Annotation of imach/src/imach.c, revision 1.292
1.292 ! brouard 1: /* $Id: imach.c,v 1.291 2019/05/09 13:44:18 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.292 ! brouard 4: Revision 1.291 2019/05/09 13:44:18 brouard
! 5: Summary: Before ncovmax
! 6:
1.291 brouard 7: Revision 1.290 2019/05/09 13:39:37 brouard
8: Summary: 0.99r18 unlimited number of individuals
9:
10: 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.
11:
1.290 brouard 12: Revision 1.289 2018/12/13 09:16:26 brouard
13: Summary: Bug for young ages (<-30) will be in r17
14:
1.289 brouard 15: Revision 1.288 2018/05/02 20:58:27 brouard
16: Summary: Some bugs fixed
17:
1.288 brouard 18: Revision 1.287 2018/05/01 17:57:25 brouard
19: Summary: Bug fixed by providing frequencies only for non missing covariates
20:
1.287 brouard 21: Revision 1.286 2018/04/27 14:27:04 brouard
22: Summary: some minor bugs
23:
1.286 brouard 24: Revision 1.285 2018/04/21 21:02:16 brouard
25: Summary: Some bugs fixed, valgrind tested
26:
1.285 brouard 27: Revision 1.284 2018/04/20 05:22:13 brouard
28: Summary: Computing mean and stdeviation of fixed quantitative variables
29:
1.284 brouard 30: Revision 1.283 2018/04/19 14:49:16 brouard
31: Summary: Some minor bugs fixed
32:
1.283 brouard 33: Revision 1.282 2018/02/27 22:50:02 brouard
34: *** empty log message ***
35:
1.282 brouard 36: Revision 1.281 2018/02/27 19:25:23 brouard
37: Summary: Adding second argument for quitting
38:
1.281 brouard 39: Revision 1.280 2018/02/21 07:58:13 brouard
40: Summary: 0.99r15
41:
42: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
43:
1.280 brouard 44: Revision 1.279 2017/07/20 13:35:01 brouard
45: Summary: temporary working
46:
1.279 brouard 47: Revision 1.278 2017/07/19 14:09:02 brouard
48: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
49:
1.278 brouard 50: Revision 1.277 2017/07/17 08:53:49 brouard
51: Summary: BOM files can be read now
52:
1.277 brouard 53: Revision 1.276 2017/06/30 15:48:31 brouard
54: Summary: Graphs improvements
55:
1.276 brouard 56: Revision 1.275 2017/06/30 13:39:33 brouard
57: Summary: Saito's color
58:
1.275 brouard 59: Revision 1.274 2017/06/29 09:47:08 brouard
60: Summary: Version 0.99r14
61:
1.274 brouard 62: Revision 1.273 2017/06/27 11:06:02 brouard
63: Summary: More documentation on projections
64:
1.273 brouard 65: Revision 1.272 2017/06/27 10:22:40 brouard
66: Summary: Color of backprojection changed from 6 to 5(yellow)
67:
1.272 brouard 68: Revision 1.271 2017/06/27 10:17:50 brouard
69: Summary: Some bug with rint
70:
1.271 brouard 71: Revision 1.270 2017/05/24 05:45:29 brouard
72: *** empty log message ***
73:
1.270 brouard 74: Revision 1.269 2017/05/23 08:39:25 brouard
75: Summary: Code into subroutine, cleanings
76:
1.269 brouard 77: Revision 1.268 2017/05/18 20:09:32 brouard
78: Summary: backprojection and confidence intervals of backprevalence
79:
1.268 brouard 80: Revision 1.267 2017/05/13 10:25:05 brouard
81: Summary: temporary save for backprojection
82:
1.267 brouard 83: Revision 1.266 2017/05/13 07:26:12 brouard
84: Summary: Version 0.99r13 (improvements and bugs fixed)
85:
1.266 brouard 86: Revision 1.265 2017/04/26 16:22:11 brouard
87: Summary: imach 0.99r13 Some bugs fixed
88:
1.265 brouard 89: Revision 1.264 2017/04/26 06:01:29 brouard
90: Summary: Labels in graphs
91:
1.264 brouard 92: Revision 1.263 2017/04/24 15:23:15 brouard
93: Summary: to save
94:
1.263 brouard 95: Revision 1.262 2017/04/18 16:48:12 brouard
96: *** empty log message ***
97:
1.262 brouard 98: Revision 1.261 2017/04/05 10:14:09 brouard
99: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
100:
1.261 brouard 101: Revision 1.260 2017/04/04 17:46:59 brouard
102: Summary: Gnuplot indexations fixed (humm)
103:
1.260 brouard 104: Revision 1.259 2017/04/04 13:01:16 brouard
105: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
106:
1.259 brouard 107: Revision 1.258 2017/04/03 10:17:47 brouard
108: Summary: Version 0.99r12
109:
110: Some cleanings, conformed with updated documentation.
111:
1.258 brouard 112: Revision 1.257 2017/03/29 16:53:30 brouard
113: Summary: Temp
114:
1.257 brouard 115: Revision 1.256 2017/03/27 05:50:23 brouard
116: Summary: Temporary
117:
1.256 brouard 118: Revision 1.255 2017/03/08 16:02:28 brouard
119: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
120:
1.255 brouard 121: Revision 1.254 2017/03/08 07:13:00 brouard
122: Summary: Fixing data parameter line
123:
1.254 brouard 124: Revision 1.253 2016/12/15 11:59:41 brouard
125: Summary: 0.99 in progress
126:
1.253 brouard 127: Revision 1.252 2016/09/15 21:15:37 brouard
128: *** empty log message ***
129:
1.252 brouard 130: Revision 1.251 2016/09/15 15:01:13 brouard
131: Summary: not working
132:
1.251 brouard 133: Revision 1.250 2016/09/08 16:07:27 brouard
134: Summary: continue
135:
1.250 brouard 136: Revision 1.249 2016/09/07 17:14:18 brouard
137: Summary: Starting values from frequencies
138:
1.249 brouard 139: Revision 1.248 2016/09/07 14:10:18 brouard
140: *** empty log message ***
141:
1.248 brouard 142: Revision 1.247 2016/09/02 11:11:21 brouard
143: *** empty log message ***
144:
1.247 brouard 145: Revision 1.246 2016/09/02 08:49:22 brouard
146: *** empty log message ***
147:
1.246 brouard 148: Revision 1.245 2016/09/02 07:25:01 brouard
149: *** empty log message ***
150:
1.245 brouard 151: Revision 1.244 2016/09/02 07:17:34 brouard
152: *** empty log message ***
153:
1.244 brouard 154: Revision 1.243 2016/09/02 06:45:35 brouard
155: *** empty log message ***
156:
1.243 brouard 157: Revision 1.242 2016/08/30 15:01:20 brouard
158: Summary: Fixing a lots
159:
1.242 brouard 160: Revision 1.241 2016/08/29 17:17:25 brouard
161: Summary: gnuplot problem in Back projection to fix
162:
1.241 brouard 163: Revision 1.240 2016/08/29 07:53:18 brouard
164: Summary: Better
165:
1.240 brouard 166: Revision 1.239 2016/08/26 15:51:03 brouard
167: Summary: Improvement in Powell output in order to copy and paste
168:
169: Author:
170:
1.239 brouard 171: Revision 1.238 2016/08/26 14:23:35 brouard
172: Summary: Starting tests of 0.99
173:
1.238 brouard 174: Revision 1.237 2016/08/26 09:20:19 brouard
175: Summary: to valgrind
176:
1.237 brouard 177: Revision 1.236 2016/08/25 10:50:18 brouard
178: *** empty log message ***
179:
1.236 brouard 180: Revision 1.235 2016/08/25 06:59:23 brouard
181: *** empty log message ***
182:
1.235 brouard 183: Revision 1.234 2016/08/23 16:51:20 brouard
184: *** empty log message ***
185:
1.234 brouard 186: Revision 1.233 2016/08/23 07:40:50 brouard
187: Summary: not working
188:
1.233 brouard 189: Revision 1.232 2016/08/22 14:20:21 brouard
190: Summary: not working
191:
1.232 brouard 192: Revision 1.231 2016/08/22 07:17:15 brouard
193: Summary: not working
194:
1.231 brouard 195: Revision 1.230 2016/08/22 06:55:53 brouard
196: Summary: Not working
197:
1.230 brouard 198: Revision 1.229 2016/07/23 09:45:53 brouard
199: Summary: Completing for func too
200:
1.229 brouard 201: Revision 1.228 2016/07/22 17:45:30 brouard
202: Summary: Fixing some arrays, still debugging
203:
1.227 brouard 204: Revision 1.226 2016/07/12 18:42:34 brouard
205: Summary: temp
206:
1.226 brouard 207: Revision 1.225 2016/07/12 08:40:03 brouard
208: Summary: saving but not running
209:
1.225 brouard 210: Revision 1.224 2016/07/01 13:16:01 brouard
211: Summary: Fixes
212:
1.224 brouard 213: Revision 1.223 2016/02/19 09:23:35 brouard
214: Summary: temporary
215:
1.223 brouard 216: Revision 1.222 2016/02/17 08:14:50 brouard
217: Summary: Probably last 0.98 stable version 0.98r6
218:
1.222 brouard 219: Revision 1.221 2016/02/15 23:35:36 brouard
220: Summary: minor bug
221:
1.220 brouard 222: Revision 1.219 2016/02/15 00:48:12 brouard
223: *** empty log message ***
224:
1.219 brouard 225: Revision 1.218 2016/02/12 11:29:23 brouard
226: Summary: 0.99 Back projections
227:
1.218 brouard 228: Revision 1.217 2015/12/23 17:18:31 brouard
229: Summary: Experimental backcast
230:
1.217 brouard 231: Revision 1.216 2015/12/18 17:32:11 brouard
232: Summary: 0.98r4 Warning and status=-2
233:
234: Version 0.98r4 is now:
235: - displaying an error when status is -1, date of interview unknown and date of death known;
236: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
237: Older changes concerning s=-2, dating from 2005 have been supersed.
238:
1.216 brouard 239: Revision 1.215 2015/12/16 08:52:24 brouard
240: Summary: 0.98r4 working
241:
1.215 brouard 242: Revision 1.214 2015/12/16 06:57:54 brouard
243: Summary: temporary not working
244:
1.214 brouard 245: Revision 1.213 2015/12/11 18:22:17 brouard
246: Summary: 0.98r4
247:
1.213 brouard 248: Revision 1.212 2015/11/21 12:47:24 brouard
249: Summary: minor typo
250:
1.212 brouard 251: Revision 1.211 2015/11/21 12:41:11 brouard
252: Summary: 0.98r3 with some graph of projected cross-sectional
253:
254: Author: Nicolas Brouard
255:
1.211 brouard 256: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 257: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 258: Summary: Adding ftolpl parameter
259: Author: N Brouard
260:
261: We had difficulties to get smoothed confidence intervals. It was due
262: to the period prevalence which wasn't computed accurately. The inner
263: parameter ftolpl is now an outer parameter of the .imach parameter
264: file after estepm. If ftolpl is small 1.e-4 and estepm too,
265: computation are long.
266:
1.209 brouard 267: Revision 1.208 2015/11/17 14:31:57 brouard
268: Summary: temporary
269:
1.208 brouard 270: Revision 1.207 2015/10/27 17:36:57 brouard
271: *** empty log message ***
272:
1.207 brouard 273: Revision 1.206 2015/10/24 07:14:11 brouard
274: *** empty log message ***
275:
1.206 brouard 276: Revision 1.205 2015/10/23 15:50:53 brouard
277: Summary: 0.98r3 some clarification for graphs on likelihood contributions
278:
1.205 brouard 279: Revision 1.204 2015/10/01 16:20:26 brouard
280: Summary: Some new graphs of contribution to likelihood
281:
1.204 brouard 282: Revision 1.203 2015/09/30 17:45:14 brouard
283: Summary: looking at better estimation of the hessian
284:
285: Also a better criteria for convergence to the period prevalence And
286: therefore adding the number of years needed to converge. (The
287: prevalence in any alive state shold sum to one
288:
1.203 brouard 289: Revision 1.202 2015/09/22 19:45:16 brouard
290: Summary: Adding some overall graph on contribution to likelihood. Might change
291:
1.202 brouard 292: Revision 1.201 2015/09/15 17:34:58 brouard
293: Summary: 0.98r0
294:
295: - Some new graphs like suvival functions
296: - Some bugs fixed like model=1+age+V2.
297:
1.201 brouard 298: Revision 1.200 2015/09/09 16:53:55 brouard
299: Summary: Big bug thanks to Flavia
300:
301: Even model=1+age+V2. did not work anymore
302:
1.200 brouard 303: Revision 1.199 2015/09/07 14:09:23 brouard
304: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
305:
1.199 brouard 306: Revision 1.198 2015/09/03 07:14:39 brouard
307: Summary: 0.98q5 Flavia
308:
1.198 brouard 309: Revision 1.197 2015/09/01 18:24:39 brouard
310: *** empty log message ***
311:
1.197 brouard 312: Revision 1.196 2015/08/18 23:17:52 brouard
313: Summary: 0.98q5
314:
1.196 brouard 315: Revision 1.195 2015/08/18 16:28:39 brouard
316: Summary: Adding a hack for testing purpose
317:
318: After reading the title, ftol and model lines, if the comment line has
319: a q, starting with #q, the answer at the end of the run is quit. It
320: permits to run test files in batch with ctest. The former workaround was
321: $ echo q | imach foo.imach
322:
1.195 brouard 323: Revision 1.194 2015/08/18 13:32:00 brouard
324: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
325:
1.194 brouard 326: Revision 1.193 2015/08/04 07:17:42 brouard
327: Summary: 0.98q4
328:
1.193 brouard 329: Revision 1.192 2015/07/16 16:49:02 brouard
330: Summary: Fixing some outputs
331:
1.192 brouard 332: Revision 1.191 2015/07/14 10:00:33 brouard
333: Summary: Some fixes
334:
1.191 brouard 335: Revision 1.190 2015/05/05 08:51:13 brouard
336: Summary: Adding digits in output parameters (7 digits instead of 6)
337:
338: Fix 1+age+.
339:
1.190 brouard 340: Revision 1.189 2015/04/30 14:45:16 brouard
341: Summary: 0.98q2
342:
1.189 brouard 343: Revision 1.188 2015/04/30 08:27:53 brouard
344: *** empty log message ***
345:
1.188 brouard 346: Revision 1.187 2015/04/29 09:11:15 brouard
347: *** empty log message ***
348:
1.187 brouard 349: Revision 1.186 2015/04/23 12:01:52 brouard
350: Summary: V1*age is working now, version 0.98q1
351:
352: Some codes had been disabled in order to simplify and Vn*age was
353: working in the optimization phase, ie, giving correct MLE parameters,
354: but, as usual, outputs were not correct and program core dumped.
355:
1.186 brouard 356: Revision 1.185 2015/03/11 13:26:42 brouard
357: Summary: Inclusion of compile and links command line for Intel Compiler
358:
1.185 brouard 359: Revision 1.184 2015/03/11 11:52:39 brouard
360: Summary: Back from Windows 8. Intel Compiler
361:
1.184 brouard 362: Revision 1.183 2015/03/10 20:34:32 brouard
363: Summary: 0.98q0, trying with directest, mnbrak fixed
364:
365: We use directest instead of original Powell test; probably no
366: incidence on the results, but better justifications;
367: We fixed Numerical Recipes mnbrak routine which was wrong and gave
368: wrong results.
369:
1.183 brouard 370: Revision 1.182 2015/02/12 08:19:57 brouard
371: Summary: Trying to keep directest which seems simpler and more general
372: Author: Nicolas Brouard
373:
1.182 brouard 374: Revision 1.181 2015/02/11 23:22:24 brouard
375: Summary: Comments on Powell added
376:
377: Author:
378:
1.181 brouard 379: Revision 1.180 2015/02/11 17:33:45 brouard
380: Summary: Finishing move from main to function (hpijx and prevalence_limit)
381:
1.180 brouard 382: Revision 1.179 2015/01/04 09:57:06 brouard
383: Summary: back to OS/X
384:
1.179 brouard 385: Revision 1.178 2015/01/04 09:35:48 brouard
386: *** empty log message ***
387:
1.178 brouard 388: Revision 1.177 2015/01/03 18:40:56 brouard
389: Summary: Still testing ilc32 on OSX
390:
1.177 brouard 391: Revision 1.176 2015/01/03 16:45:04 brouard
392: *** empty log message ***
393:
1.176 brouard 394: Revision 1.175 2015/01/03 16:33:42 brouard
395: *** empty log message ***
396:
1.175 brouard 397: Revision 1.174 2015/01/03 16:15:49 brouard
398: Summary: Still in cross-compilation
399:
1.174 brouard 400: Revision 1.173 2015/01/03 12:06:26 brouard
401: Summary: trying to detect cross-compilation
402:
1.173 brouard 403: Revision 1.172 2014/12/27 12:07:47 brouard
404: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
405:
1.172 brouard 406: Revision 1.171 2014/12/23 13:26:59 brouard
407: Summary: Back from Visual C
408:
409: Still problem with utsname.h on Windows
410:
1.171 brouard 411: Revision 1.170 2014/12/23 11:17:12 brouard
412: Summary: Cleaning some \%% back to %%
413:
414: The escape was mandatory for a specific compiler (which one?), but too many warnings.
415:
1.170 brouard 416: Revision 1.169 2014/12/22 23:08:31 brouard
417: Summary: 0.98p
418:
419: Outputs some informations on compiler used, OS etc. Testing on different platforms.
420:
1.169 brouard 421: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 422: Summary: update
1.169 brouard 423:
1.168 brouard 424: Revision 1.167 2014/12/22 13:50:56 brouard
425: Summary: Testing uname and compiler version and if compiled 32 or 64
426:
427: Testing on Linux 64
428:
1.167 brouard 429: Revision 1.166 2014/12/22 11:40:47 brouard
430: *** empty log message ***
431:
1.166 brouard 432: Revision 1.165 2014/12/16 11:20:36 brouard
433: Summary: After compiling on Visual C
434:
435: * imach.c (Module): Merging 1.61 to 1.162
436:
1.165 brouard 437: Revision 1.164 2014/12/16 10:52:11 brouard
438: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
439:
440: * imach.c (Module): Merging 1.61 to 1.162
441:
1.164 brouard 442: Revision 1.163 2014/12/16 10:30:11 brouard
443: * imach.c (Module): Merging 1.61 to 1.162
444:
1.163 brouard 445: Revision 1.162 2014/09/25 11:43:39 brouard
446: Summary: temporary backup 0.99!
447:
1.162 brouard 448: Revision 1.1 2014/09/16 11:06:58 brouard
449: Summary: With some code (wrong) for nlopt
450:
451: Author:
452:
453: Revision 1.161 2014/09/15 20:41:41 brouard
454: Summary: Problem with macro SQR on Intel compiler
455:
1.161 brouard 456: Revision 1.160 2014/09/02 09:24:05 brouard
457: *** empty log message ***
458:
1.160 brouard 459: Revision 1.159 2014/09/01 10:34:10 brouard
460: Summary: WIN32
461: Author: Brouard
462:
1.159 brouard 463: Revision 1.158 2014/08/27 17:11:51 brouard
464: *** empty log message ***
465:
1.158 brouard 466: Revision 1.157 2014/08/27 16:26:55 brouard
467: Summary: Preparing windows Visual studio version
468: Author: Brouard
469:
470: In order to compile on Visual studio, time.h is now correct and time_t
471: and tm struct should be used. difftime should be used but sometimes I
472: just make the differences in raw time format (time(&now).
473: Trying to suppress #ifdef LINUX
474: Add xdg-open for __linux in order to open default browser.
475:
1.157 brouard 476: Revision 1.156 2014/08/25 20:10:10 brouard
477: *** empty log message ***
478:
1.156 brouard 479: Revision 1.155 2014/08/25 18:32:34 brouard
480: Summary: New compile, minor changes
481: Author: Brouard
482:
1.155 brouard 483: Revision 1.154 2014/06/20 17:32:08 brouard
484: Summary: Outputs now all graphs of convergence to period prevalence
485:
1.154 brouard 486: Revision 1.153 2014/06/20 16:45:46 brouard
487: Summary: If 3 live state, convergence to period prevalence on same graph
488: Author: Brouard
489:
1.153 brouard 490: Revision 1.152 2014/06/18 17:54:09 brouard
491: Summary: open browser, use gnuplot on same dir than imach if not found in the path
492:
1.152 brouard 493: Revision 1.151 2014/06/18 16:43:30 brouard
494: *** empty log message ***
495:
1.151 brouard 496: Revision 1.150 2014/06/18 16:42:35 brouard
497: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
498: Author: brouard
499:
1.150 brouard 500: Revision 1.149 2014/06/18 15:51:14 brouard
501: Summary: Some fixes in parameter files errors
502: Author: Nicolas Brouard
503:
1.149 brouard 504: Revision 1.148 2014/06/17 17:38:48 brouard
505: Summary: Nothing new
506: Author: Brouard
507:
508: Just a new packaging for OS/X version 0.98nS
509:
1.148 brouard 510: Revision 1.147 2014/06/16 10:33:11 brouard
511: *** empty log message ***
512:
1.147 brouard 513: Revision 1.146 2014/06/16 10:20:28 brouard
514: Summary: Merge
515: Author: Brouard
516:
517: Merge, before building revised version.
518:
1.146 brouard 519: Revision 1.145 2014/06/10 21:23:15 brouard
520: Summary: Debugging with valgrind
521: Author: Nicolas Brouard
522:
523: Lot of changes in order to output the results with some covariates
524: After the Edimburgh REVES conference 2014, it seems mandatory to
525: improve the code.
526: No more memory valgrind error but a lot has to be done in order to
527: continue the work of splitting the code into subroutines.
528: Also, decodemodel has been improved. Tricode is still not
529: optimal. nbcode should be improved. Documentation has been added in
530: the source code.
531:
1.144 brouard 532: Revision 1.143 2014/01/26 09:45:38 brouard
533: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
534:
535: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
536: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
537:
1.143 brouard 538: Revision 1.142 2014/01/26 03:57:36 brouard
539: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
540:
541: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
542:
1.142 brouard 543: Revision 1.141 2014/01/26 02:42:01 brouard
544: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
545:
1.141 brouard 546: Revision 1.140 2011/09/02 10:37:54 brouard
547: Summary: times.h is ok with mingw32 now.
548:
1.140 brouard 549: Revision 1.139 2010/06/14 07:50:17 brouard
550: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
551: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
552:
1.139 brouard 553: Revision 1.138 2010/04/30 18:19:40 brouard
554: *** empty log message ***
555:
1.138 brouard 556: Revision 1.137 2010/04/29 18:11:38 brouard
557: (Module): Checking covariates for more complex models
558: than V1+V2. A lot of change to be done. Unstable.
559:
1.137 brouard 560: Revision 1.136 2010/04/26 20:30:53 brouard
561: (Module): merging some libgsl code. Fixing computation
562: of likelione (using inter/intrapolation if mle = 0) in order to
563: get same likelihood as if mle=1.
564: Some cleaning of code and comments added.
565:
1.136 brouard 566: Revision 1.135 2009/10/29 15:33:14 brouard
567: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
568:
1.135 brouard 569: Revision 1.134 2009/10/29 13:18:53 brouard
570: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
571:
1.134 brouard 572: Revision 1.133 2009/07/06 10:21:25 brouard
573: just nforces
574:
1.133 brouard 575: Revision 1.132 2009/07/06 08:22:05 brouard
576: Many tings
577:
1.132 brouard 578: Revision 1.131 2009/06/20 16:22:47 brouard
579: Some dimensions resccaled
580:
1.131 brouard 581: Revision 1.130 2009/05/26 06:44:34 brouard
582: (Module): Max Covariate is now set to 20 instead of 8. A
583: lot of cleaning with variables initialized to 0. Trying to make
584: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
585:
1.130 brouard 586: Revision 1.129 2007/08/31 13:49:27 lievre
587: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
588:
1.129 lievre 589: Revision 1.128 2006/06/30 13:02:05 brouard
590: (Module): Clarifications on computing e.j
591:
1.128 brouard 592: Revision 1.127 2006/04/28 18:11:50 brouard
593: (Module): Yes the sum of survivors was wrong since
594: imach-114 because nhstepm was no more computed in the age
595: loop. Now we define nhstepma in the age loop.
