denom = (ne * sumx2 - sumx*sumx);
5022: /* 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); */
5023: }
5024:
5025: denom = (ne * sumx2 - sumx*sumx);
5026: if (denom == 0) {
5027: // vertical, slope m is infinity
5028: *b = INFINITY;
5029: *a = 0;
5030: if (r) *r = 0;
5031: return 1;
5032: }
5033:
5034: *b = (ne * sumxy - sumx * sumy) / denom;
5035: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5036: if (r!=NULL) {
5037: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5038: sqrt((sumx2 - sumx*sumx/ne) *
5039: (sumy2 - sumy*sumy/ne));
5040: }
5041: *no=ne;
5042: for ( i=ifi, ne=0;i<=ila;i++) {
5043: if(!isfinite(x[i]) || !isfinite(y[i])){
5044: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5045: continue;
5046: }
5047: ne=ne+1;
5048: yhat = y[i] - *a -*b* x[i];
5049: sume2 += yhat * yhat ;
5050:
5051: denom = (ne * sumx2 - sumx*sumx);
5052: /* 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); */
5053: }
5054: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5055: *sa= *sb * sqrt(sumx2/ne);
5056:
5057: return 0;
5058: }
5059:
1.126 brouard 5060: /************ Prevalence ********************/
1.227 brouard 5061: 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)
5062: {
5063: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5064: in each health status at the date of interview (if between dateprev1 and dateprev2).
5065: We still use firstpass and lastpass as another selection.
5066: */
1.126 brouard 5067:
1.227 brouard 5068: int i, m, jk, j1, bool, z1,j, iv;
5069: int mi; /* Effective wave */
5070: int iage;
5071: double agebegin, ageend;
5072:
5073: double **prop;
5074: double posprop;
5075: double y2; /* in fractional years */
5076: int iagemin, iagemax;
5077: int first; /** to stop verbosity which is redirected to log file */
5078:
5079: iagemin= (int) agemin;
5080: iagemax= (int) agemax;
5081: /*pp=vector(1,nlstate);*/
1.251 brouard 5082: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5083: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5084: j1=0;
1.222 brouard 5085:
1.227 brouard 5086: /*j=cptcoveff;*/
5087: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5088:
1.288 brouard 5089: first=0;
1.227 brouard 5090: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5091: for (i=1; i<=nlstate; i++)
1.251 brouard 5092: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5093: prop[i][iage]=0.0;
5094: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5095: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5096: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5097:
5098: for (i=1; i<=imx; i++) { /* Each individual */
5099: bool=1;
5100: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5101: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5102: m=mw[mi][i];
5103: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5104: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5105: for (z1=1; z1<=cptcoveff; z1++){
5106: if( Fixed[Tmodelind[z1]]==1){
5107: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5108: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5109: bool=0;
5110: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5111: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5112: bool=0;
5113: }
5114: }
5115: if(bool==1){ /* Otherwise we skip that wave/person */
5116: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5117: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5118: if(m >=firstpass && m <=lastpass){
5119: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5120: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5121: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5122: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5123: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5124: 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);
5125: exit(1);
5126: }
5127: if (s[m][i]>0 && s[m][i]<=nlstate) {
5128: /*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]]);*/
5129: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5130: prop[s[m][i]][iagemax+3] += weight[i];
5131: } /* end valid statuses */
5132: } /* end selection of dates */
5133: } /* end selection of waves */
5134: } /* end bool */
5135: } /* end wave */
5136: } /* end individual */
5137: for(i=iagemin; i <= iagemax+3; i++){
5138: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5139: posprop += prop[jk][i];
5140: }
5141:
5142: for(jk=1; jk <=nlstate ; jk++){
5143: if( i <= iagemax){
5144: if(posprop>=1.e-5){
5145: probs[i][jk][j1]= prop[jk][i]/posprop;
5146: } else{
1.288 brouard 5147: if(!first){
5148: first=1;
1.266 brouard 5149: 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]);
5150: }else{
1.288 brouard 5151: 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 5152: }
5153: }
5154: }
5155: }/* end jk */
5156: }/* end i */
1.222 brouard 5157: /*} *//* end i1 */
1.227 brouard 5158: } /* end j1 */
1.222 brouard 5159:
1.227 brouard 5160: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5161: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5162: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5163: } /* End of prevalence */
1.126 brouard 5164:
5165: /************* Waves Concatenation ***************/
5166:
5167: 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)
5168: {
5169: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5170: Death is a valid wave (if date is known).
5171: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5172: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5173: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5174: */
1.126 brouard 5175:
1.224 brouard 5176: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5177: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5178: double sum=0., jmean=0.;*/
1.224 brouard 5179: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5180: int j, k=0,jk, ju, jl;
5181: double sum=0.;
5182: first=0;
1.214 brouard 5183: firstwo=0;
1.217 brouard 5184: firsthree=0;
1.218 brouard 5185: firstfour=0;
1.164 brouard 5186: jmin=100000;
1.126 brouard 5187: jmax=-1;
5188: jmean=0.;
1.224 brouard 5189:
5190: /* Treating live states */
1.214 brouard 5191: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5192: mi=0; /* First valid wave */
1.227 brouard 5193: mli=0; /* Last valid wave */
1.126 brouard 5194: m=firstpass;
1.214 brouard 5195: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5196: 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 */
5197: mli=m-1;/* mw[++mi][i]=m-1; */
5198: }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 */
5199: mw[++mi][i]=m;
5200: mli=m;
1.224 brouard 5201: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5202: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5203: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5204: }
1.227 brouard 5205: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5206: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5207: break;
1.224 brouard 5208: #else
1.227 brouard 5209: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5210: if(firsthree == 0){
1.262 brouard 5211: 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 5212: firsthree=1;
5213: }
1.262 brouard 5214: 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 5215: mw[++mi][i]=m;
5216: mli=m;
5217: }
5218: if(s[m][i]==-2){ /* Vital status is really unknown */
5219: nbwarn++;
5220: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5221: 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);
5222: 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);
5223: }
5224: break;
5225: }
5226: break;
1.224 brouard 5227: #endif
1.227 brouard 5228: }/* End m >= lastpass */
1.126 brouard 5229: }/* end while */
1.224 brouard 5230:
1.227 brouard 5231: /* 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 5232: /* After last pass */
1.224 brouard 5233: /* Treating death states */
1.214 brouard 5234: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5235: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5236: /* } */
1.126 brouard 5237: mi++; /* Death is another wave */
5238: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5239: /* Only death is a correct wave */
1.126 brouard 5240: mw[mi][i]=m;
1.257 brouard 5241: } /* else not in a death state */
1.224 brouard 5242: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5243: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5244: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5245: 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 */
5246: nbwarn++;
5247: if(firstfiv==0){
5248: 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 );
5249: firstfiv=1;
5250: }else{
5251: 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 );
5252: }
5253: }else{ /* Death occured afer last wave potential bias */
5254: nberr++;
5255: if(firstwo==0){
1.257 brouard 5256: 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 5257: firstwo=1;
5258: }
1.257 brouard 5259: 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 5260: }
1.257 brouard 5261: }else{ /* if date of interview is unknown */
1.227 brouard 5262: /* death is known but not confirmed by death status at any wave */
5263: if(firstfour==0){
5264: 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 );
5265: firstfour=1;
5266: }
5267: 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 5268: }
1.224 brouard 5269: } /* end if date of death is known */
5270: #endif
5271: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5272: /* wav[i]=mw[mi][i]; */
1.126 brouard 5273: if(mi==0){
5274: nbwarn++;
5275: if(first==0){
1.227 brouard 5276: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5277: first=1;
1.126 brouard 5278: }
5279: if(first==1){
1.227 brouard 5280: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5281: }
5282: } /* end mi==0 */
5283: } /* End individuals */
1.214 brouard 5284: /* wav and mw are no more changed */
1.223 brouard 5285:
1.214 brouard 5286:
1.126 brouard 5287: for(i=1; i<=imx; i++){
5288: for(mi=1; mi<wav[i];mi++){
5289: if (stepm <=0)
1.227 brouard 5290: dh[mi][i]=1;
1.126 brouard 5291: else{
1.260 brouard 5292: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5293: if (agedc[i] < 2*AGESUP) {
5294: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5295: if(j==0) j=1; /* Survives at least one month after exam */
5296: else if(j<0){
5297: nberr++;
5298: 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]);
5299: j=1; /* Temporary Dangerous patch */
5300: 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);
5301: 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]);
5302: 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);
5303: }
5304: k=k+1;
5305: if (j >= jmax){
5306: jmax=j;
5307: ijmax=i;
5308: }
5309: if (j <= jmin){
5310: jmin=j;
5311: ijmin=i;
5312: }
5313: sum=sum+j;
5314: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5315: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5316: }
5317: }
5318: else{
5319: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5320: /* 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 5321:
1.227 brouard 5322: k=k+1;
5323: if (j >= jmax) {
5324: jmax=j;
5325: ijmax=i;
5326: }
5327: else if (j <= jmin){
5328: jmin=j;
5329: ijmin=i;
5330: }
5331: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5332: /*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]);*/
5333: if(j<0){
5334: nberr++;
5335: 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]);
5336: 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]);
5337: }
5338: sum=sum+j;
5339: }
5340: jk= j/stepm;
5341: jl= j -jk*stepm;
5342: ju= j -(jk+1)*stepm;
5343: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5344: if(jl==0){
5345: dh[mi][i]=jk;
5346: bh[mi][i]=0;
5347: }else{ /* We want a negative bias in order to only have interpolation ie
5348: * to avoid the price of an extra matrix product in likelihood */
5349: dh[mi][i]=jk+1;
5350: bh[mi][i]=ju;
5351: }
5352: }else{
5353: if(jl <= -ju){
5354: dh[mi][i]=jk;
5355: bh[mi][i]=jl; /* bias is positive if real duration
5356: * is higher than the multiple of stepm and negative otherwise.
5357: */
5358: }
5359: else{
5360: dh[mi][i]=jk+1;
5361: bh[mi][i]=ju;
5362: }
5363: if(dh[mi][i]==0){
5364: dh[mi][i]=1; /* At least one step */
5365: bh[mi][i]=ju; /* At least one step */
5366: /* 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);*/
5367: }
5368: } /* end if mle */
1.126 brouard 5369: }
5370: } /* end wave */
5371: }
5372: jmean=sum/k;
5373: 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 5374: 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 5375: }
1.126 brouard 5376:
5377: /*********** Tricode ****************************/
1.220 brouard 5378: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5379: {
5380: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5381: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5382: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5383: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5384: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5385: */
1.130 brouard 5386:
1.242 brouard 5387: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5388: int modmaxcovj=0; /* Modality max of covariates j */
5389: int cptcode=0; /* Modality max of covariates j */
5390: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5391:
5392:
1.242 brouard 5393: /* cptcoveff=0; */
5394: /* *cptcov=0; */
1.126 brouard 5395:
1.242 brouard 5396: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5397: for (k=1; k <= maxncov; k++)
5398: for(j=1; j<=2; j++)
5399: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5400:
1.242 brouard 5401: /* Loop on covariates without age and products and no quantitative variable */
5402: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5403: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5404: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5405: switch(Fixed[k]) {
5406: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5407: 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*/
5408: ij=(int)(covar[Tvar[k]][i]);
5409: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5410: * If product of Vn*Vm, still boolean *:
5411: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5412: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5413: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5414: modality of the nth covariate of individual i. */
5415: if (ij > modmaxcovj)
5416: modmaxcovj=ij;
5417: else if (ij < modmincovj)
5418: modmincovj=ij;
1.287 brouard 5419: if (ij <0 || ij >1 ){
5420: printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5421: fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5422: }
5423: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5424: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5425: exit(1);
5426: }else
5427: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5428: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5429: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5430: /* getting the maximum value of the modality of the covariate
5431: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5432: female ies 1, then modmaxcovj=1.
5433: */
5434: } /* end for loop on individuals i */
5435: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5436: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5437: cptcode=modmaxcovj;
5438: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5439: /*for (i=0; i<=cptcode; i++) {*/
5440: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5441: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5442: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5443: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5444: if( j != -1){
5445: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5446: covariate for which somebody answered excluding
5447: undefined. Usually 2: 0 and 1. */
5448: }
5449: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5450: covariate for which somebody answered including
5451: undefined. Usually 3: -1, 0 and 1. */
5452: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5453: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5454: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5455:
1.242 brouard 5456: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5457: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5458: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5459: /* modmincovj=3; modmaxcovj = 7; */
5460: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5461: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5462: /* defining two dummy variables: variables V1_1 and V1_2.*/
5463: /* nbcode[Tvar[j]][ij]=k; */
5464: /* nbcode[Tvar[j]][1]=0; */
5465: /* nbcode[Tvar[j]][2]=1; */
5466: /* nbcode[Tvar[j]][3]=2; */
5467: /* To be continued (not working yet). */
5468: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5469:
5470: /* 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*/
5471: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5472: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5473: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5474: /*, could be restored in the future */
5475: 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 5476: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5477: break;
5478: }
5479: ij++;
1.287 brouard 5480: 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 5481: cptcode = ij; /* New max modality for covar j */
5482: } /* end of loop on modality i=-1 to 1 or more */
5483: break;
5484: case 1: /* Testing on varying covariate, could be simple and
5485: * should look at waves or product of fixed *
5486: * varying. No time to test -1, assuming 0 and 1 only */
5487: ij=0;
5488: for(i=0; i<=1;i++){
5489: nbcode[Tvar[k]][++ij]=i;
5490: }
5491: break;
5492: default:
5493: break;
5494: } /* end switch */
5495: } /* end dummy test */
1.287 brouard 5496: } /* 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 5497:
5498: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5499: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5500: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5501: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5502: 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 */
5503: 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 */
5504: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5505: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5506:
5507: ij=0;
5508: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5509: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5510: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5511: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5512: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5513: /* If product not in single variable we don't print results */
5514: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5515: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5516: 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*/
5517: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5518: 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 */
5519: if(Fixed[k]!=0)
5520: anyvaryingduminmodel=1;
5521: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5522: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5523: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5524: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5525: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5526: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5527: }
5528: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5529: /* ij--; */
5530: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5531: *cptcov=ij; /*Number of total real effective covariates: effective
5532: * because they can be excluded from the model and real
5533: * if in the model but excluded because missing values, but how to get k from ij?*/
5534: for(j=ij+1; j<= cptcovt; j++){
5535: Tvaraff[j]=0;
5536: Tmodelind[j]=0;
5537: }
5538: for(j=ntveff+1; j<= cptcovt; j++){
5539: TmodelInvind[j]=0;
5540: }
5541: /* To be sorted */
5542: ;
5543: }
1.126 brouard 5544:
1.145 brouard 5545:
1.126 brouard 5546: /*********** Health Expectancies ****************/
5547:
1.235 brouard 5548: 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 5549:
5550: {
5551: /* Health expectancies, no variances */
1.164 brouard 5552: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5553: int nhstepma, nstepma; /* Decreasing with age */
5554: double age, agelim, hf;
5555: double ***p3mat;
5556: double eip;
5557:
1.238 brouard 5558: /* pstamp(ficreseij); */
1.126 brouard 5559: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5560: fprintf(ficreseij,"# Age");
5561: for(i=1; i<=nlstate;i++){
5562: for(j=1; j<=nlstate;j++){
5563: fprintf(ficreseij," e%1d%1d ",i,j);
5564: }
5565: fprintf(ficreseij," e%1d. ",i);
5566: }
5567: fprintf(ficreseij,"\n");
5568:
5569:
5570: if(estepm < stepm){
5571: printf ("Problem %d lower than %d\n",estepm, stepm);
5572: }
5573: else hstepm=estepm;
5574: /* We compute the life expectancy from trapezoids spaced every estepm months
5575: * This is mainly to measure the difference between two models: for example
5576: * if stepm=24 months pijx are given only every 2 years and by summing them
5577: * we are calculating an estimate of the Life Expectancy assuming a linear
5578: * progression in between and thus overestimating or underestimating according
5579: * to the curvature of the survival function. If, for the same date, we
5580: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5581: * to compare the new estimate of Life expectancy with the same linear
5582: * hypothesis. A more precise result, taking into account a more precise
5583: * curvature will be obtained if estepm is as small as stepm. */
5584:
5585: /* For example we decided to compute the life expectancy with the smallest unit */
5586: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5587: nhstepm is the number of hstepm from age to agelim
5588: nstepm is the number of stepm from age to agelin.
1.270 brouard 5589: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5590: and note for a fixed period like estepm months */
5591: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5592: survival function given by stepm (the optimization length). Unfortunately it
5593: means that if the survival funtion is printed only each two years of age and if
5594: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5595: results. So we changed our mind and took the option of the best precision.
5596: */
5597: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5598:
5599: agelim=AGESUP;
5600: /* If stepm=6 months */
5601: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5602: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5603:
5604: /* nhstepm age range expressed in number of stepm */
5605: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5606: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5607: /* if (stepm >= YEARM) hstepm=1;*/
5608: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5609: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5610:
5611: for (age=bage; age<=fage; age ++){
5612: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5613: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5614: /* if (stepm >= YEARM) hstepm=1;*/
5615: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5616:
5617: /* If stepm=6 months */
5618: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5619: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5620:
1.235 brouard 5621: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5622:
5623: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5624:
5625: printf("%d|",(int)age);fflush(stdout);
5626: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5627:
5628: /* Computing expectancies */
5629: for(i=1; i<=nlstate;i++)
5630: for(j=1; j<=nlstate;j++)
5631: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5632: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5633:
5634: /* 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]);*/
5635:
5636: }
5637:
5638: fprintf(ficreseij,"%3.0f",age );
5639: for(i=1; i<=nlstate;i++){
5640: eip=0;
5641: for(j=1; j<=nlstate;j++){
5642: eip +=eij[i][j][(int)age];
5643: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5644: }
5645: fprintf(ficreseij,"%9.4f", eip );
5646: }
5647: fprintf(ficreseij,"\n");
5648:
5649: }
5650: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5651: printf("\n");
5652: fprintf(ficlog,"\n");
5653:
5654: }
5655:
1.235 brouard 5656: 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 5657:
5658: {
5659: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5660: to initial status i, ei. .
1.126 brouard 5661: */
5662: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5663: int nhstepma, nstepma; /* Decreasing with age */
5664: double age, agelim, hf;
5665: double ***p3matp, ***p3matm, ***varhe;
5666: double **dnewm,**doldm;
5667: double *xp, *xm;
5668: double **gp, **gm;
5669: double ***gradg, ***trgradg;
5670: int theta;
5671:
5672: double eip, vip;
5673:
5674: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5675: xp=vector(1,npar);
5676: xm=vector(1,npar);
5677: dnewm=matrix(1,nlstate*nlstate,1,npar);
5678: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5679:
5680: pstamp(ficresstdeij);
5681: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5682: fprintf(ficresstdeij,"# Age");
5683: for(i=1; i<=nlstate;i++){
5684: for(j=1; j<=nlstate;j++)
5685: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5686: fprintf(ficresstdeij," e%1d. ",i);
5687: }
5688: fprintf(ficresstdeij,"\n");
5689:
5690: pstamp(ficrescveij);
5691: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5692: fprintf(ficrescveij,"# Age");
5693: for(i=1; i<=nlstate;i++)
5694: for(j=1; j<=nlstate;j++){
5695: cptj= (j-1)*nlstate+i;
5696: for(i2=1; i2<=nlstate;i2++)
5697: for(j2=1; j2<=nlstate;j2++){
5698: cptj2= (j2-1)*nlstate+i2;
5699: if(cptj2 <= cptj)
5700: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5701: }
5702: }
5703: fprintf(ficrescveij,"\n");
5704:
5705: if(estepm < stepm){
5706: printf ("Problem %d lower than %d\n",estepm, stepm);
5707: }
5708: else hstepm=estepm;
5709: /* We compute the life expectancy from trapezoids spaced every estepm months
5710: * This is mainly to measure the difference between two models: for example
5711: * if stepm=24 months pijx are given only every 2 years and by summing them
5712: * we are calculating an estimate of the Life Expectancy assuming a linear
5713: * progression in between and thus overestimating or underestimating according
5714: * to the curvature of the survival function. If, for the same date, we
5715: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5716: * to compare the new estimate of Life expectancy with the same linear
5717: * hypothesis. A more precise result, taking into account a more precise
5718: * curvature will be obtained if estepm is as small as stepm. */
5719:
5720: /* For example we decided to compute the life expectancy with the smallest unit */
5721: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5722: nhstepm is the number of hstepm from age to agelim
5723: nstepm is the number of stepm from age to agelin.
5724: Look at hpijx to understand the reason of that which relies in memory size
5725: and note for a fixed period like estepm months */
5726: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5727: survival function given by stepm (the optimization length). Unfortunately it
5728: means that if the survival funtion is printed only each two years of age and if
5729: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5730: results. So we changed our mind and took the option of the best precision.
5731: */
5732: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5733:
5734: /* If stepm=6 months */
5735: /* nhstepm age range expressed in number of stepm */
5736: agelim=AGESUP;
5737: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5738: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5739: /* if (stepm >= YEARM) hstepm=1;*/
5740: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5741:
5742: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5743: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5744: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5745: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5746: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5747: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5748:
5749: for (age=bage; age<=fage; age ++){
5750: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5751: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5752: /* if (stepm >= YEARM) hstepm=1;*/
5753: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5754:
1.126 brouard 5755: /* If stepm=6 months */
5756: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5757: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5758:
5759: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5760:
1.126 brouard 5761: /* Computing Variances of health expectancies */
5762: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5763: decrease memory allocation */
5764: for(theta=1; theta <=npar; theta++){
5765: for(i=1; i<=npar; i++){
1.222 brouard 5766: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5767: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5768: }
1.235 brouard 5769: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5770: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5771:
1.126 brouard 5772: for(j=1; j<= nlstate; j++){
1.222 brouard 5773: for(i=1; i<=nlstate; i++){
5774: for(h=0; h<=nhstepm-1; h++){
5775: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5776: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5777: }
5778: }
1.126 brouard 5779: }
1.218 brouard 5780:
1.126 brouard 5781: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5782: for(h=0; h<=nhstepm-1; h++){
5783: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5784: }
1.126 brouard 5785: }/* End theta */
5786:
5787:
5788: for(h=0; h<=nhstepm-1; h++)
5789: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5790: for(theta=1; theta <=npar; theta++)
5791: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5792:
1.218 brouard 5793:
1.222 brouard 5794: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5795: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5796: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5797:
1.222 brouard 5798: printf("%d|",(int)age);fflush(stdout);
5799: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5800: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5801: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5802: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5803: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5804: for(ij=1;ij<=nlstate*nlstate;ij++)
5805: for(ji=1;ji<=nlstate*nlstate;ji++)
5806: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5807: }
5808: }
1.218 brouard 5809:
1.126 brouard 5810: /* Computing expectancies */
1.235 brouard 5811: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5812: for(i=1; i<=nlstate;i++)
5813: for(j=1; j<=nlstate;j++)
1.222 brouard 5814: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5815: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5816:
1.222 brouard 5817: /* 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 5818:
1.222 brouard 5819: }
1.269 brouard 5820:
5821: /* Standard deviation of expectancies ij */
1.126 brouard 5822: fprintf(ficresstdeij,"%3.0f",age );
5823: for(i=1; i<=nlstate;i++){
5824: eip=0.;
5825: vip=0.;
5826: for(j=1; j<=nlstate;j++){
1.222 brouard 5827: eip += eij[i][j][(int)age];
5828: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5829: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5830: 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 5831: }
5832: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5833: }
5834: fprintf(ficresstdeij,"\n");
1.218 brouard 5835:
1.269 brouard 5836: /* Variance of expectancies ij */
1.126 brouard 5837: fprintf(ficrescveij,"%3.0f",age );
5838: for(i=1; i<=nlstate;i++)
5839: for(j=1; j<=nlstate;j++){
1.222 brouard 5840: cptj= (j-1)*nlstate+i;
5841: for(i2=1; i2<=nlstate;i2++)
5842: for(j2=1; j2<=nlstate;j2++){
5843: cptj2= (j2-1)*nlstate+i2;
5844: if(cptj2 <= cptj)
5845: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5846: }
1.126 brouard 5847: }
5848: fprintf(ficrescveij,"\n");
1.218 brouard 5849:
1.126 brouard 5850: }
5851: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5852: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5853: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5854: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5855: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5856: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5857: printf("\n");
5858: fprintf(ficlog,"\n");
1.218 brouard 5859:
1.126 brouard 5860: free_vector(xm,1,npar);
5861: free_vector(xp,1,npar);
5862: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5863: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5864: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5865: }
1.218 brouard 5866:
1.126 brouard 5867: /************ Variance ******************/
1.235 brouard 5868: 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 5869: {
1.279 brouard 5870: /** Variance of health expectancies
5871: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5872: * double **newm;
5873: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5874: */
1.218 brouard 5875:
5876: /* int movingaverage(); */
5877: double **dnewm,**doldm;
5878: double **dnewmp,**doldmp;
5879: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 5880: int first=0;
1.218 brouard 5881: int k;
5882: double *xp;
1.279 brouard 5883: double **gp, **gm; /**< for var eij */
5884: double ***gradg, ***trgradg; /**< for var eij */
5885: double **gradgp, **trgradgp; /**< for var p point j */
5886: double *gpp, *gmp; /**< for var p point j */
5887: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5888: double ***p3mat;
5889: double age,agelim, hf;
5890: /* double ***mobaverage; */
5891: int theta;
5892: char digit[4];
5893: char digitp[25];
5894:
5895: char fileresprobmorprev[FILENAMELENGTH];
5896:
5897: if(popbased==1){
5898: if(mobilav!=0)
5899: strcpy(digitp,"-POPULBASED-MOBILAV_");
5900: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5901: }
5902: else
5903: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5904:
1.218 brouard 5905: /* if (mobilav!=0) { */
5906: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5907: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5908: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5909: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5910: /* } */
5911: /* } */
5912:
5913: strcpy(fileresprobmorprev,"PRMORPREV-");
5914: sprintf(digit,"%-d",ij);
5915: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5916: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5917: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5918: strcat(fileresprobmorprev,fileresu);
5919: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5920: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5921: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5922: }
5923: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5924: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5925: pstamp(ficresprobmorprev);
5926: 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 5927: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5928: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5929: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5930: }
5931: for(j=1;j<=cptcoveff;j++)
5932: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5933: fprintf(ficresprobmorprev,"\n");
5934:
1.218 brouard 5935: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5936: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5937: fprintf(ficresprobmorprev," p.%-d SE",j);
5938: for(i=1; i<=nlstate;i++)
5939: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5940: }
5941: fprintf(ficresprobmorprev,"\n");
5942:
5943: fprintf(ficgp,"\n# Routine varevsij");
5944: fprintf(ficgp,"\nunset title \n");
5945: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5946: 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");
5947: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5948:
1.218 brouard 5949: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5950: pstamp(ficresvij);
5951: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5952: if(popbased==1)
5953: 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);
5954: else
5955: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5956: fprintf(ficresvij,"# Age");
5957: for(i=1; i<=nlstate;i++)
5958: for(j=1; j<=nlstate;j++)
5959: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5960: fprintf(ficresvij,"\n");
5961:
5962: xp=vector(1,npar);
5963: dnewm=matrix(1,nlstate,1,npar);
5964: doldm=matrix(1,nlstate,1,nlstate);
5965: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5966: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5967:
5968: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5969: gpp=vector(nlstate+1,nlstate+ndeath);
5970: gmp=vector(nlstate+1,nlstate+ndeath);
5971: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5972:
1.218 brouard 5973: if(estepm < stepm){
5974: printf ("Problem %d lower than %d\n",estepm, stepm);
5975: }
5976: else hstepm=estepm;
5977: /* For example we decided to compute the life expectancy with the smallest unit */
5978: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5979: nhstepm is the number of hstepm from age to agelim
5980: nstepm is the number of stepm from age to agelim.