596: (Module): In order to speed up (in case of numerous covariates) we
597: compute health expectancies (without variances) in a first step
598: and then all the health expectancies with variances or standard
599: deviation (needs data from the Hessian matrices) which slows the
600: computation.
601: In the future we should be able to stop the program is only health
602: expectancies and graph are needed without standard deviations.
603:
1.127 brouard 604: Revision 1.126 2006/04/28 17:23:28 brouard
605: (Module): Yes the sum of survivors was wrong since
606: imach-114 because nhstepm was no more computed in the age
607: loop. Now we define nhstepma in the age loop.
608: Version 0.98h
609:
1.126 brouard 610: Revision 1.125 2006/04/04 15:20:31 lievre
611: Errors in calculation of health expectancies. Age was not initialized.
612: Forecasting file added.
613:
614: Revision 1.124 2006/03/22 17:13:53 lievre
615: Parameters are printed with %lf instead of %f (more numbers after the comma).
616: The log-likelihood is printed in the log file
617:
618: Revision 1.123 2006/03/20 10:52:43 brouard
619: * imach.c (Module): <title> changed, corresponds to .htm file
620: name. <head> headers where missing.
621:
622: * imach.c (Module): Weights can have a decimal point as for
623: English (a comma might work with a correct LC_NUMERIC environment,
624: otherwise the weight is truncated).
625: Modification of warning when the covariates values are not 0 or
626: 1.
627: Version 0.98g
628:
629: Revision 1.122 2006/03/20 09:45:41 brouard
630: (Module): Weights can have a decimal point as for
631: English (a comma might work with a correct LC_NUMERIC environment,
632: otherwise the weight is truncated).
633: Modification of warning when the covariates values are not 0 or
634: 1.
635: Version 0.98g
636:
637: Revision 1.121 2006/03/16 17:45:01 lievre
638: * imach.c (Module): Comments concerning covariates added
639:
640: * imach.c (Module): refinements in the computation of lli if
641: status=-2 in order to have more reliable computation if stepm is
642: not 1 month. Version 0.98f
643:
644: Revision 1.120 2006/03/16 15:10:38 lievre
645: (Module): refinements in the computation of lli if
646: status=-2 in order to have more reliable computation if stepm is
647: not 1 month. Version 0.98f
648:
649: Revision 1.119 2006/03/15 17:42:26 brouard
650: (Module): Bug if status = -2, the loglikelihood was
651: computed as likelihood omitting the logarithm. Version O.98e
652:
653: Revision 1.118 2006/03/14 18:20:07 brouard
654: (Module): varevsij Comments added explaining the second
655: table of variances if popbased=1 .
656: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
657: (Module): Function pstamp added
658: (Module): Version 0.98d
659:
660: Revision 1.117 2006/03/14 17:16:22 brouard
661: (Module): varevsij Comments added explaining the second
662: table of variances if popbased=1 .
663: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
664: (Module): Function pstamp added
665: (Module): Version 0.98d
666:
667: Revision 1.116 2006/03/06 10:29:27 brouard
668: (Module): Variance-covariance wrong links and
669: varian-covariance of ej. is needed (Saito).
670:
671: Revision 1.115 2006/02/27 12:17:45 brouard
672: (Module): One freematrix added in mlikeli! 0.98c
673:
674: Revision 1.114 2006/02/26 12:57:58 brouard
675: (Module): Some improvements in processing parameter
676: filename with strsep.
677:
678: Revision 1.113 2006/02/24 14:20:24 brouard
679: (Module): Memory leaks checks with valgrind and:
680: datafile was not closed, some imatrix were not freed and on matrix
681: allocation too.
682:
683: Revision 1.112 2006/01/30 09:55:26 brouard
684: (Module): Back to gnuplot.exe instead of wgnuplot.exe
685:
686: Revision 1.111 2006/01/25 20:38:18 brouard
687: (Module): Lots of cleaning and bugs added (Gompertz)
688: (Module): Comments can be added in data file. Missing date values
689: can be a simple dot '.'.
690:
691: Revision 1.110 2006/01/25 00:51:50 brouard
692: (Module): Lots of cleaning and bugs added (Gompertz)
693:
694: Revision 1.109 2006/01/24 19:37:15 brouard
695: (Module): Comments (lines starting with a #) are allowed in data.
696:
697: Revision 1.108 2006/01/19 18:05:42 lievre
698: Gnuplot problem appeared...
699: To be fixed
700:
701: Revision 1.107 2006/01/19 16:20:37 brouard
702: Test existence of gnuplot in imach path
703:
704: Revision 1.106 2006/01/19 13:24:36 brouard
705: Some cleaning and links added in html output
706:
707: Revision 1.105 2006/01/05 20:23:19 lievre
708: *** empty log message ***
709:
710: Revision 1.104 2005/09/30 16:11:43 lievre
711: (Module): sump fixed, loop imx fixed, and simplifications.
712: (Module): If the status is missing at the last wave but we know
713: that the person is alive, then we can code his/her status as -2
714: (instead of missing=-1 in earlier versions) and his/her
715: contributions to the likelihood is 1 - Prob of dying from last
716: health status (= 1-p13= p11+p12 in the easiest case of somebody in
717: the healthy state at last known wave). Version is 0.98
718:
719: Revision 1.103 2005/09/30 15:54:49 lievre
720: (Module): sump fixed, loop imx fixed, and simplifications.
721:
722: Revision 1.102 2004/09/15 17:31:30 brouard
723: Add the possibility to read data file including tab characters.
724:
725: Revision 1.101 2004/09/15 10:38:38 brouard
726: Fix on curr_time
727:
728: Revision 1.100 2004/07/12 18:29:06 brouard
729: Add version for Mac OS X. Just define UNIX in Makefile
730:
731: Revision 1.99 2004/06/05 08:57:40 brouard
732: *** empty log message ***
733:
734: Revision 1.98 2004/05/16 15:05:56 brouard
735: New version 0.97 . First attempt to estimate force of mortality
736: directly from the data i.e. without the need of knowing the health
737: state at each age, but using a Gompertz model: log u =a + b*age .
738: This is the basic analysis of mortality and should be done before any
739: other analysis, in order to test if the mortality estimated from the
740: cross-longitudinal survey is different from the mortality estimated
741: from other sources like vital statistic data.
742:
743: The same imach parameter file can be used but the option for mle should be -3.
744:
1.133 brouard 745: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 746: former routines in order to include the new code within the former code.
747:
748: The output is very simple: only an estimate of the intercept and of
749: the slope with 95% confident intervals.
750:
751: Current limitations:
752: A) Even if you enter covariates, i.e. with the
753: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
754: B) There is no computation of Life Expectancy nor Life Table.
755:
756: Revision 1.97 2004/02/20 13:25:42 lievre
757: Version 0.96d. Population forecasting command line is (temporarily)
758: suppressed.
759:
760: Revision 1.96 2003/07/15 15:38:55 brouard
761: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
762: rewritten within the same printf. Workaround: many printfs.
763:
764: Revision 1.95 2003/07/08 07:54:34 brouard
765: * imach.c (Repository):
766: (Repository): Using imachwizard code to output a more meaningful covariance
767: matrix (cov(a12,c31) instead of numbers.
768:
769: Revision 1.94 2003/06/27 13:00:02 brouard
770: Just cleaning
771:
772: Revision 1.93 2003/06/25 16:33:55 brouard
773: (Module): On windows (cygwin) function asctime_r doesn't
774: exist so I changed back to asctime which exists.
775: (Module): Version 0.96b
776:
777: Revision 1.92 2003/06/25 16:30:45 brouard
778: (Module): On windows (cygwin) function asctime_r doesn't
779: exist so I changed back to asctime which exists.
780:
781: Revision 1.91 2003/06/25 15:30:29 brouard
782: * imach.c (Repository): Duplicated warning errors corrected.
783: (Repository): Elapsed time after each iteration is now output. It
784: helps to forecast when convergence will be reached. Elapsed time
785: is stamped in powell. We created a new html file for the graphs
786: concerning matrix of covariance. It has extension -cov.htm.
787:
788: Revision 1.90 2003/06/24 12:34:15 brouard
789: (Module): Some bugs corrected for windows. Also, when
790: mle=-1 a template is output in file "or"mypar.txt with the design
791: of the covariance matrix to be input.
792:
793: Revision 1.89 2003/06/24 12:30:52 brouard
794: (Module): Some bugs corrected for windows. Also, when
795: mle=-1 a template is output in file "or"mypar.txt with the design
796: of the covariance matrix to be input.
797:
798: Revision 1.88 2003/06/23 17:54:56 brouard
799: * 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.
800:
801: Revision 1.87 2003/06/18 12:26:01 brouard
802: Version 0.96
803:
804: Revision 1.86 2003/06/17 20:04:08 brouard
805: (Module): Change position of html and gnuplot routines and added
806: routine fileappend.
807:
808: Revision 1.85 2003/06/17 13:12:43 brouard
809: * imach.c (Repository): Check when date of death was earlier that
810: current date of interview. It may happen when the death was just
811: prior to the death. In this case, dh was negative and likelihood
812: was wrong (infinity). We still send an "Error" but patch by
813: assuming that the date of death was just one stepm after the
814: interview.
815: (Repository): Because some people have very long ID (first column)
816: we changed int to long in num[] and we added a new lvector for
817: memory allocation. But we also truncated to 8 characters (left
818: truncation)
819: (Repository): No more line truncation errors.
820:
821: Revision 1.84 2003/06/13 21:44:43 brouard
822: * imach.c (Repository): Replace "freqsummary" at a correct
823: place. It differs from routine "prevalence" which may be called
824: many times. Probs is memory consuming and must be used with
825: parcimony.
826: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
827:
828: Revision 1.83 2003/06/10 13:39:11 lievre
829: *** empty log message ***
830:
831: Revision 1.82 2003/06/05 15:57:20 brouard
832: Add log in imach.c and fullversion number is now printed.
833:
834: */
835: /*
836: Interpolated Markov Chain
837:
838: Short summary of the programme:
839:
1.227 brouard 840: This program computes Healthy Life Expectancies or State-specific
841: (if states aren't health statuses) Expectancies from
842: cross-longitudinal data. Cross-longitudinal data consist in:
843:
844: -1- a first survey ("cross") where individuals from different ages
845: are interviewed on their health status or degree of disability (in
846: the case of a health survey which is our main interest)
847:
848: -2- at least a second wave of interviews ("longitudinal") which
849: measure each change (if any) in individual health status. Health
850: expectancies are computed from the time spent in each health state
851: according to a model. More health states you consider, more time is
852: necessary to reach the Maximum Likelihood of the parameters involved
853: in the model. The simplest model is the multinomial logistic model
854: where pij is the probability to be observed in state j at the second
855: wave conditional to be observed in state i at the first
856: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
857: etc , where 'age' is age and 'sex' is a covariate. If you want to
858: have a more complex model than "constant and age", you should modify
859: the program where the markup *Covariates have to be included here
860: again* invites you to do it. More covariates you add, slower the
1.126 brouard 861: convergence.
862:
863: The advantage of this computer programme, compared to a simple
864: multinomial logistic model, is clear when the delay between waves is not
865: identical for each individual. Also, if a individual missed an
866: intermediate interview, the information is lost, but taken into
867: account using an interpolation or extrapolation.
868:
869: hPijx is the probability to be observed in state i at age x+h
870: conditional to the observed state i at age x. The delay 'h' can be
871: split into an exact number (nh*stepm) of unobserved intermediate
872: states. This elementary transition (by month, quarter,
873: semester or year) is modelled as a multinomial logistic. The hPx
874: matrix is simply the matrix product of nh*stepm elementary matrices
875: and the contribution of each individual to the likelihood is simply
876: hPijx.
877:
878: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 879: of the life expectancies. It also computes the period (stable) prevalence.
880:
881: Back prevalence and projections:
1.227 brouard 882:
883: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
884: double agemaxpar, double ftolpl, int *ncvyearp, double
885: dateprev1,double dateprev2, int firstpass, int lastpass, int
886: mobilavproj)
887:
888: Computes the back prevalence limit for any combination of
889: covariate values k at any age between ageminpar and agemaxpar and
890: returns it in **bprlim. In the loops,
891:
892: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
893: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
894:
895: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 896: Computes for any combination of covariates k and any age between bage and fage
897: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
898: oldm=oldms;savm=savms;
1.227 brouard 899:
1.267 brouard 900: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 901: Computes the transition matrix starting at age 'age' over
902: 'nhstepm*hstepm*stepm' months (i.e. until
903: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 904: nhstepm*hstepm matrices.
905:
906: Returns p3mat[i][j][h] after calling
907: p3mat[i][j][h]=matprod2(newm,
908: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
909: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
910: oldm);
1.226 brouard 911:
912: Important routines
913:
914: - func (or funcone), computes logit (pij) distinguishing
915: o fixed variables (single or product dummies or quantitative);
916: o varying variables by:
917: (1) wave (single, product dummies, quantitative),
918: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
919: % fixed dummy (treated) or quantitative (not done because time-consuming);
920: % varying dummy (not done) or quantitative (not done);
921: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
922: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
923: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
924: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
925: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 926:
1.226 brouard 927:
928:
1.133 brouard 929: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
930: Institut national d'études démographiques, Paris.
1.126 brouard 931: This software have been partly granted by Euro-REVES, a concerted action
932: from the European Union.
933: It is copyrighted identically to a GNU software product, ie programme and
934: software can be distributed freely for non commercial use. Latest version
935: can be accessed at http://euroreves.ined.fr/imach .
936:
937: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
938: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
939:
940: **********************************************************************/
941: /*
942: main
943: read parameterfile
944: read datafile
945: concatwav
946: freqsummary
947: if (mle >= 1)
948: mlikeli
949: print results files
950: if mle==1
951: computes hessian
952: read end of parameter file: agemin, agemax, bage, fage, estepm
953: begin-prev-date,...
954: open gnuplot file
955: open html file
1.145 brouard 956: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
957: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
958: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
959: freexexit2 possible for memory heap.
960:
961: h Pij x | pij_nom ficrestpij
962: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
963: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
964: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
965:
966: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
967: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
968: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
969: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
970: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
971:
1.126 brouard 972: forecasting if prevfcast==1 prevforecast call prevalence()
973: health expectancies
974: Variance-covariance of DFLE
975: prevalence()
976: movingaverage()
977: varevsij()
978: if popbased==1 varevsij(,popbased)
979: total life expectancies
980: Variance of period (stable) prevalence
981: end
982: */
983:
1.187 brouard 984: /* #define DEBUG */
985: /* #define DEBUGBRENT */
1.203 brouard 986: /* #define DEBUGLINMIN */
987: /* #define DEBUGHESS */
988: #define DEBUGHESSIJ
1.224 brouard 989: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 990: #define POWELL /* Instead of NLOPT */
1.224 brouard 991: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 992: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
993: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 994:
995: #include <math.h>
996: #include <stdio.h>
997: #include <stdlib.h>
998: #include <string.h>
1.226 brouard 999: #include <ctype.h>
1.159 brouard 1000:
1001: #ifdef _WIN32
1002: #include <io.h>
1.172 brouard 1003: #include <windows.h>
1004: #include <tchar.h>
1.159 brouard 1005: #else
1.126 brouard 1006: #include <unistd.h>
1.159 brouard 1007: #endif
1.126 brouard 1008:
1009: #include <limits.h>
1010: #include <sys/types.h>
1.171 brouard 1011:
1012: #if defined(__GNUC__)
1013: #include <sys/utsname.h> /* Doesn't work on Windows */
1014: #endif
1015:
1.126 brouard 1016: #include <sys/stat.h>
1017: #include <errno.h>
1.159 brouard 1018: /* extern int errno; */
1.126 brouard 1019:
1.157 brouard 1020: /* #ifdef LINUX */
1021: /* #include <time.h> */
1022: /* #include "timeval.h" */
1023: /* #else */
1024: /* #include <sys/time.h> */
1025: /* #endif */
1026:
1.126 brouard 1027: #include <time.h>
1028:
1.136 brouard 1029: #ifdef GSL
1030: #include <gsl/gsl_errno.h>
1031: #include <gsl/gsl_multimin.h>
1032: #endif
1033:
1.167 brouard 1034:
1.162 brouard 1035: #ifdef NLOPT
1036: #include <nlopt.h>
1037: typedef struct {
1038: double (* function)(double [] );
1039: } myfunc_data ;
1040: #endif
1041:
1.126 brouard 1042: /* #include <libintl.h> */
1043: /* #define _(String) gettext (String) */
1044:
1.251 brouard 1045: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1046:
1047: #define GNUPLOTPROGRAM "gnuplot"
1048: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1049: #define FILENAMELENGTH 132
1050:
1051: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1052: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1053:
1.144 brouard 1054: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1055: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1056:
1057: #define NINTERVMAX 8
1.144 brouard 1058: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1059: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.291 brouard 1060: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1061: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1062: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1063: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1064: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1065: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1066: /* #define AGESUP 130 */
1.288 brouard 1067: /* #define AGESUP 150 */
1068: #define AGESUP 200
1.268 brouard 1069: #define AGEINF 0
1.218 brouard 1070: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1071: #define AGEBASE 40
1.194 brouard 1072: #define AGEOVERFLOW 1.e20
1.164 brouard 1073: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1074: #ifdef _WIN32
1075: #define DIRSEPARATOR '\\'
1076: #define CHARSEPARATOR "\\"
1077: #define ODIRSEPARATOR '/'
1078: #else
1.126 brouard 1079: #define DIRSEPARATOR '/'
1080: #define CHARSEPARATOR "/"
1081: #define ODIRSEPARATOR '\\'
1082: #endif
1083:
1.292 ! brouard 1084: /* $Id: imach.c,v 1.291 2019/05/09 13:44:18 brouard Exp $ */
1.126 brouard 1085: /* $State: Exp $ */
1.196 brouard 1086: #include "version.h"
1087: char version[]=__IMACH_VERSION__;
1.283 brouard 1088: 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";
1.292 ! brouard 1089: char fullversion[]="$Revision: 1.291 $ $Date: 2019/05/09 13:44:18 $";
1.126 brouard 1090: char strstart[80];
1091: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1092: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1093: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1094: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1095: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1096: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1097: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1098: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1099: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1100: int cptcovprodnoage=0; /**< Number of covariate products without age */
1101: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1102: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1103: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1104: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1105: int nsd=0; /**< Total number of single dummy variables (output) */
1106: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1107: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1108: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1109: int ntveff=0; /**< ntveff number of effective time varying variables */
1110: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1111: int cptcov=0; /* Working variable */
1.290 brouard 1112: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1113: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1114: int npar=NPARMAX;
1115: int nlstate=2; /* Number of live states */
1116: int ndeath=1; /* Number of dead states */
1.130 brouard 1117: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1118: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1119: int popbased=0;
1120:
1121: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1122: int maxwav=0; /* Maxim number of waves */
1123: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1124: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1125: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1126: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1127: int mle=1, weightopt=0;
1.126 brouard 1128: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1129: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1130: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1131: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1132: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1133: int selected(int kvar); /* Is covariate kvar selected for printing results */
1134:
1.130 brouard 1135: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1136: double **matprod2(); /* test */
1.126 brouard 1137: double **oldm, **newm, **savm; /* Working pointers to matrices */
1138: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1139: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1140:
1.136 brouard 1141: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1142: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1143: FILE *ficlog, *ficrespow;
1.130 brouard 1144: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1145: double fretone; /* Only one call to likelihood */
1.130 brouard 1146: long ipmx=0; /* Number of contributions */
1.126 brouard 1147: double sw; /* Sum of weights */
1148: char filerespow[FILENAMELENGTH];
1149: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1150: FILE *ficresilk;
1151: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1152: FILE *ficresprobmorprev;
1153: FILE *fichtm, *fichtmcov; /* Html File */
1154: FILE *ficreseij;
1155: char filerese[FILENAMELENGTH];
1156: FILE *ficresstdeij;
1157: char fileresstde[FILENAMELENGTH];
1158: FILE *ficrescveij;
1159: char filerescve[FILENAMELENGTH];
1160: FILE *ficresvij;
1161: char fileresv[FILENAMELENGTH];
1.269 brouard 1162:
1.126 brouard 1163: char title[MAXLINE];
1.234 brouard 1164: char model[MAXLINE]; /**< The model line */
1.217 brouard 1165: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1166: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1167: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1168: char command[FILENAMELENGTH];
1169: int outcmd=0;
1170:
1.217 brouard 1171: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1172: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1173: char filelog[FILENAMELENGTH]; /* Log file */
1174: char filerest[FILENAMELENGTH];
1175: char fileregp[FILENAMELENGTH];
1176: char popfile[FILENAMELENGTH];
1177:
1178: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1179:
1.157 brouard 1180: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1181: /* struct timezone tzp; */
1182: /* extern int gettimeofday(); */
1183: struct tm tml, *gmtime(), *localtime();
1184:
1185: extern time_t time();
1186:
1187: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1188: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1189: struct tm tm;
1190:
1.126 brouard 1191: char strcurr[80], strfor[80];
1192:
1193: char *endptr;
1194: long lval;
1195: double dval;
1196:
1197: #define NR_END 1
1198: #define FREE_ARG char*
1199: #define FTOL 1.0e-10
1200:
1201: #define NRANSI
1.240 brouard 1202: #define ITMAX 200
1203: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1204:
1205: #define TOL 2.0e-4
1206:
1207: #define CGOLD 0.3819660
1208: #define ZEPS 1.0e-10
1209: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1210:
1211: #define GOLD 1.618034
1212: #define GLIMIT 100.0
1213: #define TINY 1.0e-20
1214:
1215: static double maxarg1,maxarg2;
1216: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1217: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1218:
1219: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1220: #define rint(a) floor(a+0.5)
1.166 brouard 1221: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1222: #define mytinydouble 1.0e-16
1.166 brouard 1223: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1224: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1225: /* static double dsqrarg; */
1226: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1227: static double sqrarg;
1228: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1229: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1230: int agegomp= AGEGOMP;
1231:
1232: int imx;
1233: int stepm=1;
1234: /* Stepm, step in month: minimum step interpolation*/
1235:
1236: int estepm;
1237: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1238:
1239: int m,nb;
1240: long *num;
1.197 brouard 1241: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1242: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1243: covariate for which somebody answered excluding
1244: undefined. Usually 2: 0 and 1. */
1245: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1246: covariate for which somebody answered including
1247: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1248: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1249: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1250: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1251: double *ageexmed,*agecens;
1252: double dateintmean=0;
1253:
1254: double *weight;
1255: int **s; /* Status */
1.141 brouard 1256: double *agedc;
1.145 brouard 1257: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1258: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1259: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1260: double **coqvar; /* Fixed quantitative covariate nqv */
1261: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1262: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1263: double idx;
1264: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1265: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1266: /*k 1 2 3 4 5 6 7 8 9 */
1267: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1268: /* Tndvar[k] 1 2 3 4 5 */
1269: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1270: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1271: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1272: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1273: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1274: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1275: /* Tprod[i]=k 4 7 */
1276: /* Tage[i]=k 5 8 */
1277: /* */
1278: /* Type */
1279: /* V 1 2 3 4 5 */
1280: /* F F V V V */
1281: /* D Q D D Q */
1282: /* */
1283: int *TvarsD;
1284: int *TvarsDind;
1285: int *TvarsQ;
1286: int *TvarsQind;
1287:
1.235 brouard 1288: #define MAXRESULTLINES 10
1289: int nresult=0;
1.258 brouard 1290: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1291: int TKresult[MAXRESULTLINES];
1.237 brouard 1292: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1293: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1294: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1295: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1296: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1297: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1298:
1.234 brouard 1299: /* 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 1300: 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 */
1301: 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 */
1302: 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 */
1303: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1304: 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 */
1305: 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 1306: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1307: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1308: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1309: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1310: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1311: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1312: 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 */
1313: 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 */
1314:
1.230 brouard 1315: int *Tvarsel; /**< Selected covariates for output */
1316: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1317: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1318: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1319: 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 1320: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1321: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1322: int *Tage;
1.227 brouard 1323: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1324: 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 1325: 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*/
1326: 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 1327: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1328: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1329: int **Tvard;
1330: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1331: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1332: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1333: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1334: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1335: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1336: double *lsurv, *lpop, *tpop;
1337:
1.231 brouard 1338: #define FD 1; /* Fixed dummy covariate */
1339: #define FQ 2; /* Fixed quantitative covariate */
1340: #define FP 3; /* Fixed product covariate */
1341: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1342: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1343: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1344: #define VD 10; /* Varying dummy covariate */
1345: #define VQ 11; /* Varying quantitative covariate */
1346: #define VP 12; /* Varying product covariate */
1347: #define VPDD 13; /* Varying product dummy*dummy covariate */
1348: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1349: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1350: #define APFD 16; /* Age product * fixed dummy covariate */
1351: #define APFQ 17; /* Age product * fixed quantitative covariate */
1352: #define APVD 18; /* Age product * varying dummy covariate */
1353: #define APVQ 19; /* Age product * varying quantitative covariate */
1354:
1355: #define FTYPE 1; /* Fixed covariate */
1356: #define VTYPE 2; /* Varying covariate (loop in wave) */
1357: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1358:
1359: struct kmodel{
1360: int maintype; /* main type */
1361: int subtype; /* subtype */
1362: };
1363: struct kmodel modell[NCOVMAX];
1364:
1.143 brouard 1365: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1366: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1367:
1368: /**************** split *************************/
1369: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1370: {
1371: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1372: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1373: */
1374: char *ss; /* pointer */
1.186 brouard 1375: int l1=0, l2=0; /* length counters */
1.126 brouard 1376:
1377: l1 = strlen(path ); /* length of path */
1378: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1379: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1380: if ( ss == NULL ) { /* no directory, so determine current directory */
1381: strcpy( name, path ); /* we got the fullname name because no directory */
1382: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1383: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1384: /* get current working directory */
1385: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1386: #ifdef WIN32
1387: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1388: #else
1389: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1390: #endif
1.126 brouard 1391: return( GLOCK_ERROR_GETCWD );
1392: }
1393: /* got dirc from getcwd*/
1394: printf(" DIRC = %s \n",dirc);
1.205 brouard 1395: } else { /* strip directory from path */
1.126 brouard 1396: ss++; /* after this, the filename */
1397: l2 = strlen( ss ); /* length of filename */
1398: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1399: strcpy( name, ss ); /* save file name */
1400: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1401: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1402: printf(" DIRC2 = %s \n",dirc);
1403: }
1404: /* We add a separator at the end of dirc if not exists */
1405: l1 = strlen( dirc ); /* length of directory */
1406: if( dirc[l1-1] != DIRSEPARATOR ){
1407: dirc[l1] = DIRSEPARATOR;
1408: dirc[l1+1] = 0;
1409: printf(" DIRC3 = %s \n",dirc);
1410: }
1411: ss = strrchr( name, '.' ); /* find last / */
1412: if (ss >0){
1413: ss++;
1414: strcpy(ext,ss); /* save extension */
1415: l1= strlen( name);
1416: l2= strlen(ss)+1;
1417: strncpy( finame, name, l1-l2);
1418: finame[l1-l2]= 0;
1419: }
1420:
1421: return( 0 ); /* we're done */
1422: }
1423:
1424:
1425: /******************************************/
1426:
1427: void replace_back_to_slash(char *s, char*t)
1428: {
1429: int i;
1430: int lg=0;
1431: i=0;
1432: lg=strlen(t);
1433: for(i=0; i<= lg; i++) {
1434: (s[i] = t[i]);
1435: if (t[i]== '\\') s[i]='/';
1436: }
1437: }
1438:
1.132 brouard 1439: char *trimbb(char *out, char *in)
1.137 brouard 1440: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1441: char *s;
1442: s=out;
1443: while (*in != '\0'){
1.137 brouard 1444: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1445: in++;
1446: }
1447: *out++ = *in++;
1448: }
1449: *out='\0';
1450: return s;
1451: }
1452:
1.187 brouard 1453: /* char *substrchaine(char *out, char *in, char *chain) */
1454: /* { */
1455: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1456: /* char *s, *t; */
1457: /* t=in;s=out; */
1458: /* while ((*in != *chain) && (*in != '\0')){ */
1459: /* *out++ = *in++; */
1460: /* } */
1461:
1462: /* /\* *in matches *chain *\/ */
1463: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1464: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1465: /* } */
1466: /* in--; chain--; */
1467: /* while ( (*in != '\0')){ */
1468: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1469: /* *out++ = *in++; */
1470: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1471: /* } */
1472: /* *out='\0'; */
1473: /* out=s; */
1474: /* return out; */
1475: /* } */
1476: char *substrchaine(char *out, char *in, char *chain)
1477: {
1478: /* Substract chain 'chain' from 'in', return and output 'out' */
1479: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1480:
1481: char *strloc;
1482:
1483: strcpy (out, in);
1484: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1485: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1486: if(strloc != NULL){
1487: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1488: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1489: /* strcpy (strloc, strloc +strlen(chain));*/
1490: }
1491: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1492: return out;
1493: }
1494:
1495:
1.145 brouard 1496: char *cutl(char *blocc, char *alocc, char *in, char occ)
1497: {
1.187 brouard 1498: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1499: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1500: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1501: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1502: */
1.160 brouard 1503: char *s, *t;
1.145 brouard 1504: t=in;s=in;
1505: while ((*in != occ) && (*in != '\0')){
1506: *alocc++ = *in++;
1507: }
1508: if( *in == occ){
1509: *(alocc)='\0';
1510: s=++in;
1511: }
1512:
1513: if (s == t) {/* occ not found */
1514: *(alocc-(in-s))='\0';
1515: in=s;
1516: }
1517: while ( *in != '\0'){
1518: *blocc++ = *in++;
1519: }
1520:
1521: *blocc='\0';
1522: return t;
1523: }
1.137 brouard 1524: char *cutv(char *blocc, char *alocc, char *in, char occ)
1525: {
1.187 brouard 1526: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1527: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1528: gives blocc="abcdef2ghi" and alocc="j".
1529: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1530: */
1531: char *s, *t;
1532: t=in;s=in;
1533: while (*in != '\0'){
1534: while( *in == occ){
1535: *blocc++ = *in++;
1536: s=in;
1537: }
1538: *blocc++ = *in++;
1539: }
1540: if (s == t) /* occ not found */
1541: *(blocc-(in-s))='\0';
1542: else
1543: *(blocc-(in-s)-1)='\0';
1544: in=s;
1545: while ( *in != '\0'){
1546: *alocc++ = *in++;
1547: }
1548:
1549: *alocc='\0';
1550: return s;
1551: }
1552:
1.126 brouard 1553: int nbocc(char *s, char occ)
1554: {
1555: int i,j=0;
1556: int lg=20;
1557: i=0;
1558: lg=strlen(s);
1559: for(i=0; i<= lg; i++) {
1.234 brouard 1560: if (s[i] == occ ) j++;
1.126 brouard 1561: }
1562: return j;
1563: }
1564:
1.137 brouard 1565: /* void cutv(char *u,char *v, char*t, char occ) */
1566: /* { */
1567: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1568: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1569: /* gives u="abcdef2ghi" and v="j" *\/ */
1570: /* int i,lg,j,p=0; */
1571: /* i=0; */
1572: /* lg=strlen(t); */
1573: /* for(j=0; j<=lg-1; j++) { */
1574: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1575: /* } */
1.126 brouard 1576:
1.137 brouard 1577: /* for(j=0; j<p; j++) { */
1578: /* (u[j] = t[j]); */
1579: /* } */
1580: /* u[p]='\0'; */
1.126 brouard 1581:
1.137 brouard 1582: /* for(j=0; j<= lg; j++) { */
1583: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1584: /* } */
1585: /* } */
1.126 brouard 1586:
1.160 brouard 1587: #ifdef _WIN32
1588: char * strsep(char **pp, const char *delim)
1589: {
1590: char *p, *q;
1591:
1592: if ((p = *pp) == NULL)
1593: return 0;
1594: if ((q = strpbrk (p, delim)) != NULL)
1595: {
1596: *pp = q + 1;
1597: *q = '\0';
1598: }
1599: else
1600: *pp = 0;
1601: return p;
1602: }
1603: #endif
1604:
1.126 brouard 1605: /********************** nrerror ********************/
1606:
1607: void nrerror(char error_text[])
1608: {
1609: fprintf(stderr,"ERREUR ...\n");
1610: fprintf(stderr,"%s\n",error_text);
1611: exit(EXIT_FAILURE);
1612: }
1613: /*********************** vector *******************/
1614: double *vector(int nl, int nh)
1615: {
1616: double *v;
1617: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1618: if (!v) nrerror("allocation failure in vector");
1619: return v-nl+NR_END;
1620: }
1621:
1622: /************************ free vector ******************/
1623: void free_vector(double*v, int nl, int nh)
1624: {
1625: free((FREE_ARG)(v+nl-NR_END));
1626: }
1627:
1628: /************************ivector *******************************/
1629: int *ivector(long nl,long nh)
1630: {
1631: int *v;
1632: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1633: if (!v) nrerror("allocation failure in ivector");
1634: return v-nl+NR_END;
1635: }
1636:
1637: /******************free ivector **************************/
1638: void free_ivector(int *v, long nl, long nh)
1639: {
1640: free((FREE_ARG)(v+nl-NR_END));
1641: }
1642:
1643: /************************lvector *******************************/
1644: long *lvector(long nl,long nh)
1645: {
1646: long *v;
1647: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1648: if (!v) nrerror("allocation failure in ivector");
1649: return v-nl+NR_END;
1650: }
1651:
1652: /******************free lvector **************************/
1653: void free_lvector(long *v, long nl, long nh)
1654: {
1655: free((FREE_ARG)(v+nl-NR_END));
1656: }
1657:
1658: /******************* imatrix *******************************/
1659: int **imatrix(long nrl, long nrh, long ncl, long nch)
1660: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1661: {
1662: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1663: int **m;
1664:
1665: /* allocate pointers to rows */
1666: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1667: if (!m) nrerror("allocation failure 1 in matrix()");
1668: m += NR_END;
1669: m -= nrl;
1670:
1671:
1672: /* allocate rows and set pointers to them */
1673: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1674: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1675: m[nrl] += NR_END;
1676: m[nrl] -= ncl;
1677:
1678: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1679:
1680: /* return pointer to array of pointers to rows */
1681: return m;
1682: }
1683:
1684: /****************** free_imatrix *************************/
1685: void free_imatrix(m,nrl,nrh,ncl,nch)
1686: int **m;
1687: long nch,ncl,nrh,nrl;
1688: /* free an int matrix allocated by imatrix() */
1689: {
1690: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1691: free((FREE_ARG) (m+nrl-NR_END));
1692: }
1693:
1694: /******************* matrix *******************************/
1695: double **matrix(long nrl, long nrh, long ncl, long nch)
1696: {
1697: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1698: double **m;
1699:
1700: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1701: if (!m) nrerror("allocation failure 1 in matrix()");
1702: m += NR_END;
1703: m -= nrl;
1704:
1705: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1706: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1707: m[nrl] += NR_END;
1708: m[nrl] -= ncl;
1709:
1710: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1711: return m;
1.145 brouard 1712: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1713: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1714: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1715: */
1716: }
1717:
1718: /*************************free matrix ************************/
1719: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1720: {
1721: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1722: free((FREE_ARG)(m+nrl-NR_END));
1723: }
1724:
1725: /******************* ma3x *******************************/
1726: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1727: {
1728: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1729: double ***m;
1730:
1731: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1732: if (!m) nrerror("allocation failure 1 in matrix()");
1733: m += NR_END;
1734: m -= nrl;
1735:
1736: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1737: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1738: m[nrl] += NR_END;
1739: m[nrl] -= ncl;
1740:
1741: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1742:
1743: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1744: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1745: m[nrl][ncl] += NR_END;
1746: m[nrl][ncl] -= nll;
1747: for (j=ncl+1; j<=nch; j++)
1748: m[nrl][j]=m[nrl][j-1]+nlay;
1749:
1750: for (i=nrl+1; i<=nrh; i++) {
1751: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1752: for (j=ncl+1; j<=nch; j++)
1753: m[i][j]=m[i][j-1]+nlay;
1754: }
1755: return m;
1756: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1757: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1758: */
1759: }
1760:
1761: /*************************free ma3x ************************/
1762: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1763: {
1764: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1765: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1766: free((FREE_ARG)(m+nrl-NR_END));
1767: }
1768:
1769: /*************** function subdirf ***********/
1770: char *subdirf(char fileres[])
1771: {
1772: /* Caution optionfilefiname is hidden */
1773: strcpy(tmpout,optionfilefiname);
1774: strcat(tmpout,"/"); /* Add to the right */
1775: strcat(tmpout,fileres);
1776: return tmpout;
1777: }
1778:
1779: /*************** function subdirf2 ***********/
1780: char *subdirf2(char fileres[], char *preop)
1781: {
1782:
1783: /* Caution optionfilefiname is hidden */
1784: strcpy(tmpout,optionfilefiname);
1785: strcat(tmpout,"/");
1786: strcat(tmpout,preop);
1787: strcat(tmpout,fileres);
1788: return tmpout;
1789: }
1790:
1791: /*************** function subdirf3 ***********/
1792: char *subdirf3(char fileres[], char *preop, char *preop2)
1793: {
1794:
1795: /* Caution optionfilefiname is hidden */
1796: strcpy(tmpout,optionfilefiname);
1797: strcat(tmpout,"/");
1798: strcat(tmpout,preop);
1799: strcat(tmpout,preop2);
1800: strcat(tmpout,fileres);
1801: return tmpout;
1802: }
1.213 brouard 1803:
1804: /*************** function subdirfext ***********/
1805: char *subdirfext(char fileres[], char *preop, char *postop)
1806: {
1807:
1808: strcpy(tmpout,preop);
1809: strcat(tmpout,fileres);
1810: strcat(tmpout,postop);
1811: return tmpout;
1812: }
1.126 brouard 1813:
1.213 brouard 1814: /*************** function subdirfext3 ***********/
1815: char *subdirfext3(char fileres[], char *preop, char *postop)
1816: {
1817:
1818: /* Caution optionfilefiname is hidden */
1819: strcpy(tmpout,optionfilefiname);
1820: strcat(tmpout,"/");
1821: strcat(tmpout,preop);
1822: strcat(tmpout,fileres);
1823: strcat(tmpout,postop);
1824: return tmpout;
1825: }
1826:
1.162 brouard 1827: char *asc_diff_time(long time_sec, char ascdiff[])
1828: {
1829: long sec_left, days, hours, minutes;
1830: days = (time_sec) / (60*60*24);
1831: sec_left = (time_sec) % (60*60*24);
1832: hours = (sec_left) / (60*60) ;
1833: sec_left = (sec_left) %(60*60);
1834: minutes = (sec_left) /60;
1835: sec_left = (sec_left) % (60);
1836: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1837: return ascdiff;
1838: }
1839:
1.126 brouard 1840: /***************** f1dim *************************/
1841: extern int ncom;
1842: extern double *pcom,*xicom;
1843: extern double (*nrfunc)(double []);
1844:
1845: double f1dim(double x)
1846: {
1847: int j;
1848: double f;
1849: double *xt;
1850:
1851: xt=vector(1,ncom);
1852: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1853: f=(*nrfunc)(xt);
1854: free_vector(xt,1,ncom);
1855: return f;
1856: }
1857:
1858: /*****************brent *************************/
1859: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1860: {
1861: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1862: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1863: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1864: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1865: * returned function value.
1866: */
1.126 brouard 1867: int iter;
1868: double a,b,d,etemp;
1.159 brouard 1869: double fu=0,fv,fw,fx;
1.164 brouard 1870: double ftemp=0.;
1.126 brouard 1871: double p,q,r,tol1,tol2,u,v,w,x,xm;
1872: double e=0.0;
1873:
1874: a=(ax < cx ? ax : cx);
1875: b=(ax > cx ? ax : cx);
1876: x=w=v=bx;
1877: fw=fv=fx=(*f)(x);
1878: for (iter=1;iter<=ITMAX;iter++) {
1879: xm=0.5*(a+b);
1880: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1881: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1882: printf(".");fflush(stdout);
1883: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1884: #ifdef DEBUGBRENT
1.126 brouard 1885: 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);
1886: 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);
1887: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1888: #endif
1889: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1890: *xmin=x;
1891: return fx;
1892: }
1893: ftemp=fu;
1894: if (fabs(e) > tol1) {
1895: r=(x-w)*(fx-fv);
1896: q=(x-v)*(fx-fw);
1897: p=(x-v)*q-(x-w)*r;
1898: q=2.0*(q-r);
1899: if (q > 0.0) p = -p;
1900: q=fabs(q);
1901: etemp=e;
1902: e=d;
1903: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1904: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1905: else {
1.224 brouard 1906: d=p/q;
1907: u=x+d;
1908: if (u-a < tol2 || b-u < tol2)
1909: d=SIGN(tol1,xm-x);
1.126 brouard 1910: }
1911: } else {
1912: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1913: }
1914: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1915: fu=(*f)(u);
1916: if (fu <= fx) {
1917: if (u >= x) a=x; else b=x;
1918: SHFT(v,w,x,u)
1.183 brouard 1919: SHFT(fv,fw,fx,fu)
1920: } else {
1921: if (u < x) a=u; else b=u;
1922: if (fu <= fw || w == x) {
1.224 brouard 1923: v=w;
1924: w=u;
1925: fv=fw;
1926: fw=fu;
1.183 brouard 1927: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1928: v=u;
1929: fv=fu;
1.183 brouard 1930: }
1931: }
1.126 brouard 1932: }
1933: nrerror("Too many iterations in brent");
1934: *xmin=x;
1935: return fx;
1936: }
1937:
1938: /****************** mnbrak ***********************/
1939:
1940: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1941: double (*func)(double))
1.183 brouard 1942: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1943: the downhill direction (defined by the function as evaluated at the initial points) and returns
1944: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1945: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1946: */
1.126 brouard 1947: double ulim,u,r,q, dum;
1948: double fu;
1.187 brouard 1949:
1950: double scale=10.;
1951: int iterscale=0;
1952:
1953: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1954: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1955:
1956:
1957: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1958: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1959: /* *bx = *ax - (*ax - *bx)/scale; */
1960: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1961: /* } */
1962:
1.126 brouard 1963: if (*fb > *fa) {
1964: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1965: SHFT(dum,*fb,*fa,dum)
1966: }
1.126 brouard 1967: *cx=(*bx)+GOLD*(*bx-*ax);
1968: *fc=(*func)(*cx);
1.183 brouard 1969: #ifdef DEBUG
1.224 brouard 1970: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1971: 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 1972: #endif
1.224 brouard 1973: 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 1974: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1975: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1976: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1977: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1978: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1979: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1980: fu=(*func)(u);
1.163 brouard 1981: #ifdef DEBUG
1982: /* f(x)=A(x-u)**2+f(u) */
1983: double A, fparabu;
1984: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1985: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1986: 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);
1987: 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 1988: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1989: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1990: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1991: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1992: #endif
1.184 brouard 1993: #ifdef MNBRAKORIGINAL
1.183 brouard 1994: #else
1.191 brouard 1995: /* if (fu > *fc) { */
1996: /* #ifdef DEBUG */
1997: /* printf("mnbrak4 fu > fc \n"); */
1998: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1999: /* #endif */
2000: /* /\* 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 *\\/ *\/ */
2001: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2002: /* dum=u; /\* Shifting c and u *\/ */
2003: /* u = *cx; */
2004: /* *cx = dum; */
2005: /* dum = fu; */
2006: /* fu = *fc; */
2007: /* *fc =dum; */
2008: /* } else { /\* end *\/ */
2009: /* #ifdef DEBUG */
2010: /* printf("mnbrak3 fu < fc \n"); */
2011: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2012: /* #endif */
2013: /* dum=u; /\* Shifting c and u *\/ */
2014: /* u = *cx; */
2015: /* *cx = dum; */
2016: /* dum = fu; */
2017: /* fu = *fc; */
2018: /* *fc =dum; */
2019: /* } */
1.224 brouard 2020: #ifdef DEBUGMNBRAK
2021: double A, fparabu;
2022: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2023: fparabu= *fa - A*(*ax-u)*(*ax-u);
2024: 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);
2025: 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 2026: #endif
1.191 brouard 2027: dum=u; /* Shifting c and u */
2028: u = *cx;
2029: *cx = dum;
2030: dum = fu;
2031: fu = *fc;
2032: *fc =dum;
1.183 brouard 2033: #endif
1.162 brouard 2034: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2035: #ifdef DEBUG
1.224 brouard 2036: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2037: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2038: #endif
1.126 brouard 2039: fu=(*func)(u);
2040: if (fu < *fc) {
1.183 brouard 2041: #ifdef DEBUG
1.224 brouard 2042: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2043: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2044: #endif
2045: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2046: SHFT(*fb,*fc,fu,(*func)(u))
2047: #ifdef DEBUG
2048: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2049: #endif
2050: }
1.162 brouard 2051: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2052: #ifdef DEBUG
1.224 brouard 2053: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2054: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2055: #endif
1.126 brouard 2056: u=ulim;
2057: fu=(*func)(u);
1.183 brouard 2058: } else { /* u could be left to b (if r > q parabola has a maximum) */
2059: #ifdef DEBUG
1.224 brouard 2060: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2061: 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 2062: #endif
1.126 brouard 2063: u=(*cx)+GOLD*(*cx-*bx);
2064: fu=(*func)(u);
1.224 brouard 2065: #ifdef DEBUG
2066: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2067: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2068: #endif
1.183 brouard 2069: } /* end tests */
1.126 brouard 2070: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2071: SHFT(*fa,*fb,*fc,fu)
2072: #ifdef DEBUG
1.224 brouard 2073: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2074: 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 2075: #endif
2076: } /* 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 2077: }
2078:
2079: /*************** linmin ************************/
1.162 brouard 2080: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2081: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2082: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2083: the value of func at the returned location p . This is actually all accomplished by calling the
2084: routines mnbrak and brent .*/
1.126 brouard 2085: int ncom;
2086: double *pcom,*xicom;
2087: double (*nrfunc)(double []);
2088:
1.224 brouard 2089: #ifdef LINMINORIGINAL
1.126 brouard 2090: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2091: #else
2092: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2093: #endif
1.126 brouard 2094: {
2095: double brent(double ax, double bx, double cx,
2096: double (*f)(double), double tol, double *xmin);
2097: double f1dim(double x);
2098: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2099: double *fc, double (*func)(double));
2100: int j;
2101: double xx,xmin,bx,ax;
2102: double fx,fb,fa;
1.187 brouard 2103:
1.203 brouard 2104: #ifdef LINMINORIGINAL
2105: #else
2106: double scale=10., axs, xxs; /* Scale added for infinity */
2107: #endif
2108:
1.126 brouard 2109: ncom=n;
2110: pcom=vector(1,n);
2111: xicom=vector(1,n);
2112: nrfunc=func;
2113: for (j=1;j<=n;j++) {
2114: pcom[j]=p[j];
1.202 brouard 2115: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2116: }
1.187 brouard 2117:
1.203 brouard 2118: #ifdef LINMINORIGINAL
2119: xx=1.;
2120: #else
2121: axs=0.0;
2122: xxs=1.;
2123: do{
2124: xx= xxs;
2125: #endif
1.187 brouard 2126: ax=0.;
2127: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2128: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2129: /* 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)) */
2130: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2131: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2132: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2133: /* 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 2134: #ifdef LINMINORIGINAL
2135: #else
2136: if (fx != fx){
1.224 brouard 2137: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2138: printf("|");
2139: fprintf(ficlog,"|");
1.203 brouard 2140: #ifdef DEBUGLINMIN
1.224 brouard 2141: 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 2142: #endif
2143: }
1.224 brouard 2144: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2145: #endif
2146:
1.191 brouard 2147: #ifdef DEBUGLINMIN
2148: 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 2149: 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 2150: #endif
1.224 brouard 2151: #ifdef LINMINORIGINAL
2152: #else
2153: if(fb == fx){ /* Flat function in the direction */
2154: xmin=xx;
2155: *flat=1;
2156: }else{
2157: *flat=0;
2158: #endif
2159: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2160: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2161: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2162: /* fmin = f(p[j] + xmin * xi[j]) */
2163: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2164: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2165: #ifdef DEBUG
1.224 brouard 2166: 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);
2167: 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);
2168: #endif
2169: #ifdef LINMINORIGINAL
2170: #else
2171: }
1.126 brouard 2172: #endif
1.191 brouard 2173: #ifdef DEBUGLINMIN
2174: printf("linmin end ");
1.202 brouard 2175: fprintf(ficlog,"linmin end ");
1.191 brouard 2176: #endif
1.126 brouard 2177: for (j=1;j<=n;j++) {
1.203 brouard 2178: #ifdef LINMINORIGINAL
2179: xi[j] *= xmin;
2180: #else
2181: #ifdef DEBUGLINMIN
2182: if(xxs <1.0)
2183: printf(" before xi[%d]=%12.8f", j,xi[j]);
2184: #endif
2185: 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) */
2186: #ifdef DEBUGLINMIN
2187: if(xxs <1.0)
2188: 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 );
2189: #endif
2190: #endif
1.187 brouard 2191: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2192: }
1.191 brouard 2193: #ifdef DEBUGLINMIN
1.203 brouard 2194: printf("\n");
1.191 brouard 2195: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2196: 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 2197: for (j=1;j<=n;j++) {
1.202 brouard 2198: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2199: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2200: if(j % ncovmodel == 0){
1.191 brouard 2201: printf("\n");
1.202 brouard 2202: fprintf(ficlog,"\n");
2203: }
1.191 brouard 2204: }
1.203 brouard 2205: #else
1.191 brouard 2206: #endif
1.126 brouard 2207: free_vector(xicom,1,n);
2208: free_vector(pcom,1,n);
2209: }
2210:
2211:
2212: /*************** powell ************************/
1.162 brouard 2213: /*
2214: Minimization of a function func of n variables. Input consists of an initial starting point
2215: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2216: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2217: such that failure to decrease by more than this amount on one iteration signals doneness. On
2218: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2219: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2220: */
1.224 brouard 2221: #ifdef LINMINORIGINAL
2222: #else
2223: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2224: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2225: #endif
1.126 brouard 2226: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2227: double (*func)(double []))
2228: {
1.224 brouard 2229: #ifdef LINMINORIGINAL
2230: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2231: double (*func)(double []));
1.224 brouard 2232: #else
1.241 brouard 2233: void linmin(double p[], double xi[], int n, double *fret,
2234: double (*func)(double []),int *flat);
1.224 brouard 2235: #endif
1.239 brouard 2236: int i,ibig,j,jk,k;
1.126 brouard 2237: double del,t,*pt,*ptt,*xit;
1.181 brouard 2238: double directest;
1.126 brouard 2239: double fp,fptt;
2240: double *xits;
2241: int niterf, itmp;
1.224 brouard 2242: #ifdef LINMINORIGINAL
2243: #else
2244:
2245: flatdir=ivector(1,n);
2246: for (j=1;j<=n;j++) flatdir[j]=0;
2247: #endif
1.126 brouard 2248:
2249: pt=vector(1,n);
2250: ptt=vector(1,n);
2251: xit=vector(1,n);
2252: xits=vector(1,n);
2253: *fret=(*func)(p);
2254: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2255: rcurr_time = time(NULL);
1.126 brouard 2256: for (*iter=1;;++(*iter)) {
1.187 brouard 2257: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2258: ibig=0;
2259: del=0.0;
1.157 brouard 2260: rlast_time=rcurr_time;
2261: /* (void) gettimeofday(&curr_time,&tzp); */
2262: rcurr_time = time(NULL);
2263: curr_time = *localtime(&rcurr_time);
2264: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2265: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2266: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2267: for (i=1;i<=n;i++) {
1.126 brouard 2268: fprintf(ficrespow," %.12lf", p[i]);
2269: }
1.239 brouard 2270: fprintf(ficrespow,"\n");fflush(ficrespow);
2271: printf("\n#model= 1 + age ");
2272: fprintf(ficlog,"\n#model= 1 + age ");
2273: if(nagesqr==1){
1.241 brouard 2274: printf(" + age*age ");
2275: fprintf(ficlog," + age*age ");
1.239 brouard 2276: }
2277: for(j=1;j <=ncovmodel-2;j++){
2278: if(Typevar[j]==0) {
2279: printf(" + V%d ",Tvar[j]);
2280: fprintf(ficlog," + V%d ",Tvar[j]);
2281: }else if(Typevar[j]==1) {
2282: printf(" + V%d*age ",Tvar[j]);
2283: fprintf(ficlog," + V%d*age ",Tvar[j]);
2284: }else if(Typevar[j]==2) {