5981: Look at function hpijx to understand why because of memory size limitations,
5982: we decided (b) to get a life expectancy respecting the most precise curvature of the
5983: survival function given by stepm (the optimization length). Unfortunately it
5984: means that if the survival funtion is printed every two years of age and if
5985: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5986: results. So we changed our mind and took the option of the best precision.
5987: */
5988: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5989: agelim = AGESUP;
5990: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5991: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5992: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5993: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5994: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5995: gp=matrix(0,nhstepm,1,nlstate);
5996: gm=matrix(0,nhstepm,1,nlstate);
5997:
5998:
5999: for(theta=1; theta <=npar; theta++){
6000: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6001: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6002: }
1.279 brouard 6003: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6004: * returns into prlim .
1.288 brouard 6005: */
1.242 brouard 6006: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6007:
6008: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6009: if (popbased==1) {
6010: if(mobilav ==0){
6011: for(i=1; i<=nlstate;i++)
6012: prlim[i][i]=probs[(int)age][i][ij];
6013: }else{ /* mobilav */
6014: for(i=1; i<=nlstate;i++)
6015: prlim[i][i]=mobaverage[(int)age][i][ij];
6016: }
6017: }
1.295 ! brouard 6018: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6019: */
6020: 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 6021: /**< 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 6022: * at horizon h in state j including mortality.
6023: */
1.218 brouard 6024: for(j=1; j<= nlstate; j++){
6025: for(h=0; h<=nhstepm; h++){
6026: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6027: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6028: }
6029: }
1.279 brouard 6030: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6031: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6032: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6033: */
6034: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6035: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6036: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6037: }
6038:
6039: /* Again with minus shift */
1.218 brouard 6040:
6041: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6042: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6043:
1.242 brouard 6044: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6045:
6046: if (popbased==1) {
6047: if(mobilav ==0){
6048: for(i=1; i<=nlstate;i++)
6049: prlim[i][i]=probs[(int)age][i][ij];
6050: }else{ /* mobilav */
6051: for(i=1; i<=nlstate;i++)
6052: prlim[i][i]=mobaverage[(int)age][i][ij];
6053: }
6054: }
6055:
1.235 brouard 6056: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6057:
6058: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6059: for(h=0; h<=nhstepm; h++){
6060: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6061: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6062: }
6063: }
6064: /* This for computing probability of death (h=1 means
6065: computed over hstepm matrices product = hstepm*stepm months)
6066: as a weighted average of prlim.
6067: */
6068: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6069: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6070: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6071: }
1.279 brouard 6072: /* end shifting computations */
6073:
6074: /**< Computing gradient matrix at horizon h
6075: */
1.218 brouard 6076: for(j=1; j<= nlstate; j++) /* vareij */
6077: for(h=0; h<=nhstepm; h++){
6078: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6079: }
1.279 brouard 6080: /**< Gradient of overall mortality p.3 (or p.j)
6081: */
6082: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6083: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6084: }
6085:
6086: } /* End theta */
1.279 brouard 6087:
6088: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6089: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6090:
6091: for(h=0; h<=nhstepm; h++) /* veij */
6092: for(j=1; j<=nlstate;j++)
6093: for(theta=1; theta <=npar; theta++)
6094: trgradg[h][j][theta]=gradg[h][theta][j];
6095:
6096: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6097: for(theta=1; theta <=npar; theta++)
6098: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6099: /**< as well as its transposed matrix
6100: */
1.218 brouard 6101:
6102: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6103: for(i=1;i<=nlstate;i++)
6104: for(j=1;j<=nlstate;j++)
6105: vareij[i][j][(int)age] =0.;
1.279 brouard 6106:
6107: /* Computing trgradg by matcov by gradg at age and summing over h
6108: * and k (nhstepm) formula 15 of article
6109: * Lievre-Brouard-Heathcote
6110: */
6111:
1.218 brouard 6112: for(h=0;h<=nhstepm;h++){
6113: for(k=0;k<=nhstepm;k++){
6114: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6115: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6116: for(i=1;i<=nlstate;i++)
6117: for(j=1;j<=nlstate;j++)
6118: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6119: }
6120: }
6121:
1.279 brouard 6122: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6123: * p.j overall mortality formula 49 but computed directly because
6124: * we compute the grad (wix pijx) instead of grad (pijx),even if
6125: * wix is independent of theta.
6126: */
1.218 brouard 6127: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6128: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6129: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6130: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6131: varppt[j][i]=doldmp[j][i];
6132: /* end ppptj */
6133: /* x centered again */
6134:
1.242 brouard 6135: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6136:
6137: if (popbased==1) {
6138: if(mobilav ==0){
6139: for(i=1; i<=nlstate;i++)
6140: prlim[i][i]=probs[(int)age][i][ij];
6141: }else{ /* mobilav */
6142: for(i=1; i<=nlstate;i++)
6143: prlim[i][i]=mobaverage[(int)age][i][ij];
6144: }
6145: }
6146:
6147: /* This for computing probability of death (h=1 means
6148: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6149: as a weighted average of prlim.
6150: */
1.235 brouard 6151: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6152: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6153: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6154: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6155: }
6156: /* end probability of death */
6157:
6158: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6159: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6160: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6161: for(i=1; i<=nlstate;i++){
6162: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6163: }
6164: }
6165: fprintf(ficresprobmorprev,"\n");
6166:
6167: fprintf(ficresvij,"%.0f ",age );
6168: for(i=1; i<=nlstate;i++)
6169: for(j=1; j<=nlstate;j++){
6170: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6171: }
6172: fprintf(ficresvij,"\n");
6173: free_matrix(gp,0,nhstepm,1,nlstate);
6174: free_matrix(gm,0,nhstepm,1,nlstate);
6175: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6176: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6177: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6178: } /* End age */
6179: free_vector(gpp,nlstate+1,nlstate+ndeath);
6180: free_vector(gmp,nlstate+1,nlstate+ndeath);
6181: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6182: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6183: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6184: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6185: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6186: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6187: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6188: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6189: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6190: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6191: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6192: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6193: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6194: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6195: 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);
6196: /* 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 6197: */
1.218 brouard 6198: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6199: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6200:
1.218 brouard 6201: free_vector(xp,1,npar);
6202: free_matrix(doldm,1,nlstate,1,nlstate);
6203: free_matrix(dnewm,1,nlstate,1,npar);
6204: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6205: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6206: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6207: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6208: fclose(ficresprobmorprev);
6209: fflush(ficgp);
6210: fflush(fichtm);
6211: } /* end varevsij */
1.126 brouard 6212:
6213: /************ Variance of prevlim ******************/
1.269 brouard 6214: 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 6215: {
1.205 brouard 6216: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6217: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6218:
1.268 brouard 6219: double **dnewmpar,**doldm;
1.126 brouard 6220: int i, j, nhstepm, hstepm;
6221: double *xp;
6222: double *gp, *gm;
6223: double **gradg, **trgradg;
1.208 brouard 6224: double **mgm, **mgp;
1.126 brouard 6225: double age,agelim;
6226: int theta;
6227:
6228: pstamp(ficresvpl);
1.288 brouard 6229: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6230: fprintf(ficresvpl,"# Age ");
6231: if(nresult >=1)
6232: fprintf(ficresvpl," Result# ");
1.126 brouard 6233: for(i=1; i<=nlstate;i++)
6234: fprintf(ficresvpl," %1d-%1d",i,i);
6235: fprintf(ficresvpl,"\n");
6236:
6237: xp=vector(1,npar);
1.268 brouard 6238: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6239: doldm=matrix(1,nlstate,1,nlstate);
6240:
6241: hstepm=1*YEARM; /* Every year of age */
6242: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6243: agelim = AGESUP;
6244: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6245: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6246: if (stepm >= YEARM) hstepm=1;
6247: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6248: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6249: mgp=matrix(1,npar,1,nlstate);
6250: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6251: gp=vector(1,nlstate);
6252: gm=vector(1,nlstate);
6253:
6254: for(theta=1; theta <=npar; theta++){
6255: for(i=1; i<=npar; i++){ /* Computes gradient */
6256: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6257: }
1.288 brouard 6258: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6259: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6260: /* else */
6261: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6262: for(i=1;i<=nlstate;i++){
1.126 brouard 6263: gp[i] = prlim[i][i];
1.208 brouard 6264: mgp[theta][i] = prlim[i][i];
6265: }
1.126 brouard 6266: for(i=1; i<=npar; i++) /* Computes gradient */
6267: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6268: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6269: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6270: /* else */
6271: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6272: for(i=1;i<=nlstate;i++){
1.126 brouard 6273: gm[i] = prlim[i][i];
1.208 brouard 6274: mgm[theta][i] = prlim[i][i];
6275: }
1.126 brouard 6276: for(i=1;i<=nlstate;i++)
6277: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6278: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6279: } /* End theta */
6280:
6281: trgradg =matrix(1,nlstate,1,npar);
6282:
6283: for(j=1; j<=nlstate;j++)
6284: for(theta=1; theta <=npar; theta++)
6285: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6286: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6287: /* printf("\nmgm mgp %d ",(int)age); */
6288: /* for(j=1; j<=nlstate;j++){ */
6289: /* printf(" %d ",j); */
6290: /* for(theta=1; theta <=npar; theta++) */
6291: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6292: /* printf("\n "); */
6293: /* } */
6294: /* } */
6295: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6296: /* printf("\n gradg %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 ",theta,gradg[theta][j]); */
6301: /* printf("\n "); */
6302: /* } */
6303: /* } */
1.126 brouard 6304:
6305: for(i=1;i<=nlstate;i++)
6306: varpl[i][(int)age] =0.;
1.209 brouard 6307: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6308: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6309: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6310: }else{
1.268 brouard 6311: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6312: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6313: }
1.126 brouard 6314: for(i=1;i<=nlstate;i++)
6315: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6316:
6317: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6318: if(nresult >=1)
6319: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6320: for(i=1; i<=nlstate;i++){
1.126 brouard 6321: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6322: /* for(j=1;j<=nlstate;j++) */
6323: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6324: }
1.126 brouard 6325: fprintf(ficresvpl,"\n");
6326: free_vector(gp,1,nlstate);
6327: free_vector(gm,1,nlstate);
1.208 brouard 6328: free_matrix(mgm,1,npar,1,nlstate);
6329: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6330: free_matrix(gradg,1,npar,1,nlstate);
6331: free_matrix(trgradg,1,nlstate,1,npar);
6332: } /* End age */
6333:
6334: free_vector(xp,1,npar);
6335: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6336: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6337:
6338: }
6339:
6340:
6341: /************ Variance of backprevalence limit ******************/
1.269 brouard 6342: 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 6343: {
6344: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6345: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6346:
6347: double **dnewmpar,**doldm;
6348: int i, j, nhstepm, hstepm;
6349: double *xp;
6350: double *gp, *gm;
6351: double **gradg, **trgradg;
6352: double **mgm, **mgp;
6353: double age,agelim;
6354: int theta;
6355:
6356: pstamp(ficresvbl);
6357: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6358: fprintf(ficresvbl,"# Age ");
6359: if(nresult >=1)
6360: fprintf(ficresvbl," Result# ");
6361: for(i=1; i<=nlstate;i++)
6362: fprintf(ficresvbl," %1d-%1d",i,i);
6363: fprintf(ficresvbl,"\n");
6364:
6365: xp=vector(1,npar);
6366: dnewmpar=matrix(1,nlstate,1,npar);
6367: doldm=matrix(1,nlstate,1,nlstate);
6368:
6369: hstepm=1*YEARM; /* Every year of age */
6370: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6371: agelim = AGEINF;
6372: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6373: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6374: if (stepm >= YEARM) hstepm=1;
6375: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6376: gradg=matrix(1,npar,1,nlstate);
6377: mgp=matrix(1,npar,1,nlstate);
6378: mgm=matrix(1,npar,1,nlstate);
6379: gp=vector(1,nlstate);
6380: gm=vector(1,nlstate);
6381:
6382: for(theta=1; theta <=npar; theta++){
6383: for(i=1; i<=npar; i++){ /* Computes gradient */
6384: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6385: }
6386: if(mobilavproj > 0 )
6387: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6388: else
6389: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6390: for(i=1;i<=nlstate;i++){
6391: gp[i] = bprlim[i][i];
6392: mgp[theta][i] = bprlim[i][i];
6393: }
6394: for(i=1; i<=npar; i++) /* Computes gradient */
6395: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6396: if(mobilavproj > 0 )
6397: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6398: else
6399: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6400: for(i=1;i<=nlstate;i++){
6401: gm[i] = bprlim[i][i];
6402: mgm[theta][i] = bprlim[i][i];
6403: }
6404: for(i=1;i<=nlstate;i++)
6405: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6406: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6407: } /* End theta */
6408:
6409: trgradg =matrix(1,nlstate,1,npar);
6410:
6411: for(j=1; j<=nlstate;j++)
6412: for(theta=1; theta <=npar; theta++)
6413: trgradg[j][theta]=gradg[theta][j];
6414: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6415: /* printf("\nmgm mgp %d ",(int)age); */
6416: /* for(j=1; j<=nlstate;j++){ */
6417: /* printf(" %d ",j); */
6418: /* for(theta=1; theta <=npar; theta++) */
6419: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6420: /* printf("\n "); */
6421: /* } */
6422: /* } */
6423: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6424: /* printf("\n gradg %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 ",theta,gradg[theta][j]); */
6429: /* printf("\n "); */
6430: /* } */
6431: /* } */
6432:
6433: for(i=1;i<=nlstate;i++)
6434: varbpl[i][(int)age] =0.;
6435: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6436: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6437: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6438: }else{
6439: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6440: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6441: }
6442: for(i=1;i<=nlstate;i++)
6443: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6444:
6445: fprintf(ficresvbl,"%.0f ",age );
6446: if(nresult >=1)
6447: fprintf(ficresvbl,"%d ",nres );
6448: for(i=1; i<=nlstate;i++)
6449: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6450: fprintf(ficresvbl,"\n");
6451: free_vector(gp,1,nlstate);
6452: free_vector(gm,1,nlstate);
6453: free_matrix(mgm,1,npar,1,nlstate);
6454: free_matrix(mgp,1,npar,1,nlstate);
6455: free_matrix(gradg,1,npar,1,nlstate);
6456: free_matrix(trgradg,1,nlstate,1,npar);
6457: } /* End age */
6458:
6459: free_vector(xp,1,npar);
6460: free_matrix(doldm,1,nlstate,1,npar);
6461: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6462:
6463: }
6464:
6465: /************ Variance of one-step probabilities ******************/
6466: 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 6467: {
6468: int i, j=0, k1, l1, tj;
6469: int k2, l2, j1, z1;
6470: int k=0, l;
6471: int first=1, first1, first2;
6472: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6473: double **dnewm,**doldm;
6474: double *xp;
6475: double *gp, *gm;
6476: double **gradg, **trgradg;
6477: double **mu;
6478: double age, cov[NCOVMAX+1];
6479: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6480: int theta;
6481: char fileresprob[FILENAMELENGTH];
6482: char fileresprobcov[FILENAMELENGTH];
6483: char fileresprobcor[FILENAMELENGTH];
6484: double ***varpij;
6485:
6486: strcpy(fileresprob,"PROB_");
6487: strcat(fileresprob,fileres);
6488: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6489: printf("Problem with resultfile: %s\n", fileresprob);
6490: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6491: }
6492: strcpy(fileresprobcov,"PROBCOV_");
6493: strcat(fileresprobcov,fileresu);
6494: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6495: printf("Problem with resultfile: %s\n", fileresprobcov);
6496: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6497: }
6498: strcpy(fileresprobcor,"PROBCOR_");
6499: strcat(fileresprobcor,fileresu);
6500: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6501: printf("Problem with resultfile: %s\n", fileresprobcor);
6502: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6503: }
6504: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6505: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6506: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6507: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6508: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6509: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6510: pstamp(ficresprob);
6511: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6512: fprintf(ficresprob,"# Age");
6513: pstamp(ficresprobcov);
6514: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6515: fprintf(ficresprobcov,"# Age");
6516: pstamp(ficresprobcor);
6517: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6518: fprintf(ficresprobcor,"# Age");
1.126 brouard 6519:
6520:
1.222 brouard 6521: for(i=1; i<=nlstate;i++)
6522: for(j=1; j<=(nlstate+ndeath);j++){
6523: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6524: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6525: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6526: }
6527: /* fprintf(ficresprob,"\n");
6528: fprintf(ficresprobcov,"\n");
6529: fprintf(ficresprobcor,"\n");
6530: */
6531: xp=vector(1,npar);
6532: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6533: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6534: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6535: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6536: first=1;
6537: fprintf(ficgp,"\n# Routine varprob");
6538: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6539: fprintf(fichtm,"\n");
6540:
1.288 brouard 6541: 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 6542: 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);
6543: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6544: and drawn. It helps understanding how is the covariance between two incidences.\
6545: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6546: 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 6547: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6548: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6549: standard deviations wide on each axis. <br>\
6550: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6551: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6552: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6553:
1.222 brouard 6554: cov[1]=1;
6555: /* tj=cptcoveff; */
1.225 brouard 6556: tj = (int) pow(2,cptcoveff);
1.222 brouard 6557: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6558: j1=0;
1.224 brouard 6559: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6560: if (cptcovn>0) {
6561: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6562: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6563: fprintf(ficresprob, "**********\n#\n");
6564: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6565: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6566: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6567:
1.222 brouard 6568: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6569: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6570: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6571:
6572:
1.222 brouard 6573: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6574: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6575: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6576:
1.222 brouard 6577: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6578: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6579: fprintf(ficresprobcor, "**********\n#");
6580: if(invalidvarcomb[j1]){
6581: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6582: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6583: continue;
6584: }
6585: }
6586: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6587: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6588: gp=vector(1,(nlstate)*(nlstate+ndeath));
6589: gm=vector(1,(nlstate)*(nlstate+ndeath));
6590: for (age=bage; age<=fage; age ++){
6591: cov[2]=age;
6592: if(nagesqr==1)
6593: cov[3]= age*age;
6594: for (k=1; k<=cptcovn;k++) {
6595: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6596: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6597: * 1 1 1 1 1
6598: * 2 2 1 1 1
6599: * 3 1 2 1 1
6600: */
6601: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6602: }
6603: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6604: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6605: for (k=1; k<=cptcovprod;k++)
6606: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6607:
6608:
1.222 brouard 6609: for(theta=1; theta <=npar; theta++){
6610: for(i=1; i<=npar; i++)
6611: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6612:
1.222 brouard 6613: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6614:
1.222 brouard 6615: k=0;
6616: for(i=1; i<= (nlstate); i++){
6617: for(j=1; j<=(nlstate+ndeath);j++){
6618: k=k+1;
6619: gp[k]=pmmij[i][j];
6620: }
6621: }
1.220 brouard 6622:
1.222 brouard 6623: for(i=1; i<=npar; i++)
6624: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6625:
1.222 brouard 6626: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6627: k=0;
6628: for(i=1; i<=(nlstate); i++){
6629: for(j=1; j<=(nlstate+ndeath);j++){
6630: k=k+1;
6631: gm[k]=pmmij[i][j];
6632: }
6633: }
1.220 brouard 6634:
1.222 brouard 6635: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6636: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6637: }
1.126 brouard 6638:
1.222 brouard 6639: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6640: for(theta=1; theta <=npar; theta++)
6641: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6642:
1.222 brouard 6643: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6644: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6645:
1.222 brouard 6646: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6647:
1.222 brouard 6648: k=0;
6649: for(i=1; i<=(nlstate); i++){
6650: for(j=1; j<=(nlstate+ndeath);j++){
6651: k=k+1;
6652: mu[k][(int) age]=pmmij[i][j];
6653: }
6654: }
6655: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6656: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6657: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6658:
1.222 brouard 6659: /*printf("\n%d ",(int)age);
6660: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6661: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6662: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6663: }*/
1.220 brouard 6664:
1.222 brouard 6665: fprintf(ficresprob,"\n%d ",(int)age);
6666: fprintf(ficresprobcov,"\n%d ",(int)age);
6667: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6668:
1.222 brouard 6669: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6670: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6671: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6672: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6673: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6674: }
6675: i=0;
6676: for (k=1; k<=(nlstate);k++){
6677: for (l=1; l<=(nlstate+ndeath);l++){
6678: i++;
6679: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6680: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6681: for (j=1; j<=i;j++){
6682: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6683: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6684: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6685: }
6686: }
6687: }/* end of loop for state */
6688: } /* end of loop for age */
6689: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6690: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6691: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6692: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6693:
6694: /* Confidence intervalle of pij */
6695: /*
6696: fprintf(ficgp,"\nunset parametric;unset label");
6697: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6698: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6699: 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);
6700: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6701: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6702: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6703: */
6704:
6705: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6706: first1=1;first2=2;
6707: for (k2=1; k2<=(nlstate);k2++){
6708: for (l2=1; l2<=(nlstate+ndeath);l2++){
6709: if(l2==k2) continue;
6710: j=(k2-1)*(nlstate+ndeath)+l2;
6711: for (k1=1; k1<=(nlstate);k1++){
6712: for (l1=1; l1<=(nlstate+ndeath);l1++){
6713: if(l1==k1) continue;
6714: i=(k1-1)*(nlstate+ndeath)+l1;
6715: if(i<=j) continue;
6716: for (age=bage; age<=fage; age ++){
6717: if ((int)age %5==0){
6718: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6719: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6720: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6721: mu1=mu[i][(int) age]/stepm*YEARM ;
6722: mu2=mu[j][(int) age]/stepm*YEARM;
6723: c12=cv12/sqrt(v1*v2);
6724: /* Computing eigen value of matrix of covariance */
6725: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6726: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6727: if ((lc2 <0) || (lc1 <0) ){
6728: if(first2==1){
6729: first1=0;
6730: 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);
6731: }
6732: 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);
6733: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6734: /* lc2=fabs(lc2); */
6735: }
1.220 brouard 6736:
1.222 brouard 6737: /* Eigen vectors */
1.280 brouard 6738: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6739: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6740: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6741: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6742: }else
6743: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6744: /*v21=sqrt(1.-v11*v11); *//* error */
6745: v21=(lc1-v1)/cv12*v11;
6746: v12=-v21;
6747: v22=v11;
6748: tnalp=v21/v11;
6749: if(first1==1){
6750: first1=0;
6751: 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);
6752: }
6753: 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);
6754: /*printf(fignu*/
6755: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6756: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6757: if(first==1){
6758: first=0;
6759: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6760: fprintf(ficgp,"\nset parametric;unset label");
6761: 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);
6762: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6763: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6764: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6765: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6766: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6767: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6768: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6769: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6770: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6771: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6772: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6773: 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 6774: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6775: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6776: }else{
6777: first=0;
6778: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6779: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6780: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6781: 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 6782: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6783: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6784: }/* if first */
6785: } /* age mod 5 */
6786: } /* end loop age */
6787: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6788: first=1;
6789: } /*l12 */
6790: } /* k12 */
6791: } /*l1 */
6792: }/* k1 */
6793: } /* loop on combination of covariates j1 */
6794: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6795: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6796: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6797: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6798: free_vector(xp,1,npar);
6799: fclose(ficresprob);
6800: fclose(ficresprobcov);
6801: fclose(ficresprobcor);
6802: fflush(ficgp);
6803: fflush(fichtmcov);
6804: }
1.126 brouard 6805:
6806:
6807: /******************* Printing html file ***********/
1.201 brouard 6808: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6809: int lastpass, int stepm, int weightopt, char model[],\
6810: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6811: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.273 brouard 6812: double jprev1, double mprev1,double anprev1, double dateprev1, double dateproj1, double dateback1, \
6813: double jprev2, double mprev2,double anprev2, double dateprev2, double dateproj2, double dateback2){
1.237 brouard 6814: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6815:
6816: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6817: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6818: </ul>");
1.237 brouard 6819: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6820: </ul>", model);
1.214 brouard 6821: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6822: 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",
6823: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6824: 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 6825: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6826: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6827: fprintf(fichtm,"\
6828: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6829: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6830: fprintf(fichtm,"\
1.217 brouard 6831: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6832: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6833: fprintf(fichtm,"\
1.288 brouard 6834: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6835: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6836: fprintf(fichtm,"\
1.288 brouard 6837: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6838: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6839: fprintf(fichtm,"\
1.211 brouard 6840: - (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 6841: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6842: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6843: if(prevfcast==1){
6844: fprintf(fichtm,"\
6845: - Prevalence projections by age and states: \
1.201 brouard 6846: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6847: }
1.126 brouard 6848:
6849:
1.225 brouard 6850: m=pow(2,cptcoveff);
1.222 brouard 6851: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6852:
1.264 brouard 6853: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6854:
6855: jj1=0;
6856:
6857: fprintf(fichtm," \n<ul>");
6858: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6859: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6860: if(m != 1 && TKresult[nres]!= k1)
6861: continue;
6862: jj1++;
6863: if (cptcovn > 0) {
6864: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6865: for (cpt=1; cpt<=cptcoveff;cpt++){
6866: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6867: }
6868: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6869: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6870: }
6871: fprintf(fichtm,"\">");
6872:
6873: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6874: fprintf(fichtm,"************ Results for covariates");
6875: for (cpt=1; cpt<=cptcoveff;cpt++){
6876: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6877: }
6878: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6879: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6880: }
6881: if(invalidvarcomb[k1]){
6882: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6883: continue;
6884: }
6885: fprintf(fichtm,"</a></li>");
6886: } /* cptcovn >0 */
6887: }
6888: fprintf(fichtm," \n</ul>");
6889:
1.222 brouard 6890: jj1=0;
1.237 brouard 6891:
6892: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6893: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6894: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6895: continue;
1.220 brouard 6896:
1.222 brouard 6897: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6898: jj1++;
6899: if (cptcovn > 0) {
1.264 brouard 6900: fprintf(fichtm,"\n<p><a name=\"rescov");
6901: for (cpt=1; cpt<=cptcoveff;cpt++){
6902: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6903: }
6904: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6905: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6906: }
6907: fprintf(fichtm,"\"</a>");
6908:
1.222 brouard 6909: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6910: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6911: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6912: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6913: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6914: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6915: }
1.237 brouard 6916: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6917: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6918: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6919: }
6920:
1.230 brouard 6921: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6922: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6923: if(invalidvarcomb[k1]){
6924: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6925: printf("\nCombination (%d) ignored because no cases \n",k1);
6926: continue;
6927: }
6928: }
6929: /* aij, bij */
1.259 brouard 6930: 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 6931: <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 6932: /* Pij */
1.241 brouard 6933: 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> \
6934: <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 6935: /* Quasi-incidences */
6936: 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 6937: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6938: 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 6939: 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> \
6940: <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 6941: /* Survival functions (period) in state j */
6942: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 6943: 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 6944: <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 6945: }
6946: /* State specific survival functions (period) */
6947: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 6948: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
6949: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 6950: <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 6951: }
1.288 brouard 6952: /* Period (forward stable) prevalence in each health state */
1.222 brouard 6953: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6954: 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> \
6955: <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 6956: }
6957: if(backcast==1){
1.288 brouard 6958: /* Backward prevalence in each health state */
1.222 brouard 6959: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6960: 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 6961: <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 6962: }
1.217 brouard 6963: }
1.222 brouard 6964: if(prevfcast==1){
1.288 brouard 6965: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 6966: for(cpt=1; cpt<=nlstate;cpt++){
1.288 brouard 6967: 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> \
1.273 brouard 6968: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, dateproj1, dateproj2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 6969: }
6970: }
1.268 brouard 6971: if(backcast==1){
6972: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6973: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6974: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6975: 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 \
6976: 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) \
6977: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6978: <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 6979: }
6980: }
1.220 brouard 6981:
1.222 brouard 6982: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6983: 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> \
6984: <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 6985: }
6986: /* } /\* end i1 *\/ */
6987: }/* End k1 */
6988: fprintf(fichtm,"</ul>");
1.126 brouard 6989:
1.222 brouard 6990: fprintf(fichtm,"\
1.126 brouard 6991: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6992: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6993: - 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 6994: But because parameters are usually highly correlated (a higher incidence of disability \
6995: and a higher incidence of recovery can give very close observed transition) it might \
6996: be very useful to look not only at linear confidence intervals estimated from the \
6997: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6998: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6999: covariance matrix of the one-step probabilities. \
7000: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7001:
1.222 brouard 7002: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7003: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7004: fprintf(fichtm,"\
1.126 brouard 7005: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7006: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7007:
1.222 brouard 7008: fprintf(fichtm,"\
1.126 brouard 7009: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7010: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7011: fprintf(fichtm,"\
1.126 brouard 7012: - 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): \
7013: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7014: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7015: fprintf(fichtm,"\
1.126 brouard 7016: - (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): \
7017: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7018: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7019: fprintf(fichtm,"\
1.288 brouard 7020: - 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 7021: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7022: fprintf(fichtm,"\
1.128 brouard 7023: - 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 7024: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7025: fprintf(fichtm,"\
1.288 brouard 7026: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7027: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7028:
7029: /* if(popforecast==1) fprintf(fichtm,"\n */
7030: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7031: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7032: /* <br>",fileres,fileres,fileres,fileres); */
7033: /* else */
7034: /* 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 7035: fflush(fichtm);
7036: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7037:
1.225 brouard 7038: m=pow(2,cptcoveff);
1.222 brouard 7039: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7040:
1.222 brouard 7041: jj1=0;
1.237 brouard 7042:
1.241 brouard 7043: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7044: for(k1=1; k1<=m;k1++){
1.253 brouard 7045: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7046: continue;
1.222 brouard 7047: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7048: jj1++;
1.126 brouard 7049: if (cptcovn > 0) {
7050: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7051: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7052: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7053: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7054: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7055: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7056: }
7057:
1.126 brouard 7058: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7059:
1.222 brouard 7060: if(invalidvarcomb[k1]){
7061: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7062: continue;
7063: }
1.126 brouard 7064: }
7065: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7066: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7067: 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 7068: <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 7069: }
7070: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7071: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7072: true period expectancies (those weighted with period prevalences are also\
7073: drawn in addition to the population based expectancies computed using\
1.241 brouard 7074: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7075: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7076: /* } /\* end i1 *\/ */
7077: }/* End k1 */
1.241 brouard 7078: }/* End nres */
1.222 brouard 7079: fprintf(fichtm,"</ul>");
7080: fflush(fichtm);
1.126 brouard 7081: }
7082:
7083: /******************* Gnuplot file **************/
1.270 brouard 7084: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double bage, double fage , int prevfcast, int backcast, char pathc[], double p[], int offyear, int offbyear){
1.126 brouard 7085:
7086: char dirfileres[132],optfileres[132];
1.264 brouard 7087: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7088: 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 7089: int lv=0, vlv=0, kl=0;