2285: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2286: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2287: }
2288: }
1.126 brouard 2289: printf("\n");
1.239 brouard 2290: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2291: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2292: fprintf(ficlog,"\n");
1.239 brouard 2293: for(i=1,jk=1; i <=nlstate; i++){
2294: for(k=1; k <=(nlstate+ndeath); k++){
2295: if (k != i) {
2296: printf("%d%d ",i,k);
2297: fprintf(ficlog,"%d%d ",i,k);
2298: for(j=1; j <=ncovmodel; j++){
2299: printf("%12.7f ",p[jk]);
2300: fprintf(ficlog,"%12.7f ",p[jk]);
2301: jk++;
2302: }
2303: printf("\n");
2304: fprintf(ficlog,"\n");
2305: }
2306: }
2307: }
1.241 brouard 2308: if(*iter <=3 && *iter >1){
1.157 brouard 2309: tml = *localtime(&rcurr_time);
2310: strcpy(strcurr,asctime(&tml));
2311: rforecast_time=rcurr_time;
1.126 brouard 2312: itmp = strlen(strcurr);
2313: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2314: strcurr[itmp-1]='\0';
1.162 brouard 2315: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2316: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2317: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2318: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2319: forecast_time = *localtime(&rforecast_time);
2320: strcpy(strfor,asctime(&forecast_time));
2321: itmp = strlen(strfor);
2322: if(strfor[itmp-1]=='\n')
2323: strfor[itmp-1]='\0';
2324: 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);
2325: 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 2326: }
2327: }
1.187 brouard 2328: for (i=1;i<=n;i++) { /* For each direction i */
2329: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2330: fptt=(*fret);
2331: #ifdef DEBUG
1.203 brouard 2332: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2333: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2334: #endif
1.203 brouard 2335: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2336: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2337: #ifdef LINMINORIGINAL
1.188 brouard 2338: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2339: #else
2340: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2341: flatdir[i]=flat; /* Function is vanishing in that direction i */
2342: #endif
2343: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2344: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2345: /* because that direction will be replaced unless the gain del is small */
2346: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2347: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2348: /* with the new direction. */
2349: del=fabs(fptt-(*fret));
2350: ibig=i;
1.126 brouard 2351: }
2352: #ifdef DEBUG
2353: printf("%d %.12e",i,(*fret));
2354: fprintf(ficlog,"%d %.12e",i,(*fret));
2355: for (j=1;j<=n;j++) {
1.224 brouard 2356: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2357: printf(" x(%d)=%.12e",j,xit[j]);
2358: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2359: }
2360: for(j=1;j<=n;j++) {
1.225 brouard 2361: printf(" p(%d)=%.12e",j,p[j]);
2362: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2363: }
2364: printf("\n");
2365: fprintf(ficlog,"\n");
2366: #endif
1.187 brouard 2367: } /* end loop on each direction i */
2368: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2369: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2370: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2371: for(j=1;j<=n;j++) {
1.225 brouard 2372: if(flatdir[j] >0){
2373: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2374: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2375: }
2376: /* printf("\n"); */
2377: /* fprintf(ficlog,"\n"); */
2378: }
1.243 brouard 2379: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2380: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2381: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2382: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2383: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2384: /* decreased of more than 3.84 */
2385: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2386: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2387: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2388:
1.188 brouard 2389: /* Starting the program with initial values given by a former maximization will simply change */
2390: /* the scales of the directions and the directions, because the are reset to canonical directions */
2391: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2392: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2393: #ifdef DEBUG
2394: int k[2],l;
2395: k[0]=1;
2396: k[1]=-1;
2397: printf("Max: %.12e",(*func)(p));
2398: fprintf(ficlog,"Max: %.12e",(*func)(p));
2399: for (j=1;j<=n;j++) {
2400: printf(" %.12e",p[j]);
2401: fprintf(ficlog," %.12e",p[j]);
2402: }
2403: printf("\n");
2404: fprintf(ficlog,"\n");
2405: for(l=0;l<=1;l++) {
2406: for (j=1;j<=n;j++) {
2407: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2408: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2409: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2410: }
2411: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2412: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2413: }
2414: #endif
2415:
1.224 brouard 2416: #ifdef LINMINORIGINAL
2417: #else
2418: free_ivector(flatdir,1,n);
2419: #endif
1.126 brouard 2420: free_vector(xit,1,n);
2421: free_vector(xits,1,n);
2422: free_vector(ptt,1,n);
2423: free_vector(pt,1,n);
2424: return;
1.192 brouard 2425: } /* enough precision */
1.240 brouard 2426: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2427: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2428: ptt[j]=2.0*p[j]-pt[j];
2429: xit[j]=p[j]-pt[j];
2430: pt[j]=p[j];
2431: }
1.181 brouard 2432: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2433: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2434: if (*iter <=4) {
1.225 brouard 2435: #else
2436: #endif
1.224 brouard 2437: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2438: #else
1.161 brouard 2439: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2440: #endif
1.162 brouard 2441: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2442: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2443: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2444: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2445: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2446: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2447: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2448: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2449: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2450: /* Even if f3 <f1, directest can be negative and t >0 */
2451: /* mu² and del² are equal when f3=f1 */
2452: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2453: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2454: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2455: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2456: #ifdef NRCORIGINAL
2457: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2458: #else
2459: 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 2460: t= t- del*SQR(fp-fptt);
1.183 brouard 2461: #endif
1.202 brouard 2462: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2463: #ifdef DEBUG
1.181 brouard 2464: 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);
2465: 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 2466: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2467: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2468: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2469: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2470: 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);
2471: 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);
2472: #endif
1.183 brouard 2473: #ifdef POWELLORIGINAL
2474: if (t < 0.0) { /* Then we use it for new direction */
2475: #else
1.182 brouard 2476: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2477: 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 2478: 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 2479: 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 2480: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2481: }
1.181 brouard 2482: if (directest < 0.0) { /* Then we use it for new direction */
2483: #endif
1.191 brouard 2484: #ifdef DEBUGLINMIN
1.234 brouard 2485: printf("Before linmin in direction P%d-P0\n",n);
2486: for (j=1;j<=n;j++) {
2487: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2488: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2489: if(j % ncovmodel == 0){
2490: printf("\n");
2491: fprintf(ficlog,"\n");
2492: }
2493: }
1.224 brouard 2494: #endif
2495: #ifdef LINMINORIGINAL
1.234 brouard 2496: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2497: #else
1.234 brouard 2498: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2499: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2500: #endif
1.234 brouard 2501:
1.191 brouard 2502: #ifdef DEBUGLINMIN
1.234 brouard 2503: for (j=1;j<=n;j++) {
2504: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2505: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2506: if(j % ncovmodel == 0){
2507: printf("\n");
2508: fprintf(ficlog,"\n");
2509: }
2510: }
1.224 brouard 2511: #endif
1.234 brouard 2512: for (j=1;j<=n;j++) {
2513: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2514: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2515: }
1.224 brouard 2516: #ifdef LINMINORIGINAL
2517: #else
1.234 brouard 2518: for (j=1, flatd=0;j<=n;j++) {
2519: if(flatdir[j]>0)
2520: flatd++;
2521: }
2522: if(flatd >0){
1.255 brouard 2523: printf("%d flat directions: ",flatd);
2524: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2525: for (j=1;j<=n;j++) {
2526: if(flatdir[j]>0){
2527: printf("%d ",j);
2528: fprintf(ficlog,"%d ",j);
2529: }
2530: }
2531: printf("\n");
2532: fprintf(ficlog,"\n");
2533: }
1.191 brouard 2534: #endif
1.234 brouard 2535: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2536: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2537:
1.126 brouard 2538: #ifdef DEBUG
1.234 brouard 2539: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2540: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2541: for(j=1;j<=n;j++){
2542: printf(" %lf",xit[j]);
2543: fprintf(ficlog," %lf",xit[j]);
2544: }
2545: printf("\n");
2546: fprintf(ficlog,"\n");
1.126 brouard 2547: #endif
1.192 brouard 2548: } /* end of t or directest negative */
1.224 brouard 2549: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2550: #else
1.234 brouard 2551: } /* end if (fptt < fp) */
1.192 brouard 2552: #endif
1.225 brouard 2553: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2554: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2555: #else
1.224 brouard 2556: #endif
1.234 brouard 2557: } /* loop iteration */
1.126 brouard 2558: }
1.234 brouard 2559:
1.126 brouard 2560: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2561:
1.235 brouard 2562: 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 2563: {
1.279 brouard 2564: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2565: * (and selected quantitative values in nres)
2566: * by left multiplying the unit
2567: * matrix by transitions matrix until convergence is reached with precision ftolpl
2568: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2569: * Wx is row vector: population in state 1, population in state 2, population dead
2570: * or prevalence in state 1, prevalence in state 2, 0
2571: * newm is the matrix after multiplications, its rows are identical at a factor.
2572: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2573: * Output is prlim.
2574: * Initial matrix pimij
2575: */
1.206 brouard 2576: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2577: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2578: /* 0, 0 , 1} */
2579: /*
2580: * and after some iteration: */
2581: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2582: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2583: /* 0, 0 , 1} */
2584: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2585: /* {0.51571254859325999, 0.4842874514067399, */
2586: /* 0.51326036147820708, 0.48673963852179264} */
2587: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2588:
1.126 brouard 2589: int i, ii,j,k;
1.209 brouard 2590: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2591: /* double **matprod2(); */ /* test */
1.218 brouard 2592: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2593: double **newm;
1.209 brouard 2594: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2595: int ncvloop=0;
1.288 brouard 2596: int first=0;
1.169 brouard 2597:
1.209 brouard 2598: min=vector(1,nlstate);
2599: max=vector(1,nlstate);
2600: meandiff=vector(1,nlstate);
2601:
1.218 brouard 2602: /* Starting with matrix unity */
1.126 brouard 2603: for (ii=1;ii<=nlstate+ndeath;ii++)
2604: for (j=1;j<=nlstate+ndeath;j++){
2605: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2606: }
1.169 brouard 2607:
2608: cov[1]=1.;
2609:
2610: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2611: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2612: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2613: ncvloop++;
1.126 brouard 2614: newm=savm;
2615: /* Covariates have to be included here again */
1.138 brouard 2616: cov[2]=agefin;
1.187 brouard 2617: if(nagesqr==1)
2618: cov[3]= agefin*agefin;;
1.234 brouard 2619: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2620: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2621: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2622: /* 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 2623: }
2624: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2625: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2626: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2627: /* 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 2628: }
1.237 brouard 2629: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2630: if(Dummy[Tvar[Tage[k]]]){
2631: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2632: } else{
1.235 brouard 2633: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2634: }
1.235 brouard 2635: /* 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 2636: }
1.237 brouard 2637: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2638: /* 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 2639: if(Dummy[Tvard[k][1]==0]){
2640: if(Dummy[Tvard[k][2]==0]){
2641: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2642: }else{
2643: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2644: }
2645: }else{
2646: if(Dummy[Tvard[k][2]==0]){
2647: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2648: }else{
2649: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2650: }
2651: }
1.234 brouard 2652: }
1.138 brouard 2653: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2654: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2655: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2656: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2657: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2658: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2659: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2660:
1.126 brouard 2661: savm=oldm;
2662: oldm=newm;
1.209 brouard 2663:
2664: for(j=1; j<=nlstate; j++){
2665: max[j]=0.;
2666: min[j]=1.;
2667: }
2668: for(i=1;i<=nlstate;i++){
2669: sumnew=0;
2670: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2671: for(j=1; j<=nlstate; j++){
2672: prlim[i][j]= newm[i][j]/(1-sumnew);
2673: max[j]=FMAX(max[j],prlim[i][j]);
2674: min[j]=FMIN(min[j],prlim[i][j]);
2675: }
2676: }
2677:
1.126 brouard 2678: maxmax=0.;
1.209 brouard 2679: for(j=1; j<=nlstate; j++){
2680: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2681: maxmax=FMAX(maxmax,meandiff[j]);
2682: /* 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 2683: } /* j loop */
1.203 brouard 2684: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2685: /* 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 2686: if(maxmax < ftolpl){
1.209 brouard 2687: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2688: free_vector(min,1,nlstate);
2689: free_vector(max,1,nlstate);
2690: free_vector(meandiff,1,nlstate);
1.126 brouard 2691: return prlim;
2692: }
1.288 brouard 2693: } /* agefin loop */
1.208 brouard 2694: /* After some age loop it doesn't converge */
1.288 brouard 2695: if(!first){
2696: first=1;
2697: 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);
2698: }
2699: 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);
2700:
1.209 brouard 2701: /* 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); */
2702: free_vector(min,1,nlstate);
2703: free_vector(max,1,nlstate);
2704: free_vector(meandiff,1,nlstate);
1.208 brouard 2705:
1.169 brouard 2706: return prlim; /* should not reach here */
1.126 brouard 2707: }
2708:
1.217 brouard 2709:
2710: /**** Back Prevalence limit (stable or period prevalence) ****************/
2711:
1.218 brouard 2712: /* 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) */
2713: /* 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 2714: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2715: {
1.264 brouard 2716: /* 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 2717: matrix by transitions matrix until convergence is reached with precision ftolpl */
2718: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2719: /* Wx is row vector: population in state 1, population in state 2, population dead */
2720: /* or prevalence in state 1, prevalence in state 2, 0 */
2721: /* newm is the matrix after multiplications, its rows are identical at a factor */
2722: /* Initial matrix pimij */
2723: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2724: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2725: /* 0, 0 , 1} */
2726: /*
2727: * and after some iteration: */
2728: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2729: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2730: /* 0, 0 , 1} */
2731: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2732: /* {0.51571254859325999, 0.4842874514067399, */
2733: /* 0.51326036147820708, 0.48673963852179264} */
2734: /* If we start from prlim again, prlim tends to a constant matrix */
2735:
2736: int i, ii,j,k;
1.247 brouard 2737: int first=0;
1.217 brouard 2738: double *min, *max, *meandiff, maxmax,sumnew=0.;
2739: /* double **matprod2(); */ /* test */
2740: double **out, cov[NCOVMAX+1], **bmij();
2741: double **newm;
1.218 brouard 2742: double **dnewm, **doldm, **dsavm; /* for use */
2743: double **oldm, **savm; /* for use */
2744:
1.217 brouard 2745: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2746: int ncvloop=0;
2747:
2748: min=vector(1,nlstate);
2749: max=vector(1,nlstate);
2750: meandiff=vector(1,nlstate);
2751:
1.266 brouard 2752: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2753: oldm=oldms; savm=savms;
2754:
2755: /* Starting with matrix unity */
2756: for (ii=1;ii<=nlstate+ndeath;ii++)
2757: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2758: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2759: }
2760:
2761: cov[1]=1.;
2762:
2763: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2764: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2765: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2766: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2767: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2768: ncvloop++;
1.218 brouard 2769: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2770: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2771: /* Covariates have to be included here again */
2772: cov[2]=agefin;
2773: if(nagesqr==1)
2774: cov[3]= agefin*agefin;;
1.242 brouard 2775: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2776: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2777: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2778: /* 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 2779: }
2780: /* for (k=1; k<=cptcovn;k++) { */
2781: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2782: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2783: /* /\* 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])]); *\/ */
2784: /* } */
2785: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2786: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2787: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2788: /* 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]); */
2789: }
2790: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2791: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2792: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2793: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2794: for (k=1; k<=cptcovage;k++){ /* For product with age */
2795: if(Dummy[Tvar[Tage[k]]]){
2796: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2797: } else{
2798: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2799: }
2800: /* 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]); */
2801: }
2802: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2803: /* 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]); */
2804: if(Dummy[Tvard[k][1]==0]){
2805: if(Dummy[Tvard[k][2]==0]){
2806: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2807: }else{
2808: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2809: }
2810: }else{
2811: if(Dummy[Tvard[k][2]==0]){
2812: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2813: }else{
2814: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2815: }
2816: }
1.217 brouard 2817: }
2818:
2819: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2820: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2821: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2822: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2823: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2824: /* ij should be linked to the correct index of cov */
2825: /* age and covariate values ij are in 'cov', but we need to pass
2826: * ij for the observed prevalence at age and status and covariate
2827: * number: prevacurrent[(int)agefin][ii][ij]
2828: */
2829: /* 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 *\/ */
2830: /* 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 *\/ */
2831: 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 2832: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2833: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2834: /* for(i=1; i<=nlstate+ndeath; i++) { */
2835: /* printf("%d newm= ",i); */
2836: /* for(j=1;j<=nlstate+ndeath;j++) { */
2837: /* printf("%f ",newm[i][j]); */
2838: /* } */
2839: /* printf("oldm * "); */
2840: /* for(j=1;j<=nlstate+ndeath;j++) { */
2841: /* printf("%f ",oldm[i][j]); */
2842: /* } */
1.268 brouard 2843: /* printf(" bmmij "); */
1.266 brouard 2844: /* for(j=1;j<=nlstate+ndeath;j++) { */
2845: /* printf("%f ",pmmij[i][j]); */
2846: /* } */
2847: /* printf("\n"); */
2848: /* } */
2849: /* } */
1.217 brouard 2850: savm=oldm;
2851: oldm=newm;
1.266 brouard 2852:
1.217 brouard 2853: for(j=1; j<=nlstate; j++){
2854: max[j]=0.;
2855: min[j]=1.;
2856: }
2857: for(j=1; j<=nlstate; j++){
2858: for(i=1;i<=nlstate;i++){
1.234 brouard 2859: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2860: bprlim[i][j]= newm[i][j];
2861: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2862: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2863: }
2864: }
1.218 brouard 2865:
1.217 brouard 2866: maxmax=0.;
2867: for(i=1; i<=nlstate; i++){
2868: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2869: maxmax=FMAX(maxmax,meandiff[i]);
2870: /* 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 2871: } /* i loop */
1.217 brouard 2872: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2873: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2874: if(maxmax < ftolpl){
1.220 brouard 2875: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2876: free_vector(min,1,nlstate);
2877: free_vector(max,1,nlstate);
2878: free_vector(meandiff,1,nlstate);
2879: return bprlim;
2880: }
1.288 brouard 2881: } /* agefin loop */
1.217 brouard 2882: /* After some age loop it doesn't converge */
1.288 brouard 2883: if(!first){
1.247 brouard 2884: first=1;
2885: 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\
2886: 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);
2887: }
2888: 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 2889: 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);
2890: /* 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); */
2891: free_vector(min,1,nlstate);
2892: free_vector(max,1,nlstate);
2893: free_vector(meandiff,1,nlstate);
2894:
2895: return bprlim; /* should not reach here */
2896: }
2897:
1.126 brouard 2898: /*************** transition probabilities ***************/
2899:
2900: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2901: {
1.138 brouard 2902: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2903: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2904: model to the ncovmodel covariates (including constant and age).
2905: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2906: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2907: ncth covariate in the global vector x is given by the formula:
2908: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2909: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2910: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2911: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2912: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2913: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2914: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2915: */
2916: double s1, lnpijopii;
1.126 brouard 2917: /*double t34;*/
1.164 brouard 2918: int i,j, nc, ii, jj;
1.126 brouard 2919:
1.223 brouard 2920: for(i=1; i<= nlstate; i++){
2921: for(j=1; j<i;j++){
2922: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2923: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2924: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2925: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2926: }
2927: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2928: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2929: }
2930: for(j=i+1; j<=nlstate+ndeath;j++){
2931: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2932: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2933: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2934: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2935: }
2936: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2937: }
2938: }
1.218 brouard 2939:
1.223 brouard 2940: for(i=1; i<= nlstate; i++){
2941: s1=0;
2942: for(j=1; j<i; j++){
2943: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2944: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2945: }
2946: for(j=i+1; j<=nlstate+ndeath; j++){
2947: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2948: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2949: }
2950: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2951: ps[i][i]=1./(s1+1.);
2952: /* Computing other pijs */
2953: for(j=1; j<i; j++)
2954: ps[i][j]= exp(ps[i][j])*ps[i][i];
2955: for(j=i+1; j<=nlstate+ndeath; j++)
2956: ps[i][j]= exp(ps[i][j])*ps[i][i];
2957: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2958: } /* end i */
1.218 brouard 2959:
1.223 brouard 2960: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2961: for(jj=1; jj<= nlstate+ndeath; jj++){
2962: ps[ii][jj]=0;
2963: ps[ii][ii]=1;
2964: }
2965: }
1.218 brouard 2966:
2967:
1.223 brouard 2968: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2969: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2970: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2971: /* } */
2972: /* printf("\n "); */
2973: /* } */
2974: /* printf("\n ");printf("%lf ",cov[2]);*/
2975: /*
2976: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2977: goto end;*/
1.266 brouard 2978: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2979: }
2980:
1.218 brouard 2981: /*************** backward transition probabilities ***************/
2982:
2983: /* 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 ) */
2984: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2985: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2986: {
1.266 brouard 2987: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2988: * 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 2989: */
1.218 brouard 2990: int i, ii, j,k;
1.222 brouard 2991:
2992: double **out, **pmij();
2993: double sumnew=0.;
1.218 brouard 2994: double agefin;
1.292 ! brouard 2995: 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 2996: double **dnewm, **dsavm, **doldm;
2997: double **bbmij;
2998:
1.218 brouard 2999: doldm=ddoldms; /* global pointers */
1.222 brouard 3000: dnewm=ddnewms;
3001: dsavm=ddsavms;
3002:
3003: agefin=cov[2];
1.268 brouard 3004: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3005: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3006: the observed prevalence (with this covariate ij) at beginning of transition */
3007: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3008:
3009: /* P_x */
1.266 brouard 3010: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3011: /* outputs pmmij which is a stochastic matrix in row */
3012:
3013: /* Diag(w_x) */
1.292 ! brouard 3014: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3015: sumnew=0.;
1.269 brouard 3016: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3017: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 3018: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3019: sumnew+=prevacurrent[(int)agefin][ii][ij];
3020: }
3021: if(sumnew >0.01){ /* At least some value in the prevalence */
3022: for (ii=1;ii<=nlstate+ndeath;ii++){
3023: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3024: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3025: }
3026: }else{
3027: for (ii=1;ii<=nlstate+ndeath;ii++){
3028: for (j=1;j<=nlstate+ndeath;j++)
3029: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3030: }
3031: /* if(sumnew <0.9){ */
3032: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3033: /* } */
3034: }
3035: k3=0.0; /* We put the last diagonal to 0 */
3036: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3037: doldm[ii][ii]= k3;
3038: }
3039: /* End doldm, At the end doldm is diag[(w_i)] */
3040:
1.292 ! brouard 3041: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
! 3042: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3043:
1.292 ! brouard 3044: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3045: /* 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 3046: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3047: sumnew=0.;
1.222 brouard 3048: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3049: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3050: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3051: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3052: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3053: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3054: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3055: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3056: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3057: /* }else */
1.268 brouard 3058: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3059: } /*End ii */
3060: } /* 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 */
3061:
1.292 ! brouard 3062: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3063: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3064: /* end bmij */
1.266 brouard 3065: return ps; /*pointer is unchanged */
1.218 brouard 3066: }
1.217 brouard 3067: /*************** transition probabilities ***************/
3068:
1.218 brouard 3069: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3070: {
3071: /* According to parameters values stored in x and the covariate's values stored in cov,
3072: computes the probability to be observed in state j being in state i by appying the
3073: model to the ncovmodel covariates (including constant and age).
3074: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3075: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3076: ncth covariate in the global vector x is given by the formula:
3077: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3078: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3079: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3080: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3081: Outputs ps[i][j] the probability to be observed in j being in j according to
3082: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3083: */
3084: double s1, lnpijopii;
3085: /*double t34;*/
3086: int i,j, nc, ii, jj;
3087:
1.234 brouard 3088: for(i=1; i<= nlstate; i++){
3089: for(j=1; j<i;j++){
3090: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3091: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3092: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3093: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3094: }
3095: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3096: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3097: }
3098: for(j=i+1; j<=nlstate+ndeath;j++){
3099: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3100: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3101: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3102: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3103: }
3104: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3105: }
3106: }
3107:
3108: for(i=1; i<= nlstate; i++){
3109: s1=0;
3110: for(j=1; j<i; j++){
3111: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3112: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3113: }
3114: for(j=i+1; j<=nlstate+ndeath; j++){
3115: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3116: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3117: }
3118: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3119: ps[i][i]=1./(s1+1.);
3120: /* Computing other pijs */
3121: for(j=1; j<i; j++)
3122: ps[i][j]= exp(ps[i][j])*ps[i][i];
3123: for(j=i+1; j<=nlstate+ndeath; j++)
3124: ps[i][j]= exp(ps[i][j])*ps[i][i];
3125: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3126: } /* end i */
3127:
3128: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3129: for(jj=1; jj<= nlstate+ndeath; jj++){
3130: ps[ii][jj]=0;
3131: ps[ii][ii]=1;
3132: }
3133: }
3134: /* Added for backcast */ /* Transposed matrix too */
3135: for(jj=1; jj<= nlstate+ndeath; jj++){
3136: s1=0.;
3137: for(ii=1; ii<= nlstate+ndeath; ii++){
3138: s1+=ps[ii][jj];
3139: }
3140: for(ii=1; ii<= nlstate; ii++){
3141: ps[ii][jj]=ps[ii][jj]/s1;
3142: }
3143: }
3144: /* Transposition */
3145: for(jj=1; jj<= nlstate+ndeath; jj++){
3146: for(ii=jj; ii<= nlstate+ndeath; ii++){
3147: s1=ps[ii][jj];
3148: ps[ii][jj]=ps[jj][ii];
3149: ps[jj][ii]=s1;
3150: }
3151: }
3152: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3153: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3154: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3155: /* } */
3156: /* printf("\n "); */
3157: /* } */
3158: /* printf("\n ");printf("%lf ",cov[2]);*/
3159: /*
3160: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3161: goto end;*/
3162: return ps;
1.217 brouard 3163: }
3164:
3165:
1.126 brouard 3166: /**************** Product of 2 matrices ******************/
3167:
1.145 brouard 3168: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3169: {
3170: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3171: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3172: /* in, b, out are matrice of pointers which should have been initialized
3173: before: only the contents of out is modified. The function returns
3174: a pointer to pointers identical to out */
1.145 brouard 3175: int i, j, k;
1.126 brouard 3176: for(i=nrl; i<= nrh; i++)
1.145 brouard 3177: for(k=ncolol; k<=ncoloh; k++){
3178: out[i][k]=0.;
3179: for(j=ncl; j<=nch; j++)
3180: out[i][k] +=in[i][j]*b[j][k];
3181: }
1.126 brouard 3182: return out;
3183: }
3184:
3185:
3186: /************* Higher Matrix Product ***************/
3187:
1.235 brouard 3188: 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 3189: {
1.218 brouard 3190: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3191: 'nhstepm*hstepm*stepm' months (i.e. until
3192: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3193: nhstepm*hstepm matrices.
3194: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3195: (typically every 2 years instead of every month which is too big
3196: for the memory).
3197: Model is determined by parameters x and covariates have to be
3198: included manually here.
3199:
3200: */
3201:
3202: int i, j, d, h, k;
1.131 brouard 3203: double **out, cov[NCOVMAX+1];
1.126 brouard 3204: double **newm;
1.187 brouard 3205: double agexact;
1.214 brouard 3206: double agebegin, ageend;
1.126 brouard 3207:
3208: /* Hstepm could be zero and should return the unit matrix */
3209: for (i=1;i<=nlstate+ndeath;i++)
3210: for (j=1;j<=nlstate+ndeath;j++){
3211: oldm[i][j]=(i==j ? 1.0 : 0.0);
3212: po[i][j][0]=(i==j ? 1.0 : 0.0);
3213: }
3214: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3215: for(h=1; h <=nhstepm; h++){
3216: for(d=1; d <=hstepm; d++){
3217: newm=savm;
3218: /* Covariates have to be included here again */
3219: cov[1]=1.;
1.214 brouard 3220: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3221: cov[2]=agexact;
3222: if(nagesqr==1)
1.227 brouard 3223: cov[3]= agexact*agexact;
1.235 brouard 3224: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3225: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3226: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3227: /* 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)); */
3228: }
3229: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3230: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3231: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3232: /* 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]); */
3233: }
3234: for (k=1; k<=cptcovage;k++){
3235: if(Dummy[Tvar[Tage[k]]]){
3236: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3237: } else{
3238: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3239: }
3240: /* 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]); */
3241: }
3242: for (k=1; k<=cptcovprod;k++){ /* */
3243: /* 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]); */
3244: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3245: }
3246: /* for (k=1; k<=cptcovn;k++) */
3247: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3248: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3249: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3250: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3251: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3252:
3253:
1.126 brouard 3254: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3255: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3256: /* right multiplication of oldm by the current matrix */
1.126 brouard 3257: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3258: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3259: /* if((int)age == 70){ */
3260: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3261: /* for(i=1; i<=nlstate+ndeath; i++) { */
3262: /* printf("%d pmmij ",i); */
3263: /* for(j=1;j<=nlstate+ndeath;j++) { */
3264: /* printf("%f ",pmmij[i][j]); */
3265: /* } */
3266: /* printf(" oldm "); */
3267: /* for(j=1;j<=nlstate+ndeath;j++) { */
3268: /* printf("%f ",oldm[i][j]); */
3269: /* } */
3270: /* printf("\n"); */
3271: /* } */
3272: /* } */
1.126 brouard 3273: savm=oldm;
3274: oldm=newm;
3275: }
3276: for(i=1; i<=nlstate+ndeath; i++)
3277: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3278: po[i][j][h]=newm[i][j];
3279: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3280: }
1.128 brouard 3281: /*printf("h=%d ",h);*/
1.126 brouard 3282: } /* end h */
1.267 brouard 3283: /* printf("\n H=%d \n",h); */
1.126 brouard 3284: return po;
3285: }
3286:
1.217 brouard 3287: /************* Higher Back Matrix Product ***************/
1.218 brouard 3288: /* 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 3289: 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 3290: {
1.266 brouard 3291: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3292: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3293: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3294: nhstepm*hstepm matrices.
3295: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3296: (typically every 2 years instead of every month which is too big
1.217 brouard 3297: for the memory).
1.218 brouard 3298: Model is determined by parameters x and covariates have to be
1.266 brouard 3299: included manually here. Then we use a call to bmij(x and cov)
3300: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3301: */
1.217 brouard 3302:
3303: int i, j, d, h, k;
1.266 brouard 3304: double **out, cov[NCOVMAX+1], **bmij();
3305: double **newm, ***newmm;
1.217 brouard 3306: double agexact;
3307: double agebegin, ageend;
1.222 brouard 3308: double **oldm, **savm;
1.217 brouard 3309:
1.266 brouard 3310: newmm=po; /* To be saved */
3311: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3312: /* Hstepm could be zero and should return the unit matrix */
3313: for (i=1;i<=nlstate+ndeath;i++)
3314: for (j=1;j<=nlstate+ndeath;j++){
3315: oldm[i][j]=(i==j ? 1.0 : 0.0);
3316: po[i][j][0]=(i==j ? 1.0 : 0.0);
3317: }
3318: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3319: for(h=1; h <=nhstepm; h++){
3320: for(d=1; d <=hstepm; d++){
3321: newm=savm;
3322: /* Covariates have to be included here again */
3323: cov[1]=1.;
1.271 brouard 3324: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3325: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3326: cov[2]=agexact;
3327: if(nagesqr==1)
1.222 brouard 3328: cov[3]= agexact*agexact;
1.266 brouard 3329: for (k=1; k<=cptcovn;k++){
3330: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3331: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3332: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3333: /* 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)); */
3334: }
1.267 brouard 3335: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3336: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3337: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3338: /* 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]); */
3339: }
3340: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3341: if(Dummy[Tvar[Tage[k]]]){
3342: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3343: } else{
3344: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3345: }
3346: /* 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]); */
3347: }
3348: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3349: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3350: }
1.217 brouard 3351: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3352: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3353:
1.218 brouard 3354: /* Careful transposed matrix */
1.266 brouard 3355: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3356: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3357: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3358: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3359: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3360: /* if((int)age == 70){ */
3361: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3362: /* for(i=1; i<=nlstate+ndeath; i++) { */
3363: /* printf("%d pmmij ",i); */
3364: /* for(j=1;j<=nlstate+ndeath;j++) { */
3365: /* printf("%f ",pmmij[i][j]); */
3366: /* } */
3367: /* printf(" oldm "); */
3368: /* for(j=1;j<=nlstate+ndeath;j++) { */
3369: /* printf("%f ",oldm[i][j]); */
3370: /* } */
3371: /* printf("\n"); */
3372: /* } */
3373: /* } */
3374: savm=oldm;
3375: oldm=newm;
3376: }
3377: for(i=1; i<=nlstate+ndeath; i++)
3378: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3379: po[i][j][h]=newm[i][j];
1.268 brouard 3380: /* if(h==nhstepm) */
3381: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3382: }
1.268 brouard 3383: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3384: } /* end h */
1.268 brouard 3385: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3386: return po;
3387: }
3388:
3389:
1.162 brouard 3390: #ifdef NLOPT
3391: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3392: double fret;
3393: double *xt;
3394: int j;
3395: myfunc_data *d2 = (myfunc_data *) pd;
3396: /* xt = (p1-1); */
3397: xt=vector(1,n);
3398: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3399:
3400: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3401: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3402: printf("Function = %.12lf ",fret);
3403: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3404: printf("\n");
3405: free_vector(xt,1,n);
3406: return fret;
3407: }
3408: #endif
1.126 brouard 3409:
3410: /*************** log-likelihood *************/
3411: double func( double *x)
3412: {
1.226 brouard 3413: int i, ii, j, k, mi, d, kk;
3414: int ioffset=0;
3415: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3416: double **out;
3417: double lli; /* Individual log likelihood */
3418: int s1, s2;
1.228 brouard 3419: 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 3420: double bbh, survp;
3421: long ipmx;
3422: double agexact;
3423: /*extern weight */
3424: /* We are differentiating ll according to initial status */
3425: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3426: /*for(i=1;i<imx;i++)
3427: printf(" %d\n",s[4][i]);
3428: */
1.162 brouard 3429:
1.226 brouard 3430: ++countcallfunc;
1.162 brouard 3431:
1.226 brouard 3432: cov[1]=1.;
1.126 brouard 3433:
1.226 brouard 3434: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3435: ioffset=0;
1.226 brouard 3436: if(mle==1){
3437: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3438: /* Computes the values of the ncovmodel covariates of the model
3439: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3440: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3441: to be observed in j being in i according to the model.
3442: */
1.243 brouard 3443: ioffset=2+nagesqr ;
1.233 brouard 3444: /* Fixed */
1.234 brouard 3445: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3446: 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)*/
3447: }
1.226 brouard 3448: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3449: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3450: has been calculated etc */
3451: /* For an individual i, wav[i] gives the number of effective waves */
3452: /* We compute the contribution to Likelihood of each effective transition
3453: mw[mi][i] is real wave of the mi th effectve wave */
3454: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3455: s2=s[mw[mi+1][i]][i];
3456: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3457: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3458: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3459: */
3460: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3461: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3462: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3463: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3464: }
3465: for (ii=1;ii<=nlstate+ndeath;ii++)
3466: for (j=1;j<=nlstate+ndeath;j++){
3467: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3468: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3469: }
3470: for(d=0; d<dh[mi][i]; d++){
3471: newm=savm;
3472: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3473: cov[2]=agexact;
3474: if(nagesqr==1)
3475: cov[3]= agexact*agexact; /* Should be changed here */
3476: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3477: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3478: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3479: else
3480: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3481: }
3482: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3483: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3484: savm=oldm;
3485: oldm=newm;
3486: } /* end mult */
3487:
3488: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3489: /* But now since version 0.9 we anticipate for bias at large stepm.
3490: * If stepm is larger than one month (smallest stepm) and if the exact delay
3491: * (in months) between two waves is not a multiple of stepm, we rounded to
3492: * the nearest (and in case of equal distance, to the lowest) interval but now
3493: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3494: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3495: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3496: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3497: * -stepm/2 to stepm/2 .
3498: * For stepm=1 the results are the same as for previous versions of Imach.
3499: * For stepm > 1 the results are less biased than in previous versions.
3500: */
1.234 brouard 3501: s1=s[mw[mi][i]][i];
3502: s2=s[mw[mi+1][i]][i];
3503: bbh=(double)bh[mi][i]/(double)stepm;
3504: /* bias bh is positive if real duration
3505: * is higher than the multiple of stepm and negative otherwise.
3506: */
3507: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3508: if( s2 > nlstate){
3509: /* i.e. if s2 is a death state and if the date of death is known
3510: then the contribution to the likelihood is the probability to
3511: die between last step unit time and current step unit time,
3512: which is also equal to probability to die before dh
3513: minus probability to die before dh-stepm .
3514: In version up to 0.92 likelihood was computed
3515: as if date of death was unknown. Death was treated as any other
3516: health state: the date of the interview describes the actual state
3517: and not the date of a change in health state. The former idea was
3518: to consider that at each interview the state was recorded
3519: (healthy, disable or death) and IMaCh was corrected; but when we
3520: introduced the exact date of death then we should have modified
3521: the contribution of an exact death to the likelihood. This new
3522: contribution is smaller and very dependent of the step unit
3523: stepm. It is no more the probability to die between last interview
3524: and month of death but the probability to survive from last
3525: interview up to one month before death multiplied by the
3526: probability to die within a month. Thanks to Chris
3527: Jackson for correcting this bug. Former versions increased
3528: mortality artificially. The bad side is that we add another loop
3529: which slows down the processing. The difference can be up to 10%
3530: lower mortality.
3531: */
3532: /* If, at the beginning of the maximization mostly, the
3533: cumulative probability or probability to be dead is
3534: constant (ie = 1) over time d, the difference is equal to
3535: 0. out[s1][3] = savm[s1][3]: probability, being at state
3536: s1 at precedent wave, to be dead a month before current
3537: wave is equal to probability, being at state s1 at
3538: precedent wave, to be dead at mont of the current
3539: wave. Then the observed probability (that this person died)
3540: is null according to current estimated parameter. In fact,
3541: it should be very low but not zero otherwise the log go to
3542: infinity.
3543: */
1.183 brouard 3544: /* #ifdef INFINITYORIGINAL */
3545: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3546: /* #else */
3547: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3548: /* lli=log(mytinydouble); */
3549: /* else */
3550: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3551: /* #endif */
1.226 brouard 3552: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3553:
1.226 brouard 3554: } else if ( s2==-1 ) { /* alive */
3555: for (j=1,survp=0. ; j<=nlstate; j++)
3556: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3557: /*survp += out[s1][j]; */
3558: lli= log(survp);
3559: }
3560: else if (s2==-4) {
3561: for (j=3,survp=0. ; j<=nlstate; j++)
3562: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3563: lli= log(survp);
3564: }
3565: else if (s2==-5) {
3566: for (j=1,survp=0. ; j<=2; j++)
3567: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3568: lli= log(survp);
3569: }
3570: else{
3571: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3572: /* 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 */
3573: }
3574: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3575: /*if(lli ==000.0)*/
3576: /*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); */
3577: ipmx +=1;
3578: sw += weight[i];
3579: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3580: /* if (lli < log(mytinydouble)){ */
3581: /* 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); */
3582: /* 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]); */
3583: /* } */
3584: } /* end of wave */
3585: } /* end of individual */
3586: } else if(mle==2){
3587: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3588: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3589: for(mi=1; mi<= wav[i]-1; mi++){
3590: for (ii=1;ii<=nlstate+ndeath;ii++)
3591: for (j=1;j<=nlstate+ndeath;j++){
3592: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3593: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3594: }
3595: for(d=0; d<=dh[mi][i]; d++){
3596: newm=savm;
3597: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3598: cov[2]=agexact;
3599: if(nagesqr==1)
3600: cov[3]= agexact*agexact;
3601: for (kk=1; kk<=cptcovage;kk++) {
3602: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3603: }
3604: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3605: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3606: savm=oldm;
3607: oldm=newm;
3608: } /* end mult */
3609:
3610: s1=s[mw[mi][i]][i];
3611: s2=s[mw[mi+1][i]][i];
3612: bbh=(double)bh[mi][i]/(double)stepm;
3613: 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 */
3614: ipmx +=1;
3615: sw += weight[i];
3616: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3617: } /* end of wave */
3618: } /* end of individual */
3619: } else if(mle==3){ /* exponential inter-extrapolation */
3620: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3621: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3622: for(mi=1; mi<= wav[i]-1; mi++){
3623: for (ii=1;ii<=nlstate+ndeath;ii++)
3624: for (j=1;j<=nlstate+ndeath;j++){
3625: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3626: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3627: }
3628: for(d=0; d<dh[mi][i]; d++){
3629: newm=savm;
3630: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3631: cov[2]=agexact;
3632: if(nagesqr==1)
3633: cov[3]= agexact*agexact;
3634: for (kk=1; kk<=cptcovage;kk++) {
3635: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3636: }
3637: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3638: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3639: savm=oldm;
3640: oldm=newm;
3641: } /* end mult */
3642:
3643: s1=s[mw[mi][i]][i];
3644: s2=s[mw[mi+1][i]][i];
3645: bbh=(double)bh[mi][i]/(double)stepm;
3646: 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 */
3647: ipmx +=1;
3648: sw += weight[i];
3649: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3650: } /* end of wave */
3651: } /* end of individual */
3652: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3653: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3654: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3655: for(mi=1; mi<= wav[i]-1; mi++){
3656: for (ii=1;ii<=nlstate+ndeath;ii++)
3657: for (j=1;j<=nlstate+ndeath;j++){
3658: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3659: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3660: }
3661: for(d=0; d<dh[mi][i]; d++){
3662: newm=savm;
3663: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3664: cov[2]=agexact;
3665: if(nagesqr==1)
3666: cov[3]= agexact*agexact;
3667: for (kk=1; kk<=cptcovage;kk++) {
3668: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3669: }
1.126 brouard 3670:
1.226 brouard 3671: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3672: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3673: savm=oldm;
3674: oldm=newm;
3675: } /* end mult */
3676:
3677: s1=s[mw[mi][i]][i];
3678: s2=s[mw[mi+1][i]][i];
3679: if( s2 > nlstate){
3680: lli=log(out[s1][s2] - savm[s1][s2]);
3681: } else if ( s2==-1 ) { /* alive */
3682: for (j=1,survp=0. ; j<=nlstate; j++)
3683: survp += out[s1][j];
3684: lli= log(survp);
3685: }else{
3686: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3687: }
3688: ipmx +=1;
3689: sw += weight[i];
3690: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3691: /* 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 3692: } /* end of wave */
3693: } /* end of individual */
3694: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3695: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3696: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3697: for(mi=1; mi<= wav[i]-1; mi++){
3698: for (ii=1;ii<=nlstate+ndeath;ii++)
3699: for (j=1;j<=nlstate+ndeath;j++){
3700: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3701: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3702: }
3703: for(d=0; d<dh[mi][i]; d++){
3704: newm=savm;
3705: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3706: cov[2]=agexact;
3707: if(nagesqr==1)
3708: cov[3]= agexact*agexact;
3709: for (kk=1; kk<=cptcovage;kk++) {
3710: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3711: }
1.126 brouard 3712:
1.226 brouard 3713: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3714: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3715: savm=oldm;
3716: oldm=newm;
3717: } /* end mult */
3718:
3719: s1=s[mw[mi][i]][i];
3720: s2=s[mw[mi+1][i]][i];
3721: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3722: ipmx +=1;
3723: sw += weight[i];
3724: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3725: /*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]);*/
3726: } /* end of wave */
3727: } /* end of individual */
3728: } /* End of if */
3729: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3730: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3731: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3732: return -l;
1.126 brouard 3733: }
3734:
3735: /*************** log-likelihood *************/
3736: double funcone( double *x)
3737: {
1.228 brouard 3738: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3739: int i, ii, j, k, mi, d, kk;
1.228 brouard 3740: int ioffset=0;
1.131 brouard 3741: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3742: double **out;
3743: double lli; /* Individual log likelihood */
3744: double llt;
3745: int s1, s2;
1.228 brouard 3746: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3747:
1.126 brouard 3748: double bbh, survp;
1.187 brouard 3749: double agexact;
1.214 brouard 3750: double agebegin, ageend;
1.126 brouard 3751: /*extern weight */
3752: /* We are differentiating ll according to initial status */
3753: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3754: /*for(i=1;i<imx;i++)
3755: printf(" %d\n",s[4][i]);
3756: */
3757: cov[1]=1.;
3758:
3759: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3760: ioffset=0;
3761: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3762: /* ioffset=2+nagesqr+cptcovage; */
3763: ioffset=2+nagesqr;
1.232 brouard 3764: /* Fixed */
1.224 brouard 3765: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3766: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3767: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3768: 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)*/
3769: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3770: /* cov[2+6]=covar[Tvar[6]][i]; */
3771: /* cov[2+6]=covar[2][i]; V2 */
3772: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3773: /* cov[2+7]=covar[Tvar[7]][i]; */
3774: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3775: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3776: /* cov[2+9]=covar[Tvar[9]][i]; */
3777: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3778: }
1.232 brouard 3779: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3780: /* 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?)*\/ */
3781: /* } */
1.231 brouard 3782: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3783: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3784: /* } */
1.225 brouard 3785:
1.233 brouard 3786:
3787: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3788: /* Wave varying (but not age varying) */
3789: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3790: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3791: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3792: }
1.232 brouard 3793: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3794: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3795: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3796: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3797: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3798: /* 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 3799: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3800: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3801: /* /\* 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]); *\/ */
3802: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3803: /* } */
1.126 brouard 3804: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3805: for (j=1;j<=nlstate+ndeath;j++){
3806: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3807: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3808: }
1.214 brouard 3809:
3810: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3811: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3812: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3813: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3814: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3815: and mw[mi+1][i]. dh depends on stepm.*/
3816: newm=savm;
1.247 brouard 3817: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3818: cov[2]=agexact;
3819: if(nagesqr==1)
3820: cov[3]= agexact*agexact;
3821: for (kk=1; kk<=cptcovage;kk++) {
3822: if(!FixedV[Tvar[Tage[kk]]])
3823: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3824: else
3825: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3826: }
3827: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3828: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3829: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3830: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3831: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3832: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3833: savm=oldm;
3834: oldm=newm;
1.126 brouard 3835: } /* end mult */
3836:
3837: s1=s[mw[mi][i]][i];
3838: s2=s[mw[mi+1][i]][i];
1.217 brouard 3839: /* if(s2==-1){ */
1.268 brouard 3840: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3841: /* /\* exit(1); *\/ */
3842: /* } */
1.126 brouard 3843: bbh=(double)bh[mi][i]/(double)stepm;
3844: /* bias is positive if real duration
3845: * is higher than the multiple of stepm and negative otherwise.