1.130 brouard 7090: int ng=0;
1.201 brouard 7091: int vpopbased;
1.223 brouard 7092: int ioffset; /* variable offset for columns */
1.270 brouard 7093: int iyearc=1; /* variable column for year of projection */
7094: int iagec=1; /* variable column for age of projection */
1.235 brouard 7095: int nres=0; /* Index of resultline */
1.266 brouard 7096: int istart=1; /* For starting graphs in projections */
1.219 brouard 7097:
1.126 brouard 7098: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7099: /* printf("Problem with file %s",optionfilegnuplot); */
7100: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7101: /* } */
7102:
7103: /*#ifdef windows */
7104: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7105: /*#endif */
1.225 brouard 7106: m=pow(2,cptcoveff);
1.126 brouard 7107:
1.274 brouard 7108: /* diagram of the model */
7109: fprintf(ficgp,"\n#Diagram of the model \n");
7110: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7111: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7112: 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);
7113:
7114: 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);
7115: fprintf(ficgp,"\n#show arrow\nunset label\n");
7116: 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);
7117: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7118: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7119: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7120: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7121:
1.202 brouard 7122: /* Contribution to likelihood */
7123: /* Plot the probability implied in the likelihood */
1.223 brouard 7124: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7125: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7126: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7127: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7128: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7129: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7130: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7131: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7132: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7133: 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));
7134: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7135: 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));
7136: for (i=1; i<= nlstate ; i ++) {
7137: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7138: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7139: 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);
7140: for (j=2; j<= nlstate+ndeath ; j ++) {
7141: 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);
7142: }
7143: fprintf(ficgp,";\nset out; unset ylabel;\n");
7144: }
7145: /* 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 */
7146: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7147: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7148: fprintf(ficgp,"\nset out;unset log\n");
7149: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7150:
1.126 brouard 7151: strcpy(dirfileres,optionfilefiname);
7152: strcpy(optfileres,"vpl");
1.223 brouard 7153: /* 1eme*/
1.238 brouard 7154: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7155: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7156: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7157: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7158: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7159: continue;
7160: /* We are interested in selected combination by the resultline */
1.246 brouard 7161: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7162: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7163: strcpy(gplotlabel,"(");
1.238 brouard 7164: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7165: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7166: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7167: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7168: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7169: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7170: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7171: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7172: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7173: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7174: }
7175: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7176: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7177: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7178: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7179: }
7180: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7181: /* printf("\n#\n"); */
1.238 brouard 7182: fprintf(ficgp,"\n#\n");
7183: if(invalidvarcomb[k1]){
1.260 brouard 7184: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7185: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7186: continue;
7187: }
1.235 brouard 7188:
1.241 brouard 7189: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7190: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7191: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7192: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7193: 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);
7194: /* 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); */
7195: /* k1-1 error should be nres-1*/
1.238 brouard 7196: for (i=1; i<= nlstate ; i ++) {
7197: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7198: else fprintf(ficgp," %%*lf (%%*lf)");
7199: }
1.288 brouard 7200: 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 7201: for (i=1; i<= nlstate ; i ++) {
7202: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7203: else fprintf(ficgp," %%*lf (%%*lf)");
7204: }
1.260 brouard 7205: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7206: for (i=1; i<= nlstate ; i ++) {
7207: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7208: else fprintf(ficgp," %%*lf (%%*lf)");
7209: }
1.265 brouard 7210: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7211:
7212: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7213: if(cptcoveff ==0){
1.271 brouard 7214: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7215: }else{
7216: kl=0;
7217: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7218: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7219: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7220: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7221: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7222: vlv= nbcode[Tvaraff[k]][lv];
7223: kl++;
7224: /* 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 *\/ */
7225: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7226: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7227: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7228: if(k==cptcoveff){
7229: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7230: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7231: }else{
7232: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7233: kl++;
7234: }
7235: } /* end covariate */
7236: } /* end if no covariate */
7237:
1.238 brouard 7238: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7239: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7240: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7241: if(cptcoveff ==0){
1.245 brouard 7242: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7243: }else{
7244: kl=0;
7245: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7246: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7247: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7248: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7249: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7250: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7251: kl++;
1.238 brouard 7252: /* 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 *\/ */
7253: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7254: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7255: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7256: if(k==cptcoveff){
1.245 brouard 7257: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7258: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7259: }else{
7260: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7261: kl++;
7262: }
7263: } /* end covariate */
7264: } /* end if no covariate */
1.268 brouard 7265: if(backcast == 1){
7266: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7267: /* k1-1 error should be nres-1*/
7268: for (i=1; i<= nlstate ; i ++) {
7269: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7270: else fprintf(ficgp," %%*lf (%%*lf)");
7271: }
1.271 brouard 7272: 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 7273: for (i=1; i<= nlstate ; i ++) {
7274: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7275: else fprintf(ficgp," %%*lf (%%*lf)");
7276: }
1.276 brouard 7277: 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 7278: for (i=1; i<= nlstate ; i ++) {
7279: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7280: else fprintf(ficgp," %%*lf (%%*lf)");
7281: }
1.274 brouard 7282: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7283: } /* end if backprojcast */
1.238 brouard 7284: } /* end if backcast */
1.276 brouard 7285: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7286: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7287: } /* nres */
1.201 brouard 7288: } /* k1 */
7289: } /* cpt */
1.235 brouard 7290:
7291:
1.126 brouard 7292: /*2 eme*/
1.238 brouard 7293: for (k1=1; k1<= m ; k1 ++){
7294: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7295: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7296: continue;
7297: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7298: strcpy(gplotlabel,"(");
1.238 brouard 7299: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7300: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7301: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7302: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7303: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7304: vlv= nbcode[Tvaraff[k]][lv];
7305: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7306: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7307: }
1.237 brouard 7308: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7309: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7310: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7311: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7312: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7313: }
1.264 brouard 7314: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7315: fprintf(ficgp,"\n#\n");
1.223 brouard 7316: if(invalidvarcomb[k1]){
7317: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7318: continue;
7319: }
1.219 brouard 7320:
1.241 brouard 7321: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7322: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7323: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7324: if(vpopbased==0){
1.238 brouard 7325: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7326: }else
1.238 brouard 7327: fprintf(ficgp,"\nreplot ");
7328: for (i=1; i<= nlstate+1 ; i ++) {
7329: k=2*i;
1.261 brouard 7330: 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 7331: for (j=1; j<= nlstate+1 ; j ++) {
7332: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7333: else fprintf(ficgp," %%*lf (%%*lf)");
7334: }
7335: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7336: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7337: 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 7338: for (j=1; j<= nlstate+1 ; j ++) {
7339: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7340: else fprintf(ficgp," %%*lf (%%*lf)");
7341: }
7342: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7343: 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 7344: for (j=1; j<= nlstate+1 ; j ++) {
7345: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7346: else fprintf(ficgp," %%*lf (%%*lf)");
7347: }
7348: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7349: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7350: } /* state */
7351: } /* vpopbased */
1.264 brouard 7352: 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 7353: } /* end nres */
7354: } /* k1 end 2 eme*/
7355:
7356:
7357: /*3eme*/
7358: for (k1=1; k1<= m ; k1 ++){
7359: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7360: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7361: continue;
7362:
7363: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7364: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7365: strcpy(gplotlabel,"(");
1.238 brouard 7366: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7367: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7368: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7369: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7370: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7371: vlv= nbcode[Tvaraff[k]][lv];
7372: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7373: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7374: }
7375: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7376: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7377: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7378: }
1.264 brouard 7379: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7380: fprintf(ficgp,"\n#\n");
7381: if(invalidvarcomb[k1]){
7382: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7383: continue;
7384: }
7385:
7386: /* k=2+nlstate*(2*cpt-2); */
7387: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7388: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7389: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7390: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7391: 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 7392: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7393: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7394: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7395: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7396: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7397: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7398:
1.238 brouard 7399: */
7400: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7401: 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 7402: /* 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 7403:
1.238 brouard 7404: }
1.261 brouard 7405: 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 7406: }
1.264 brouard 7407: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7408: } /* end nres */
7409: } /* end kl 3eme */
1.126 brouard 7410:
1.223 brouard 7411: /* 4eme */
1.201 brouard 7412: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7413: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7414: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7415: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7416: continue;
1.238 brouard 7417: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7418: strcpy(gplotlabel,"(");
1.238 brouard 7419: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7420: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7421: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7422: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7423: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7424: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7425: vlv= nbcode[Tvaraff[k]][lv];
7426: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7427: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7428: }
7429: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7430: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7431: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7432: }
1.264 brouard 7433: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7434: fprintf(ficgp,"\n#\n");
7435: if(invalidvarcomb[k1]){
7436: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7437: continue;
1.223 brouard 7438: }
1.238 brouard 7439:
1.241 brouard 7440: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7441: 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 7442: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7443: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7444: k=3;
7445: for (i=1; i<= nlstate ; i ++){
7446: if(i==1){
7447: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7448: }else{
7449: fprintf(ficgp,", '' ");
7450: }
7451: l=(nlstate+ndeath)*(i-1)+1;
7452: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7453: for (j=2; j<= nlstate+ndeath ; j ++)
7454: fprintf(ficgp,"+$%d",k+l+j-1);
7455: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7456: } /* nlstate */
1.264 brouard 7457: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7458: } /* end cpt state*/
7459: } /* end nres */
7460: } /* end covariate k1 */
7461:
1.220 brouard 7462: /* 5eme */
1.201 brouard 7463: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7464: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7465: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7466: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7467: continue;
1.238 brouard 7468: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7469: strcpy(gplotlabel,"(");
1.238 brouard 7470: 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);
7471: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7472: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7473: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7474: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7475: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7476: vlv= nbcode[Tvaraff[k]][lv];
7477: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7478: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7479: }
7480: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7481: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7482: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7483: }
1.264 brouard 7484: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7485: fprintf(ficgp,"\n#\n");
7486: if(invalidvarcomb[k1]){
7487: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7488: continue;
7489: }
1.227 brouard 7490:
1.241 brouard 7491: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7492: 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 7493: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7494: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7495: k=3;
7496: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7497: if(j==1)
7498: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7499: else
7500: fprintf(ficgp,", '' ");
7501: l=(nlstate+ndeath)*(cpt-1) +j;
7502: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7503: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7504: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7505: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7506: } /* nlstate */
7507: fprintf(ficgp,", '' ");
7508: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7509: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7510: l=(nlstate+ndeath)*(cpt-1) +j;
7511: if(j < nlstate)
7512: fprintf(ficgp,"$%d +",k+l);
7513: else
7514: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7515: }
1.264 brouard 7516: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7517: } /* end cpt state*/
7518: } /* end covariate */
7519: } /* end nres */
1.227 brouard 7520:
1.220 brouard 7521: /* 6eme */
1.202 brouard 7522: /* CV preval stable (period) for each covariate */
1.237 brouard 7523: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7524: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7525: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7526: continue;
1.255 brouard 7527: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7528: strcpy(gplotlabel,"(");
1.288 brouard 7529: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7530: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7531: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7532: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7533: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7534: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7535: vlv= nbcode[Tvaraff[k]][lv];
7536: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7537: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7538: }
1.237 brouard 7539: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7540: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7541: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7542: }
1.264 brouard 7543: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7544: fprintf(ficgp,"\n#\n");
1.223 brouard 7545: if(invalidvarcomb[k1]){
1.227 brouard 7546: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7547: continue;
1.223 brouard 7548: }
1.227 brouard 7549:
1.241 brouard 7550: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7551: 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 7552: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7553: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7554: k=3; /* Offset */
1.255 brouard 7555: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7556: if(i==1)
7557: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7558: else
7559: fprintf(ficgp,", '' ");
1.255 brouard 7560: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7561: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7562: for (j=2; j<= nlstate ; j ++)
7563: fprintf(ficgp,"+$%d",k+l+j-1);
7564: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7565: } /* nlstate */
1.264 brouard 7566: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7567: } /* end cpt state*/
7568: } /* end covariate */
1.227 brouard 7569:
7570:
1.220 brouard 7571: /* 7eme */
1.218 brouard 7572: if(backcast == 1){
1.288 brouard 7573: /* CV backward prevalence for each covariate */
1.237 brouard 7574: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7575: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7576: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7577: continue;
1.268 brouard 7578: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7579: strcpy(gplotlabel,"(");
1.288 brouard 7580: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7581: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7582: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7583: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7584: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7585: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7586: vlv= nbcode[Tvaraff[k]][lv];
7587: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7588: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7589: }
1.237 brouard 7590: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7591: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7592: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7593: }
1.264 brouard 7594: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7595: fprintf(ficgp,"\n#\n");
7596: if(invalidvarcomb[k1]){
7597: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7598: continue;
7599: }
7600:
1.241 brouard 7601: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7602: 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 7603: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7604: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7605: k=3; /* Offset */
1.268 brouard 7606: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7607: if(i==1)
7608: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7609: else
7610: fprintf(ficgp,", '' ");
7611: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7612: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7613: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7614: /* 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 7615: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7616: /* for (j=2; j<= nlstate ; j ++) */
7617: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7618: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7619: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7620: } /* nlstate */
1.264 brouard 7621: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7622: } /* end cpt state*/
7623: } /* end covariate */
7624: } /* End if backcast */
7625:
1.223 brouard 7626: /* 8eme */
1.218 brouard 7627: if(prevfcast==1){
1.288 brouard 7628: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7629:
1.237 brouard 7630: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7631: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7632: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7633: continue;
1.211 brouard 7634: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7635: strcpy(gplotlabel,"(");
1.288 brouard 7636: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7637: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7638: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7639: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7640: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7641: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7642: vlv= nbcode[Tvaraff[k]][lv];
7643: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7644: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7645: }
1.237 brouard 7646: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7647: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7648: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7649: }
1.264 brouard 7650: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7651: fprintf(ficgp,"\n#\n");
7652: if(invalidvarcomb[k1]){
7653: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7654: continue;
7655: }
7656:
7657: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7658: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7659: 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 7660: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7661: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7662:
7663: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7664: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7665: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7666: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7667: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7668: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7669: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7670: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7671: if(i==istart){
1.227 brouard 7672: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7673: }else{
7674: fprintf(ficgp,",\\\n '' ");
7675: }
7676: if(cptcoveff ==0){ /* No covariate */
7677: ioffset=2; /* Age is in 2 */
7678: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7679: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7680: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7681: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7682: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7683: if(i==nlstate+1){
1.270 brouard 7684: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7685: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7686: fprintf(ficgp,",\\\n '' ");
7687: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7688: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7689: offyear, \
1.268 brouard 7690: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7691: }else
1.227 brouard 7692: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7693: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7694: }else{ /* more than 2 covariates */
1.270 brouard 7695: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7696: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7697: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7698: iyearc=ioffset-1;
7699: iagec=ioffset;
1.227 brouard 7700: fprintf(ficgp," u %d:(",ioffset);
7701: kl=0;
7702: strcpy(gplotcondition,"(");
7703: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7704: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7705: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7706: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7707: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7708: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7709: kl++;
7710: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7711: kl++;
7712: if(k <cptcoveff && cptcoveff>1)
7713: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7714: }
7715: strcpy(gplotcondition+strlen(gplotcondition),")");
7716: /* 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 *\/ */
7717: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7718: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7719: /* '' 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*/
7720: if(i==nlstate+1){
1.270 brouard 7721: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7722: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7723: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7724: fprintf(ficgp," u %d:(",iagec);
7725: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7726: iyearc, iagec, offyear, \
7727: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7728: /* '' 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 7729: }else{
7730: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7731: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7732: }
7733: } /* end if covariate */
7734: } /* nlstate */
1.264 brouard 7735: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7736: } /* end cpt state*/
7737: } /* end covariate */
7738: } /* End if prevfcast */
1.227 brouard 7739:
1.268 brouard 7740: if(backcast==1){
7741: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7742:
7743: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7744: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7745: if(m != 1 && TKresult[nres]!= k1)
7746: continue;
7747: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7748: strcpy(gplotlabel,"(");
7749: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7750: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7751: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7752: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7753: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7754: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7755: vlv= nbcode[Tvaraff[k]][lv];
7756: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7757: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7758: }
7759: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7760: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7761: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7762: }
7763: strcpy(gplotlabel+strlen(gplotlabel),")");
7764: fprintf(ficgp,"\n#\n");
7765: if(invalidvarcomb[k1]){
7766: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7767: continue;
7768: }
7769:
7770: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7771: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7772: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7773: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7774: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7775:
7776: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7777: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7778: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7779: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7780: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7781: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7782: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7783: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7784: if(i==istart){
7785: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7786: }else{
7787: fprintf(ficgp,",\\\n '' ");
7788: }
7789: if(cptcoveff ==0){ /* No covariate */
7790: ioffset=2; /* Age is in 2 */
7791: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7792: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7793: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7794: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7795: fprintf(ficgp," u %d:(", ioffset);
7796: if(i==nlstate+1){
1.270 brouard 7797: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7798: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7799: fprintf(ficgp,",\\\n '' ");
7800: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7801: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7802: offbyear, \
7803: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7804: }else
7805: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7806: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7807: }else{ /* more than 2 covariates */
1.270 brouard 7808: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7809: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7810: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7811: iyearc=ioffset-1;
7812: iagec=ioffset;
1.268 brouard 7813: fprintf(ficgp," u %d:(",ioffset);
7814: kl=0;
7815: strcpy(gplotcondition,"(");
7816: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7817: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7818: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7819: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7820: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7821: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7822: kl++;
7823: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7824: kl++;
7825: if(k <cptcoveff && cptcoveff>1)
7826: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7827: }
7828: strcpy(gplotcondition+strlen(gplotcondition),")");
7829: /* 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 *\/ */
7830: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7831: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7832: /* '' 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*/
7833: if(i==nlstate+1){
1.270 brouard 7834: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7835: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7836: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7837: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7838: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7839: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7840: iyearc,iagec,offbyear, \
7841: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7842: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7843: }else{
7844: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7845: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7846: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7847: }
7848: } /* end if covariate */
7849: } /* nlstate */
7850: fprintf(ficgp,"\nset out; unset label;\n");
7851: } /* end cpt state*/
7852: } /* end covariate */
7853: } /* End if backcast */
7854:
1.227 brouard 7855:
1.238 brouard 7856: /* 9eme writing MLE parameters */
7857: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7858: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7859: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7860: for(k=1; k <=(nlstate+ndeath); k++){
7861: if (k != i) {
1.227 brouard 7862: fprintf(ficgp,"# current state %d\n",k);
7863: for(j=1; j <=ncovmodel; j++){
7864: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7865: jk++;
7866: }
7867: fprintf(ficgp,"\n");
1.126 brouard 7868: }
7869: }
1.223 brouard 7870: }
1.187 brouard 7871: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7872:
1.145 brouard 7873: /*goto avoid;*/
1.238 brouard 7874: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7875: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7876: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7877: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7878: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7879: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7880: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7881: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7882: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7883: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7884: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7885: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7886: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7887: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7888: fprintf(ficgp,"#\n");
1.223 brouard 7889: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7890: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7891: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7892: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7893: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7894: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7895: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7896: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7897: continue;
1.264 brouard 7898: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7899: strcpy(gplotlabel,"(");
1.276 brouard 7900: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7901: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7902: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7903: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7904: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7905: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7906: vlv= nbcode[Tvaraff[k]][lv];
7907: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7908: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7909: }
1.237 brouard 7910: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7911: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7912: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7913: }
1.264 brouard 7914: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7915: fprintf(ficgp,"\n#\n");
1.264 brouard 7916: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7917: fprintf(ficgp,"\nset key outside ");
7918: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7919: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7920: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7921: if (ng==1){
7922: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7923: fprintf(ficgp,"\nunset log y");
7924: }else if (ng==2){
7925: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7926: fprintf(ficgp,"\nset log y");
7927: }else if (ng==3){
7928: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7929: fprintf(ficgp,"\nset log y");
7930: }else
7931: fprintf(ficgp,"\nunset title ");
7932: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7933: i=1;
7934: for(k2=1; k2<=nlstate; k2++) {
7935: k3=i;
7936: for(k=1; k<=(nlstate+ndeath); k++) {
7937: if (k != k2){
7938: switch( ng) {
7939: case 1:
7940: if(nagesqr==0)
7941: fprintf(ficgp," p%d+p%d*x",i,i+1);
7942: else /* nagesqr =1 */
7943: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7944: break;
7945: case 2: /* ng=2 */
7946: if(nagesqr==0)
7947: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7948: else /* nagesqr =1 */
7949: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7950: break;
7951: case 3:
7952: if(nagesqr==0)
7953: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7954: else /* nagesqr =1 */
7955: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7956: break;
7957: }
7958: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7959: ijp=1; /* product no age */
7960: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7961: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7962: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7963: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7964: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7965: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7966: if(DummyV[j]==0){
7967: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7968: }else{ /* quantitative */
7969: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7970: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7971: }
7972: ij++;
1.237 brouard 7973: }
1.268 brouard 7974: }
7975: }else if(cptcovprod >0){
7976: if(j==Tprod[ijp]) { /* */
7977: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7978: if(ijp <=cptcovprod) { /* Product */
7979: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7980: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7981: /* 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)]); */
7982: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7983: }else{ /* Vn is dummy and Vm is quanti */
7984: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7985: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7986: }
7987: }else{ /* Vn*Vm Vn is quanti */
7988: if(DummyV[Tvard[ijp][2]]==0){
7989: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7990: }else{ /* Both quanti */
7991: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7992: }
1.237 brouard 7993: }
1.268 brouard 7994: ijp++;
1.237 brouard 7995: }
1.268 brouard 7996: } /* end Tprod */
1.237 brouard 7997: } else{ /* simple covariate */
1.264 brouard 7998: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7999: if(Dummy[j]==0){
8000: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8001: }else{ /* quantitative */
8002: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8003: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8004: }
1.237 brouard 8005: } /* end simple */
8006: } /* end j */
1.223 brouard 8007: }else{
8008: i=i-ncovmodel;
8009: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8010: fprintf(ficgp," (1.");
8011: }
1.227 brouard 8012:
1.223 brouard 8013: if(ng != 1){
8014: fprintf(ficgp,")/(1");
1.227 brouard 8015:
1.264 brouard 8016: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8017: if(nagesqr==0)
1.264 brouard 8018: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8019: else /* nagesqr =1 */
1.264 brouard 8020: 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 8021:
1.223 brouard 8022: ij=1;
8023: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8024: if(cptcovage >0){
8025: if((j-2)==Tage[ij]) { /* Bug valgrind */
8026: if(ij <=cptcovage) { /* Bug valgrind */
8027: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8028: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8029: ij++;
8030: }
8031: }
8032: }else
8033: 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 8034: }
8035: fprintf(ficgp,")");
8036: }
8037: fprintf(ficgp,")");
8038: if(ng ==2)
1.276 brouard 8039: 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 8040: else /* ng= 3 */
1.276 brouard 8041: 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 8042: }else{ /* end ng <> 1 */
8043: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8044: 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 8045: }
8046: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8047: fprintf(ficgp,",");
8048: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8049: fprintf(ficgp,",");
8050: i=i+ncovmodel;
8051: } /* end k */
8052: } /* end k2 */
1.276 brouard 8053: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8054: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8055: } /* end k1 */
1.223 brouard 8056: } /* end ng */
8057: /* avoid: */
8058: fflush(ficgp);
1.126 brouard 8059: } /* end gnuplot */
8060:
8061:
8062: /*************** Moving average **************/
1.219 brouard 8063: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8064: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8065:
1.222 brouard 8066: int i, cpt, cptcod;
8067: int modcovmax =1;
8068: int mobilavrange, mob;
8069: int iage=0;
1.288 brouard 8070: int firstA1=0, firstA2=0;
1.222 brouard 8071:
1.266 brouard 8072: double sum=0., sumr=0.;
1.222 brouard 8073: double age;
1.266 brouard 8074: double *sumnewp, *sumnewm, *sumnewmr;
8075: double *agemingood, *agemaxgood;
8076: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8077:
8078:
1.278 brouard 8079: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8080: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8081:
8082: sumnewp = vector(1,ncovcombmax);
8083: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8084: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8085: agemingood = vector(1,ncovcombmax);
1.266 brouard 8086: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8087: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8088: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8089:
8090: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8091: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8092: sumnewp[cptcod]=0.;
1.266 brouard 8093: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8094: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8095: }
8096: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8097:
1.266 brouard 8098: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8099: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8100: else mobilavrange=mobilav;
8101: for (age=bage; age<=fage; age++)
8102: for (i=1; i<=nlstate;i++)
8103: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8104: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8105: /* We keep the original values on the extreme ages bage, fage and for
8106: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8107: we use a 5 terms etc. until the borders are no more concerned.