3846: */
3847: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3848: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3849: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3850: for (j=1,survp=0. ; j<=nlstate; j++)
3851: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3852: lli= log(survp);
1.126 brouard 3853: }else if (mle==1){
1.242 brouard 3854: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3855: } else if(mle==2){
1.242 brouard 3856: 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 3857: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3858: 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 3859: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3860: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3861: } else{ /* mle=0 back to 1 */
1.242 brouard 3862: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3863: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3864: } /* End of if */
3865: ipmx +=1;
3866: sw += weight[i];
3867: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3868: /*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 3869: if(globpr){
1.246 brouard 3870: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3871: %11.6f %11.6f %11.6f ", \
1.242 brouard 3872: 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 3873: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3874: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3875: llt +=ll[k]*gipmx/gsw;
3876: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3877: }
3878: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3879: }
1.232 brouard 3880: } /* end of wave */
3881: } /* end of individual */
3882: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3883: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3884: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3885: if(globpr==0){ /* First time we count the contributions and weights */
3886: gipmx=ipmx;
3887: gsw=sw;
3888: }
3889: return -l;
1.126 brouard 3890: }
3891:
3892:
3893: /*************** function likelione ***********/
1.292 ! brouard 3894: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 3895: {
3896: /* This routine should help understanding what is done with
3897: the selection of individuals/waves and
3898: to check the exact contribution to the likelihood.
3899: Plotting could be done.
3900: */
3901: int k;
3902:
3903: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3904: strcpy(fileresilk,"ILK_");
1.202 brouard 3905: strcat(fileresilk,fileresu);
1.126 brouard 3906: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3907: printf("Problem with resultfile: %s\n", fileresilk);
3908: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3909: }
1.214 brouard 3910: 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");
3911: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3912: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3913: for(k=1; k<=nlstate; k++)
3914: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3915: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3916: }
3917:
1.292 ! brouard 3918: *fretone=(*func)(p);
1.126 brouard 3919: if(*globpri !=0){
3920: fclose(ficresilk);
1.205 brouard 3921: if (mle ==0)
3922: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3923: else if(mle >=1)
3924: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3925: 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 3926: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3927:
3928: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3929: 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 3930: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3931: }
1.207 brouard 3932: 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 3933: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3934: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3935: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3936: fflush(fichtm);
1.205 brouard 3937: }
1.126 brouard 3938: return;
3939: }
3940:
3941:
3942: /*********** Maximum Likelihood Estimation ***************/
3943:
3944: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3945: {
1.165 brouard 3946: int i,j, iter=0;
1.126 brouard 3947: double **xi;
3948: double fret;
3949: double fretone; /* Only one call to likelihood */
3950: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3951:
3952: #ifdef NLOPT
3953: int creturn;
3954: nlopt_opt opt;
3955: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3956: double *lb;
3957: double minf; /* the minimum objective value, upon return */
3958: double * p1; /* Shifted parameters from 0 instead of 1 */
3959: myfunc_data dinst, *d = &dinst;
3960: #endif
3961:
3962:
1.126 brouard 3963: xi=matrix(1,npar,1,npar);
3964: for (i=1;i<=npar;i++)
3965: for (j=1;j<=npar;j++)
3966: xi[i][j]=(i==j ? 1.0 : 0.0);
3967: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3968: strcpy(filerespow,"POW_");
1.126 brouard 3969: strcat(filerespow,fileres);
3970: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3971: printf("Problem with resultfile: %s\n", filerespow);
3972: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3973: }
3974: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3975: for (i=1;i<=nlstate;i++)
3976: for(j=1;j<=nlstate+ndeath;j++)
3977: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3978: fprintf(ficrespow,"\n");
1.162 brouard 3979: #ifdef POWELL
1.126 brouard 3980: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3981: #endif
1.126 brouard 3982:
1.162 brouard 3983: #ifdef NLOPT
3984: #ifdef NEWUOA
3985: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3986: #else
3987: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3988: #endif
3989: lb=vector(0,npar-1);
3990: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3991: nlopt_set_lower_bounds(opt, lb);
3992: nlopt_set_initial_step1(opt, 0.1);
3993:
3994: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3995: d->function = func;
3996: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3997: nlopt_set_min_objective(opt, myfunc, d);
3998: nlopt_set_xtol_rel(opt, ftol);
3999: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4000: printf("nlopt failed! %d\n",creturn);
4001: }
4002: else {
4003: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4004: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4005: iter=1; /* not equal */
4006: }
4007: nlopt_destroy(opt);
4008: #endif
1.126 brouard 4009: free_matrix(xi,1,npar,1,npar);
4010: fclose(ficrespow);
1.203 brouard 4011: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4012: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4013: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4014:
4015: }
4016:
4017: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4018: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4019: {
4020: double **a,**y,*x,pd;
1.203 brouard 4021: /* double **hess; */
1.164 brouard 4022: int i, j;
1.126 brouard 4023: int *indx;
4024:
4025: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4026: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4027: void lubksb(double **a, int npar, int *indx, double b[]) ;
4028: void ludcmp(double **a, int npar, int *indx, double *d) ;
4029: double gompertz(double p[]);
1.203 brouard 4030: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4031:
4032: printf("\nCalculation of the hessian matrix. Wait...\n");
4033: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4034: for (i=1;i<=npar;i++){
1.203 brouard 4035: printf("%d-",i);fflush(stdout);
4036: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4037:
4038: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4039:
4040: /* printf(" %f ",p[i]);
4041: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4042: }
4043:
4044: for (i=1;i<=npar;i++) {
4045: for (j=1;j<=npar;j++) {
4046: if (j>i) {
1.203 brouard 4047: printf(".%d-%d",i,j);fflush(stdout);
4048: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4049: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4050:
4051: hess[j][i]=hess[i][j];
4052: /*printf(" %lf ",hess[i][j]);*/
4053: }
4054: }
4055: }
4056: printf("\n");
4057: fprintf(ficlog,"\n");
4058:
4059: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4060: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4061:
4062: a=matrix(1,npar,1,npar);
4063: y=matrix(1,npar,1,npar);
4064: x=vector(1,npar);
4065: indx=ivector(1,npar);
4066: for (i=1;i<=npar;i++)
4067: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4068: ludcmp(a,npar,indx,&pd);
4069:
4070: for (j=1;j<=npar;j++) {
4071: for (i=1;i<=npar;i++) x[i]=0;
4072: x[j]=1;
4073: lubksb(a,npar,indx,x);
4074: for (i=1;i<=npar;i++){
4075: matcov[i][j]=x[i];
4076: }
4077: }
4078:
4079: printf("\n#Hessian matrix#\n");
4080: fprintf(ficlog,"\n#Hessian matrix#\n");
4081: for (i=1;i<=npar;i++) {
4082: for (j=1;j<=npar;j++) {
1.203 brouard 4083: printf("%.6e ",hess[i][j]);
4084: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4085: }
4086: printf("\n");
4087: fprintf(ficlog,"\n");
4088: }
4089:
1.203 brouard 4090: /* printf("\n#Covariance matrix#\n"); */
4091: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4092: /* for (i=1;i<=npar;i++) { */
4093: /* for (j=1;j<=npar;j++) { */
4094: /* printf("%.6e ",matcov[i][j]); */
4095: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4096: /* } */
4097: /* printf("\n"); */
4098: /* fprintf(ficlog,"\n"); */
4099: /* } */
4100:
1.126 brouard 4101: /* Recompute Inverse */
1.203 brouard 4102: /* for (i=1;i<=npar;i++) */
4103: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4104: /* ludcmp(a,npar,indx,&pd); */
4105:
4106: /* printf("\n#Hessian matrix recomputed#\n"); */
4107:
4108: /* for (j=1;j<=npar;j++) { */
4109: /* for (i=1;i<=npar;i++) x[i]=0; */
4110: /* x[j]=1; */
4111: /* lubksb(a,npar,indx,x); */
4112: /* for (i=1;i<=npar;i++){ */
4113: /* y[i][j]=x[i]; */
4114: /* printf("%.3e ",y[i][j]); */
4115: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4116: /* } */
4117: /* printf("\n"); */
4118: /* fprintf(ficlog,"\n"); */
4119: /* } */
4120:
4121: /* Verifying the inverse matrix */
4122: #ifdef DEBUGHESS
4123: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4124:
1.203 brouard 4125: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4126: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4127:
4128: for (j=1;j<=npar;j++) {
4129: for (i=1;i<=npar;i++){
1.203 brouard 4130: printf("%.2f ",y[i][j]);
4131: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4132: }
4133: printf("\n");
4134: fprintf(ficlog,"\n");
4135: }
1.203 brouard 4136: #endif
1.126 brouard 4137:
4138: free_matrix(a,1,npar,1,npar);
4139: free_matrix(y,1,npar,1,npar);
4140: free_vector(x,1,npar);
4141: free_ivector(indx,1,npar);
1.203 brouard 4142: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4143:
4144:
4145: }
4146:
4147: /*************** hessian matrix ****************/
4148: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4149: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4150: int i;
4151: int l=1, lmax=20;
1.203 brouard 4152: double k1,k2, res, fx;
1.132 brouard 4153: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4154: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4155: int k=0,kmax=10;
4156: double l1;
4157:
4158: fx=func(x);
4159: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4160: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4161: l1=pow(10,l);
4162: delts=delt;
4163: for(k=1 ; k <kmax; k=k+1){
4164: delt = delta*(l1*k);
4165: p2[theta]=x[theta] +delt;
1.145 brouard 4166: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4167: p2[theta]=x[theta]-delt;
4168: k2=func(p2)-fx;
4169: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4170: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4171:
1.203 brouard 4172: #ifdef DEBUGHESSII
1.126 brouard 4173: 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);
4174: 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);
4175: #endif
4176: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4177: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4178: k=kmax;
4179: }
4180: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4181: k=kmax; l=lmax*10;
1.126 brouard 4182: }
4183: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4184: delts=delt;
4185: }
1.203 brouard 4186: } /* End loop k */
1.126 brouard 4187: }
4188: delti[theta]=delts;
4189: return res;
4190:
4191: }
4192:
1.203 brouard 4193: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4194: {
4195: int i;
1.164 brouard 4196: int l=1, lmax=20;
1.126 brouard 4197: double k1,k2,k3,k4,res,fx;
1.132 brouard 4198: double p2[MAXPARM+1];
1.203 brouard 4199: int k, kmax=1;
4200: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4201:
4202: int firstime=0;
1.203 brouard 4203:
1.126 brouard 4204: fx=func(x);
1.203 brouard 4205: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4206: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4207: p2[thetai]=x[thetai]+delti[thetai]*k;
4208: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4209: k1=func(p2)-fx;
4210:
1.203 brouard 4211: p2[thetai]=x[thetai]+delti[thetai]*k;
4212: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4213: k2=func(p2)-fx;
4214:
1.203 brouard 4215: p2[thetai]=x[thetai]-delti[thetai]*k;
4216: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4217: k3=func(p2)-fx;
4218:
1.203 brouard 4219: p2[thetai]=x[thetai]-delti[thetai]*k;
4220: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4221: k4=func(p2)-fx;
1.203 brouard 4222: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4223: if(k1*k2*k3*k4 <0.){
1.208 brouard 4224: firstime=1;
1.203 brouard 4225: kmax=kmax+10;
1.208 brouard 4226: }
4227: if(kmax >=10 || firstime ==1){
1.246 brouard 4228: 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);
4229: 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 4230: 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);
4231: 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);
4232: }
4233: #ifdef DEBUGHESSIJ
4234: v1=hess[thetai][thetai];
4235: v2=hess[thetaj][thetaj];
4236: cv12=res;
4237: /* Computing eigen value of Hessian matrix */
4238: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4239: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4240: if ((lc2 <0) || (lc1 <0) ){
4241: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4242: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4243: 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);
4244: 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);
4245: }
1.126 brouard 4246: #endif
4247: }
4248: return res;
4249: }
4250:
1.203 brouard 4251: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4252: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4253: /* { */
4254: /* int i; */
4255: /* int l=1, lmax=20; */
4256: /* double k1,k2,k3,k4,res,fx; */
4257: /* double p2[MAXPARM+1]; */
4258: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4259: /* int k=0,kmax=10; */
4260: /* double l1; */
4261:
4262: /* fx=func(x); */
4263: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4264: /* l1=pow(10,l); */
4265: /* delts=delt; */
4266: /* for(k=1 ; k <kmax; k=k+1){ */
4267: /* delt = delti*(l1*k); */
4268: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4269: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4270: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4271: /* k1=func(p2)-fx; */
4272:
4273: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4274: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4275: /* k2=func(p2)-fx; */
4276:
4277: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4278: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4279: /* k3=func(p2)-fx; */
4280:
4281: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4282: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4283: /* k4=func(p2)-fx; */
4284: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4285: /* #ifdef DEBUGHESSIJ */
4286: /* 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); */
4287: /* 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); */
4288: /* #endif */
4289: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4290: /* k=kmax; */
4291: /* } */
4292: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4293: /* k=kmax; l=lmax*10; */
4294: /* } */
4295: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4296: /* delts=delt; */
4297: /* } */
4298: /* } /\* End loop k *\/ */
4299: /* } */
4300: /* delti[theta]=delts; */
4301: /* return res; */
4302: /* } */
4303:
4304:
1.126 brouard 4305: /************** Inverse of matrix **************/
4306: void ludcmp(double **a, int n, int *indx, double *d)
4307: {
4308: int i,imax,j,k;
4309: double big,dum,sum,temp;
4310: double *vv;
4311:
4312: vv=vector(1,n);
4313: *d=1.0;
4314: for (i=1;i<=n;i++) {
4315: big=0.0;
4316: for (j=1;j<=n;j++)
4317: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4318: if (big == 0.0){
4319: printf(" Singular Hessian matrix at row %d:\n",i);
4320: for (j=1;j<=n;j++) {
4321: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4322: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4323: }
4324: fflush(ficlog);
4325: fclose(ficlog);
4326: nrerror("Singular matrix in routine ludcmp");
4327: }
1.126 brouard 4328: vv[i]=1.0/big;
4329: }
4330: for (j=1;j<=n;j++) {
4331: for (i=1;i<j;i++) {
4332: sum=a[i][j];
4333: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4334: a[i][j]=sum;
4335: }
4336: big=0.0;
4337: for (i=j;i<=n;i++) {
4338: sum=a[i][j];
4339: for (k=1;k<j;k++)
4340: sum -= a[i][k]*a[k][j];
4341: a[i][j]=sum;
4342: if ( (dum=vv[i]*fabs(sum)) >= big) {
4343: big=dum;
4344: imax=i;
4345: }
4346: }
4347: if (j != imax) {
4348: for (k=1;k<=n;k++) {
4349: dum=a[imax][k];
4350: a[imax][k]=a[j][k];
4351: a[j][k]=dum;
4352: }
4353: *d = -(*d);
4354: vv[imax]=vv[j];
4355: }
4356: indx[j]=imax;
4357: if (a[j][j] == 0.0) a[j][j]=TINY;
4358: if (j != n) {
4359: dum=1.0/(a[j][j]);
4360: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4361: }
4362: }
4363: free_vector(vv,1,n); /* Doesn't work */
4364: ;
4365: }
4366:
4367: void lubksb(double **a, int n, int *indx, double b[])
4368: {
4369: int i,ii=0,ip,j;
4370: double sum;
4371:
4372: for (i=1;i<=n;i++) {
4373: ip=indx[i];
4374: sum=b[ip];
4375: b[ip]=b[i];
4376: if (ii)
4377: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4378: else if (sum) ii=i;
4379: b[i]=sum;
4380: }
4381: for (i=n;i>=1;i--) {
4382: sum=b[i];
4383: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4384: b[i]=sum/a[i][i];
4385: }
4386: }
4387:
4388: void pstamp(FILE *fichier)
4389: {
1.196 brouard 4390: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4391: }
4392:
1.253 brouard 4393:
4394:
1.126 brouard 4395: /************ Frequencies ********************/
1.251 brouard 4396: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4397: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4398: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4399: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4400:
1.265 brouard 4401: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4402: int iind=0, iage=0;
4403: int mi; /* Effective wave */
4404: int first;
4405: double ***freq; /* Frequencies */
1.268 brouard 4406: 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 */
4407: 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 4408: double *meanq, *stdq, *idq;
1.226 brouard 4409: double **meanqt;
4410: double *pp, **prop, *posprop, *pospropt;
4411: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4412: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4413: double agebegin, ageend;
4414:
4415: pp=vector(1,nlstate);
1.251 brouard 4416: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4417: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4418: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4419: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4420: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4421: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4422: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4423: meanqt=matrix(1,lastpass,1,nqtveff);
4424: strcpy(fileresp,"P_");
4425: strcat(fileresp,fileresu);
4426: /*strcat(fileresphtm,fileresu);*/
4427: if((ficresp=fopen(fileresp,"w"))==NULL) {
4428: printf("Problem with prevalence resultfile: %s\n", fileresp);
4429: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4430: exit(0);
4431: }
1.240 brouard 4432:
1.226 brouard 4433: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4434: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4435: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4436: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4437: fflush(ficlog);
4438: exit(70);
4439: }
4440: else{
4441: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4442: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4443: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4444: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4445: }
1.237 brouard 4446: 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 4447:
1.226 brouard 4448: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4449: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4450: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4451: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4452: fflush(ficlog);
4453: exit(70);
1.240 brouard 4454: } else{
1.226 brouard 4455: 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 4456: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4457: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4458: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4459: }
1.240 brouard 4460: 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);
4461:
1.253 brouard 4462: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4463: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4464: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4465: j1=0;
1.126 brouard 4466:
1.227 brouard 4467: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4468: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4469: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4470:
4471:
1.226 brouard 4472: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4473: reference=low_education V1=0,V2=0
4474: med_educ V1=1 V2=0,
4475: high_educ V1=0 V2=1
4476: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4477: */
1.249 brouard 4478: dateintsum=0;
4479: k2cpt=0;
4480:
1.253 brouard 4481: if(cptcoveff == 0 )
1.265 brouard 4482: nl=1; /* Constant and age model only */
1.253 brouard 4483: else
4484: nl=2;
1.265 brouard 4485:
4486: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4487: /* Loop on nj=1 or 2 if dummy covariates j!=0
4488: * Loop on j1(1 to 2**cptcoveff) covariate combination
4489: * freq[s1][s2][iage] =0.
4490: * Loop on iind
4491: * ++freq[s1][s2][iage] weighted
4492: * end iind
4493: * if covariate and j!0
4494: * headers Variable on one line
4495: * endif cov j!=0
4496: * header of frequency table by age
4497: * Loop on age
4498: * pp[s1]+=freq[s1][s2][iage] weighted
4499: * pos+=freq[s1][s2][iage] weighted
4500: * Loop on s1 initial state
4501: * fprintf(ficresp
4502: * end s1
4503: * end age
4504: * if j!=0 computes starting values
4505: * end compute starting values
4506: * end j1
4507: * end nl
4508: */
1.253 brouard 4509: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4510: if(nj==1)
4511: j=0; /* First pass for the constant */
1.265 brouard 4512: else{
1.253 brouard 4513: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4514: }
1.251 brouard 4515: first=1;
1.265 brouard 4516: 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 4517: posproptt=0.;
4518: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4519: scanf("%d", i);*/
4520: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4521: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4522: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4523: freq[i][s2][m]=0;
1.251 brouard 4524:
4525: for (i=1; i<=nlstate; i++) {
1.240 brouard 4526: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4527: prop[i][m]=0;
4528: posprop[i]=0;
4529: pospropt[i]=0;
4530: }
1.283 brouard 4531: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4532: idq[z1]=0.;
4533: meanq[z1]=0.;
4534: stdq[z1]=0.;
1.283 brouard 4535: }
4536: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4537: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4538: /* meanqt[m][z1]=0.; */
4539: /* } */
4540: /* } */
1.251 brouard 4541: /* dateintsum=0; */
4542: /* k2cpt=0; */
4543:
1.265 brouard 4544: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4545: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4546: bool=1;
4547: if(j !=0){
4548: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4549: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4550: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4551: /* if(Tvaraff[z1] ==-20){ */
4552: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4553: /* }else if(Tvaraff[z1] ==-10){ */
4554: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4555: /* }else */
4556: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4557: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4558: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4559: /* 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",
4560: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4561: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4562: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4563: } /* Onlyf fixed */
4564: } /* end z1 */
4565: } /* cptcovn > 0 */
4566: } /* end any */
4567: }/* end j==0 */
1.265 brouard 4568: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4569: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4570: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4571: m=mw[mi][iind];
4572: if(j!=0){
4573: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4574: for (z1=1; z1<=cptcoveff; z1++) {
4575: if( Fixed[Tmodelind[z1]]==1){
4576: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4577: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4578: value is -1, we don't select. It differs from the
4579: constant and age model which counts them. */
4580: bool=0; /* not selected */
4581: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4582: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4583: bool=0;
4584: }
4585: }
4586: }
4587: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4588: } /* end j==0 */
4589: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4590: if(bool==1){ /*Selected */
1.251 brouard 4591: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4592: and mw[mi+1][iind]. dh depends on stepm. */
4593: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4594: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4595: if(m >=firstpass && m <=lastpass){
4596: k2=anint[m][iind]+(mint[m][iind]/12.);
4597: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4598: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4599: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4600: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4601: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4602: if (m<lastpass) {
4603: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4604: /* 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]); */
4605: if(s[m][iind]==-1)
4606: 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.));
4607: 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 4608: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4609: idq[z1]=idq[z1]+weight[iind];
4610: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4611: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4612: }
1.251 brouard 4613: /* if((int)agev[m][iind] == 55) */
4614: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4615: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4616: 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 4617: }
1.251 brouard 4618: } /* end if between passes */
4619: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4620: dateintsum=dateintsum+k2; /* on all covariates ?*/
4621: k2cpt++;
4622: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4623: }
1.251 brouard 4624: }else{
4625: bool=1;
4626: }/* end bool 2 */
4627: } /* end m */
1.284 brouard 4628: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4629: /* idq[z1]=idq[z1]+weight[iind]; */
4630: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4631: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4632: /* } */
1.251 brouard 4633: } /* end bool */
4634: } /* end iind = 1 to imx */
4635: /* prop[s][age] is feeded for any initial and valid live state as well as
4636: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4637:
4638:
4639: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4640: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4641: pstamp(ficresp);
1.251 brouard 4642: if (cptcoveff>0 && j!=0){
1.265 brouard 4643: pstamp(ficresp);
1.251 brouard 4644: printf( "\n#********** Variable ");
4645: fprintf(ficresp, "\n#********** Variable ");
4646: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4647: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4648: fprintf(ficlog, "\n#********** Variable ");
4649: for (z1=1; z1<=cptcoveff; z1++){
4650: if(!FixedV[Tvaraff[z1]]){
4651: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4652: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4653: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4654: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4655: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4656: }else{
1.251 brouard 4657: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4658: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4659: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4660: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4661: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4662: }
4663: }
4664: printf( "**********\n#");
4665: fprintf(ficresp, "**********\n#");
4666: fprintf(ficresphtm, "**********</h3>\n");
4667: fprintf(ficresphtmfr, "**********</h3>\n");
4668: fprintf(ficlog, "**********\n");
4669: }
1.284 brouard 4670: /*
4671: Printing means of quantitative variables if any
4672: */
4673: for (z1=1; z1<= nqfveff; z1++) {
1.285 brouard 4674: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4675: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4676: if(weightopt==1){
4677: printf(" Weighted mean and standard deviation of");
4678: fprintf(ficlog," Weighted mean and standard deviation of");
4679: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4680: }
1.285 brouard 4681: 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]));
4682: 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]));
4683: 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 4684: }
4685: /* for (z1=1; z1<= nqtveff; z1++) { */
4686: /* for(m=1;m<=lastpass;m++){ */
4687: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4688: /* } */
4689: /* } */
1.283 brouard 4690:
1.251 brouard 4691: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4692: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4693: fprintf(ficresp, " Age");
4694: 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 4695: for(i=1; i<=nlstate;i++) {
1.265 brouard 4696: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4697: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4698: }
1.265 brouard 4699: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4700: fprintf(ficresphtm, "\n");
4701:
4702: /* Header of frequency table by age */
4703: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4704: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4705: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4706: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4707: if(s2!=0 && m!=0)
4708: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4709: }
1.226 brouard 4710: }
1.251 brouard 4711: fprintf(ficresphtmfr, "\n");
4712:
4713: /* For each age */
4714: for(iage=iagemin; iage <= iagemax+3; iage++){
4715: fprintf(ficresphtm,"<tr>");
4716: if(iage==iagemax+1){
4717: fprintf(ficlog,"1");
4718: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4719: }else if(iage==iagemax+2){
4720: fprintf(ficlog,"0");
4721: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4722: }else if(iage==iagemax+3){
4723: fprintf(ficlog,"Total");
4724: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4725: }else{
1.240 brouard 4726: if(first==1){
1.251 brouard 4727: first=0;
4728: printf("See log file for details...\n");
4729: }
4730: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4731: fprintf(ficlog,"Age %d", iage);
4732: }
1.265 brouard 4733: for(s1=1; s1 <=nlstate ; s1++){
4734: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4735: pp[s1] += freq[s1][m][iage];
1.251 brouard 4736: }
1.265 brouard 4737: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4738: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4739: pos += freq[s1][m][iage];
4740: if(pp[s1]>=1.e-10){
1.251 brouard 4741: if(first==1){
1.265 brouard 4742: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4743: }
1.265 brouard 4744: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4745: }else{
4746: if(first==1)
1.265 brouard 4747: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4748: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4749: }
4750: }
4751:
1.265 brouard 4752: for(s1=1; s1 <=nlstate ; s1++){
4753: /* posprop[s1]=0; */
4754: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4755: pp[s1] += freq[s1][m][iage];
4756: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4757:
4758: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4759: pos += pp[s1]; /* pos is the total number of transitions until this age */
4760: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4761: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4762: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4763: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4764: }
4765:
4766: /* Writing ficresp */
4767: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4768: if( iage <= iagemax){
4769: fprintf(ficresp," %d",iage);
4770: }
4771: }else if( nj==2){
4772: if( iage <= iagemax){
4773: fprintf(ficresp," %d",iage);
4774: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4775: }
1.240 brouard 4776: }
1.265 brouard 4777: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4778: if(pos>=1.e-5){
1.251 brouard 4779: if(first==1)
1.265 brouard 4780: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4781: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4782: }else{
4783: if(first==1)
1.265 brouard 4784: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4785: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4786: }
4787: if( iage <= iagemax){
4788: if(pos>=1.e-5){
1.265 brouard 4789: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4790: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4791: }else if( nj==2){
4792: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4793: }
4794: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4795: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4796: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4797: } else{
4798: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4799: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4800: }
1.240 brouard 4801: }
1.265 brouard 4802: pospropt[s1] +=posprop[s1];
4803: } /* end loop s1 */
1.251 brouard 4804: /* pospropt=0.; */
1.265 brouard 4805: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4806: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4807: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4808: if(first==1){
1.265 brouard 4809: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4810: }
1.265 brouard 4811: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4812: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4813: }
1.265 brouard 4814: if(s1!=0 && m!=0)
4815: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4816: }
1.265 brouard 4817: } /* end loop s1 */
1.251 brouard 4818: posproptt=0.;
1.265 brouard 4819: for(s1=1; s1 <=nlstate; s1++){
4820: posproptt += pospropt[s1];
1.251 brouard 4821: }
4822: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4823: fprintf(ficresphtm,"</tr>\n");
4824: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4825: if(iage <= iagemax)
4826: fprintf(ficresp,"\n");
1.240 brouard 4827: }
1.251 brouard 4828: if(first==1)
4829: printf("Others in log...\n");
4830: fprintf(ficlog,"\n");
4831: } /* end loop age iage */
1.265 brouard 4832:
1.251 brouard 4833: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4834: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4835: if(posproptt < 1.e-5){
1.265 brouard 4836: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4837: }else{
1.265 brouard 4838: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4839: }
1.226 brouard 4840: }
1.251 brouard 4841: fprintf(ficresphtm,"</tr>\n");
4842: fprintf(ficresphtm,"</table>\n");
4843: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4844: if(posproptt < 1.e-5){
1.251 brouard 4845: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4846: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4847: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4848: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4849: invalidvarcomb[j1]=1;
1.226 brouard 4850: }else{
1.251 brouard 4851: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4852: invalidvarcomb[j1]=0;
1.226 brouard 4853: }
1.251 brouard 4854: fprintf(ficresphtmfr,"</table>\n");
4855: fprintf(ficlog,"\n");
4856: if(j!=0){
4857: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4858: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4859: for(k=1; k <=(nlstate+ndeath); k++){
4860: if (k != i) {
1.265 brouard 4861: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4862: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4863: if(j1==1){ /* All dummy covariates to zero */
4864: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4865: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4866: printf("%d%d ",i,k);
4867: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4868: 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]));
4869: 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]));
4870: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4871: }
1.253 brouard 4872: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4873: for(iage=iagemin; iage <= iagemax+3; iage++){
4874: x[iage]= (double)iage;
4875: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4876: /* 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 4877: }
1.268 brouard 4878: /* Some are not finite, but linreg will ignore these ages */
4879: no=0;
1.253 brouard 4880: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4881: pstart[s1]=b;
4882: pstart[s1-1]=a;
1.252 brouard 4883: }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 */
4884: 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]);
4885: 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 4886: 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 4887: printf("%d%d ",i,k);
4888: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4889: 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 4890: }else{ /* Other cases, like quantitative fixed or varying covariates */
4891: ;
4892: }
4893: /* printf("%12.7f )", param[i][jj][k]); */
4894: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4895: s1++;
1.251 brouard 4896: } /* end jj */
4897: } /* end k!= i */
4898: } /* end k */
1.265 brouard 4899: } /* end i, s1 */
1.251 brouard 4900: } /* end j !=0 */
4901: } /* end selected combination of covariate j1 */
4902: if(j==0){ /* We can estimate starting values from the occurences in each case */
4903: printf("#Freqsummary: Starting values for the constants:\n");
4904: fprintf(ficlog,"\n");
1.265 brouard 4905: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4906: for(k=1; k <=(nlstate+ndeath); k++){
4907: if (k != i) {
4908: printf("%d%d ",i,k);
4909: fprintf(ficlog,"%d%d ",i,k);
4910: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4911: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4912: if(jj==1){ /* Age has to be done */
1.265 brouard 4913: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4914: 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]));
4915: 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 4916: }
4917: /* printf("%12.7f )", param[i][jj][k]); */
4918: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4919: s1++;
1.250 brouard 4920: }
1.251 brouard 4921: printf("\n");
4922: fprintf(ficlog,"\n");
1.250 brouard 4923: }
4924: }
1.284 brouard 4925: } /* end of state i */
1.251 brouard 4926: printf("#Freqsummary\n");
4927: fprintf(ficlog,"\n");
1.265 brouard 4928: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4929: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4930: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4931: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4932: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4933: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4934: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4935: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4936: /* } */
4937: }
1.265 brouard 4938: } /* end loop s1 */
1.251 brouard 4939:
4940: printf("\n");
4941: fprintf(ficlog,"\n");
4942: } /* end j=0 */
1.249 brouard 4943: } /* end j */
1.252 brouard 4944:
1.253 brouard 4945: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4946: for(i=1, jk=1; i <=nlstate; i++){
4947: for(j=1; j <=nlstate+ndeath; j++){
4948: if(j!=i){
4949: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4950: printf("%1d%1d",i,j);
4951: fprintf(ficparo,"%1d%1d",i,j);
4952: for(k=1; k<=ncovmodel;k++){
4953: /* printf(" %lf",param[i][j][k]); */
4954: /* fprintf(ficparo," %lf",param[i][j][k]); */
4955: p[jk]=pstart[jk];
4956: printf(" %f ",pstart[jk]);
4957: fprintf(ficparo," %f ",pstart[jk]);
4958: jk++;
4959: }
4960: printf("\n");
4961: fprintf(ficparo,"\n");
4962: }
4963: }
4964: }
4965: } /* end mle=-2 */
1.226 brouard 4966: dateintmean=dateintsum/k2cpt;
1.240 brouard 4967:
1.226 brouard 4968: fclose(ficresp);
4969: fclose(ficresphtm);
4970: fclose(ficresphtmfr);
1.283 brouard 4971: free_vector(idq,1,nqfveff);
1.226 brouard 4972: free_vector(meanq,1,nqfveff);
1.284 brouard 4973: free_vector(stdq,1,nqfveff);
1.226 brouard 4974: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4975: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4976: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4977: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4978: free_vector(pospropt,1,nlstate);
4979: free_vector(posprop,1,nlstate);
1.251 brouard 4980: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4981: free_vector(pp,1,nlstate);
4982: /* End of freqsummary */
4983: }
1.126 brouard 4984:
1.268 brouard 4985: /* Simple linear regression */
4986: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4987:
4988: /* y=a+bx regression */
4989: double sumx = 0.0; /* sum of x */
4990: double sumx2 = 0.0; /* sum of x**2 */
4991: double sumxy = 0.0; /* sum of x * y */
4992: double sumy = 0.0; /* sum of y */
4993: double sumy2 = 0.0; /* sum of y**2 */
4994: double sume2 = 0.0; /* sum of square or residuals */
4995: double yhat;
4996:
4997: double denom=0;
4998: int i;
4999: int ne=*no;
5000:
5001: for ( i=ifi, ne=0;i<=ila;i++) {
5002: if(!isfinite(x[i]) || !isfinite(y[i])){
5003: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5004: continue;
5005: }
5006: ne=ne+1;
5007: sumx += x[i];
5008: sumx2 += x[i]*x[i];
5009: sumxy += x[i] * y[i];
5010: sumy += y[i];
5011: sumy2 += y[i]*y[i];
5012: denom = (ne * sumx2 - sumx*sumx);
5013: /* 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); */
5014: }
5015:
5016: denom = (ne * sumx2 - sumx*sumx);
5017: if (denom == 0) {
5018: // vertical, slope m is infinity
5019: *b = INFINITY;
5020: *a = 0;
5021: if (r) *r = 0;
5022: return 1;
5023: }
5024:
5025: *b = (ne * sumxy - sumx * sumy) / denom;
5026: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5027: if (r!=NULL) {
5028: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5029: sqrt((sumx2 - sumx*sumx/ne) *
5030: (sumy2 - sumy*sumy/ne));
5031: }
5032: *no=ne;
5033: for ( i=ifi, ne=0;i<=ila;i++) {
5034: if(!isfinite(x[i]) || !isfinite(y[i])){
5035: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5036: continue;
5037: }
5038: ne=ne+1;
5039: yhat = y[i] - *a -*b* x[i];
5040: sume2 += yhat * yhat ;
5041:
5042: denom = (ne * sumx2 - sumx*sumx);
5043: /* 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); */
5044: }
5045: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5046: *sa= *sb * sqrt(sumx2/ne);
5047:
5048: return 0;
5049: }
5050:
1.126 brouard 5051: /************ Prevalence ********************/
1.227 brouard 5052: 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)
5053: {
5054: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5055: in each health status at the date of interview (if between dateprev1 and dateprev2).
5056: We still use firstpass and lastpass as another selection.
5057: */
1.126 brouard 5058:
1.227 brouard 5059: int i, m, jk, j1, bool, z1,j, iv;
5060: int mi; /* Effective wave */
5061: int iage;
5062: double agebegin, ageend;
5063:
5064: double **prop;
5065: double posprop;
5066: double y2; /* in fractional years */
5067: int iagemin, iagemax;
5068: int first; /** to stop verbosity which is redirected to log file */
5069:
5070: iagemin= (int) agemin;
5071: iagemax= (int) agemax;
5072: /*pp=vector(1,nlstate);*/
1.251 brouard 5073: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5074: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5075: j1=0;
1.222 brouard 5076:
1.227 brouard 5077: /*j=cptcoveff;*/
5078: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5079:
1.288 brouard 5080: first=0;
1.227 brouard 5081: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5082: for (i=1; i<=nlstate; i++)
1.251 brouard 5083: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5084: prop[i][iage]=0.0;
5085: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5086: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5087: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5088:
5089: for (i=1; i<=imx; i++) { /* Each individual */
5090: bool=1;
5091: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5092: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5093: m=mw[mi][i];
5094: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5095: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5096: for (z1=1; z1<=cptcoveff; z1++){
5097: if( Fixed[Tmodelind[z1]]==1){
5098: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5099: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5100: bool=0;
5101: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5102: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5103: bool=0;
5104: }
5105: }
5106: if(bool==1){ /* Otherwise we skip that wave/person */
5107: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5108: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5109: if(m >=firstpass && m <=lastpass){
5110: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5111: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5112: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5113: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5114: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5115: 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);
5116: exit(1);
5117: }
5118: if (s[m][i]>0 && s[m][i]<=nlstate) {
5119: /*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]]);*/
5120: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5121: prop[s[m][i]][iagemax+3] += weight[i];
5122: } /* end valid statuses */
5123: } /* end selection of dates */
5124: } /* end selection of waves */
5125: } /* end bool */
5126: } /* end wave */
5127: } /* end individual */
5128: for(i=iagemin; i <= iagemax+3; i++){
5129: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5130: posprop += prop[jk][i];
5131: }
5132:
5133: for(jk=1; jk <=nlstate ; jk++){
5134: if( i <= iagemax){
5135: if(posprop>=1.e-5){
5136: probs[i][jk][j1]= prop[jk][i]/posprop;
5137: } else{
1.288 brouard 5138: if(!first){
5139: first=1;
1.266 brouard 5140: 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]);
5141: }else{
1.288 brouard 5142: 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 5143: }
5144: }
5145: }
5146: }/* end jk */
5147: }/* end i */
1.222 brouard 5148: /*} *//* end i1 */
1.227 brouard 5149: } /* end j1 */
1.222 brouard 5150:
1.227 brouard 5151: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5152: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5153: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5154: } /* End of prevalence */
1.126 brouard 5155:
5156: /************* Waves Concatenation ***************/
5157:
5158: 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)
5159: {
5160: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5161: Death is a valid wave (if date is known).
5162: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5163: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5164: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5165: */
1.126 brouard 5166:
1.224 brouard 5167: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5168: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5169: double sum=0., jmean=0.;*/
1.224 brouard 5170: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5171: int j, k=0,jk, ju, jl;
5172: double sum=0.;
5173: first=0;
1.214 brouard 5174: firstwo=0;
1.217 brouard 5175: firsthree=0;
1.218 brouard 5176: firstfour=0;
1.164 brouard 5177: jmin=100000;
1.126 brouard 5178: jmax=-1;
5179: jmean=0.;
1.224 brouard 5180:
5181: /* Treating live states */
1.214 brouard 5182: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5183: mi=0; /* First valid wave */
1.227 brouard 5184: mli=0; /* Last valid wave */
1.126 brouard 5185: m=firstpass;
1.214 brouard 5186: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5187: 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 */
5188: mli=m-1;/* mw[++mi][i]=m-1; */
5189: }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 */
5190: mw[++mi][i]=m;
5191: mli=m;
1.224 brouard 5192: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5193: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5194: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5195: }
1.227 brouard 5196: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5197: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5198: break;
1.224 brouard 5199: #else
1.227 brouard 5200: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5201: if(firsthree == 0){
1.262 brouard 5202: 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 5203: firsthree=1;
5204: }
1.262 brouard 5205: 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 5206: mw[++mi][i]=m;
5207: mli=m;
5208: }
5209: if(s[m][i]==-2){ /* Vital status is really unknown */
5210: nbwarn++;
5211: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5212: 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);
5213: 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);
5214: }
5215: break;
5216: }
5217: break;
1.224 brouard 5218: #endif
1.227 brouard 5219: }/* End m >= lastpass */
1.126 brouard 5220: }/* end while */
1.224 brouard 5221:
1.227 brouard 5222: /* 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 5223: /* After last pass */
1.224 brouard 5224: /* Treating death states */
1.214 brouard 5225: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5226: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5227: /* } */
1.126 brouard 5228: mi++; /* Death is another wave */
5229: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5230: /* Only death is a correct wave */
1.126 brouard 5231: mw[mi][i]=m;
1.257 brouard 5232: } /* else not in a death state */
1.224 brouard 5233: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5234: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5235: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5236: 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 */
5237: nbwarn++;
5238: if(firstfiv==0){
5239: 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 );
5240: firstfiv=1;
5241: }else{
5242: 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 );
5243: }
5244: }else{ /* Death occured afer last wave potential bias */
5245: nberr++;
5246: if(firstwo==0){
1.257 brouard 5247: 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 5248: firstwo=1;
5249: }
1.257 brouard 5250: 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 5251: }
1.257 brouard 5252: }else{ /* if date of interview is unknown */
1.227 brouard 5253: /* death is known but not confirmed by death status at any wave */
5254: if(firstfour==0){
5255: 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 );
5256: firstfour=1;
5257: }
5258: 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 5259: }
1.224 brouard 5260: } /* end if date of death is known */
5261: #endif
5262: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5263: /* wav[i]=mw[mi][i]; */
1.126 brouard 5264: if(mi==0){
5265: nbwarn++;
5266: if(first==0){
1.227 brouard 5267: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5268: first=1;
1.126 brouard 5269: }
5270: if(first==1){
1.227 brouard 5271: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5272: }
5273: } /* end mi==0 */
5274: } /* End individuals */
1.214 brouard 5275: /* wav and mw are no more changed */
1.223 brouard 5276:
1.214 brouard 5277:
1.126 brouard 5278: for(i=1; i<=imx; i++){
5279: for(mi=1; mi<wav[i];mi++){
5280: if (stepm <=0)
1.227 brouard 5281: dh[mi][i]=1;
1.126 brouard 5282: else{
1.260 brouard 5283: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5284: if (agedc[i] < 2*AGESUP) {
5285: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5286: if(j==0) j=1; /* Survives at least one month after exam */
5287: else if(j<0){
5288: nberr++;
5289: 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]);
5290: j=1; /* Temporary Dangerous patch */
5291: 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);
5292: 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]);
5293: 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);
5294: }
5295: k=k+1;
5296: if (j >= jmax){
5297: jmax=j;
5298: ijmax=i;
5299: }
5300: if (j <= jmin){
5301: jmin=j;
5302: ijmin=i;
5303: }
5304: sum=sum+j;
5305: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5306: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5307: }
5308: }
5309: else{
5310: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5311: /* 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 5312:
1.227 brouard 5313: k=k+1;
5314: if (j >= jmax) {
5315: jmax=j;
5316: ijmax=i;
5317: }
5318: else if (j <= jmin){
5319: jmin=j;
5320: ijmin=i;
5321: }
5322: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5323: /*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]);*/
5324: if(j<0){
5325: nberr++;
5326: 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]);
5327: 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]);
5328: }
5329: sum=sum+j;
5330: }
5331: jk= j/stepm;
5332: jl= j -jk*stepm;
5333: ju= j -(jk+1)*stepm;
5334: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5335: if(jl==0){
5336: dh[mi][i]=jk;
5337: bh[mi][i]=0;
5338: }else{ /* We want a negative bias in order to only have interpolation ie
5339: * to avoid the price of an extra matrix product in likelihood */
5340: dh[mi][i]=jk+1;
5341: bh[mi][i]=ju;
5342: }
5343: }else{
5344: if(jl <= -ju){
5345: dh[mi][i]=jk;
5346: bh[mi][i]=jl; /* bias is positive if real duration
5347: * is higher than the multiple of stepm and negative otherwise.
5348: */
5349: }
5350: else{
5351: dh[mi][i]=jk+1;
5352: bh[mi][i]=ju;
5353: }
5354: if(dh[mi][i]==0){
5355: dh[mi][i]=1; /* At least one step */
5356: bh[mi][i]=ju; /* At least one step */
5357: /* 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);*/
5358: }
5359: } /* end if mle */
1.126 brouard 5360: }
5361: } /* end wave */
5362: }
5363: jmean=sum/k;
5364: 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 5365: 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 5366: }
1.126 brouard 5367:
5368: /*********** Tricode ****************************/
1.220 brouard 5369: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5370: {
5371: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5372: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5373: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5374: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5375: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5376: */
1.130 brouard 5377:
1.242 brouard 5378: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5379: int modmaxcovj=0; /* Modality max of covariates j */
5380: int cptcode=0; /* Modality max of covariates j */
5381: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5382:
5383:
1.242 brouard 5384: /* cptcoveff=0; */
5385: /* *cptcov=0; */
1.126 brouard 5386:
1.242 brouard 5387: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5388: for (k=1; k <= maxncov; k++)
5389: for(j=1; j<=2; j++)
5390: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5391:
1.242 brouard 5392: /* Loop on covariates without age and products and no quantitative variable */
5393: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5394: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5395: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5396: switch(Fixed[k]) {
5397: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5398: 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*/
5399: ij=(int)(covar[Tvar[k]][i]);
5400: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5401: * If product of Vn*Vm, still boolean *:
5402: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5403: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5404: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5405: modality of the nth covariate of individual i. */
5406: if (ij > modmaxcovj)
5407: modmaxcovj=ij;
5408: else if (ij < modmincovj)
5409: modmincovj=ij;
1.287 brouard 5410: if (ij <0 || ij >1 ){
5411: printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5412: fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5413: }
5414: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5415: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5416: exit(1);
5417: }else
5418: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5419: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5420: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5421: /* getting the maximum value of the modality of the covariate
5422: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5423: female ies 1, then modmaxcovj=1.