8108: */
8109: for (mob=3;mob <=mobilavrange;mob=mob+2){
8110: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8111: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8112: sumnewm[cptcod]=0.;
8113: for (i=1; i<=nlstate;i++){
1.222 brouard 8114: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8115: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8116: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8117: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8118: }
8119: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8120: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8121: } /* end i */
8122: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8123: } /* end cptcod */
1.222 brouard 8124: }/* end age */
8125: }/* end mob */
1.266 brouard 8126: }else{
8127: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8128: return -1;
1.266 brouard 8129: }
8130:
8131: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8132: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8133: if(invalidvarcomb[cptcod]){
8134: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8135: continue;
8136: }
1.219 brouard 8137:
1.266 brouard 8138: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8139: sumnewm[cptcod]=0.;
8140: sumnewmr[cptcod]=0.;
8141: for (i=1; i<=nlstate;i++){
8142: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8143: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8144: }
8145: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8146: agemingoodr[cptcod]=age;
8147: }
8148: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8149: agemingood[cptcod]=age;
8150: }
8151: } /* age */
8152: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8153: sumnewm[cptcod]=0.;
1.266 brouard 8154: sumnewmr[cptcod]=0.;
1.222 brouard 8155: for (i=1; i<=nlstate;i++){
8156: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8157: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8158: }
8159: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8160: agemaxgoodr[cptcod]=age;
1.222 brouard 8161: }
8162: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8163: agemaxgood[cptcod]=age;
8164: }
8165: } /* age */
8166: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8167: /* but they will change */
1.288 brouard 8168: firstA1=0;firstA2=0;
1.266 brouard 8169: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8170: sumnewm[cptcod]=0.;
8171: sumnewmr[cptcod]=0.;
8172: for (i=1; i<=nlstate;i++){
8173: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8174: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8175: }
8176: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8177: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8178: agemaxgoodr[cptcod]=age; /* age min */
8179: for (i=1; i<=nlstate;i++)
8180: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8181: }else{ /* bad we change the value with the values of good ages */
8182: for (i=1; i<=nlstate;i++){
8183: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8184: } /* i */
8185: } /* end bad */
8186: }else{
8187: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8188: agemaxgood[cptcod]=age;
8189: }else{ /* bad we change the value with the values of good ages */
8190: for (i=1; i<=nlstate;i++){
8191: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8192: } /* i */
8193: } /* end bad */
8194: }/* end else */
8195: sum=0.;sumr=0.;
8196: for (i=1; i<=nlstate;i++){
8197: sum+=mobaverage[(int)age][i][cptcod];
8198: sumr+=probs[(int)age][i][cptcod];
8199: }
8200: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8201: if(!firstA1){
8202: firstA1=1;
8203: 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);
8204: }
8205: 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 8206: } /* end bad */
8207: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8208: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8209: if(!firstA2){
8210: firstA2=1;
8211: 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);
8212: }
8213: 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 8214: } /* end bad */
8215: }/* age */
1.266 brouard 8216:
8217: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8218: sumnewm[cptcod]=0.;
1.266 brouard 8219: sumnewmr[cptcod]=0.;
1.222 brouard 8220: for (i=1; i<=nlstate;i++){
8221: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8222: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8223: }
8224: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8225: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8226: agemingoodr[cptcod]=age;
8227: for (i=1; i<=nlstate;i++)
8228: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8229: }else{ /* bad we change the value with the values of good ages */
8230: for (i=1; i<=nlstate;i++){
8231: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8232: } /* i */
8233: } /* end bad */
8234: }else{
8235: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8236: agemingood[cptcod]=age;
8237: }else{ /* bad */
8238: for (i=1; i<=nlstate;i++){
8239: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8240: } /* i */
8241: } /* end bad */
8242: }/* end else */
8243: sum=0.;sumr=0.;
8244: for (i=1; i<=nlstate;i++){
8245: sum+=mobaverage[(int)age][i][cptcod];
8246: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8247: }
1.266 brouard 8248: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8249: 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 8250: } /* end bad */
8251: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8252: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8253: 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 8254: } /* end bad */
8255: }/* age */
1.266 brouard 8256:
1.222 brouard 8257:
8258: for (age=bage; age<=fage; age++){
1.235 brouard 8259: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8260: sumnewp[cptcod]=0.;
8261: sumnewm[cptcod]=0.;
8262: for (i=1; i<=nlstate;i++){
8263: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8264: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8265: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8266: }
8267: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8268: }
8269: /* printf("\n"); */
8270: /* } */
1.266 brouard 8271:
1.222 brouard 8272: /* brutal averaging */
1.266 brouard 8273: /* for (i=1; i<=nlstate;i++){ */
8274: /* for (age=1; age<=bage; age++){ */
8275: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8276: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8277: /* } */
8278: /* for (age=fage; age<=AGESUP; age++){ */
8279: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8280: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8281: /* } */
8282: /* } /\* end i status *\/ */
8283: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8284: /* for (age=1; age<=AGESUP; age++){ */
8285: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8286: /* mobaverage[(int)age][i][cptcod]=0.; */
8287: /* } */
8288: /* } */
1.222 brouard 8289: }/* end cptcod */
1.266 brouard 8290: free_vector(agemaxgoodr,1, ncovcombmax);
8291: free_vector(agemaxgood,1, ncovcombmax);
8292: free_vector(agemingood,1, ncovcombmax);
8293: free_vector(agemingoodr,1, ncovcombmax);
8294: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8295: free_vector(sumnewm,1, ncovcombmax);
8296: free_vector(sumnewp,1, ncovcombmax);
8297: return 0;
8298: }/* End movingaverage */
1.218 brouard 8299:
1.126 brouard 8300:
8301: /************** Forecasting ******************/
1.269 brouard 8302: void prevforecast(char fileres[], double anproj1, double mproj1, double jproj1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double anproj2, double p[], int cptcoveff){
1.126 brouard 8303: /* proj1, year, month, day of starting projection
8304: agemin, agemax range of age
8305: dateprev1 dateprev2 range of dates during which prevalence is computed
8306: anproj2 year of en of projection (same day and month as proj1).
8307: */
1.267 brouard 8308: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8309: double agec; /* generic age */
8310: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8311: double *popeffectif,*popcount;
8312: double ***p3mat;
1.218 brouard 8313: /* double ***mobaverage; */
1.126 brouard 8314: char fileresf[FILENAMELENGTH];
8315:
8316: agelim=AGESUP;
1.211 brouard 8317: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8318: in each health status at the date of interview (if between dateprev1 and dateprev2).
8319: We still use firstpass and lastpass as another selection.
8320: */
1.214 brouard 8321: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8322: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8323:
1.201 brouard 8324: strcpy(fileresf,"F_");
8325: strcat(fileresf,fileresu);
1.126 brouard 8326: if((ficresf=fopen(fileresf,"w"))==NULL) {
8327: printf("Problem with forecast resultfile: %s\n", fileresf);
8328: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8329: }
1.235 brouard 8330: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8331: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8332:
1.225 brouard 8333: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8334:
8335:
8336: stepsize=(int) (stepm+YEARM-1)/YEARM;
8337: if (stepm<=12) stepsize=1;
8338: if(estepm < stepm){
8339: printf ("Problem %d lower than %d\n",estepm, stepm);
8340: }
1.270 brouard 8341: else{
8342: hstepm=estepm;
8343: }
8344: if(estepm > stepm){ /* Yes every two year */
8345: stepsize=2;
8346: }
1.126 brouard 8347:
8348: hstepm=hstepm/stepm;
8349: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8350: fractional in yp1 */
8351: anprojmean=yp;
8352: yp2=modf((yp1*12),&yp);
8353: mprojmean=yp;
8354: yp1=modf((yp2*30.5),&yp);
8355: jprojmean=yp;
8356: if(jprojmean==0) jprojmean=1;
8357: if(mprojmean==0) jprojmean=1;
8358:
1.227 brouard 8359: i1=pow(2,cptcoveff);
1.126 brouard 8360: if (cptcovn < 1){i1=1;}
8361:
8362: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8363:
8364: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8365:
1.126 brouard 8366: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8367: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8368: for(k=1; k<=i1;k++){
1.253 brouard 8369: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8370: continue;
1.227 brouard 8371: if(invalidvarcomb[k]){
8372: printf("\nCombination (%d) projection ignored because no cases \n",k);
8373: continue;
8374: }
8375: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8376: for(j=1;j<=cptcoveff;j++) {
8377: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8378: }
1.235 brouard 8379: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8380: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8381: }
1.227 brouard 8382: fprintf(ficresf," yearproj age");
8383: for(j=1; j<=nlstate+ndeath;j++){
8384: for(i=1; i<=nlstate;i++)
8385: fprintf(ficresf," p%d%d",i,j);
8386: fprintf(ficresf," wp.%d",j);
8387: }
8388: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8389: fprintf(ficresf,"\n");
8390: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8391: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8392: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8393: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8394: nhstepm = nhstepm/hstepm;
8395: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8396: oldm=oldms;savm=savms;
1.268 brouard 8397: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8398: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8399: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8400: for (h=0; h<=nhstepm; h++){
8401: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8402: break;
8403: }
8404: }
8405: fprintf(ficresf,"\n");
8406: for(j=1;j<=cptcoveff;j++)
8407: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8408: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8409:
8410: for(j=1; j<=nlstate+ndeath;j++) {
8411: ppij=0.;
8412: for(i=1; i<=nlstate;i++) {
1.278 brouard 8413: if (mobilav>=1)
8414: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8415: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8416: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8417: }
1.268 brouard 8418: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8419: } /* end i */
8420: fprintf(ficresf," %.3f", ppij);
8421: }/* end j */
1.227 brouard 8422: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8423: } /* end agec */
1.266 brouard 8424: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8425: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8426: } /* end yearp */
8427: } /* end k */
1.219 brouard 8428:
1.126 brouard 8429: fclose(ficresf);
1.215 brouard 8430: printf("End of Computing forecasting \n");
8431: fprintf(ficlog,"End of Computing forecasting\n");
8432:
1.126 brouard 8433: }
8434:
1.269 brouard 8435: /************** Back Forecasting ******************/
8436: 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){
1.267 brouard 8437: /* back1, year, month, day of starting backection
8438: agemin, agemax range of age
8439: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8440: anback2 year of end of backprojection (same day and month as back1).
8441: prevacurrent and prev are prevalences.
1.267 brouard 8442: */
8443: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8444: double agec; /* generic age */
1.268 brouard 8445: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8446: double *popeffectif,*popcount;
8447: double ***p3mat;
8448: /* double ***mobaverage; */
8449: char fileresfb[FILENAMELENGTH];
8450:
1.268 brouard 8451: agelim=AGEINF;
1.267 brouard 8452: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8453: in each health status at the date of interview (if between dateprev1 and dateprev2).
8454: We still use firstpass and lastpass as another selection.
8455: */
8456: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8457: /* firstpass, lastpass, stepm, weightopt, model); */
8458:
8459: /*Do we need to compute prevalence again?*/
8460:
8461: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8462:
8463: strcpy(fileresfb,"FB_");
8464: strcat(fileresfb,fileresu);
8465: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8466: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8467: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8468: }
8469: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8470: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8471:
8472: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8473:
8474:
8475: stepsize=(int) (stepm+YEARM-1)/YEARM;
8476: if (stepm<=12) stepsize=1;
8477: if(estepm < stepm){
8478: printf ("Problem %d lower than %d\n",estepm, stepm);
8479: }
1.270 brouard 8480: else{
8481: hstepm=estepm;
8482: }
8483: if(estepm >= stepm){ /* Yes every two year */
8484: stepsize=2;
8485: }
1.267 brouard 8486:
8487: hstepm=hstepm/stepm;
8488: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8489: fractional in yp1 */
8490: anprojmean=yp;
8491: yp2=modf((yp1*12),&yp);
8492: mprojmean=yp;
8493: yp1=modf((yp2*30.5),&yp);
8494: jprojmean=yp;
8495: if(jprojmean==0) jprojmean=1;
8496: if(mprojmean==0) jprojmean=1;
8497:
8498: i1=pow(2,cptcoveff);
8499: if (cptcovn < 1){i1=1;}
8500:
8501: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8502: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8503:
8504: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8505:
8506: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8507: for(k=1; k<=i1;k++){
8508: if(i1 != 1 && TKresult[nres]!= k)
8509: continue;
8510: if(invalidvarcomb[k]){
8511: printf("\nCombination (%d) projection ignored because no cases \n",k);
8512: continue;
8513: }
1.268 brouard 8514: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8515: for(j=1;j<=cptcoveff;j++) {
8516: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8517: }
8518: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8519: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8520: }
8521: fprintf(ficresfb," yearbproj age");
8522: for(j=1; j<=nlstate+ndeath;j++){
8523: for(i=1; i<=nlstate;i++)
1.268 brouard 8524: fprintf(ficresfb," b%d%d",i,j);
8525: fprintf(ficresfb," b.%d",j);
1.267 brouard 8526: }
8527: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8528: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8529: fprintf(ficresfb,"\n");
8530: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.273 brouard 8531: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8532: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8533: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8534: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8535: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8536: nhstepm = nhstepm/hstepm;
8537: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8538: oldm=oldms;savm=savms;
1.268 brouard 8539: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8540: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8541: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8542: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8543: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8544: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8545: for (h=0; h<=nhstepm; h++){
1.268 brouard 8546: if (h*hstepm/YEARM*stepm ==-yearp) {
8547: break;
8548: }
8549: }
8550: fprintf(ficresfb,"\n");
8551: for(j=1;j<=cptcoveff;j++)
8552: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8553: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8554: for(i=1; i<=nlstate+ndeath;i++) {
8555: ppij=0.;ppi=0.;
8556: for(j=1; j<=nlstate;j++) {
8557: /* if (mobilav==1) */
1.269 brouard 8558: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8559: ppi=ppi+prevacurrent[(int)agec][j][k];
8560: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8561: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8562: /* else { */
8563: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8564: /* } */
1.268 brouard 8565: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8566: } /* end j */
8567: if(ppi <0.99){
8568: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8569: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8570: }
8571: fprintf(ficresfb," %.3f", ppij);
8572: }/* end j */
1.267 brouard 8573: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8574: } /* end agec */
8575: } /* end yearp */
8576: } /* end k */
1.217 brouard 8577:
1.267 brouard 8578: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8579:
1.267 brouard 8580: fclose(ficresfb);
8581: printf("End of Computing Back forecasting \n");
8582: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8583:
1.267 brouard 8584: }
1.217 brouard 8585:
1.269 brouard 8586: /* Variance of prevalence limit: varprlim */
8587: 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 8588: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8589:
8590: char fileresvpl[FILENAMELENGTH];
8591: FILE *ficresvpl;
8592: double **oldm, **savm;
8593: double **varpl; /* Variances of prevalence limits by age */
8594: int i1, k, nres, j ;
8595:
8596: strcpy(fileresvpl,"VPL_");
8597: strcat(fileresvpl,fileresu);
8598: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8599: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8600: exit(0);
8601: }
1.288 brouard 8602: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8603: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8604:
8605: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8606: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8607:
8608: i1=pow(2,cptcoveff);
8609: if (cptcovn < 1){i1=1;}
8610:
8611: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8612: for(k=1; k<=i1;k++){
8613: if(i1 != 1 && TKresult[nres]!= k)
8614: continue;
8615: fprintf(ficresvpl,"\n#****** ");
8616: printf("\n#****** ");
8617: fprintf(ficlog,"\n#****** ");
8618: for(j=1;j<=cptcoveff;j++) {
8619: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8620: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8621: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8622: }
8623: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8624: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8625: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8626: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8627: }
8628: fprintf(ficresvpl,"******\n");
8629: printf("******\n");
8630: fprintf(ficlog,"******\n");
8631:
8632: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8633: oldm=oldms;savm=savms;
8634: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8635: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8636: /*}*/
8637: }
8638:
8639: fclose(ficresvpl);
1.288 brouard 8640: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8641: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8642:
8643: }
8644: /* Variance of back prevalence: varbprlim */
8645: 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){
8646: /*------- Variance of back (stable) prevalence------*/
8647:
8648: char fileresvbl[FILENAMELENGTH];
8649: FILE *ficresvbl;
8650:
8651: double **oldm, **savm;
8652: double **varbpl; /* Variances of back prevalence limits by age */
8653: int i1, k, nres, j ;
8654:
8655: strcpy(fileresvbl,"VBL_");
8656: strcat(fileresvbl,fileresu);
8657: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8658: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8659: exit(0);
8660: }
8661: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8662: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8663:
8664:
8665: i1=pow(2,cptcoveff);
8666: if (cptcovn < 1){i1=1;}
8667:
8668: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8669: for(k=1; k<=i1;k++){
8670: if(i1 != 1 && TKresult[nres]!= k)
8671: continue;
8672: fprintf(ficresvbl,"\n#****** ");
8673: printf("\n#****** ");
8674: fprintf(ficlog,"\n#****** ");
8675: for(j=1;j<=cptcoveff;j++) {
8676: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8677: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8678: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8679: }
8680: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8681: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8682: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8683: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8684: }
8685: fprintf(ficresvbl,"******\n");
8686: printf("******\n");
8687: fprintf(ficlog,"******\n");
8688:
8689: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8690: oldm=oldms;savm=savms;
8691:
8692: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8693: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8694: /*}*/
8695: }
8696:
8697: fclose(ficresvbl);
8698: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8699: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8700:
8701: } /* End of varbprlim */
8702:
1.126 brouard 8703: /************** Forecasting *****not tested NB*************/
1.227 brouard 8704: /* 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 8705:
1.227 brouard 8706: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8707: /* int *popage; */
8708: /* double calagedatem, agelim, kk1, kk2; */
8709: /* double *popeffectif,*popcount; */
8710: /* double ***p3mat,***tabpop,***tabpopprev; */
8711: /* /\* double ***mobaverage; *\/ */
8712: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8713:
1.227 brouard 8714: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8715: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8716: /* agelim=AGESUP; */
8717: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8718:
1.227 brouard 8719: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8720:
8721:
1.227 brouard 8722: /* strcpy(filerespop,"POP_"); */
8723: /* strcat(filerespop,fileresu); */
8724: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8725: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8726: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8727: /* } */
8728: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8729: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8730:
1.227 brouard 8731: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8732:
1.227 brouard 8733: /* /\* if (mobilav!=0) { *\/ */
8734: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8735: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8736: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8737: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8738: /* /\* } *\/ */
8739: /* /\* } *\/ */
1.126 brouard 8740:
1.227 brouard 8741: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8742: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8743:
1.227 brouard 8744: /* agelim=AGESUP; */
1.126 brouard 8745:
1.227 brouard 8746: /* hstepm=1; */
8747: /* hstepm=hstepm/stepm; */
1.218 brouard 8748:
1.227 brouard 8749: /* if (popforecast==1) { */
8750: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8751: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8752: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8753: /* } */
8754: /* popage=ivector(0,AGESUP); */
8755: /* popeffectif=vector(0,AGESUP); */
8756: /* popcount=vector(0,AGESUP); */
1.126 brouard 8757:
1.227 brouard 8758: /* i=1; */
8759: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8760:
1.227 brouard 8761: /* imx=i; */
8762: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8763: /* } */
1.218 brouard 8764:
1.227 brouard 8765: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8766: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8767: /* k=k+1; */
8768: /* fprintf(ficrespop,"\n#******"); */
8769: /* for(j=1;j<=cptcoveff;j++) { */
8770: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8771: /* } */
8772: /* fprintf(ficrespop,"******\n"); */
8773: /* fprintf(ficrespop,"# Age"); */
8774: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8775: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8776:
1.227 brouard 8777: /* for (cpt=0; cpt<=0;cpt++) { */
8778: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8779:
1.227 brouard 8780: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8781: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8782: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8783:
1.227 brouard 8784: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8785: /* oldm=oldms;savm=savms; */
8786: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8787:
1.227 brouard 8788: /* for (h=0; h<=nhstepm; h++){ */
8789: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8790: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8791: /* } */
8792: /* for(j=1; j<=nlstate+ndeath;j++) { */
8793: /* kk1=0.;kk2=0; */
8794: /* for(i=1; i<=nlstate;i++) { */
8795: /* if (mobilav==1) */
8796: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8797: /* else { */
8798: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8799: /* } */
8800: /* } */
8801: /* if (h==(int)(calagedatem+12*cpt)){ */
8802: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8803: /* /\*fprintf(ficrespop," %.3f", kk1); */
8804: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8805: /* } */
8806: /* } */
8807: /* for(i=1; i<=nlstate;i++){ */
8808: /* kk1=0.; */
8809: /* for(j=1; j<=nlstate;j++){ */
8810: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8811: /* } */
8812: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8813: /* } */
1.218 brouard 8814:
1.227 brouard 8815: /* if (h==(int)(calagedatem+12*cpt)) */
8816: /* for(j=1; j<=nlstate;j++) */
8817: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8818: /* } */
8819: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8820: /* } */
8821: /* } */
1.218 brouard 8822:
1.227 brouard 8823: /* /\******\/ */
1.218 brouard 8824:
1.227 brouard 8825: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8826: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8827: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8828: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8829: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8830:
1.227 brouard 8831: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8832: /* oldm=oldms;savm=savms; */
8833: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8834: /* for (h=0; h<=nhstepm; h++){ */
8835: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8836: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8837: /* } */
8838: /* for(j=1; j<=nlstate+ndeath;j++) { */
8839: /* kk1=0.;kk2=0; */
8840: /* for(i=1; i<=nlstate;i++) { */
8841: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8842: /* } */
8843: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8844: /* } */
8845: /* } */
8846: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8847: /* } */
8848: /* } */
8849: /* } */
8850: /* } */
1.218 brouard 8851:
1.227 brouard 8852: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8853:
1.227 brouard 8854: /* if (popforecast==1) { */
8855: /* free_ivector(popage,0,AGESUP); */
8856: /* free_vector(popeffectif,0,AGESUP); */
8857: /* free_vector(popcount,0,AGESUP); */
8858: /* } */
8859: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8860: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8861: /* fclose(ficrespop); */
8862: /* } /\* End of popforecast *\/ */
1.218 brouard 8863:
1.126 brouard 8864: int fileappend(FILE *fichier, char *optionfich)
8865: {
8866: if((fichier=fopen(optionfich,"a"))==NULL) {
8867: printf("Problem with file: %s\n", optionfich);
8868: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8869: return (0);
8870: }
8871: fflush(fichier);
8872: return (1);
8873: }
8874:
8875:
8876: /**************** function prwizard **********************/
8877: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8878: {
8879:
8880: /* Wizard to print covariance matrix template */
8881:
1.164 brouard 8882: char ca[32], cb[32];
8883: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8884: int numlinepar;
8885:
8886: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8887: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8888: for(i=1; i <=nlstate; i++){
8889: jj=0;
8890: for(j=1; j <=nlstate+ndeath; j++){
8891: if(j==i) continue;
8892: jj++;
8893: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8894: printf("%1d%1d",i,j);
8895: fprintf(ficparo,"%1d%1d",i,j);
8896: for(k=1; k<=ncovmodel;k++){
8897: /* printf(" %lf",param[i][j][k]); */
8898: /* fprintf(ficparo," %lf",param[i][j][k]); */
8899: printf(" 0.");
8900: fprintf(ficparo," 0.");
8901: }
8902: printf("\n");
8903: fprintf(ficparo,"\n");
8904: }
8905: }
8906: printf("# Scales (for hessian or gradient estimation)\n");
8907: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8908: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8909: for(i=1; i <=nlstate; i++){
8910: jj=0;
8911: for(j=1; j <=nlstate+ndeath; j++){
8912: if(j==i) continue;
8913: jj++;
8914: fprintf(ficparo,"%1d%1d",i,j);
8915: printf("%1d%1d",i,j);
8916: fflush(stdout);
8917: for(k=1; k<=ncovmodel;k++){
8918: /* printf(" %le",delti3[i][j][k]); */
8919: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8920: printf(" 0.");
8921: fprintf(ficparo," 0.");
8922: }
8923: numlinepar++;
8924: printf("\n");
8925: fprintf(ficparo,"\n");
8926: }
8927: }
8928: printf("# Covariance matrix\n");
8929: /* # 121 Var(a12)\n\ */
8930: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8931: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8932: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8933: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8934: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8935: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8936: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8937: fflush(stdout);
8938: fprintf(ficparo,"# Covariance matrix\n");
8939: /* # 121 Var(a12)\n\ */
8940: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8941: /* # ...\n\ */
8942: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8943:
8944: for(itimes=1;itimes<=2;itimes++){
8945: jj=0;
8946: for(i=1; i <=nlstate; i++){
8947: for(j=1; j <=nlstate+ndeath; j++){
8948: if(j==i) continue;
8949: for(k=1; k<=ncovmodel;k++){
8950: jj++;
8951: ca[0]= k+'a'-1;ca[1]='\0';
8952: if(itimes==1){
8953: printf("#%1d%1d%d",i,j,k);
8954: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8955: }else{
8956: printf("%1d%1d%d",i,j,k);
8957: fprintf(ficparo,"%1d%1d%d",i,j,k);
8958: /* printf(" %.5le",matcov[i][j]); */
8959: }
8960: ll=0;
8961: for(li=1;li <=nlstate; li++){
8962: for(lj=1;lj <=nlstate+ndeath; lj++){
8963: if(lj==li) continue;
8964: for(lk=1;lk<=ncovmodel;lk++){
8965: ll++;
8966: if(ll<=jj){
8967: cb[0]= lk +'a'-1;cb[1]='\0';
8968: if(ll<jj){
8969: if(itimes==1){
8970: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8971: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8972: }else{
8973: printf(" 0.");
8974: fprintf(ficparo," 0.");
8975: }
8976: }else{
8977: if(itimes==1){
8978: printf(" Var(%s%1d%1d)",ca,i,j);
8979: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8980: }else{
8981: printf(" 0.");
8982: fprintf(ficparo," 0.");
8983: }
8984: }
8985: }
8986: } /* end lk */
8987: } /* end lj */
8988: } /* end li */
8989: printf("\n");
8990: fprintf(ficparo,"\n");
8991: numlinepar++;
8992: } /* end k*/
8993: } /*end j */
8994: } /* end i */
8995: } /* end itimes */
8996:
8997: } /* end of prwizard */
8998: /******************* Gompertz Likelihood ******************************/
8999: double gompertz(double x[])
9000: {
9001: double A,B,L=0.0,sump=0.,num=0.;
9002: int i,n=0; /* n is the size of the sample */
9003:
1.220 brouard 9004: for (i=1;i<=imx ; i++) {
1.126 brouard 9005: sump=sump+weight[i];
9006: /* sump=sump+1;*/
9007: num=num+1;
9008: }
9009:
9010:
9011: /* for (i=0; i<=imx; i++)
9012: 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]);*/
9013:
9014: for (i=1;i<=imx ; i++)
9015: {
9016: if (cens[i] == 1 && wav[i]>1)
9017: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9018:
9019: if (cens[i] == 0 && wav[i]>1)
9020: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
9021: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
9022:
9023: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9024: if (wav[i] > 1 ) { /* ??? */
9025: L=L+A*weight[i];
9026: /* 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]);*/
9027: }
9028: }
9029:
9030: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9031:
9032: return -2*L*num/sump;
9033: }
9034:
1.136 brouard 9035: #ifdef GSL
9036: /******************* Gompertz_f Likelihood ******************************/
9037: double gompertz_f(const gsl_vector *v, void *params)
9038: {
9039: double A,B,LL=0.0,sump=0.,num=0.;
9040: double *x= (double *) v->data;
9041: int i,n=0; /* n is the size of the sample */
9042:
9043: for (i=0;i<=imx-1 ; i++) {
9044: sump=sump+weight[i];
9045: /* sump=sump+1;*/
9046: num=num+1;
9047: }
9048:
9049:
9050: /* for (i=0; i<=imx; i++)
9051: 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]);*/
9052: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9053: for (i=1;i<=imx ; i++)
9054: {
9055: if (cens[i] == 1 && wav[i]>1)
9056: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9057:
9058: if (cens[i] == 0 && wav[i]>1)
9059: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9060: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9061:
9062: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9063: if (wav[i] > 1 ) { /* ??? */
9064: LL=LL+A*weight[i];
9065: /* 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]);*/
9066: }
9067: }
9068:
9069: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9070: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9071:
9072: return -2*LL*num/sump;
9073: }
9074: #endif
9075:
1.126 brouard 9076: /******************* Printing html file ***********/
1.201 brouard 9077: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9078: int lastpass, int stepm, int weightopt, char model[],\
9079: int imx, double p[],double **matcov,double agemortsup){
9080: int i,k;
9081:
9082: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9083: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9084: for (i=1;i<=2;i++)
9085: 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 9086: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9087: fprintf(fichtm,"</ul>");
9088:
9089: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9090:
9091: 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>");
9092:
9093: for (k=agegomp;k<(agemortsup-2);k++)
9094: 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]);
9095:
9096:
9097: fflush(fichtm);
9098: }
9099:
9100: /******************* Gnuplot file **************/
1.201 brouard 9101: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9102:
9103: char dirfileres[132],optfileres[132];
1.164 brouard 9104:
1.126 brouard 9105: int ng;
9106:
9107:
9108: /*#ifdef windows */
9109: fprintf(ficgp,"cd \"%s\" \n",pathc);
9110: /*#endif */
9111:
9112:
9113: strcpy(dirfileres,optionfilefiname);
9114: strcpy(optfileres,"vpl");
1.199 brouard 9115: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9116: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9117: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9118: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9119: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9120:
9121: }
9122:
1.136 brouard 9123: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9124: {
1.126 brouard 9125:
1.136 brouard 9126: /*-------- data file ----------*/
9127: FILE *fic;
9128: char dummy[]=" ";
1.240 brouard 9129: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9130: int lstra;
1.136 brouard 9131: int linei, month, year,iout;
9132: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9133: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9134: char *stratrunc;
1.223 brouard 9135:
1.240 brouard 9136: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9137: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9138:
1.240 brouard 9139: for(v=1; v <=ncovcol;v++){
9140: DummyV[v]=0;
9141: FixedV[v]=0;
9142: }
9143: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9144: DummyV[v]=1;
9145: FixedV[v]=0;
9146: }
9147: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9148: DummyV[v]=0;
9149: FixedV[v]=1;
9150: }
9151: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9152: DummyV[v]=1;
9153: FixedV[v]=1;
9154: }
9155: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9156: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9157: 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]);
9158: }
1.126 brouard 9159:
1.136 brouard 9160: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9161: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9162: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9163: }
1.126 brouard 9164:
1.136 brouard 9165: i=1;
9166: linei=0;
9167: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9168: linei=linei+1;
9169: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9170: if(line[j] == '\t')
9171: line[j] = ' ';
9172: }
9173: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9174: ;
9175: };
9176: line[j+1]=0; /* Trims blanks at end of line */
9177: if(line[0]=='#'){
9178: fprintf(ficlog,"Comment line\n%s\n",line);
9179: printf("Comment line\n%s\n",line);
9180: continue;
9181: }
9182: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9183: strcpy(line, linetmp);
1.223 brouard 9184:
9185: /* Loops on waves */
9186: for (j=maxwav;j>=1;j--){
9187: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9188: cutv(stra, strb, line, ' ');
9189: if(strb[0]=='.') { /* Missing value */
9190: lval=-1;
9191: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9192: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9193: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9194: 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);
9195: 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);
9196: return 1;
9197: }
9198: }else{
9199: errno=0;
9200: /* what_kind_of_number(strb); */
9201: dval=strtod(strb,&endptr);
9202: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9203: /* if(strb != endptr && *endptr == '\0') */
9204: /* dval=dlval; */
9205: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9206: if( strb[0]=='\0' || (*endptr != '\0')){
9207: 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);
9208: 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);
9209: return 1;
9210: }
9211: cotqvar[j][iv][i]=dval;
9212: cotvar[j][ntv+iv][i]=dval;
9213: }
9214: strcpy(line,stra);
1.223 brouard 9215: }/* end loop ntqv */
1.225 brouard 9216:
1.223 brouard 9217: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9218: cutv(stra, strb, line, ' ');
9219: if(strb[0]=='.') { /* Missing value */
9220: lval=-1;
9221: }else{
9222: errno=0;
9223: lval=strtol(strb,&endptr,10);
9224: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9225: if( strb[0]=='\0' || (*endptr != '\0')){
9226: 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);
9227: 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);
9228: return 1;
9229: }
9230: }
9231: if(lval <-1 || lval >1){
9232: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9233: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9234: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9235: For example, for multinomial values like 1, 2 and 3,\n \
9236: build V1=0 V2=0 for the reference value (1),\n \
9237: V1=1 V2=0 for (2) \n \
1.223 brouard 9238: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9239: output of IMaCh is often meaningless.\n \
1.223 brouard 9240: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9241: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9242: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9243: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9244: For example, for multinomial values like 1, 2 and 3,\n \
9245: build V1=0 V2=0 for the reference value (1),\n \
9246: V1=1 V2=0 for (2) \n \
1.223 brouard 9247: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9248: output of IMaCh is often meaningless.\n \
1.223 brouard 9249: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9250: return 1;
9251: }
9252: cotvar[j][iv][i]=(double)(lval);
9253: strcpy(line,stra);
1.223 brouard 9254: }/* end loop ntv */
1.225 brouard 9255:
1.223 brouard 9256: /* Statuses at wave */
1.137 brouard 9257: cutv(stra, strb, line, ' ');
1.223 brouard 9258: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9259: lval=-1;
1.136 brouard 9260: }else{
1.238 brouard 9261: errno=0;
9262: lval=strtol(strb,&endptr,10);
9263: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9264: if( strb[0]=='\0' || (*endptr != '\0')){
9265: 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);
9266: 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);
9267: return 1;
9268: }
1.136 brouard 9269: }
1.225 brouard 9270:
1.136 brouard 9271: s[j][i]=lval;
1.225 brouard 9272:
1.223 brouard 9273: /* Date of Interview */
1.136 brouard 9274: strcpy(line,stra);
9275: cutv(stra, strb,line,' ');
1.169 brouard 9276: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9277: }
1.169 brouard 9278: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9279: month=99;
9280: year=9999;
1.136 brouard 9281: }else{
1.225 brouard 9282: 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);
9283: 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);
9284: return 1;
1.136 brouard 9285: }
9286: anint[j][i]= (double) year;
9287: mint[j][i]= (double)month;
9288: strcpy(line,stra);
1.223 brouard 9289: } /* End loop on waves */
1.225 brouard 9290:
1.223 brouard 9291: /* Date of death */
1.136 brouard 9292: cutv(stra, strb,line,' ');
1.169 brouard 9293: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9294: }
1.169 brouard 9295: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9296: month=99;
9297: year=9999;
9298: }else{
1.141 brouard 9299: 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 9300: 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);
9301: return 1;
1.136 brouard 9302: }
9303: andc[i]=(double) year;
9304: moisdc[i]=(double) month;
9305: strcpy(line,stra);
9306:
1.223 brouard 9307: /* Date of birth */
1.136 brouard 9308: cutv(stra, strb,line,' ');
1.169 brouard 9309: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9310: }
1.169 brouard 9311: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9312: month=99;
9313: year=9999;
9314: }else{
1.141 brouard 9315: 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);
9316: 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 9317: return 1;
1.136 brouard 9318: }
9319: if (year==9999) {
1.141 brouard 9320: 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);
9321: 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 9322: return 1;
9323:
1.136 brouard 9324: }
9325: annais[i]=(double)(year);
9326: moisnais[i]=(double)(month);
9327: strcpy(line,stra);
1.225 brouard 9328:
1.223 brouard 9329: /* Sample weight */
1.136 brouard 9330: cutv(stra, strb,line,' ');
9331: errno=0;
9332: dval=strtod(strb,&endptr);
9333: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9334: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9335: 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 9336: fflush(ficlog);
9337: return 1;
9338: }
9339: weight[i]=dval;
9340: strcpy(line,stra);
1.225 brouard 9341:
1.223 brouard 9342: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9343: cutv(stra, strb, line, ' ');
9344: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9345: lval=-1;
1.223 brouard 9346: }else{
1.225 brouard 9347: errno=0;
9348: /* what_kind_of_number(strb); */
9349: dval=strtod(strb,&endptr);
9350: /* if(strb != endptr && *endptr == '\0') */
9351: /* dval=dlval; */
9352: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9353: if( strb[0]=='\0' || (*endptr != '\0')){
9354: 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);
9355: 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);
9356: return 1;
9357: }
9358: coqvar[iv][i]=dval;
1.226 brouard 9359: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9360: }
9361: strcpy(line,stra);
9362: }/* end loop nqv */
1.136 brouard 9363:
1.223 brouard 9364: /* Covariate values */
1.136 brouard 9365: for (j=ncovcol;j>=1;j--){
9366: cutv(stra, strb,line,' ');
1.223 brouard 9367: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9368: lval=-1;
1.136 brouard 9369: }else{
1.225 brouard 9370: errno=0;
9371: lval=strtol(strb,&endptr,10);
9372: if( strb[0]=='\0' || (*endptr != '\0')){
9373: 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);
9374: 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);
9375: return 1;
9376: }
1.136 brouard 9377: }
9378: if(lval <-1 || lval >1){
1.225 brouard 9379: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9380: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9381: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9382: For example, for multinomial values like 1, 2 and 3,\n \
9383: build V1=0 V2=0 for the reference value (1),\n \
9384: V1=1 V2=0 for (2) \n \
1.136 brouard 9385: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9386: output of IMaCh is often meaningless.\n \
1.136 brouard 9387: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9388: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9389: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9390: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9391: For example, for multinomial values like 1, 2 and 3,\n \
9392: build V1=0 V2=0 for the reference value (1),\n \
9393: V1=1 V2=0 for (2) \n \
1.136 brouard 9394: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9395: output of IMaCh is often meaningless.\n \
1.136 brouard 9396: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9397: return 1;
1.136 brouard 9398: }
9399: covar[j][i]=(double)(lval);
9400: strcpy(line,stra);
9401: }
9402: lstra=strlen(stra);
1.225 brouard 9403:
1.136 brouard 9404: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9405: stratrunc = &(stra[lstra-9]);
9406: num[i]=atol(stratrunc);
9407: }
9408: else
9409: num[i]=atol(stra);
9410: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9411: 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;}*/
9412:
9413: i=i+1;
9414: } /* End loop reading data */
1.225 brouard 9415:
1.136 brouard 9416: *imax=i-1; /* Number of individuals */
9417: fclose(fic);
1.225 brouard 9418:
1.136 brouard 9419: return (0);
1.164 brouard 9420: /* endread: */
1.225 brouard 9421: printf("Exiting readdata: ");
9422: fclose(fic);
9423: return (1);
1.223 brouard 9424: }
1.126 brouard 9425:
1.234 brouard 9426: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9427: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9428: while (*p2 == ' ')
1.234 brouard 9429: p2++;
9430: /* while ((*p1++ = *p2++) !=0) */
9431: /* ; */
9432: /* do */
9433: /* while (*p2 == ' ') */
9434: /* p2++; */
9435: /* while (*p1++ == *p2++); */
9436: *stri=p2;
1.145 brouard 9437: }
9438:
1.235 brouard 9439: int decoderesult ( char resultline[], int nres)
1.230 brouard 9440: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9441: {
1.235 brouard 9442: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9443: char resultsav[MAXLINE];
1.234 brouard 9444: int resultmodel[MAXLINE];
9445: int modelresult[MAXLINE];
1.230 brouard 9446: char stra[80], strb[80], strc[80], strd[80],stre[80];
9447:
1.234 brouard 9448: removefirstspace(&resultline);
1.233 brouard 9449: printf("decoderesult:%s\n",resultline);
1.230 brouard 9450:
9451: if (strstr(resultline,"v") !=0){
9452: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9453: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9454: return 1;
9455: }
9456: trimbb(resultsav, resultline);
9457: if (strlen(resultsav) >1){
9458: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9459: }
1.253 brouard 9460: if(j == 0){ /* Resultline but no = */
9461: TKresult[nres]=0; /* Combination for the nresult and the model */
9462: return (0);
9463: }
9464:
1.234 brouard 9465: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9466: 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);
9467: 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);
9468: }
9469: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9470: if(nbocc(resultsav,'=') >1){
9471: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9472: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9473: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9474: }else
9475: cutl(strc,strd,resultsav,'=');
1.230 brouard 9476: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9477:
1.230 brouard 9478: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9479: Tvarsel[k]=atoi(strc);
9480: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9481: /* cptcovsel++; */
9482: if (nbocc(stra,'=') >0)
9483: strcpy(resultsav,stra); /* and analyzes it */
9484: }
1.235 brouard 9485: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9486: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9487: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9488: match=0;
1.236 brouard 9489: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9490: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9491: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9492: match=1;
9493: break;
9494: }
9495: }
9496: if(match == 0){
9497: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9498: }
9499: }
9500: }
1.235 brouard 9501: /* Checking for missing or useless values in comparison of current model needs */
9502: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9503: match=0;
1.235 brouard 9504: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9505: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9506: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9507: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9508: ++match;
9509: }
9510: }
9511: }
9512: if(match == 0){
9513: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9514: }else if(match > 1){
9515: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9516: }
9517: }
1.235 brouard 9518:
1.234 brouard 9519: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9520: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9521: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9522: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9523: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9524: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9525: /* 1 0 0 0 */
9526: /* 2 1 0 0 */
9527: /* 3 0 1 0 */
9528: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9529: /* 5 0 0 1 */
9530: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9531: /* 7 0 1 1 */
9532: /* 8 1 1 1 */
1.237 brouard 9533: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9534: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9535: /* V5*age V5 known which value for nres? */
9536: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9537: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9538: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9539: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9540: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9541: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9542: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9543: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9544: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9545: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9546: k4++;;
9547: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9548: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9549: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9550: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9551: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9552: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9553: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9554: k4q++;;
9555: }
9556: }
1.234 brouard 9557:
1.235 brouard 9558: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9559: return (0);
9560: }
1.235 brouard 9561:
1.230 brouard 9562: int decodemodel( char model[], int lastobs)
9563: /**< This routine decodes the model and returns:
1.224 brouard 9564: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9565: * - nagesqr = 1 if age*age in the model, otherwise 0.
9566: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9567: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9568: * - cptcovage number of covariates with age*products =2
9569: * - cptcovs number of simple covariates
9570: * - 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
9571: * which is a new column after the 9 (ncovcol) variables.
9572: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9573: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9574: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9575: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9576: */
1.136 brouard 9577: {
1.238 brouard 9578: int i, j, k, ks, v;
1.227 brouard 9579: int j1, k1, k2, k3, k4;
1.136 brouard 9580: char modelsav[80];
1.145 brouard 9581: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9582: char *strpt;
1.136 brouard 9583:
1.145 brouard 9584: /*removespace(model);*/
1.136 brouard 9585: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9586: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9587: if (strstr(model,"AGE") !=0){
1.192 brouard 9588: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9589: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9590: return 1;
9591: }
1.141 brouard 9592: if (strstr(model,"v") !=0){
9593: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9594: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9595: return 1;
9596: }
1.187 brouard 9597: strcpy(modelsav,model);
9598: if ((strpt=strstr(model,"age*age")) !=0){
9599: printf(" strpt=%s, model=%s\n",strpt, model);
9600: if(strpt != model){
1.234 brouard 9601: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9602: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9603: corresponding column of parameters.\n",model);
1.234 brouard 9604: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9605: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9606: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9607: return 1;
1.225 brouard 9608: }
1.187 brouard 9609: nagesqr=1;
9610: if (strstr(model,"+age*age") !=0)
1.234 brouard 9611: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9612: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9613: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9614: else
1.234 brouard 9615: substrchaine(modelsav, model, "age*age");
1.187 brouard 9616: }else
9617: nagesqr=0;
9618: if (strlen(modelsav) >1){
9619: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9620: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9621: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9622: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9623: * cst, age and age*age
9624: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9625: /* including age products which are counted in cptcovage.
9626: * but the covariates which are products must be treated
9627: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9628: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9629: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9630:
9631:
1.187 brouard 9632: /* Design
9633: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9634: * < ncovcol=8 >
9635: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9636: * k= 1 2 3 4 5 6 7 8
9637: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9638: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9639: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9640: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9641: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9642: * Tage[++cptcovage]=k
9643: * if products, new covar are created after ncovcol with k1
9644: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9645: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9646: * 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
9647: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9648: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9649: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9650: * < ncovcol=8 >
9651: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9652: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9653: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9654: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9655: * p Tprod[1]@2={ 6, 5}
9656: *p Tvard[1][1]@4= {7, 8, 5, 6}
9657: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9658: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9659: *How to reorganize?
9660: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9661: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9662: * {2, 1, 4, 8, 5, 6, 3, 7}
9663: * Struct []
9664: */
1.225 brouard 9665:
1.187 brouard 9666: /* This loop fills the array Tvar from the string 'model'.*/
9667: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9668: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9669: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9670: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9671: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9672: /* k=1 Tvar[1]=2 (from V2) */
9673: /* k=5 Tvar[5] */
9674: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9675: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9676: /* } */
1.198 brouard 9677: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9678: /*
9679: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9680: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9681: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9682: }
1.187 brouard 9683: cptcovage=0;
9684: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9685: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9686: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9687: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9688: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9689: /*scanf("%d",i);*/
9690: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9691: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9692: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9693: /* covar is not filled and then is empty */
9694: cptcovprod--;
9695: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9696: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9697: Typevar[k]=1; /* 1 for age product */
9698: cptcovage++; /* Sums the number of covariates which include age as a product */
9699: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9700: /*printf("stre=%s ", stre);*/
9701: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9702: cptcovprod--;
9703: cutl(stre,strb,strc,'V');
9704: Tvar[k]=atoi(stre);
9705: Typevar[k]=1; /* 1 for age product */
9706: cptcovage++;
9707: Tage[cptcovage]=k;
9708: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9709: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9710: cptcovn++;
9711: cptcovprodnoage++;k1++;
9712: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9713: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9714: because this model-covariate is a construction we invent a new column
9715: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9716: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9717: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9718: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9719: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9720: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9721: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9722: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9723: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9724: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9725: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9726: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9727: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9728: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9729: for (i=1; i<=lastobs;i++){
9730: /* Computes the new covariate which is a product of
9731: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9732: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9733: }
9734: } /* End age is not in the model */
9735: } /* End if model includes a product */
9736: else { /* no more sum */
9737: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9738: /* scanf("%d",i);*/
9739: cutl(strd,strc,strb,'V');
9740: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9741: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9742: Tvar[k]=atoi(strd);
9743: Typevar[k]=0; /* 0 for simple covariates */
9744: }
9745: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9746: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9747: scanf("%d",i);*/
1.187 brouard 9748: } /* end of loop + on total covariates */
9749: } /* end if strlen(modelsave == 0) age*age might exist */
9750: } /* end if strlen(model == 0) */
1.136 brouard 9751:
9752: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9753: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9754:
1.136 brouard 9755: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9756: printf("cptcovprod=%d ", cptcovprod);
9757: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9758: scanf("%d ",i);*/
9759:
9760:
1.230 brouard 9761: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9762: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9763: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9764: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9765: k = 1 2 3 4 5 6 7 8 9
9766: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9767: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9768: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9769: Dummy[k] 1 0 0 0 3 1 1 2 3
9770: Tmodelind[combination of covar]=k;
1.225 brouard 9771: */
9772: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9773: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9774: /* 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 9775: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9776: printf("Model=%s\n\
9777: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9778: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9779: 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);
9780: fprintf(ficlog,"Model=%s\n\
9781: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9782: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9783: 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 9784: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9785: 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 */
9786: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9787: Fixed[k]= 0;
9788: Dummy[k]= 0;
1.225 brouard 9789: ncoveff++;
1.232 brouard 9790: ncovf++;
1.234 brouard 9791: nsd++;
9792: modell[k].maintype= FTYPE;
9793: TvarsD[nsd]=Tvar[k];
9794: TvarsDind[nsd]=k;
9795: TvarF[ncovf]=Tvar[k];
9796: TvarFind[ncovf]=k;
9797: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9798: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9799: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9800: Fixed[k]= 0;
9801: Dummy[k]= 0;
9802: ncoveff++;
9803: ncovf++;
9804: modell[k].maintype= FTYPE;
9805: TvarF[ncovf]=Tvar[k];
9806: TvarFind[ncovf]=k;
1.230 brouard 9807: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9808: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9809: }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 9810: Fixed[k]= 0;
9811: Dummy[k]= 1;
1.230 brouard 9812: nqfveff++;
1.234 brouard 9813: modell[k].maintype= FTYPE;
9814: modell[k].subtype= FQ;
9815: nsq++;
9816: TvarsQ[nsq]=Tvar[k];
9817: TvarsQind[nsq]=k;
1.232 brouard 9818: ncovf++;
1.234 brouard 9819: TvarF[ncovf]=Tvar[k];
9820: TvarFind[ncovf]=k;
1.231 brouard 9821: 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 9822: 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 9823: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9824: Fixed[k]= 1;
9825: Dummy[k]= 0;
1.225 brouard 9826: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9827: modell[k].maintype= VTYPE;
9828: modell[k].subtype= VD;
9829: nsd++;
9830: TvarsD[nsd]=Tvar[k];
9831: TvarsDind[nsd]=k;
9832: ncovv++; /* Only simple time varying variables */
9833: TvarV[ncovv]=Tvar[k];
1.242 brouard 9834: 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 9835: 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 */
9836: 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 9837: 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);
9838: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9839: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9840: Fixed[k]= 1;
9841: Dummy[k]= 1;
9842: nqtveff++;
9843: modell[k].maintype= VTYPE;
9844: modell[k].subtype= VQ;
9845: ncovv++; /* Only simple time varying variables */
9846: nsq++;
9847: TvarsQ[nsq]=Tvar[k];
9848: TvarsQind[nsq]=k;
9849: TvarV[ncovv]=Tvar[k];
1.242 brouard 9850: 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 9851: 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 */
9852: 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 9853: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9854: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9855: 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 9856: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9857: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9858: ncova++;
9859: TvarA[ncova]=Tvar[k];
9860: TvarAind[ncova]=k;
1.231 brouard 9861: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9862: Fixed[k]= 2;
9863: Dummy[k]= 2;
9864: modell[k].maintype= ATYPE;
9865: modell[k].subtype= APFD;
9866: /* ncoveff++; */
1.227 brouard 9867: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9868: Fixed[k]= 2;
9869: Dummy[k]= 3;
9870: modell[k].maintype= ATYPE;
9871: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9872: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9873: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9874: Fixed[k]= 3;
9875: Dummy[k]= 2;
9876: modell[k].maintype= ATYPE;
9877: modell[k].subtype= APVD; /* Product age * varying dummy */
9878: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9879: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9880: Fixed[k]= 3;
9881: Dummy[k]= 3;
9882: modell[k].maintype= ATYPE;
9883: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9884: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9885: }
9886: }else if (Typevar[k] == 2) { /* product without age */
9887: k1=Tposprod[k];
9888: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9889: if(Tvard[k1][2] <=ncovcol){
9890: Fixed[k]= 1;
9891: Dummy[k]= 0;
9892: modell[k].maintype= FTYPE;
9893: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9894: ncovf++; /* Fixed variables without age */
9895: TvarF[ncovf]=Tvar[k];
9896: TvarFind[ncovf]=k;
9897: }else if(Tvard[k1][2] <=ncovcol+nqv){
9898: Fixed[k]= 0; /* or 2 ?*/
9899: Dummy[k]= 1;
9900: modell[k].maintype= FTYPE;
9901: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9902: ncovf++; /* Varying variables without age */
9903: TvarF[ncovf]=Tvar[k];
9904: TvarFind[ncovf]=k;
9905: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9906: Fixed[k]= 1;
9907: Dummy[k]= 0;
9908: modell[k].maintype= VTYPE;
9909: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9910: ncovv++; /* Varying variables without age */
9911: TvarV[ncovv]=Tvar[k];
9912: TvarVind[ncovv]=k;
9913: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9914: Fixed[k]= 1;
9915: Dummy[k]= 1;
9916: modell[k].maintype= VTYPE;
9917: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9918: ncovv++; /* Varying variables without age */
9919: TvarV[ncovv]=Tvar[k];
9920: TvarVind[ncovv]=k;
9921: }
1.227 brouard 9922: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9923: if(Tvard[k1][2] <=ncovcol){
9924: Fixed[k]= 0; /* or 2 ?*/
9925: Dummy[k]= 1;
9926: modell[k].maintype= FTYPE;
9927: modell[k].subtype= FPDQ; /* Product fixed quantitative * 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+ntv){
9932: Fixed[k]= 1;
9933: Dummy[k]= 1;
9934: modell[k].maintype= VTYPE;
9935: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9936: ncovv++; /* Varying variables without age */
9937: TvarV[ncovv]=Tvar[k];
9938: TvarVind[ncovv]=k;
9939: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9940: Fixed[k]= 1;
9941: Dummy[k]= 1;
9942: modell[k].maintype= VTYPE;
9943: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9944: ncovv++; /* Varying variables without age */
9945: TvarV[ncovv]=Tvar[k];
9946: TvarVind[ncovv]=k;
9947: ncovv++; /* Varying variables without age */
9948: TvarV[ncovv]=Tvar[k];
9949: TvarVind[ncovv]=k;
9950: }
1.227 brouard 9951: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9952: if(Tvard[k1][2] <=ncovcol){
9953: Fixed[k]= 1;
9954: Dummy[k]= 1;
9955: modell[k].maintype= VTYPE;
9956: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9957: ncovv++; /* Varying variables without age */
9958: TvarV[ncovv]=Tvar[k];
9959: TvarVind[ncovv]=k;
9960: }else if(Tvard[k1][2] <=ncovcol+nqv){
9961: Fixed[k]= 1;
9962: Dummy[k]= 1;
9963: modell[k].maintype= VTYPE;
9964: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9965: ncovv++; /* Varying variables without age */
9966: TvarV[ncovv]=Tvar[k];
9967: TvarVind[ncovv]=k;
9968: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9969: Fixed[k]= 1;
9970: Dummy[k]= 0;
9971: modell[k].maintype= VTYPE;
9972: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9973: ncovv++; /* Varying variables without age */
9974: TvarV[ncovv]=Tvar[k];
9975: TvarVind[ncovv]=k;
9976: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9977: Fixed[k]= 1;
9978: Dummy[k]= 1;
9979: modell[k].maintype= VTYPE;
9980: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
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+nqtv){
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= VPDQ; /* Product time varying quantitative * 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= VPQQ; /* Product time varying quantitative * 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]= 1;
10005: modell[k].maintype= VTYPE;
10006: modell[k].subtype= VPDQ; /* Product time varying quantitative * 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= VPQQ; /* Product time varying quantitative * time varying quantitative */
10015: ncovv++; /* Varying variables without age */
10016: TvarV[ncovv]=Tvar[k];
10017: TvarVind[ncovv]=k;
10018: }
1.227 brouard 10019: }else{
1.240 brouard 10020: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10021: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10022: } /*end k1*/
1.225 brouard 10023: }else{
1.226 brouard 10024: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10025: 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 10026: }
1.227 brouard 10027: 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 10028: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10029: 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]);
10030: }
10031: /* Searching for doublons in the model */
10032: for(k1=1; k1<= cptcovt;k1++){
10033: for(k2=1; k2 <k1;k2++){
1.285 brouard 10034: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10035: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10036: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10037: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10038: 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]);
10039: 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 10040: return(1);
10041: }
10042: }else if (Typevar[k1] ==2){
10043: k3=Tposprod[k1];
10044: k4=Tposprod[k2];
10045: 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])) ){
10046: 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]]);
10047: 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);
10048: return(1);
10049: }
10050: }
1.227 brouard 10051: }
10052: }
1.225 brouard 10053: }
10054: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10055: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10056: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10057: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10058: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10059: /*endread:*/
1.225 brouard 10060: printf("Exiting decodemodel: ");
10061: return (1);
1.136 brouard 10062: }
10063:
1.169 brouard 10064: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10065: {/* Check ages at death */
1.136 brouard 10066: int i, m;
1.218 brouard 10067: int firstone=0;
10068:
1.136 brouard 10069: for (i=1; i<=imx; i++) {
10070: for(m=2; (m<= maxwav); m++) {
10071: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10072: anint[m][i]=9999;
1.216 brouard 10073: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10074: s[m][i]=-1;
1.136 brouard 10075: }
10076: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10077: *nberr = *nberr + 1;
1.218 brouard 10078: if(firstone == 0){
10079: firstone=1;
1.260 brouard 10080: 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 10081: }
1.262 brouard 10082: 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 10083: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10084: }
10085: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10086: (*nberr)++;
1.259 brouard 10087: 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 10088: 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 10089: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10090: }
10091: }
10092: }
10093:
10094: for (i=1; i<=imx; i++) {
10095: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10096: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10097: 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 10098: if (s[m][i] >= nlstate+1) {
1.169 brouard 10099: if(agedc[i]>0){
10100: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10101: agev[m][i]=agedc[i];
1.214 brouard 10102: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10103: }else {
1.136 brouard 10104: if ((int)andc[i]!=9999){
10105: nbwarn++;
10106: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10107: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10108: agev[m][i]=-1;
10109: }
10110: }
1.169 brouard 10111: } /* agedc > 0 */
1.214 brouard 10112: } /* end if */
1.136 brouard 10113: else if(s[m][i] !=9){ /* Standard case, age in fractional
10114: years but with the precision of a month */
10115: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10116: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10117: agev[m][i]=1;
10118: else if(agev[m][i] < *agemin){
10119: *agemin=agev[m][i];
10120: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10121: }
10122: else if(agev[m][i] >*agemax){
10123: *agemax=agev[m][i];
1.156 brouard 10124: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10125: }
10126: /*agev[m][i]=anint[m][i]-annais[i];*/
10127: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10128: } /* en if 9*/
1.136 brouard 10129: else { /* =9 */
1.214 brouard 10130: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10131: agev[m][i]=1;
10132: s[m][i]=-1;
10133: }
10134: }
1.214 brouard 10135: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10136: agev[m][i]=1;
1.214 brouard 10137: else{
10138: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10139: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10140: agev[m][i]=0;
10141: }
10142: } /* End for lastpass */
10143: }
1.136 brouard 10144:
10145: for (i=1; i<=imx; i++) {
10146: for(m=firstpass; (m<=lastpass); m++){
10147: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10148: (*nberr)++;
1.136 brouard 10149: 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);
10150: 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);
10151: return 1;
10152: }
10153: }
10154: }
10155:
10156: /*for (i=1; i<=imx; i++){
10157: for (m=firstpass; (m<lastpass); m++){
10158: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10159: }
10160:
10161: }*/
10162:
10163:
1.139 brouard 10164: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10165: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10166:
10167: return (0);
1.164 brouard 10168: /* endread:*/
1.136 brouard 10169: printf("Exiting calandcheckages: ");
10170: return (1);
10171: }
10172:
1.172 brouard 10173: #if defined(_MSC_VER)
10174: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10175: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10176: //#include "stdafx.h"
10177: //#include <stdio.h>
10178: //#include <tchar.h>
10179: //#include <windows.h>
10180: //#include <iostream>
10181: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10182:
10183: LPFN_ISWOW64PROCESS fnIsWow64Process;
10184:
10185: BOOL IsWow64()
10186: {
10187: BOOL bIsWow64 = FALSE;
10188:
10189: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10190: // (HANDLE, PBOOL);
10191:
10192: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10193:
10194: HMODULE module = GetModuleHandle(_T("kernel32"));
10195: const char funcName[] = "IsWow64Process";
10196: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10197: GetProcAddress(module, funcName);
10198:
10199: if (NULL != fnIsWow64Process)
10200: {
10201: if (!fnIsWow64Process(GetCurrentProcess(),
10202: &bIsWow64))
10203: //throw std::exception("Unknown error");
10204: printf("Unknown error\n");
10205: }
10206: return bIsWow64 != FALSE;
10207: }
10208: #endif
1.177 brouard 10209:
1.191 brouard 10210: void syscompilerinfo(int logged)
1.292 brouard 10211: {
10212: #include <stdint.h>
10213:
10214: /* #include "syscompilerinfo.h"*/
1.185 brouard 10215: /* command line Intel compiler 32bit windows, XP compatible:*/
10216: /* /GS /W3 /Gy
10217: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10218: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10219: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10220: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10221: */
10222: /* 64 bits */
1.185 brouard 10223: /*
10224: /GS /W3 /Gy
10225: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10226: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10227: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10228: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10229: /* Optimization are useless and O3 is slower than O2 */
10230: /*
10231: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10232: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10233: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10234: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10235: */
1.186 brouard 10236: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10237: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10238: /PDB:"visual studio
10239: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10240: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10241: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10242: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10243: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10244: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10245: uiAccess='false'"
10246: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10247: /NOLOGO /TLBID:1
10248: */
1.292 brouard 10249:
10250:
1.177 brouard 10251: #if defined __INTEL_COMPILER
1.178 brouard 10252: #if defined(__GNUC__)
10253: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10254: #endif
1.177 brouard 10255: #elif defined(__GNUC__)
1.179 brouard 10256: #ifndef __APPLE__
1.174 brouard 10257: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10258: #endif
1.177 brouard 10259: struct utsname sysInfo;
1.178 brouard 10260: int cross = CROSS;
10261: if (cross){
10262: printf("Cross-");
1.191 brouard 10263: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10264: }
1.174 brouard 10265: #endif
10266:
1.191 brouard 10267: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10268: #if defined(__clang__)
1.191 brouard 10269: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10270: #endif
10271: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10272: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10273: #endif
10274: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10275: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10276: #endif
10277: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10278: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10279: #endif
10280: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10281: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10282: #endif
10283: #if defined(_MSC_VER)
1.191 brouard 10284: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10285: #endif
10286: #if defined(__PGI)
1.191 brouard 10287: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10288: #endif
10289: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10290: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10291: #endif
1.191 brouard 10292: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10293:
1.167 brouard 10294: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10295: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10296: // Windows (x64 and x86)
1.191 brouard 10297: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10298: #elif __unix__ // all unices, not all compilers
10299: // Unix
1.191 brouard 10300: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10301: #elif __linux__
10302: // linux
1.191 brouard 10303: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10304: #elif __APPLE__
1.174 brouard 10305: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10306: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10307: #endif
10308:
10309: /* __MINGW32__ */
10310: /* __CYGWIN__ */
10311: /* __MINGW64__ */
10312: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10313: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10314: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10315: /* _WIN64 // Defined for applications for Win64. */
10316: /* _M_X64 // Defined for compilations that target x64 processors. */
10317: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10318:
1.167 brouard 10319: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10320: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10321: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10322: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10323: #else
1.191 brouard 10324: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10325: #endif
10326:
1.169 brouard 10327: #if defined(__GNUC__)
10328: # if defined(__GNUC_PATCHLEVEL__)
10329: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10330: + __GNUC_MINOR__ * 100 \
10331: + __GNUC_PATCHLEVEL__)
10332: # else
10333: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10334: + __GNUC_MINOR__ * 100)
10335: # endif
1.174 brouard 10336: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10337: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10338:
10339: if (uname(&sysInfo) != -1) {
10340: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10341: 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 10342: }
10343: else
10344: perror("uname() error");
1.179 brouard 10345: //#ifndef __INTEL_COMPILER
10346: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10347: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10348: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10349: #endif
1.169 brouard 10350: #endif
1.172 brouard 10351:
1.286 brouard 10352: // void main ()
1.172 brouard 10353: // {
1.169 brouard 10354: #if defined(_MSC_VER)
1.174 brouard 10355: if (IsWow64()){
1.191 brouard 10356: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10357: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10358: }
10359: else{
1.191 brouard 10360: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10361: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10362: }
1.172 brouard 10363: // printf("\nPress Enter to continue...");
10364: // getchar();
10365: // }
10366:
1.169 brouard 10367: #endif
10368:
1.167 brouard 10369:
1.219 brouard 10370: }
1.136 brouard 10371:
1.219 brouard 10372: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10373: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10374: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10375: /* double ftolpl = 1.e-10; */
1.180 brouard 10376: double age, agebase, agelim;
1.203 brouard 10377: double tot;
1.180 brouard 10378:
1.202 brouard 10379: strcpy(filerespl,"PL_");
10380: strcat(filerespl,fileresu);
10381: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10382: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10383: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10384: }
1.288 brouard 10385: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10386: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10387: pstamp(ficrespl);
1.288 brouard 10388: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10389: fprintf(ficrespl,"#Age ");
10390: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10391: fprintf(ficrespl,"\n");
1.180 brouard 10392:
1.219 brouard 10393: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10394:
1.219 brouard 10395: agebase=ageminpar;
10396: agelim=agemaxpar;
1.180 brouard 10397:
1.227 brouard 10398: /* i1=pow(2,ncoveff); */
1.234 brouard 10399: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10400: if (cptcovn < 1){i1=1;}
1.180 brouard 10401:
1.238 brouard 10402: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10403: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10404: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10405: continue;
1.235 brouard 10406:
1.238 brouard 10407: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10408: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10409: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10410: /* k=k+1; */
10411: /* to clean */
10412: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10413: fprintf(ficrespl,"#******");
10414: printf("#******");
10415: fprintf(ficlog,"#******");
10416: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10417: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10418: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10419: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10420: }
10421: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10422: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10423: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10424: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10425: }
10426: fprintf(ficrespl,"******\n");
10427: printf("******\n");
10428: fprintf(ficlog,"******\n");
10429: if(invalidvarcomb[k]){
10430: printf("\nCombination (%d) ignored because no case \n",k);
10431: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10432: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10433: continue;
10434: }
1.219 brouard 10435:
1.238 brouard 10436: fprintf(ficrespl,"#Age ");
10437: for(j=1;j<=cptcoveff;j++) {
10438: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10439: }
10440: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10441: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10442:
1.238 brouard 10443: for (age=agebase; age<=agelim; age++){
10444: /* for (age=agebase; age<=agebase; age++){ */
10445: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10446: fprintf(ficrespl,"%.0f ",age );
10447: for(j=1;j<=cptcoveff;j++)
10448: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10449: tot=0.;
10450: for(i=1; i<=nlstate;i++){
10451: tot += prlim[i][i];
10452: fprintf(ficrespl," %.5f", prlim[i][i]);
10453: }
10454: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10455: } /* Age */
10456: /* was end of cptcod */
10457: } /* cptcov */
10458: } /* nres */
1.219 brouard 10459: return 0;
1.180 brouard 10460: }
10461:
1.218 brouard 10462: 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 10463: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10464:
10465: /* Computes the back prevalence limit for any combination of covariate values
10466: * at any age between ageminpar and agemaxpar
10467: */
1.235 brouard 10468: int i, j, k, i1, nres=0 ;
1.217 brouard 10469: /* double ftolpl = 1.e-10; */
10470: double age, agebase, agelim;
10471: double tot;
1.218 brouard 10472: /* double ***mobaverage; */
10473: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10474:
10475: strcpy(fileresplb,"PLB_");
10476: strcat(fileresplb,fileresu);
10477: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10478: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10479: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10480: }
1.288 brouard 10481: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10482: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10483: pstamp(ficresplb);
1.288 brouard 10484: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10485: fprintf(ficresplb,"#Age ");
10486: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10487: fprintf(ficresplb,"\n");
10488:
1.218 brouard 10489:
10490: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10491:
10492: agebase=ageminpar;
10493: agelim=agemaxpar;
10494:
10495:
1.227 brouard 10496: i1=pow(2,cptcoveff);
1.218 brouard 10497: if (cptcovn < 1){i1=1;}
1.227 brouard 10498:
1.238 brouard 10499: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10500: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10501: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10502: continue;
10503: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10504: fprintf(ficresplb,"#******");
10505: printf("#******");
10506: fprintf(ficlog,"#******");
10507: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10508: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10509: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10510: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10511: }
10512: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10513: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10514: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10515: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10516: }
10517: fprintf(ficresplb,"******\n");
10518: printf("******\n");
10519: fprintf(ficlog,"******\n");
10520: if(invalidvarcomb[k]){
10521: printf("\nCombination (%d) ignored because no cases \n",k);
10522: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10523: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10524: continue;
10525: }
1.218 brouard 10526:
1.238 brouard 10527: fprintf(ficresplb,"#Age ");
10528: for(j=1;j<=cptcoveff;j++) {
10529: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10530: }
10531: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10532: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10533:
10534:
1.238 brouard 10535: for (age=agebase; age<=agelim; age++){
10536: /* for (age=agebase; age<=agebase; age++){ */
10537: if(mobilavproj > 0){
10538: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10539: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10540: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10541: }else if (mobilavproj == 0){
10542: 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);
10543: 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);
10544: exit(1);
10545: }else{
10546: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10547: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10548: /* printf("TOTOT\n"); */
10549: /* exit(1); */
1.238 brouard 10550: }
10551: fprintf(ficresplb,"%.0f ",age );
10552: for(j=1;j<=cptcoveff;j++)
10553: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10554: tot=0.;
10555: for(i=1; i<=nlstate;i++){
10556: tot += bprlim[i][i];
10557: fprintf(ficresplb," %.5f", bprlim[i][i]);
10558: }
10559: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10560: } /* Age */
10561: /* was end of cptcod */
1.255 brouard 10562: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10563: } /* end of any combination */
10564: } /* end of nres */
1.218 brouard 10565: /* hBijx(p, bage, fage); */
10566: /* fclose(ficrespijb); */
10567:
10568: return 0;
1.217 brouard 10569: }
1.218 brouard 10570:
1.180 brouard 10571: int hPijx(double *p, int bage, int fage){
10572: /*------------- h Pij x at various ages ------------*/
10573:
10574: int stepsize;
10575: int agelim;
10576: int hstepm;
10577: int nhstepm;
1.235 brouard 10578: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10579:
10580: double agedeb;
10581: double ***p3mat;
10582:
1.201 brouard 10583: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10584: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10585: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10586: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10587: }
10588: printf("Computing pij: result on file '%s' \n", filerespij);
10589: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10590:
10591: stepsize=(int) (stepm+YEARM-1)/YEARM;
10592: /*if (stepm<=24) stepsize=2;*/
10593:
10594: agelim=AGESUP;
10595: hstepm=stepsize*YEARM; /* Every year of age */
10596: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10597:
1.180 brouard 10598: /* hstepm=1; aff par mois*/
10599: pstamp(ficrespij);
10600: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10601: i1= pow(2,cptcoveff);
1.218 brouard 10602: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10603: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10604: /* k=k+1; */
1.235 brouard 10605: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10606: for(k=1; k<=i1;k++){
1.253 brouard 10607: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10608: continue;
1.183 brouard 10609: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10610: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10611: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10612: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10613: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10614: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10615: }
1.183 brouard 10616: fprintf(ficrespij,"******\n");
10617:
10618: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10619: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10620: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10621:
10622: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10623:
1.183 brouard 10624: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10625: oldm=oldms;savm=savms;
1.235 brouard 10626: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10627: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10628: for(i=1; i<=nlstate;i++)
10629: for(j=1; j<=nlstate+ndeath;j++)
10630: fprintf(ficrespij," %1d-%1d",i,j);
10631: fprintf(ficrespij,"\n");
10632: for (h=0; h<=nhstepm; h++){
10633: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10634: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10635: for(i=1; i<=nlstate;i++)
10636: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10637: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10638: fprintf(ficrespij,"\n");
10639: }
1.183 brouard 10640: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10641: fprintf(ficrespij,"\n");
10642: }
1.180 brouard 10643: /*}*/
10644: }
1.218 brouard 10645: return 0;
1.180 brouard 10646: }
1.218 brouard 10647:
10648: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10649: /*------------- h Bij x at various ages ------------*/
10650:
10651: int stepsize;
1.218 brouard 10652: /* int agelim; */
10653: int ageminl;
1.217 brouard 10654: int hstepm;
10655: int nhstepm;
1.238 brouard 10656: int h, i, i1, j, k, nres;
1.218 brouard 10657:
1.217 brouard 10658: double agedeb;
10659: double ***p3mat;
1.218 brouard 10660:
10661: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10662: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10663: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10664: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10665: }
10666: printf("Computing pij back: result on file '%s' \n", filerespijb);
10667: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10668:
10669: stepsize=(int) (stepm+YEARM-1)/YEARM;
10670: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10671:
1.218 brouard 10672: /* agelim=AGESUP; */
1.289 brouard 10673: ageminl=AGEINF; /* was 30 */
1.218 brouard 10674: hstepm=stepsize*YEARM; /* Every year of age */
10675: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10676:
10677: /* hstepm=1; aff par mois*/
10678: pstamp(ficrespijb);
1.255 brouard 10679: 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 10680: i1= pow(2,cptcoveff);
1.218 brouard 10681: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10682: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10683: /* k=k+1; */
1.238 brouard 10684: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10685: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10686: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10687: continue;
10688: fprintf(ficrespijb,"\n#****** ");
10689: for(j=1;j<=cptcoveff;j++)
10690: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10691: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10692: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10693: }
10694: fprintf(ficrespijb,"******\n");
1.264 brouard 10695: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10696: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10697: continue;
10698: }
10699:
10700: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10701: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10702: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10703: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10704: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10705:
10706: /* nhstepm=nhstepm*YEARM; aff par mois*/
10707:
1.266 brouard 10708: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10709: /* and memory limitations if stepm is small */
10710:
1.238 brouard 10711: /* oldm=oldms;savm=savms; */
10712: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10713: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10714: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10715: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10716: for(i=1; i<=nlstate;i++)
10717: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10718: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10719: fprintf(ficrespijb,"\n");
1.238 brouard 10720: for (h=0; h<=nhstepm; h++){
10721: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10722: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10723: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10724: for(i=1; i<=nlstate;i++)
10725: for(j=1; j<=nlstate+ndeath;j++)
10726: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10727: fprintf(ficrespijb,"\n");
10728: }
10729: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10730: fprintf(ficrespijb,"\n");
10731: } /* end age deb */
10732: } /* end combination */
10733: } /* end nres */
1.218 brouard 10734: return 0;
10735: } /* hBijx */
1.217 brouard 10736:
1.180 brouard 10737:
1.136 brouard 10738: /***********************************************/
10739: /**************** Main Program *****************/
10740: /***********************************************/
10741:
10742: int main(int argc, char *argv[])
10743: {
10744: #ifdef GSL
10745: const gsl_multimin_fminimizer_type *T;
10746: size_t iteri = 0, it;
10747: int rval = GSL_CONTINUE;
10748: int status = GSL_SUCCESS;
10749: double ssval;
10750: #endif
10751: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 10752: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
10753: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 10754: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10755: int jj, ll, li, lj, lk;
1.136 brouard 10756: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10757: int num_filled;
1.136 brouard 10758: int itimes;
10759: int NDIM=2;
10760: int vpopbased=0;
1.235 brouard 10761: int nres=0;
1.258 brouard 10762: int endishere=0;
1.277 brouard 10763: int noffset=0;
1.274 brouard 10764: int ncurrv=0; /* Temporary variable */
10765:
1.164 brouard 10766: char ca[32], cb[32];
1.136 brouard 10767: /* FILE *fichtm; *//* Html File */
10768: /* FILE *ficgp;*/ /*Gnuplot File */
10769: struct stat info;
1.191 brouard 10770: double agedeb=0.;
1.194 brouard 10771:
10772: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10773: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10774:
1.165 brouard 10775: double fret;
1.191 brouard 10776: double dum=0.; /* Dummy variable */
1.136 brouard 10777: double ***p3mat;
1.218 brouard 10778: /* double ***mobaverage; */
1.164 brouard 10779:
10780: char line[MAXLINE];
1.197 brouard 10781: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10782:
1.234 brouard 10783: char modeltemp[MAXLINE];
1.230 brouard 10784: char resultline[MAXLINE];
10785:
1.136 brouard 10786: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10787: char *tok, *val; /* pathtot */
1.290 brouard 10788: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 10789: int c, h , cpt, c2;
1.191 brouard 10790: int jl=0;
10791: int i1, j1, jk, stepsize=0;
1.194 brouard 10792: int count=0;
10793:
1.164 brouard 10794: int *tab;
1.136 brouard 10795: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.293 brouard 10796: int backcast=0; /* defined as global for mlikeli and mle*/
1.136 brouard 10797: int mobilav=0,popforecast=0;
1.191 brouard 10798: int hstepm=0, nhstepm=0;
1.136 brouard 10799: int agemortsup;
10800: float sumlpop=0.;
10801: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10802: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10803:
1.191 brouard 10804: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10805: double ftolpl=FTOL;
10806: double **prlim;
1.217 brouard 10807: double **bprlim;
1.136 brouard 10808: double ***param; /* Matrix of parameters */
1.251 brouard 10809: double ***paramstart; /* Matrix of starting parameter values */
10810: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10811: double **matcov; /* Matrix of covariance */
1.203 brouard 10812: double **hess; /* Hessian matrix */
1.136 brouard 10813: double ***delti3; /* Scale */
10814: double *delti; /* Scale */
10815: double ***eij, ***vareij;
10816: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10817:
1.136 brouard 10818: double *epj, vepp;
1.164 brouard 10819:
1.273 brouard 10820: double dateprev1, dateprev2;
10821: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0;
10822: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0;
1.217 brouard 10823:
1.136 brouard 10824: double **ximort;
1.145 brouard 10825: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10826: int *dcwave;
10827:
1.164 brouard 10828: char z[1]="c";
1.136 brouard 10829:
10830: /*char *strt;*/
10831: char strtend[80];
1.126 brouard 10832:
1.164 brouard 10833:
1.126 brouard 10834: /* setlocale (LC_ALL, ""); */
10835: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10836: /* textdomain (PACKAGE); */
10837: /* setlocale (LC_CTYPE, ""); */
10838: /* setlocale (LC_MESSAGES, ""); */
10839:
10840: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10841: rstart_time = time(NULL);
10842: /* (void) gettimeofday(&start_time,&tzp);*/
10843: start_time = *localtime(&rstart_time);
1.126 brouard 10844: curr_time=start_time;
1.157 brouard 10845: /*tml = *localtime(&start_time.tm_sec);*/
10846: /* strcpy(strstart,asctime(&tml)); */
10847: strcpy(strstart,asctime(&start_time));
1.126 brouard 10848:
10849: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10850: /* tp.tm_sec = tp.tm_sec +86400; */
10851: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10852: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10853: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10854: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10855: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10856: /* strt=asctime(&tmg); */
10857: /* printf("Time(after) =%s",strstart); */
10858: /* (void) time (&time_value);
10859: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10860: * tm = *localtime(&time_value);
10861: * strstart=asctime(&tm);
10862: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10863: */
10864:
10865: nberr=0; /* Number of errors and warnings */
10866: nbwarn=0;
1.184 brouard 10867: #ifdef WIN32
10868: _getcwd(pathcd, size);
10869: #else
1.126 brouard 10870: getcwd(pathcd, size);
1.184 brouard 10871: #endif
1.191 brouard 10872: syscompilerinfo(0);
1.196 brouard 10873: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10874: if(argc <=1){
10875: printf("\nEnter the parameter file name: ");
1.205 brouard 10876: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10877: printf("ERROR Empty parameter file name\n");
10878: goto end;
10879: }
1.126 brouard 10880: i=strlen(pathr);
10881: if(pathr[i-1]=='\n')
10882: pathr[i-1]='\0';
1.156 brouard 10883: i=strlen(pathr);
1.205 brouard 10884: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10885: pathr[i-1]='\0';
1.205 brouard 10886: }
10887: i=strlen(pathr);
10888: if( i==0 ){
10889: printf("ERROR Empty parameter file name\n");
10890: goto end;
10891: }
10892: for (tok = pathr; tok != NULL; ){
1.126 brouard 10893: printf("Pathr |%s|\n",pathr);
10894: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10895: printf("val= |%s| pathr=%s\n",val,pathr);
10896: strcpy (pathtot, val);
10897: if(pathr[0] == '\0') break; /* Dirty */
10898: }
10899: }
1.281 brouard 10900: else if (argc<=2){
10901: strcpy(pathtot,argv[1]);
10902: }
1.126 brouard 10903: else{
10904: strcpy(pathtot,argv[1]);
1.281 brouard 10905: strcpy(z,argv[2]);
10906: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10907: }
10908: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10909: /*cygwin_split_path(pathtot,path,optionfile);
10910: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10911: /* cutv(path,optionfile,pathtot,'\\');*/
10912:
10913: /* Split argv[0], imach program to get pathimach */
10914: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10915: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10916: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10917: /* strcpy(pathimach,argv[0]); */
10918: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10919: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10920: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10921: #ifdef WIN32
10922: _chdir(path); /* Can be a relative path */
10923: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10924: #else
1.126 brouard 10925: chdir(path); /* Can be a relative path */
1.184 brouard 10926: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10927: #endif
10928: printf("Current directory %s!\n",pathcd);
1.126 brouard 10929: strcpy(command,"mkdir ");
10930: strcat(command,optionfilefiname);
10931: if((outcmd=system(command)) != 0){
1.169 brouard 10932: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10933: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10934: /* fclose(ficlog); */
10935: /* exit(1); */
10936: }
10937: /* if((imk=mkdir(optionfilefiname))<0){ */
10938: /* perror("mkdir"); */
10939: /* } */
10940:
10941: /*-------- arguments in the command line --------*/
10942:
1.186 brouard 10943: /* Main Log file */
1.126 brouard 10944: strcat(filelog, optionfilefiname);
10945: strcat(filelog,".log"); /* */
10946: if((ficlog=fopen(filelog,"w"))==NULL) {
10947: printf("Problem with logfile %s\n",filelog);
10948: goto end;
10949: }
10950: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10951: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10952: fprintf(ficlog,"\nEnter the parameter file name: \n");
10953: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10954: path=%s \n\
10955: optionfile=%s\n\
10956: optionfilext=%s\n\
1.156 brouard 10957: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10958:
1.197 brouard 10959: syscompilerinfo(1);
1.167 brouard 10960:
1.126 brouard 10961: printf("Local time (at start):%s",strstart);
10962: fprintf(ficlog,"Local time (at start): %s",strstart);
10963: fflush(ficlog);
10964: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10965: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10966:
10967: /* */
10968: strcpy(fileres,"r");
10969: strcat(fileres, optionfilefiname);
1.201 brouard 10970: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10971: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10972: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10973:
1.186 brouard 10974: /* Main ---------arguments file --------*/
1.126 brouard 10975:
10976: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10977: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10978: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10979: fflush(ficlog);
1.149 brouard 10980: /* goto end; */
10981: exit(70);
1.126 brouard 10982: }
10983:
10984: strcpy(filereso,"o");
1.201 brouard 10985: strcat(filereso,fileresu);
1.126 brouard 10986: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10987: printf("Problem with Output resultfile: %s\n", filereso);
10988: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10989: fflush(ficlog);
10990: goto end;
10991: }
1.278 brouard 10992: /*-------- Rewriting parameter file ----------*/
10993: strcpy(rfileres,"r"); /* "Rparameterfile */
10994: strcat(rfileres,optionfilefiname); /* Parameter file first name */
10995: strcat(rfileres,"."); /* */
10996: strcat(rfileres,optionfilext); /* Other files have txt extension */
10997: if((ficres =fopen(rfileres,"w"))==NULL) {
10998: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10999: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11000: fflush(ficlog);
11001: goto end;
11002: }
11003: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11004:
1.278 brouard 11005:
1.126 brouard 11006: /* Reads comments: lines beginning with '#' */
11007: numlinepar=0;
1.277 brouard 11008: /* Is it a BOM UTF-8 Windows file? */
11009: /* First parameter line */
1.197 brouard 11010: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11011: noffset=0;
11012: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11013: {
11014: noffset=noffset+3;
11015: printf("# File is an UTF8 Bom.\n"); // 0xBF
11016: }
11017: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
11018: {
11019: noffset=noffset+2;
11020: printf("# File is an UTF16BE BOM file\n");
11021: }
11022: else if( line[0] == 0 && line[1] == 0)
11023: {
11024: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11025: noffset=noffset+4;
11026: printf("# File is an UTF16BE BOM file\n");
11027: }
11028: } else{
11029: ;/*printf(" Not a BOM file\n");*/
11030: }
11031:
1.197 brouard 11032: /* If line starts with a # it is a comment */
1.277 brouard 11033: if (line[noffset] == '#') {
1.197 brouard 11034: numlinepar++;
11035: fputs(line,stdout);
11036: fputs(line,ficparo);
1.278 brouard 11037: fputs(line,ficres);
1.197 brouard 11038: fputs(line,ficlog);
11039: continue;
11040: }else
11041: break;
11042: }
11043: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11044: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11045: if (num_filled != 5) {
11046: printf("Should be 5 parameters\n");
1.283 brouard 11047: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11048: }
1.126 brouard 11049: numlinepar++;
1.197 brouard 11050: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11051: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11052: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11053: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11054: }
11055: /* Second parameter line */
11056: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11057: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11058: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11059: if (line[0] == '#') {
11060: numlinepar++;
1.283 brouard 11061: printf("%s",line);
11062: fprintf(ficres,"%s",line);
11063: fprintf(ficparo,"%s",line);
11064: fprintf(ficlog,"%s",line);
1.197 brouard 11065: continue;
11066: }else
11067: break;
11068: }
1.223 brouard 11069: 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", \
11070: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11071: if (num_filled != 11) {
11072: 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 11073: printf("but line=%s\n",line);
1.283 brouard 11074: 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");
11075: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11076: }
1.286 brouard 11077: if( lastpass > maxwav){
11078: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11079: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11080: fflush(ficlog);
11081: goto end;
11082: }
11083: 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 11084: 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 11085: 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 11086: 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 11087: }
1.203 brouard 11088: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11089: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11090: /* Third parameter line */
11091: while(fgets(line, MAXLINE, ficpar)) {
11092: /* If line starts with a # it is a comment */
11093: if (line[0] == '#') {
11094: numlinepar++;
1.283 brouard 11095: printf("%s",line);
11096: fprintf(ficres,"%s",line);
11097: fprintf(ficparo,"%s",line);
11098: fprintf(ficlog,"%s",line);
1.197 brouard 11099: continue;
11100: }else
11101: break;
11102: }
1.201 brouard 11103: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11104: if (num_filled != 1){
11105: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11106: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11107: model[0]='\0';
11108: goto end;
11109: }
11110: else{
11111: if (model[0]=='+'){
11112: for(i=1; i<=strlen(model);i++)
11113: modeltemp[i-1]=model[i];
1.201 brouard 11114: strcpy(model,modeltemp);
1.197 brouard 11115: }
11116: }
1.199 brouard 11117: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11118: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11119: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11120: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11121: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11122: }
11123: /* 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); */
11124: /* numlinepar=numlinepar+3; /\* In general *\/ */
11125: /* 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 11126: /* 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); */
11127: /* 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 11128: fflush(ficlog);
1.190 brouard 11129: /* if(model[0]=='#'|| model[0]== '\0'){ */
11130: if(model[0]=='#'){
1.279 brouard 11131: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11132: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11133: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11134: if(mle != -1){
1.279 brouard 11135: 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 11136: exit(1);
11137: }
11138: }
1.126 brouard 11139: while((c=getc(ficpar))=='#' && c!= EOF){
11140: ungetc(c,ficpar);
11141: fgets(line, MAXLINE, ficpar);
11142: numlinepar++;
1.195 brouard 11143: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11144: z[0]=line[1];
11145: }
11146: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11147: fputs(line, stdout);
11148: //puts(line);
1.126 brouard 11149: fputs(line,ficparo);
11150: fputs(line,ficlog);
11151: }
11152: ungetc(c,ficpar);
11153:
11154:
1.290 brouard 11155: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11156: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11157: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11158: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11159: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11160: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11161: v1+v2*age+v2*v3 makes cptcovn = 3
11162: */
11163: if (strlen(model)>1)
1.187 brouard 11164: 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 11165: else
1.187 brouard 11166: ncovmodel=2; /* Constant and age */
1.133 brouard 11167: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11168: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11169: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11170: 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);
11171: 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);
11172: fflush(stdout);
11173: fclose (ficlog);
11174: goto end;
11175: }
1.126 brouard 11176: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11177: delti=delti3[1][1];
11178: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11179: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11180: /* We could also provide initial parameters values giving by simple logistic regression
11181: * only one way, that is without matrix product. We will have nlstate maximizations */
11182: /* for(i=1;i<nlstate;i++){ */
11183: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11184: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11185: /* } */
1.126 brouard 11186: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11187: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11188: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11189: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11190: fclose (ficparo);
11191: fclose (ficlog);
11192: goto end;
11193: exit(0);
1.220 brouard 11194: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11195: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11196: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11197: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11198: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11199: matcov=matrix(1,npar,1,npar);
1.203 brouard 11200: hess=matrix(1,npar,1,npar);
1.220 brouard 11201: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11202: /* Read guessed parameters */
1.126 brouard 11203: /* Reads comments: lines beginning with '#' */
11204: while((c=getc(ficpar))=='#' && c!= EOF){
11205: ungetc(c,ficpar);
11206: fgets(line, MAXLINE, ficpar);
11207: numlinepar++;
1.141 brouard 11208: fputs(line,stdout);
1.126 brouard 11209: fputs(line,ficparo);
11210: fputs(line,ficlog);
11211: }
11212: ungetc(c,ficpar);
11213:
11214: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11215: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11216: for(i=1; i <=nlstate; i++){
1.234 brouard 11217: j=0;
1.126 brouard 11218: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11219: if(jj==i) continue;
11220: j++;
1.292 brouard 11221: while((c=getc(ficpar))=='#' && c!= EOF){
11222: ungetc(c,ficpar);
11223: fgets(line, MAXLINE, ficpar);
11224: numlinepar++;
11225: fputs(line,stdout);
11226: fputs(line,ficparo);
11227: fputs(line,ficlog);
11228: }
11229: ungetc(c,ficpar);
1.234 brouard 11230: fscanf(ficpar,"%1d%1d",&i1,&j1);
11231: if ((i1 != i) || (j1 != jj)){
11232: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11233: It might be a problem of design; if ncovcol and the model are correct\n \
11234: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11235: exit(1);
11236: }
11237: fprintf(ficparo,"%1d%1d",i1,j1);
11238: if(mle==1)
11239: printf("%1d%1d",i,jj);
11240: fprintf(ficlog,"%1d%1d",i,jj);
11241: for(k=1; k<=ncovmodel;k++){
11242: fscanf(ficpar," %lf",¶m[i][j][k]);
11243: if(mle==1){
11244: printf(" %lf",param[i][j][k]);
11245: fprintf(ficlog," %lf",param[i][j][k]);
11246: }
11247: else
11248: fprintf(ficlog," %lf",param[i][j][k]);
11249: fprintf(ficparo," %lf",param[i][j][k]);
11250: }
11251: fscanf(ficpar,"\n");
11252: numlinepar++;
11253: if(mle==1)
11254: printf("\n");
11255: fprintf(ficlog,"\n");
11256: fprintf(ficparo,"\n");
1.126 brouard 11257: }
11258: }
11259: fflush(ficlog);
1.234 brouard 11260:
1.251 brouard 11261: /* Reads parameters values */
1.126 brouard 11262: p=param[1][1];
1.251 brouard 11263: pstart=paramstart[1][1];
1.126 brouard 11264:
11265: /* Reads comments: lines beginning with '#' */
11266: while((c=getc(ficpar))=='#' && c!= EOF){
11267: ungetc(c,ficpar);
11268: fgets(line, MAXLINE, ficpar);
11269: numlinepar++;
1.141 brouard 11270: fputs(line,stdout);
1.126 brouard 11271: fputs(line,ficparo);
11272: fputs(line,ficlog);
11273: }
11274: ungetc(c,ficpar);
11275:
11276: for(i=1; i <=nlstate; i++){
11277: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11278: fscanf(ficpar,"%1d%1d",&i1,&j1);
11279: if ( (i1-i) * (j1-j) != 0){
11280: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11281: exit(1);
11282: }
11283: printf("%1d%1d",i,j);
11284: fprintf(ficparo,"%1d%1d",i1,j1);
11285: fprintf(ficlog,"%1d%1d",i1,j1);
11286: for(k=1; k<=ncovmodel;k++){
11287: fscanf(ficpar,"%le",&delti3[i][j][k]);
11288: printf(" %le",delti3[i][j][k]);
11289: fprintf(ficparo," %le",delti3[i][j][k]);
11290: fprintf(ficlog," %le",delti3[i][j][k]);
11291: }
11292: fscanf(ficpar,"\n");
11293: numlinepar++;
11294: printf("\n");
11295: fprintf(ficparo,"\n");
11296: fprintf(ficlog,"\n");
1.126 brouard 11297: }
11298: }
11299: fflush(ficlog);
1.234 brouard 11300:
1.145 brouard 11301: /* Reads covariance matrix */
1.126 brouard 11302: delti=delti3[1][1];
1.220 brouard 11303:
11304:
1.126 brouard 11305: /* 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 11306:
1.126 brouard 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);
1.220 brouard 11317:
1.126 brouard 11318: matcov=matrix(1,npar,1,npar);
1.203 brouard 11319: hess=matrix(1,npar,1,npar);
1.131 brouard 11320: for(i=1; i <=npar; i++)
11321: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11322:
1.194 brouard 11323: /* Scans npar lines */
1.126 brouard 11324: for(i=1; i <=npar; i++){
1.226 brouard 11325: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11326: if(count != 3){
1.226 brouard 11327: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11328: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11329: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11330: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11331: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11332: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11333: exit(1);
1.220 brouard 11334: }else{
1.226 brouard 11335: if(mle==1)
11336: printf("%1d%1d%d",i1,j1,jk);
11337: }
11338: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11339: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11340: for(j=1; j <=i; j++){
1.226 brouard 11341: fscanf(ficpar," %le",&matcov[i][j]);
11342: if(mle==1){
11343: printf(" %.5le",matcov[i][j]);
11344: }
11345: fprintf(ficlog," %.5le",matcov[i][j]);
11346: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11347: }
11348: fscanf(ficpar,"\n");
11349: numlinepar++;
11350: if(mle==1)
1.220 brouard 11351: printf("\n");
1.126 brouard 11352: fprintf(ficlog,"\n");
11353: fprintf(ficparo,"\n");
11354: }
1.194 brouard 11355: /* End of read covariance matrix npar lines */
1.126 brouard 11356: for(i=1; i <=npar; i++)
11357: for(j=i+1;j<=npar;j++)
1.226 brouard 11358: matcov[i][j]=matcov[j][i];
1.126 brouard 11359:
11360: if(mle==1)
11361: printf("\n");
11362: fprintf(ficlog,"\n");
11363:
11364: fflush(ficlog);
11365:
11366: } /* End of mle != -3 */
1.218 brouard 11367:
1.186 brouard 11368: /* Main data
11369: */
1.290 brouard 11370: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11371: /* num=lvector(1,n); */
11372: /* moisnais=vector(1,n); */
11373: /* annais=vector(1,n); */
11374: /* moisdc=vector(1,n); */
11375: /* andc=vector(1,n); */
11376: /* weight=vector(1,n); */
11377: /* agedc=vector(1,n); */
11378: /* cod=ivector(1,n); */
11379: /* for(i=1;i<=n;i++){ */
11380: num=lvector(firstobs,lastobs);
11381: moisnais=vector(firstobs,lastobs);
11382: annais=vector(firstobs,lastobs);
11383: moisdc=vector(firstobs,lastobs);
11384: andc=vector(firstobs,lastobs);
11385: weight=vector(firstobs,lastobs);
11386: agedc=vector(firstobs,lastobs);
11387: cod=ivector(firstobs,lastobs);
11388: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11389: num[i]=0;
11390: moisnais[i]=0;
11391: annais[i]=0;
11392: moisdc[i]=0;
11393: andc[i]=0;
11394: agedc[i]=0;
11395: cod[i]=0;
11396: weight[i]=1.0; /* Equal weights, 1 by default */
11397: }
1.290 brouard 11398: mint=matrix(1,maxwav,firstobs,lastobs);
11399: anint=matrix(1,maxwav,firstobs,lastobs);
11400: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11401: tab=ivector(1,NCOVMAX);
1.144 brouard 11402: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11403: 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 11404:
1.136 brouard 11405: /* Reads data from file datafile */
11406: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11407: goto end;
11408:
11409: /* Calculation of the number of parameters from char model */
1.234 brouard 11410: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11411: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11412: k=3 V4 Tvar[k=3]= 4 (from V4)
11413: k=2 V1 Tvar[k=2]= 1 (from V1)
11414: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11415: */
11416:
11417: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11418: TvarsDind=ivector(1,NCOVMAX); /* */
11419: TvarsD=ivector(1,NCOVMAX); /* */
11420: TvarsQind=ivector(1,NCOVMAX); /* */
11421: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11422: TvarF=ivector(1,NCOVMAX); /* */
11423: TvarFind=ivector(1,NCOVMAX); /* */
11424: TvarV=ivector(1,NCOVMAX); /* */
11425: TvarVind=ivector(1,NCOVMAX); /* */
11426: TvarA=ivector(1,NCOVMAX); /* */
11427: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11428: TvarFD=ivector(1,NCOVMAX); /* */
11429: TvarFDind=ivector(1,NCOVMAX); /* */
11430: TvarFQ=ivector(1,NCOVMAX); /* */
11431: TvarFQind=ivector(1,NCOVMAX); /* */
11432: TvarVD=ivector(1,NCOVMAX); /* */
11433: TvarVDind=ivector(1,NCOVMAX); /* */
11434: TvarVQ=ivector(1,NCOVMAX); /* */
11435: TvarVQind=ivector(1,NCOVMAX); /* */
11436:
1.230 brouard 11437: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11438: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11439: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11440: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11441: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11442: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11443: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11444: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11445: */
11446: /* For model-covariate k tells which data-covariate to use but
11447: because this model-covariate is a construction we invent a new column
11448: ncovcol + k1
11449: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11450: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11451: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11452: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11453: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11454: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11455: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11456: */
1.145 brouard 11457: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11458: 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 11459: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11460: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11461: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11462: 4 covariates (3 plus signs)
11463: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11464: */
1.230 brouard 11465: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11466: * individual dummy, fixed or varying:
11467: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11468: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11469: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11470: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11471: * Tmodelind[1]@9={9,0,3,2,}*/
11472: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11473: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11474: * individual quantitative, fixed or varying:
11475: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11476: * 3, 1, 0, 0, 0, 0, 0, 0},
11477: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11478: /* Main decodemodel */
11479:
1.187 brouard 11480:
1.223 brouard 11481: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11482: goto end;
11483:
1.137 brouard 11484: if((double)(lastobs-imx)/(double)imx > 1.10){
11485: nbwarn++;
11486: 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);
11487: 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);
11488: }
1.136 brouard 11489: /* if(mle==1){*/
1.137 brouard 11490: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11491: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11492: }
11493:
11494: /*-calculation of age at interview from date of interview and age at death -*/
11495: agev=matrix(1,maxwav,1,imx);
11496:
11497: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11498: goto end;
11499:
1.126 brouard 11500:
1.136 brouard 11501: agegomp=(int)agemin;
1.290 brouard 11502: free_vector(moisnais,firstobs,lastobs);
11503: free_vector(annais,firstobs,lastobs);
1.126 brouard 11504: /* free_matrix(mint,1,maxwav,1,n);
11505: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11506: /* free_vector(moisdc,1,n); */
11507: /* free_vector(andc,1,n); */
1.145 brouard 11508: /* */
11509:
1.126 brouard 11510: wav=ivector(1,imx);
1.214 brouard 11511: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11512: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11513: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11514: 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.*/
11515: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11516: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11517:
11518: /* Concatenates waves */
1.214 brouard 11519: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11520: Death is a valid wave (if date is known).
11521: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11522: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11523: and mw[mi+1][i]. dh depends on stepm.
11524: */
11525:
1.126 brouard 11526: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11527: /* Concatenates waves */
1.145 brouard 11528:
1.290 brouard 11529: free_vector(moisdc,firstobs,lastobs);
11530: free_vector(andc,firstobs,lastobs);
1.215 brouard 11531:
1.126 brouard 11532: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11533: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11534: ncodemax[1]=1;
1.145 brouard 11535: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11536: cptcoveff=0;
1.220 brouard 11537: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11538: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11539: }
11540:
11541: ncovcombmax=pow(2,cptcoveff);
11542: invalidvarcomb=ivector(1, ncovcombmax);
11543: for(i=1;i<ncovcombmax;i++)
11544: invalidvarcomb[i]=0;
11545:
1.211 brouard 11546: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11547: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11548: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11549:
1.200 brouard 11550: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11551: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11552: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11553: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11554: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11555: * (currently 0 or 1) in the data.
11556: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11557: * corresponding modality (h,j).
11558: */
11559:
1.145 brouard 11560: h=0;
11561: /*if (cptcovn > 0) */
1.126 brouard 11562: m=pow(2,cptcoveff);
11563:
1.144 brouard 11564: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11565: * For k=4 covariates, h goes from 1 to m=2**k
11566: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11567: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11568: * h\k 1 2 3 4
1.143 brouard 11569: *______________________________
11570: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11571: * 2 2 1 1 1
11572: * 3 i=2 1 2 1 1
11573: * 4 2 2 1 1
11574: * 5 i=3 1 i=2 1 2 1
11575: * 6 2 1 2 1
11576: * 7 i=4 1 2 2 1
11577: * 8 2 2 2 1
1.197 brouard 11578: * 9 i=5 1 i=3 1 i=2 1 2
11579: * 10 2 1 1 2
11580: * 11 i=6 1 2 1 2
11581: * 12 2 2 1 2
11582: * 13 i=7 1 i=4 1 2 2
11583: * 14 2 1 2 2
11584: * 15 i=8 1 2 2 2
11585: * 16 2 2 2 2
1.143 brouard 11586: */
1.212 brouard 11587: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11588: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11589: * and the value of each covariate?
11590: * V1=1, V2=1, V3=2, V4=1 ?
11591: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11592: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11593: * In order to get the real value in the data, we use nbcode
11594: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11595: * We are keeping this crazy system in order to be able (in the future?)
11596: * to have more than 2 values (0 or 1) for a covariate.
11597: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11598: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11599: * bbbbbbbb
11600: * 76543210
11601: * h-1 00000101 (6-1=5)
1.219 brouard 11602: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11603: * &
11604: * 1 00000001 (1)
1.219 brouard 11605: * 00000000 = 1 & ((h-1) >> (k-1))
11606: * +1= 00000001 =1
1.211 brouard 11607: *
11608: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11609: * h' 1101 =2^3+2^2+0x2^1+2^0
11610: * >>k' 11
11611: * & 00000001
11612: * = 00000001
11613: * +1 = 00000010=2 = codtabm(14,3)
11614: * Reverse h=6 and m=16?
11615: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11616: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11617: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11618: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11619: * V3=decodtabm(14,3,2**4)=2
11620: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11621: *(h-1) >> (j-1) 0011 =13 >> 2
11622: * &1 000000001
11623: * = 000000001
11624: * +1= 000000010 =2
11625: * 2211
11626: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11627: * V3=2
1.220 brouard 11628: * codtabm and decodtabm are identical
1.211 brouard 11629: */
11630:
1.145 brouard 11631:
11632: free_ivector(Ndum,-1,NCOVMAX);
11633:
11634:
1.126 brouard 11635:
1.186 brouard 11636: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11637: strcpy(optionfilegnuplot,optionfilefiname);
11638: if(mle==-3)
1.201 brouard 11639: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11640: strcat(optionfilegnuplot,".gp");
11641:
11642: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11643: printf("Problem with file %s",optionfilegnuplot);
11644: }
11645: else{
1.204 brouard 11646: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11647: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11648: //fprintf(ficgp,"set missing 'NaNq'\n");
11649: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11650: }
11651: /* fclose(ficgp);*/
1.186 brouard 11652:
11653:
11654: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11655:
11656: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11657: if(mle==-3)
1.201 brouard 11658: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11659: strcat(optionfilehtm,".htm");
11660: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11661: printf("Problem with %s \n",optionfilehtm);
11662: exit(0);
1.126 brouard 11663: }
11664:
11665: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11666: strcat(optionfilehtmcov,"-cov.htm");
11667: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11668: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11669: }
11670: else{
11671: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11672: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11673: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11674: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11675: }
11676:
1.213 brouard 11677: 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 11678: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11679: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11680: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11681: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11682: \n\
11683: <hr size=\"2\" color=\"#EC5E5E\">\
11684: <ul><li><h4>Parameter files</h4>\n\
11685: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11686: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11687: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11688: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11689: - Date and time at start: %s</ul>\n",\
11690: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11691: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11692: fileres,fileres,\
11693: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11694: fflush(fichtm);
11695:
11696: strcpy(pathr,path);
11697: strcat(pathr,optionfilefiname);
1.184 brouard 11698: #ifdef WIN32
11699: _chdir(optionfilefiname); /* Move to directory named optionfile */
11700: #else
1.126 brouard 11701: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11702: #endif
11703:
1.126 brouard 11704:
1.220 brouard 11705: /* Calculates basic frequencies. Computes observed prevalence at single age
11706: and for any valid combination of covariates
1.126 brouard 11707: and prints on file fileres'p'. */
1.251 brouard 11708: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11709: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11710:
11711: fprintf(fichtm,"\n");
1.286 brouard 11712: 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 11713: ftol, stepm);
11714: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11715: ncurrv=1;
11716: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11717: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11718: ncurrv=i;
11719: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11720: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 11721: ncurrv=i;
11722: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11723: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 11724: ncurrv=i;
11725: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11726: 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", \
11727: nlstate, ndeath, maxwav, mle, weightopt);
11728:
11729: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11730: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11731:
11732:
11733: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11734: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11735: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11736: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11737: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11738: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11739: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11740: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11741: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11742:
1.126 brouard 11743: /* For Powell, parameters are in a vector p[] starting at p[1]
11744: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11745: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11746:
11747: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11748: /* For mortality only */
1.126 brouard 11749: if (mle==-3){
1.136 brouard 11750: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11751: for(i=1;i<=NDIM;i++)
11752: for(j=1;j<=NDIM;j++)
11753: ximort[i][j]=0.;
1.186 brouard 11754: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 11755: cens=ivector(firstobs,lastobs);
11756: ageexmed=vector(firstobs,lastobs);
11757: agecens=vector(firstobs,lastobs);
11758: dcwave=ivector(firstobs,lastobs);
1.223 brouard 11759:
1.126 brouard 11760: for (i=1; i<=imx; i++){
11761: dcwave[i]=-1;
11762: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11763: if (s[m][i]>nlstate) {
11764: dcwave[i]=m;
11765: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11766: break;
11767: }
1.126 brouard 11768: }
1.226 brouard 11769:
1.126 brouard 11770: for (i=1; i<=imx; i++) {
11771: if (wav[i]>0){
1.226 brouard 11772: ageexmed[i]=agev[mw[1][i]][i];
11773: j=wav[i];
11774: agecens[i]=1.;
11775:
11776: if (ageexmed[i]> 1 && wav[i] > 0){
11777: agecens[i]=agev[mw[j][i]][i];
11778: cens[i]= 1;
11779: }else if (ageexmed[i]< 1)
11780: cens[i]= -1;
11781: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11782: cens[i]=0 ;
1.126 brouard 11783: }
11784: else cens[i]=-1;
11785: }
11786:
11787: for (i=1;i<=NDIM;i++) {
11788: for (j=1;j<=NDIM;j++)
1.226 brouard 11789: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11790: }
11791:
1.145 brouard 11792: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11793: /*printf("%lf %lf", p[1], p[2]);*/
11794:
11795:
1.136 brouard 11796: #ifdef GSL
11797: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11798: #else
1.126 brouard 11799: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11800: #endif
1.201 brouard 11801: strcpy(filerespow,"POW-MORT_");
11802: strcat(filerespow,fileresu);
1.126 brouard 11803: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11804: printf("Problem with resultfile: %s\n", filerespow);
11805: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11806: }
1.136 brouard 11807: #ifdef GSL
11808: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11809: #else
1.126 brouard 11810: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11811: #endif
1.126 brouard 11812: /* for (i=1;i<=nlstate;i++)
11813: for(j=1;j<=nlstate+ndeath;j++)
11814: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11815: */
11816: fprintf(ficrespow,"\n");
1.136 brouard 11817: #ifdef GSL
11818: /* gsl starts here */
11819: T = gsl_multimin_fminimizer_nmsimplex;
11820: gsl_multimin_fminimizer *sfm = NULL;
11821: gsl_vector *ss, *x;
11822: gsl_multimin_function minex_func;
11823:
11824: /* Initial vertex size vector */
11825: ss = gsl_vector_alloc (NDIM);
11826:
11827: if (ss == NULL){
11828: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11829: }
11830: /* Set all step sizes to 1 */
11831: gsl_vector_set_all (ss, 0.001);
11832:
11833: /* Starting point */
1.126 brouard 11834:
1.136 brouard 11835: x = gsl_vector_alloc (NDIM);
11836:
11837: if (x == NULL){
11838: gsl_vector_free(ss);
11839: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11840: }
11841:
11842: /* Initialize method and iterate */
11843: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11844: /* gsl_vector_set(x, 0, 0.0268); */
11845: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11846: gsl_vector_set(x, 0, p[1]);
11847: gsl_vector_set(x, 1, p[2]);
11848:
11849: minex_func.f = &gompertz_f;
11850: minex_func.n = NDIM;
11851: minex_func.params = (void *)&p; /* ??? */
11852:
11853: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11854: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11855:
11856: printf("Iterations beginning .....\n\n");
11857: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11858:
11859: iteri=0;
11860: while (rval == GSL_CONTINUE){
11861: iteri++;
11862: status = gsl_multimin_fminimizer_iterate(sfm);
11863:
11864: if (status) printf("error: %s\n", gsl_strerror (status));
11865: fflush(0);
11866:
11867: if (status)
11868: break;
11869:
11870: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11871: ssval = gsl_multimin_fminimizer_size (sfm);
11872:
11873: if (rval == GSL_SUCCESS)
11874: printf ("converged to a local maximum at\n");
11875:
11876: printf("%5d ", iteri);
11877: for (it = 0; it < NDIM; it++){
11878: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11879: }
11880: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11881: }
11882:
11883: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11884:
11885: gsl_vector_free(x); /* initial values */
11886: gsl_vector_free(ss); /* inital step size */
11887: for (it=0; it<NDIM; it++){
11888: p[it+1]=gsl_vector_get(sfm->x,it);
11889: fprintf(ficrespow," %.12lf", p[it]);
11890: }
11891: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11892: #endif
11893: #ifdef POWELL
11894: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11895: #endif
1.126 brouard 11896: fclose(ficrespow);
11897:
1.203 brouard 11898: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11899:
11900: for(i=1; i <=NDIM; i++)
11901: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11902: matcov[i][j]=matcov[j][i];
1.126 brouard 11903:
11904: printf("\nCovariance matrix\n ");
1.203 brouard 11905: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11906: for(i=1; i <=NDIM; i++) {
11907: for(j=1;j<=NDIM;j++){
1.220 brouard 11908: printf("%f ",matcov[i][j]);
11909: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11910: }
1.203 brouard 11911: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11912: }
11913:
11914: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11915: for (i=1;i<=NDIM;i++) {
1.126 brouard 11916: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11917: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11918: }
1.126 brouard 11919: lsurv=vector(1,AGESUP);
11920: lpop=vector(1,AGESUP);
11921: tpop=vector(1,AGESUP);
11922: lsurv[agegomp]=100000;
11923:
11924: for (k=agegomp;k<=AGESUP;k++) {
11925: agemortsup=k;
11926: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11927: }
11928:
11929: for (k=agegomp;k<agemortsup;k++)
11930: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11931:
11932: for (k=agegomp;k<agemortsup;k++){
11933: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11934: sumlpop=sumlpop+lpop[k];
11935: }
11936:
11937: tpop[agegomp]=sumlpop;
11938: for (k=agegomp;k<(agemortsup-3);k++){
11939: /* tpop[k+1]=2;*/
11940: tpop[k+1]=tpop[k]-lpop[k];
11941: }
11942:
11943:
11944: printf("\nAge lx qx dx Lx Tx e(x)\n");
11945: for (k=agegomp;k<(agemortsup-2);k++)
11946: 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]);
11947:
11948:
11949: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11950: ageminpar=50;
11951: agemaxpar=100;
1.194 brouard 11952: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11953: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11954: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11955: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11956: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11957: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11958: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11959: }else{
11960: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11961: 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 11962: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11963: }
1.201 brouard 11964: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11965: stepm, weightopt,\
11966: model,imx,p,matcov,agemortsup);
11967:
11968: free_vector(lsurv,1,AGESUP);
11969: free_vector(lpop,1,AGESUP);
11970: free_vector(tpop,1,AGESUP);
1.220 brouard 11971: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 11972: free_ivector(dcwave,firstobs,lastobs);
11973: free_vector(agecens,firstobs,lastobs);
11974: free_vector(ageexmed,firstobs,lastobs);
11975: free_ivector(cens,firstobs,lastobs);
1.220 brouard 11976: #ifdef GSL
1.136 brouard 11977: #endif
1.186 brouard 11978: } /* Endof if mle==-3 mortality only */
1.205 brouard 11979: /* Standard */
11980: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11981: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11982: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11983: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11984: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11985: for (k=1; k<=npar;k++)
11986: printf(" %d %8.5f",k,p[k]);
11987: printf("\n");
1.205 brouard 11988: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11989: /* mlikeli uses func not funcone */
1.247 brouard 11990: /* for(i=1;i<nlstate;i++){ */
11991: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11992: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11993: /* } */
1.205 brouard 11994: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11995: }
11996: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11997: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11998: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11999: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12000: }
12001: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12002: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12003: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12004: for (k=1; k<=npar;k++)
12005: printf(" %d %8.5f",k,p[k]);
12006: printf("\n");
12007:
12008: /*--------- results files --------------*/
1.283 brouard 12009: /* 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 12010:
12011:
12012: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12013: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12014: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12015: for(i=1,jk=1; i <=nlstate; i++){
12016: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12017: if (k != i) {
12018: printf("%d%d ",i,k);
12019: fprintf(ficlog,"%d%d ",i,k);
12020: fprintf(ficres,"%1d%1d ",i,k);
12021: for(j=1; j <=ncovmodel; j++){
12022: printf("%12.7f ",p[jk]);
12023: fprintf(ficlog,"%12.7f ",p[jk]);
12024: fprintf(ficres,"%12.7f ",p[jk]);
12025: jk++;
12026: }
12027: printf("\n");
12028: fprintf(ficlog,"\n");
12029: fprintf(ficres,"\n");
12030: }
1.126 brouard 12031: }
12032: }
1.203 brouard 12033: if(mle != 0){
12034: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12035: ftolhess=ftol; /* Usually correct */
1.203 brouard 12036: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12037: 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");
12038: 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");
12039: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12040: for(k=1; k <=(nlstate+ndeath); k++){
12041: if (k != i) {
12042: printf("%d%d ",i,k);
12043: fprintf(ficlog,"%d%d ",i,k);
12044: for(j=1; j <=ncovmodel; j++){
12045: 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]));
12046: 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]));
12047: jk++;
12048: }
12049: printf("\n");
12050: fprintf(ficlog,"\n");
12051: }
12052: }
1.193 brouard 12053: }
1.203 brouard 12054: } /* end of hesscov and Wald tests */
1.225 brouard 12055:
1.203 brouard 12056: /* */
1.126 brouard 12057: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12058: printf("# Scales (for hessian or gradient estimation)\n");
12059: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12060: for(i=1,jk=1; i <=nlstate; i++){
12061: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12062: if (j!=i) {
12063: fprintf(ficres,"%1d%1d",i,j);
12064: printf("%1d%1d",i,j);
12065: fprintf(ficlog,"%1d%1d",i,j);
12066: for(k=1; k<=ncovmodel;k++){
12067: printf(" %.5e",delti[jk]);
12068: fprintf(ficlog," %.5e",delti[jk]);
12069: fprintf(ficres," %.5e",delti[jk]);
12070: jk++;
12071: }
12072: printf("\n");
12073: fprintf(ficlog,"\n");
12074: fprintf(ficres,"\n");
12075: }
1.126 brouard 12076: }
12077: }
12078:
12079: 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 12080: if(mle >= 1) /* To big for the screen */
1.126 brouard 12081: 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");
12082: 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");
12083: /* # 121 Var(a12)\n\ */
12084: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12085: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12086: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12087: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12088: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12089: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12090: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12091:
12092:
12093: /* Just to have a covariance matrix which will be more understandable
12094: even is we still don't want to manage dictionary of variables
12095: */
12096: for(itimes=1;itimes<=2;itimes++){
12097: jj=0;
12098: for(i=1; i <=nlstate; i++){
1.225 brouard 12099: for(j=1; j <=nlstate+ndeath; j++){
12100: if(j==i) continue;
12101: for(k=1; k<=ncovmodel;k++){
12102: jj++;
12103: ca[0]= k+'a'-1;ca[1]='\0';
12104: if(itimes==1){
12105: if(mle>=1)
12106: printf("#%1d%1d%d",i,j,k);
12107: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12108: fprintf(ficres,"#%1d%1d%d",i,j,k);
12109: }else{
12110: if(mle>=1)
12111: printf("%1d%1d%d",i,j,k);
12112: fprintf(ficlog,"%1d%1d%d",i,j,k);
12113: fprintf(ficres,"%1d%1d%d",i,j,k);
12114: }
12115: ll=0;
12116: for(li=1;li <=nlstate; li++){
12117: for(lj=1;lj <=nlstate+ndeath; lj++){
12118: if(lj==li) continue;
12119: for(lk=1;lk<=ncovmodel;lk++){
12120: ll++;
12121: if(ll<=jj){
12122: cb[0]= lk +'a'-1;cb[1]='\0';
12123: if(ll<jj){
12124: if(itimes==1){
12125: if(mle>=1)
12126: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12127: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12128: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12129: }else{
12130: if(mle>=1)
12131: printf(" %.5e",matcov[jj][ll]);
12132: fprintf(ficlog," %.5e",matcov[jj][ll]);
12133: fprintf(ficres," %.5e",matcov[jj][ll]);
12134: }
12135: }else{
12136: if(itimes==1){
12137: if(mle>=1)
12138: printf(" Var(%s%1d%1d)",ca,i,j);
12139: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12140: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12141: }else{
12142: if(mle>=1)
12143: printf(" %.7e",matcov[jj][ll]);
12144: fprintf(ficlog," %.7e",matcov[jj][ll]);
12145: fprintf(ficres," %.7e",matcov[jj][ll]);
12146: }
12147: }
12148: }
12149: } /* end lk */
12150: } /* end lj */
12151: } /* end li */
12152: if(mle>=1)
12153: printf("\n");
12154: fprintf(ficlog,"\n");
12155: fprintf(ficres,"\n");
12156: numlinepar++;
12157: } /* end k*/
12158: } /*end j */
1.126 brouard 12159: } /* end i */
12160: } /* end itimes */
12161:
12162: fflush(ficlog);
12163: fflush(ficres);
1.225 brouard 12164: while(fgets(line, MAXLINE, ficpar)) {
12165: /* If line starts with a # it is a comment */
12166: if (line[0] == '#') {
12167: numlinepar++;
12168: fputs(line,stdout);
12169: fputs(line,ficparo);
12170: fputs(line,ficlog);
12171: continue;
12172: }else
12173: break;
12174: }
12175:
1.209 brouard 12176: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12177: /* ungetc(c,ficpar); */
12178: /* fgets(line, MAXLINE, ficpar); */
12179: /* fputs(line,stdout); */
12180: /* fputs(line,ficparo); */
12181: /* } */
12182: /* ungetc(c,ficpar); */
1.126 brouard 12183:
12184: estepm=0;
1.209 brouard 12185: 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 12186:
12187: if (num_filled != 6) {
12188: 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);
12189: 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);
12190: goto end;
12191: }
12192: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12193: }
12194: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12195: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12196:
1.209 brouard 12197: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12198: if (estepm==0 || estepm < stepm) estepm=stepm;
12199: if (fage <= 2) {
12200: bage = ageminpar;
12201: fage = agemaxpar;
12202: }
12203:
12204: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12205: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12206: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12207:
1.186 brouard 12208: /* Other stuffs, more or less useful */
1.254 brouard 12209: while(fgets(line, MAXLINE, ficpar)) {
12210: /* If line starts with a # it is a comment */
12211: if (line[0] == '#') {
12212: numlinepar++;
12213: fputs(line,stdout);
12214: fputs(line,ficparo);
12215: fputs(line,ficlog);
12216: continue;
12217: }else
12218: break;
12219: }
12220:
12221: 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){
12222:
12223: if (num_filled != 7) {
12224: 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);
12225: 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);
12226: goto end;
12227: }
12228: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12229: 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);
12230: 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);
12231: 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 12232: }
1.254 brouard 12233:
12234: while(fgets(line, MAXLINE, ficpar)) {
12235: /* If line starts with a # it is a comment */
12236: if (line[0] == '#') {
12237: numlinepar++;
12238: fputs(line,stdout);
12239: fputs(line,ficparo);
12240: fputs(line,ficlog);
12241: continue;
12242: }else
12243: break;
1.126 brouard 12244: }
12245:
12246:
12247: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12248: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12249:
1.254 brouard 12250: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12251: if (num_filled != 1) {
12252: 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);
12253: 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);
12254: goto end;
12255: }
12256: printf("pop_based=%d\n",popbased);
12257: fprintf(ficlog,"pop_based=%d\n",popbased);
12258: fprintf(ficparo,"pop_based=%d\n",popbased);
12259: fprintf(ficres,"pop_based=%d\n",popbased);
12260: }
12261:
1.258 brouard 12262: /* Results */
12263: nresult=0;
12264: do{
12265: if(!fgets(line, MAXLINE, ficpar)){
12266: endishere=1;
12267: parameterline=14;
12268: }else if (line[0] == '#') {
12269: /* If line starts with a # it is a comment */
1.254 brouard 12270: numlinepar++;
12271: fputs(line,stdout);
12272: fputs(line,ficparo);
12273: fputs(line,ficlog);
12274: continue;
1.258 brouard 12275: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12276: parameterline=11;
12277: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12278: parameterline=12;
12279: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12280: parameterline=13;
12281: else{
12282: parameterline=14;
1.254 brouard 12283: }
1.258 brouard 12284: switch (parameterline){
12285: case 11:
12286: 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){
12287: if (num_filled != 8) {
12288: 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\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
12289: 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 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
12290: goto end;
12291: }
12292: 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);
12293: 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);
12294: 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);
12295: 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);
12296: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12297: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12298: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
12299:
1.258 brouard 12300: }
1.254 brouard 12301: break;
1.258 brouard 12302: case 12:
12303: /*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);*/
12304: 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){
12305: if (num_filled != 8) {
1.262 brouard 12306: 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);
12307: 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);
1.258 brouard 12308: goto end;
12309: }
12310: 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);
12311: 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);
12312: 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);
12313: 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);
12314: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12315: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12316: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.258 brouard 12317: }
1.230 brouard 12318: break;
1.258 brouard 12319: case 13:
12320: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12321: if (num_filled == 0){
12322: resultline[0]='\0';
12323: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12324: 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);
12325: break;
12326: } else if (num_filled != 1){
12327: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12328: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12329: }
12330: nresult++; /* Sum of resultlines */
12331: printf("Result %d: result=%s\n",nresult, resultline);
12332: if(nresult > MAXRESULTLINES){
12333: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12334: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12335: goto end;
12336: }
12337: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12338: fprintf(ficparo,"result: %s\n",resultline);
12339: fprintf(ficres,"result: %s\n",resultline);
12340: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12341: break;
1.258 brouard 12342: case 14:
1.259 brouard 12343: if(ncovmodel >2 && nresult==0 ){
12344: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12345: goto end;
12346: }
1.259 brouard 12347: break;
1.258 brouard 12348: default:
12349: nresult=1;
12350: decoderesult(".",nresult ); /* No covariate */
12351: }
12352: } /* End switch parameterline */
12353: }while(endishere==0); /* End do */
1.126 brouard 12354:
1.230 brouard 12355: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12356: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12357:
12358: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12359: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12360: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12361: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12362: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12363: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12364: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12365: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12366: }else{
1.270 brouard 12367: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12368: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12369: }
12370: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12371: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.273 brouard 12372: jprev1,mprev1,anprev1,dateprev1, dateproj1, dateback1,jprev2,mprev2,anprev2,dateprev2,dateproj2, dateback2);
1.220 brouard 12373:
1.225 brouard 12374: /*------------ free_vector -------------*/
12375: /* chdir(path); */
1.220 brouard 12376:
1.215 brouard 12377: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12378: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12379: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12380: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12381: free_lvector(num,firstobs,lastobs);
12382: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12383: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12384: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12385: fclose(ficparo);
12386: fclose(ficres);
1.220 brouard 12387:
12388:
1.186 brouard 12389: /* Other results (useful)*/
1.220 brouard 12390:
12391:
1.126 brouard 12392: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12393: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12394: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12395: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12396: fclose(ficrespl);
12397:
12398: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12399: /*#include "hpijx.h"*/
12400: hPijx(p, bage, fage);
1.145 brouard 12401: fclose(ficrespij);
1.227 brouard 12402:
1.220 brouard 12403: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12404: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12405: k=1;
1.126 brouard 12406: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12407:
1.269 brouard 12408: /* Prevalence for each covariate combination in probs[age][status][cov] */
12409: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12410: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12411: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12412: for(k=1;k<=ncovcombmax;k++)
12413: probs[i][j][k]=0.;
1.269 brouard 12414: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12415: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12416: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12417: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12418: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12419: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12420: for(k=1;k<=ncovcombmax;k++)
12421: mobaverages[i][j][k]=0.;
1.219 brouard 12422: mobaverage=mobaverages;
12423: if (mobilav!=0) {
1.235 brouard 12424: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12425: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12426: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12427: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12428: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12429: }
1.269 brouard 12430: } else if (mobilavproj !=0) {
1.235 brouard 12431: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12432: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12433: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12434: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12435: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12436: }
1.269 brouard 12437: }else{
12438: printf("Internal error moving average\n");
12439: fflush(stdout);
12440: exit(1);
1.219 brouard 12441: }
12442: }/* end if moving average */
1.227 brouard 12443:
1.126 brouard 12444: /*---------- Forecasting ------------------*/
12445: if(prevfcast==1){
12446: /* if(stepm ==1){*/
1.269 brouard 12447: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12448: }
1.269 brouard 12449:
12450: /* Backcasting */
1.217 brouard 12451: if(backcast==1){
1.219 brouard 12452: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12453: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12454: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12455:
12456: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12457:
12458: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12459:
1.219 brouard 12460: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12461: fclose(ficresplb);
12462:
1.222 brouard 12463: hBijx(p, bage, fage, mobaverage);
12464: fclose(ficrespijb);
1.219 brouard 12465:
1.269 brouard 12466: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12467: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12468: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12469:
12470:
1.269 brouard 12471: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12472: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12473: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12474: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12475: } /* end Backcasting */
1.268 brouard 12476:
1.186 brouard 12477:
12478: /* ------ Other prevalence ratios------------ */
1.126 brouard 12479:
1.215 brouard 12480: free_ivector(wav,1,imx);
12481: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12482: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12483: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12484:
12485:
1.127 brouard 12486: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12487:
1.201 brouard 12488: strcpy(filerese,"E_");
12489: strcat(filerese,fileresu);
1.126 brouard 12490: if((ficreseij=fopen(filerese,"w"))==NULL) {
12491: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12492: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12493: }
1.208 brouard 12494: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12495: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12496:
12497: pstamp(ficreseij);
1.219 brouard 12498:
1.235 brouard 12499: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12500: if (cptcovn < 1){i1=1;}
12501:
12502: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12503: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12504: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12505: continue;
1.219 brouard 12506: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12507: printf("\n#****** ");
1.225 brouard 12508: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12509: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12510: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12511: }
12512: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12513: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12514: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12515: }
12516: fprintf(ficreseij,"******\n");
1.235 brouard 12517: printf("******\n");
1.219 brouard 12518:
12519: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12520: oldm=oldms;savm=savms;
1.235 brouard 12521: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12522:
1.219 brouard 12523: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12524: }
12525: fclose(ficreseij);
1.208 brouard 12526: printf("done evsij\n");fflush(stdout);
12527: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12528:
1.218 brouard 12529:
1.227 brouard 12530: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12531:
1.201 brouard 12532: strcpy(filerest,"T_");
12533: strcat(filerest,fileresu);
1.127 brouard 12534: if((ficrest=fopen(filerest,"w"))==NULL) {
12535: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12536: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12537: }
1.208 brouard 12538: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12539: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12540: strcpy(fileresstde,"STDE_");
12541: strcat(fileresstde,fileresu);
1.126 brouard 12542: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12543: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12544: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12545: }
1.227 brouard 12546: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12547: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12548:
1.201 brouard 12549: strcpy(filerescve,"CVE_");
12550: strcat(filerescve,fileresu);
1.126 brouard 12551: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12552: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12553: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12554: }
1.227 brouard 12555: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12556: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12557:
1.201 brouard 12558: strcpy(fileresv,"V_");
12559: strcat(fileresv,fileresu);
1.126 brouard 12560: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12561: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12562: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12563: }
1.227 brouard 12564: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12565: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12566:
1.235 brouard 12567: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12568: if (cptcovn < 1){i1=1;}
12569:
12570: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12571: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12572: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12573: continue;
1.242 brouard 12574: printf("\n#****** Result for:");
12575: fprintf(ficrest,"\n#****** Result for:");
12576: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12577: for(j=1;j<=cptcoveff;j++){
12578: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12579: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12580: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12581: }
1.235 brouard 12582: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12583: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12584: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12585: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12586: }
1.208 brouard 12587: fprintf(ficrest,"******\n");
1.227 brouard 12588: fprintf(ficlog,"******\n");
12589: printf("******\n");
1.208 brouard 12590:
12591: fprintf(ficresstdeij,"\n#****** ");
12592: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12593: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12594: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12595: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12596: }
1.235 brouard 12597: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12598: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12599: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12600: }
1.208 brouard 12601: fprintf(ficresstdeij,"******\n");
12602: fprintf(ficrescveij,"******\n");
12603:
12604: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12605: /* pstamp(ficresvij); */
1.225 brouard 12606: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12607: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12608: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12609: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12610: }
1.208 brouard 12611: fprintf(ficresvij,"******\n");
12612:
12613: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12614: oldm=oldms;savm=savms;
1.235 brouard 12615: printf(" cvevsij ");
12616: fprintf(ficlog, " cvevsij ");
12617: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12618: printf(" end cvevsij \n ");
12619: fprintf(ficlog, " end cvevsij \n ");
12620:
12621: /*
12622: */
12623: /* goto endfree; */
12624:
12625: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12626: pstamp(ficrest);
12627:
1.269 brouard 12628: epj=vector(1,nlstate+1);
1.208 brouard 12629: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12630: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12631: cptcod= 0; /* To be deleted */
12632: printf("varevsij vpopbased=%d \n",vpopbased);
12633: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12634: 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 12635: 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 ");
12636: if(vpopbased==1)
12637: 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);
12638: else
1.288 brouard 12639: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12640: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12641: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12642: fprintf(ficrest,"\n");
12643: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 12644: printf("Computing age specific forward period (stable) prevalences in each health state \n");
12645: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12646: for(age=bage; age <=fage ;age++){
1.235 brouard 12647: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12648: if (vpopbased==1) {
12649: if(mobilav ==0){
12650: for(i=1; i<=nlstate;i++)
12651: prlim[i][i]=probs[(int)age][i][k];
12652: }else{ /* mobilav */
12653: for(i=1; i<=nlstate;i++)
12654: prlim[i][i]=mobaverage[(int)age][i][k];
12655: }
12656: }
1.219 brouard 12657:
1.227 brouard 12658: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12659: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12660: /* printf(" age %4.0f ",age); */
12661: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12662: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12663: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12664: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12665: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12666: }
12667: epj[nlstate+1] +=epj[j];
12668: }
12669: /* printf(" age %4.0f \n",age); */
1.219 brouard 12670:
1.227 brouard 12671: for(i=1, vepp=0.;i <=nlstate;i++)
12672: for(j=1;j <=nlstate;j++)
12673: vepp += vareij[i][j][(int)age];
12674: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12675: for(j=1;j <=nlstate;j++){
12676: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12677: }
12678: fprintf(ficrest,"\n");
12679: }
1.208 brouard 12680: } /* End vpopbased */
1.269 brouard 12681: free_vector(epj,1,nlstate+1);
1.208 brouard 12682: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12683: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12684: printf("done selection\n");fflush(stdout);
12685: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12686:
1.235 brouard 12687: } /* End k selection */
1.227 brouard 12688:
12689: printf("done State-specific expectancies\n");fflush(stdout);
12690: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12691:
1.288 brouard 12692: /* variance-covariance of forward period prevalence*/
1.269 brouard 12693: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12694:
1.227 brouard 12695:
1.290 brouard 12696: free_vector(weight,firstobs,lastobs);
1.227 brouard 12697: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 12698: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
12699: free_matrix(anint,1,maxwav,firstobs,lastobs);
12700: free_matrix(mint,1,maxwav,firstobs,lastobs);
12701: free_ivector(cod,firstobs,lastobs);
1.227 brouard 12702: free_ivector(tab,1,NCOVMAX);
12703: fclose(ficresstdeij);
12704: fclose(ficrescveij);
12705: fclose(ficresvij);
12706: fclose(ficrest);
12707: fclose(ficpar);
12708:
12709:
1.126 brouard 12710: /*---------- End : free ----------------*/
1.219 brouard 12711: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12712: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12713: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12714: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12715: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12716: } /* mle==-3 arrives here for freeing */
1.227 brouard 12717: /* endfree:*/
12718: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12719: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12720: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 12721: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
12722: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
12723: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
12724: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 12725: free_matrix(matcov,1,npar,1,npar);
12726: free_matrix(hess,1,npar,1,npar);
12727: /*free_vector(delti,1,npar);*/
12728: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12729: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12730: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12731: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12732:
12733: free_ivector(ncodemax,1,NCOVMAX);
12734: free_ivector(ncodemaxwundef,1,NCOVMAX);
12735: free_ivector(Dummy,-1,NCOVMAX);
12736: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12737: free_ivector(DummyV,1,NCOVMAX);
12738: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12739: free_ivector(Typevar,-1,NCOVMAX);
12740: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12741: free_ivector(TvarsQ,1,NCOVMAX);
12742: free_ivector(TvarsQind,1,NCOVMAX);
12743: free_ivector(TvarsD,1,NCOVMAX);
12744: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12745: free_ivector(TvarFD,1,NCOVMAX);
12746: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12747: free_ivector(TvarF,1,NCOVMAX);
12748: free_ivector(TvarFind,1,NCOVMAX);
12749: free_ivector(TvarV,1,NCOVMAX);
12750: free_ivector(TvarVind,1,NCOVMAX);
12751: free_ivector(TvarA,1,NCOVMAX);
12752: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12753: free_ivector(TvarFQ,1,NCOVMAX);
12754: free_ivector(TvarFQind,1,NCOVMAX);
12755: free_ivector(TvarVD,1,NCOVMAX);
12756: free_ivector(TvarVDind,1,NCOVMAX);
12757: free_ivector(TvarVQ,1,NCOVMAX);
12758: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12759: free_ivector(Tvarsel,1,NCOVMAX);
12760: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12761: free_ivector(Tposprod,1,NCOVMAX);
12762: free_ivector(Tprod,1,NCOVMAX);
12763: free_ivector(Tvaraff,1,NCOVMAX);
12764: free_ivector(invalidvarcomb,1,ncovcombmax);
12765: free_ivector(Tage,1,NCOVMAX);
12766: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12767: free_ivector(TmodelInvind,1,NCOVMAX);
12768: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12769:
12770: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12771: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12772: fflush(fichtm);
12773: fflush(ficgp);
12774:
1.227 brouard 12775:
1.126 brouard 12776: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12777: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12778: 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 12779: }else{
12780: printf("End of Imach\n");
12781: fprintf(ficlog,"End of Imach\n");
12782: }
12783: printf("See log file on %s\n",filelog);
12784: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12785: /*(void) gettimeofday(&end_time,&tzp);*/
12786: rend_time = time(NULL);
12787: end_time = *localtime(&rend_time);
12788: /* tml = *localtime(&end_time.tm_sec); */
12789: strcpy(strtend,asctime(&end_time));
1.126 brouard 12790: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12791: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12792: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12793:
1.157 brouard 12794: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12795: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12796: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12797: /* printf("Total time was %d uSec.\n", total_usecs);*/
12798: /* if(fileappend(fichtm,optionfilehtm)){ */
12799: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12800: fclose(fichtm);
12801: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12802: fclose(fichtmcov);
12803: fclose(ficgp);
12804: fclose(ficlog);
12805: /*------ End -----------*/
1.227 brouard 12806:
1.281 brouard 12807:
12808: /* Executes gnuplot */
1.227 brouard 12809:
12810: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12811: #ifdef WIN32
1.227 brouard 12812: if (_chdir(pathcd) != 0)
12813: printf("Can't move to directory %s!\n",path);
12814: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12815: #else
1.227 brouard 12816: if(chdir(pathcd) != 0)
12817: printf("Can't move to directory %s!\n", path);
12818: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12819: #endif
1.126 brouard 12820: printf("Current directory %s!\n",pathcd);
12821: /*strcat(plotcmd,CHARSEPARATOR);*/
12822: sprintf(plotcmd,"gnuplot");
1.157 brouard 12823: #ifdef _WIN32
1.126 brouard 12824: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12825: #endif
12826: if(!stat(plotcmd,&info)){
1.158 brouard 12827: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12828: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12829: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12830: }else
12831: strcpy(pplotcmd,plotcmd);
1.157 brouard 12832: #ifdef __unix
1.126 brouard 12833: strcpy(plotcmd,GNUPLOTPROGRAM);
12834: if(!stat(plotcmd,&info)){
1.158 brouard 12835: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12836: }else
12837: strcpy(pplotcmd,plotcmd);
12838: #endif
12839: }else
12840: strcpy(pplotcmd,plotcmd);
12841:
12842: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12843: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 12844: strcpy(pplotcmd,plotcmd);
1.227 brouard 12845:
1.126 brouard 12846: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 12847: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12848: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12849: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 12850: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 12851: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 12852: strcpy(plotcmd,pplotcmd);
12853: }
1.126 brouard 12854: }
1.158 brouard 12855: printf(" Successful, please wait...");
1.126 brouard 12856: while (z[0] != 'q') {
12857: /* chdir(path); */
1.154 brouard 12858: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12859: scanf("%s",z);
12860: /* if (z[0] == 'c') system("./imach"); */
12861: if (z[0] == 'e') {
1.158 brouard 12862: #ifdef __APPLE__
1.152 brouard 12863: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12864: #elif __linux
12865: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12866: #else
1.152 brouard 12867: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12868: #endif
12869: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12870: system(pplotcmd);
1.126 brouard 12871: }
12872: else if (z[0] == 'g') system(plotcmd);
12873: else if (z[0] == 'q') exit(0);
12874: }
1.227 brouard 12875: end:
1.126 brouard 12876: while (z[0] != 'q') {
1.195 brouard 12877: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12878: scanf("%s",z);
12879: }
1.283 brouard 12880: printf("End\n");
1.282 brouard 12881: exit(0);
1.126 brouard 12882: }
FreeBSD-CVSweb <freebsd-cvsweb@FreeBSD.org>
![[BACK]](/icons/small/back.gif){kind=icon}
Return to imach.c CVS log ![[TXT]](/icons/small/text.gif){kind=icon}
![[DIR]](/icons/small/dir.gif){kind=icon}
Up to [Local Repository] / imach / src