5424: */
5425: } /* end for loop on individuals i */
5426: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5427: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5428: cptcode=modmaxcovj;
5429: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5430: /*for (i=0; i<=cptcode; i++) {*/
5431: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5432: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5433: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5434: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5435: if( j != -1){
5436: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5437: covariate for which somebody answered excluding
5438: undefined. Usually 2: 0 and 1. */
5439: }
5440: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5441: covariate for which somebody answered including
5442: undefined. Usually 3: -1, 0 and 1. */
5443: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5444: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5445: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5446:
1.242 brouard 5447: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5448: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5449: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5450: /* modmincovj=3; modmaxcovj = 7; */
5451: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5452: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5453: /* defining two dummy variables: variables V1_1 and V1_2.*/
5454: /* nbcode[Tvar[j]][ij]=k; */
5455: /* nbcode[Tvar[j]][1]=0; */
5456: /* nbcode[Tvar[j]][2]=1; */
5457: /* nbcode[Tvar[j]][3]=2; */
5458: /* To be continued (not working yet). */
5459: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5460:
5461: /* 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*/
5462: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5463: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5464: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5465: /*, could be restored in the future */
5466: 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 5467: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5468: break;
5469: }
5470: ij++;
1.287 brouard 5471: 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 5472: cptcode = ij; /* New max modality for covar j */
5473: } /* end of loop on modality i=-1 to 1 or more */
5474: break;
5475: case 1: /* Testing on varying covariate, could be simple and
5476: * should look at waves or product of fixed *
5477: * varying. No time to test -1, assuming 0 and 1 only */
5478: ij=0;
5479: for(i=0; i<=1;i++){
5480: nbcode[Tvar[k]][++ij]=i;
5481: }
5482: break;
5483: default:
5484: break;
5485: } /* end switch */
5486: } /* end dummy test */
1.287 brouard 5487: } /* 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 5488:
5489: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5490: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5491: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5492: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5493: 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 */
5494: 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 */
5495: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5496: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5497:
5498: ij=0;
5499: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5500: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5501: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5502: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5503: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5504: /* If product not in single variable we don't print results */
5505: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5506: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5507: 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*/
5508: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5509: 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 */
5510: if(Fixed[k]!=0)
5511: anyvaryingduminmodel=1;
5512: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5513: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5514: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5515: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5516: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5517: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5518: }
5519: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5520: /* ij--; */
5521: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5522: *cptcov=ij; /*Number of total real effective covariates: effective
5523: * because they can be excluded from the model and real
5524: * if in the model but excluded because missing values, but how to get k from ij?*/
5525: for(j=ij+1; j<= cptcovt; j++){
5526: Tvaraff[j]=0;
5527: Tmodelind[j]=0;
5528: }
5529: for(j=ntveff+1; j<= cptcovt; j++){
5530: TmodelInvind[j]=0;
5531: }
5532: /* To be sorted */
5533: ;
5534: }
1.126 brouard 5535:
1.145 brouard 5536:
1.126 brouard 5537: /*********** Health Expectancies ****************/
5538:
1.235 brouard 5539: 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 5540:
5541: {
5542: /* Health expectancies, no variances */
1.164 brouard 5543: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5544: int nhstepma, nstepma; /* Decreasing with age */
5545: double age, agelim, hf;
5546: double ***p3mat;
5547: double eip;
5548:
1.238 brouard 5549: /* pstamp(ficreseij); */
1.126 brouard 5550: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5551: fprintf(ficreseij,"# Age");
5552: for(i=1; i<=nlstate;i++){
5553: for(j=1; j<=nlstate;j++){
5554: fprintf(ficreseij," e%1d%1d ",i,j);
5555: }
5556: fprintf(ficreseij," e%1d. ",i);
5557: }
5558: fprintf(ficreseij,"\n");
5559:
5560:
5561: if(estepm < stepm){
5562: printf ("Problem %d lower than %d\n",estepm, stepm);
5563: }
5564: else hstepm=estepm;
5565: /* We compute the life expectancy from trapezoids spaced every estepm months
5566: * This is mainly to measure the difference between two models: for example
5567: * if stepm=24 months pijx are given only every 2 years and by summing them
5568: * we are calculating an estimate of the Life Expectancy assuming a linear
5569: * progression in between and thus overestimating or underestimating according
5570: * to the curvature of the survival function. If, for the same date, we
5571: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5572: * to compare the new estimate of Life expectancy with the same linear
5573: * hypothesis. A more precise result, taking into account a more precise
5574: * curvature will be obtained if estepm is as small as stepm. */
5575:
5576: /* For example we decided to compute the life expectancy with the smallest unit */
5577: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5578: nhstepm is the number of hstepm from age to agelim
5579: nstepm is the number of stepm from age to agelin.
1.270 brouard 5580: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5581: and note for a fixed period like estepm months */
5582: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5583: survival function given by stepm (the optimization length). Unfortunately it
5584: means that if the survival funtion is printed only each two years of age and if
5585: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5586: results. So we changed our mind and took the option of the best precision.
5587: */
5588: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5589:
5590: agelim=AGESUP;
5591: /* If stepm=6 months */
5592: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5593: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5594:
5595: /* nhstepm age range expressed in number of stepm */
5596: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5597: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5598: /* if (stepm >= YEARM) hstepm=1;*/
5599: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5600: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5601:
5602: for (age=bage; age<=fage; age ++){
5603: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5604: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5605: /* if (stepm >= YEARM) hstepm=1;*/
5606: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5607:
5608: /* If stepm=6 months */
5609: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5610: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5611:
1.235 brouard 5612: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5613:
5614: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5615:
5616: printf("%d|",(int)age);fflush(stdout);
5617: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5618:
5619: /* Computing expectancies */
5620: for(i=1; i<=nlstate;i++)
5621: for(j=1; j<=nlstate;j++)
5622: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5623: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5624:
5625: /* 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]);*/
5626:
5627: }
5628:
5629: fprintf(ficreseij,"%3.0f",age );
5630: for(i=1; i<=nlstate;i++){
5631: eip=0;
5632: for(j=1; j<=nlstate;j++){
5633: eip +=eij[i][j][(int)age];
5634: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5635: }
5636: fprintf(ficreseij,"%9.4f", eip );
5637: }
5638: fprintf(ficreseij,"\n");
5639:
5640: }
5641: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5642: printf("\n");
5643: fprintf(ficlog,"\n");
5644:
5645: }
5646:
1.235 brouard 5647: 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 5648:
5649: {
5650: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5651: to initial status i, ei. .
1.126 brouard 5652: */
5653: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5654: int nhstepma, nstepma; /* Decreasing with age */
5655: double age, agelim, hf;
5656: double ***p3matp, ***p3matm, ***varhe;
5657: double **dnewm,**doldm;
5658: double *xp, *xm;
5659: double **gp, **gm;
5660: double ***gradg, ***trgradg;
5661: int theta;
5662:
5663: double eip, vip;
5664:
5665: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5666: xp=vector(1,npar);
5667: xm=vector(1,npar);
5668: dnewm=matrix(1,nlstate*nlstate,1,npar);
5669: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5670:
5671: pstamp(ficresstdeij);
5672: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5673: fprintf(ficresstdeij,"# Age");
5674: for(i=1; i<=nlstate;i++){
5675: for(j=1; j<=nlstate;j++)
5676: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5677: fprintf(ficresstdeij," e%1d. ",i);
5678: }
5679: fprintf(ficresstdeij,"\n");
5680:
5681: pstamp(ficrescveij);
5682: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5683: fprintf(ficrescveij,"# Age");
5684: for(i=1; i<=nlstate;i++)
5685: for(j=1; j<=nlstate;j++){
5686: cptj= (j-1)*nlstate+i;
5687: for(i2=1; i2<=nlstate;i2++)
5688: for(j2=1; j2<=nlstate;j2++){
5689: cptj2= (j2-1)*nlstate+i2;
5690: if(cptj2 <= cptj)
5691: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5692: }
5693: }
5694: fprintf(ficrescveij,"\n");
5695:
5696: if(estepm < stepm){
5697: printf ("Problem %d lower than %d\n",estepm, stepm);
5698: }
5699: else hstepm=estepm;
5700: /* We compute the life expectancy from trapezoids spaced every estepm months
5701: * This is mainly to measure the difference between two models: for example
5702: * if stepm=24 months pijx are given only every 2 years and by summing them
5703: * we are calculating an estimate of the Life Expectancy assuming a linear
5704: * progression in between and thus overestimating or underestimating according
5705: * to the curvature of the survival function. If, for the same date, we
5706: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5707: * to compare the new estimate of Life expectancy with the same linear
5708: * hypothesis. A more precise result, taking into account a more precise
5709: * curvature will be obtained if estepm is as small as stepm. */
5710:
5711: /* For example we decided to compute the life expectancy with the smallest unit */
5712: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5713: nhstepm is the number of hstepm from age to agelim
5714: nstepm is the number of stepm from age to agelin.
5715: Look at hpijx to understand the reason of that which relies in memory size
5716: and note for a fixed period like estepm months */
5717: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5718: survival function given by stepm (the optimization length). Unfortunately it
5719: means that if the survival funtion is printed only each two years of age and if
5720: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5721: results. So we changed our mind and took the option of the best precision.
5722: */
5723: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5724:
5725: /* If stepm=6 months */
5726: /* nhstepm age range expressed in number of stepm */
5727: agelim=AGESUP;
5728: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5729: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5730: /* if (stepm >= YEARM) hstepm=1;*/
5731: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5732:
5733: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5734: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5735: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5736: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5737: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5738: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5739:
5740: for (age=bage; age<=fage; age ++){
5741: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5742: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5743: /* if (stepm >= YEARM) hstepm=1;*/
5744: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5745:
1.126 brouard 5746: /* If stepm=6 months */
5747: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5748: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5749:
5750: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5751:
1.126 brouard 5752: /* Computing Variances of health expectancies */
5753: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5754: decrease memory allocation */
5755: for(theta=1; theta <=npar; theta++){
5756: for(i=1; i<=npar; i++){
1.222 brouard 5757: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5758: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5759: }
1.235 brouard 5760: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5761: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5762:
1.126 brouard 5763: for(j=1; j<= nlstate; j++){
1.222 brouard 5764: for(i=1; i<=nlstate; i++){
5765: for(h=0; h<=nhstepm-1; h++){
5766: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5767: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5768: }
5769: }
1.126 brouard 5770: }
1.218 brouard 5771:
1.126 brouard 5772: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5773: for(h=0; h<=nhstepm-1; h++){
5774: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5775: }
1.126 brouard 5776: }/* End theta */
5777:
5778:
5779: for(h=0; h<=nhstepm-1; h++)
5780: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5781: for(theta=1; theta <=npar; theta++)
5782: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5783:
1.218 brouard 5784:
1.222 brouard 5785: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5786: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5787: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5788:
1.222 brouard 5789: printf("%d|",(int)age);fflush(stdout);
5790: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5791: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5792: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5793: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5794: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5795: for(ij=1;ij<=nlstate*nlstate;ij++)
5796: for(ji=1;ji<=nlstate*nlstate;ji++)
5797: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5798: }
5799: }
1.218 brouard 5800:
1.126 brouard 5801: /* Computing expectancies */
1.235 brouard 5802: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5803: for(i=1; i<=nlstate;i++)
5804: for(j=1; j<=nlstate;j++)
1.222 brouard 5805: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5806: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5807:
1.222 brouard 5808: /* 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 5809:
1.222 brouard 5810: }
1.269 brouard 5811:
5812: /* Standard deviation of expectancies ij */
1.126 brouard 5813: fprintf(ficresstdeij,"%3.0f",age );
5814: for(i=1; i<=nlstate;i++){
5815: eip=0.;
5816: vip=0.;
5817: for(j=1; j<=nlstate;j++){
1.222 brouard 5818: eip += eij[i][j][(int)age];
5819: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5820: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5821: 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 5822: }
5823: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5824: }
5825: fprintf(ficresstdeij,"\n");
1.218 brouard 5826:
1.269 brouard 5827: /* Variance of expectancies ij */
1.126 brouard 5828: fprintf(ficrescveij,"%3.0f",age );
5829: for(i=1; i<=nlstate;i++)
5830: for(j=1; j<=nlstate;j++){
1.222 brouard 5831: cptj= (j-1)*nlstate+i;
5832: for(i2=1; i2<=nlstate;i2++)
5833: for(j2=1; j2<=nlstate;j2++){
5834: cptj2= (j2-1)*nlstate+i2;
5835: if(cptj2 <= cptj)
5836: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5837: }
1.126 brouard 5838: }
5839: fprintf(ficrescveij,"\n");
1.218 brouard 5840:
1.126 brouard 5841: }
5842: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5843: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5844: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5845: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5846: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5847: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5848: printf("\n");
5849: fprintf(ficlog,"\n");
1.218 brouard 5850:
1.126 brouard 5851: free_vector(xm,1,npar);
5852: free_vector(xp,1,npar);
5853: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5854: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5855: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5856: }
1.218 brouard 5857:
1.126 brouard 5858: /************ Variance ******************/
1.235 brouard 5859: 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 5860: {
1.279 brouard 5861: /** Variance of health expectancies
5862: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5863: * double **newm;
5864: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5865: */
1.218 brouard 5866:
5867: /* int movingaverage(); */
5868: double **dnewm,**doldm;
5869: double **dnewmp,**doldmp;
5870: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 5871: int first=0;
1.218 brouard 5872: int k;
5873: double *xp;
1.279 brouard 5874: double **gp, **gm; /**< for var eij */
5875: double ***gradg, ***trgradg; /**< for var eij */
5876: double **gradgp, **trgradgp; /**< for var p point j */
5877: double *gpp, *gmp; /**< for var p point j */
5878: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5879: double ***p3mat;
5880: double age,agelim, hf;
5881: /* double ***mobaverage; */
5882: int theta;
5883: char digit[4];
5884: char digitp[25];
5885:
5886: char fileresprobmorprev[FILENAMELENGTH];
5887:
5888: if(popbased==1){
5889: if(mobilav!=0)
5890: strcpy(digitp,"-POPULBASED-MOBILAV_");
5891: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5892: }
5893: else
5894: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5895:
1.218 brouard 5896: /* if (mobilav!=0) { */
5897: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5898: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5899: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5900: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5901: /* } */
5902: /* } */
5903:
5904: strcpy(fileresprobmorprev,"PRMORPREV-");
5905: sprintf(digit,"%-d",ij);
5906: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5907: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5908: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5909: strcat(fileresprobmorprev,fileresu);
5910: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5911: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5912: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5913: }
5914: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5915: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5916: pstamp(ficresprobmorprev);
5917: 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 5918: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5919: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5920: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5921: }
5922: for(j=1;j<=cptcoveff;j++)
5923: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5924: fprintf(ficresprobmorprev,"\n");
5925:
1.218 brouard 5926: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5927: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5928: fprintf(ficresprobmorprev," p.%-d SE",j);
5929: for(i=1; i<=nlstate;i++)
5930: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5931: }
5932: fprintf(ficresprobmorprev,"\n");
5933:
5934: fprintf(ficgp,"\n# Routine varevsij");
5935: fprintf(ficgp,"\nunset title \n");
5936: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5937: 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");
5938: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5939:
1.218 brouard 5940: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5941: pstamp(ficresvij);
5942: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5943: if(popbased==1)
5944: 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);
5945: else
5946: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5947: fprintf(ficresvij,"# Age");
5948: for(i=1; i<=nlstate;i++)
5949: for(j=1; j<=nlstate;j++)
5950: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5951: fprintf(ficresvij,"\n");
5952:
5953: xp=vector(1,npar);
5954: dnewm=matrix(1,nlstate,1,npar);
5955: doldm=matrix(1,nlstate,1,nlstate);
5956: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5957: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5958:
5959: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5960: gpp=vector(nlstate+1,nlstate+ndeath);
5961: gmp=vector(nlstate+1,nlstate+ndeath);
5962: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5963:
1.218 brouard 5964: if(estepm < stepm){
5965: printf ("Problem %d lower than %d\n",estepm, stepm);
5966: }
5967: else hstepm=estepm;
5968: /* For example we decided to compute the life expectancy with the smallest unit */
5969: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5970: nhstepm is the number of hstepm from age to agelim
5971: nstepm is the number of stepm from age to agelim.
5972: Look at function hpijx to understand why because of memory size limitations,
5973: we decided (b) to get a life expectancy respecting the most precise curvature of the
5974: survival function given by stepm (the optimization length). Unfortunately it
5975: means that if the survival funtion is printed every two years of age and if
5976: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5977: results. So we changed our mind and took the option of the best precision.
5978: */
5979: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5980: agelim = AGESUP;
5981: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5982: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5983: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5984: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5985: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5986: gp=matrix(0,nhstepm,1,nlstate);
5987: gm=matrix(0,nhstepm,1,nlstate);
5988:
5989:
5990: for(theta=1; theta <=npar; theta++){
5991: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5992: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5993: }
1.279 brouard 5994: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
5995: * returns into prlim .
1.288 brouard 5996: */
1.242 brouard 5997: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 5998:
5999: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6000: if (popbased==1) {
6001: if(mobilav ==0){
6002: for(i=1; i<=nlstate;i++)
6003: prlim[i][i]=probs[(int)age][i][ij];
6004: }else{ /* mobilav */
6005: for(i=1; i<=nlstate;i++)
6006: prlim[i][i]=mobaverage[(int)age][i][ij];
6007: }
6008: }
1.279 brouard 6009: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}_x\f$ at horizon h.
6010: */
6011: 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 6012: /**< 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 6013: * at horizon h in state j including mortality.
6014: */
1.218 brouard 6015: for(j=1; j<= nlstate; j++){
6016: for(h=0; h<=nhstepm; h++){
6017: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6018: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6019: }
6020: }
1.279 brouard 6021: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6022: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6023: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6024: */
6025: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6026: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6027: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6028: }
6029:
6030: /* Again with minus shift */
1.218 brouard 6031:
6032: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6033: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6034:
1.242 brouard 6035: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6036:
6037: if (popbased==1) {
6038: if(mobilav ==0){
6039: for(i=1; i<=nlstate;i++)
6040: prlim[i][i]=probs[(int)age][i][ij];
6041: }else{ /* mobilav */
6042: for(i=1; i<=nlstate;i++)
6043: prlim[i][i]=mobaverage[(int)age][i][ij];
6044: }
6045: }
6046:
1.235 brouard 6047: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6048:
6049: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6050: for(h=0; h<=nhstepm; h++){
6051: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6052: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6053: }
6054: }
6055: /* This for computing probability of death (h=1 means
6056: computed over hstepm matrices product = hstepm*stepm months)
6057: as a weighted average of prlim.
6058: */
6059: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6060: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6061: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6062: }
1.279 brouard 6063: /* end shifting computations */
6064:
6065: /**< Computing gradient matrix at horizon h
6066: */
1.218 brouard 6067: for(j=1; j<= nlstate; j++) /* vareij */
6068: for(h=0; h<=nhstepm; h++){
6069: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6070: }
1.279 brouard 6071: /**< Gradient of overall mortality p.3 (or p.j)
6072: */
6073: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6074: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6075: }
6076:
6077: } /* End theta */
1.279 brouard 6078:
6079: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6080: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6081:
6082: for(h=0; h<=nhstepm; h++) /* veij */
6083: for(j=1; j<=nlstate;j++)
6084: for(theta=1; theta <=npar; theta++)
6085: trgradg[h][j][theta]=gradg[h][theta][j];
6086:
6087: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6088: for(theta=1; theta <=npar; theta++)
6089: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6090: /**< as well as its transposed matrix
6091: */
1.218 brouard 6092:
6093: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6094: for(i=1;i<=nlstate;i++)
6095: for(j=1;j<=nlstate;j++)
6096: vareij[i][j][(int)age] =0.;
1.279 brouard 6097:
6098: /* Computing trgradg by matcov by gradg at age and summing over h
6099: * and k (nhstepm) formula 15 of article
6100: * Lievre-Brouard-Heathcote
6101: */
6102:
1.218 brouard 6103: for(h=0;h<=nhstepm;h++){
6104: for(k=0;k<=nhstepm;k++){
6105: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6106: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6107: for(i=1;i<=nlstate;i++)
6108: for(j=1;j<=nlstate;j++)
6109: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6110: }
6111: }
6112:
1.279 brouard 6113: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6114: * p.j overall mortality formula 49 but computed directly because
6115: * we compute the grad (wix pijx) instead of grad (pijx),even if
6116: * wix is independent of theta.
6117: */
1.218 brouard 6118: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6119: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6120: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6121: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6122: varppt[j][i]=doldmp[j][i];
6123: /* end ppptj */
6124: /* x centered again */
6125:
1.242 brouard 6126: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6127:
6128: if (popbased==1) {
6129: if(mobilav ==0){
6130: for(i=1; i<=nlstate;i++)
6131: prlim[i][i]=probs[(int)age][i][ij];
6132: }else{ /* mobilav */
6133: for(i=1; i<=nlstate;i++)
6134: prlim[i][i]=mobaverage[(int)age][i][ij];
6135: }
6136: }
6137:
6138: /* This for computing probability of death (h=1 means
6139: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6140: as a weighted average of prlim.
6141: */
1.235 brouard 6142: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6143: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6144: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6145: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6146: }
6147: /* end probability of death */
6148:
6149: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6150: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6151: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6152: for(i=1; i<=nlstate;i++){
6153: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6154: }
6155: }
6156: fprintf(ficresprobmorprev,"\n");
6157:
6158: fprintf(ficresvij,"%.0f ",age );
6159: for(i=1; i<=nlstate;i++)
6160: for(j=1; j<=nlstate;j++){
6161: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6162: }
6163: fprintf(ficresvij,"\n");
6164: free_matrix(gp,0,nhstepm,1,nlstate);
6165: free_matrix(gm,0,nhstepm,1,nlstate);
6166: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6167: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6168: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6169: } /* End age */
6170: free_vector(gpp,nlstate+1,nlstate+ndeath);
6171: free_vector(gmp,nlstate+1,nlstate+ndeath);
6172: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6173: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6174: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6175: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6176: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6177: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6178: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6179: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6180: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6181: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6182: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6183: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6184: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6185: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6186: 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);
6187: /* 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 6188: */
1.218 brouard 6189: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6190: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6191:
1.218 brouard 6192: free_vector(xp,1,npar);
6193: free_matrix(doldm,1,nlstate,1,nlstate);
6194: free_matrix(dnewm,1,nlstate,1,npar);
6195: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6196: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6197: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6198: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6199: fclose(ficresprobmorprev);
6200: fflush(ficgp);
6201: fflush(fichtm);
6202: } /* end varevsij */
1.126 brouard 6203:
6204: /************ Variance of prevlim ******************/
1.269 brouard 6205: 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 6206: {
1.205 brouard 6207: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6208: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6209:
1.268 brouard 6210: double **dnewmpar,**doldm;
1.126 brouard 6211: int i, j, nhstepm, hstepm;
6212: double *xp;
6213: double *gp, *gm;
6214: double **gradg, **trgradg;
1.208 brouard 6215: double **mgm, **mgp;
1.126 brouard 6216: double age,agelim;
6217: int theta;
6218:
6219: pstamp(ficresvpl);
1.288 brouard 6220: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6221: fprintf(ficresvpl,"# Age ");
6222: if(nresult >=1)
6223: fprintf(ficresvpl," Result# ");
1.126 brouard 6224: for(i=1; i<=nlstate;i++)
6225: fprintf(ficresvpl," %1d-%1d",i,i);
6226: fprintf(ficresvpl,"\n");
6227:
6228: xp=vector(1,npar);
1.268 brouard 6229: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6230: doldm=matrix(1,nlstate,1,nlstate);
6231:
6232: hstepm=1*YEARM; /* Every year of age */
6233: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6234: agelim = AGESUP;
6235: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6236: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6237: if (stepm >= YEARM) hstepm=1;
6238: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6239: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6240: mgp=matrix(1,npar,1,nlstate);
6241: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6242: gp=vector(1,nlstate);
6243: gm=vector(1,nlstate);
6244:
6245: for(theta=1; theta <=npar; theta++){
6246: for(i=1; i<=npar; i++){ /* Computes gradient */
6247: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6248: }
1.288 brouard 6249: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6250: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6251: /* else */
6252: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6253: for(i=1;i<=nlstate;i++){
1.126 brouard 6254: gp[i] = prlim[i][i];
1.208 brouard 6255: mgp[theta][i] = prlim[i][i];
6256: }
1.126 brouard 6257: for(i=1; i<=npar; i++) /* Computes gradient */
6258: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6259: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6260: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6261: /* else */
6262: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6263: for(i=1;i<=nlstate;i++){
1.126 brouard 6264: gm[i] = prlim[i][i];
1.208 brouard 6265: mgm[theta][i] = prlim[i][i];
6266: }
1.126 brouard 6267: for(i=1;i<=nlstate;i++)
6268: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6269: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6270: } /* End theta */
6271:
6272: trgradg =matrix(1,nlstate,1,npar);
6273:
6274: for(j=1; j<=nlstate;j++)
6275: for(theta=1; theta <=npar; theta++)
6276: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6277: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6278: /* printf("\nmgm mgp %d ",(int)age); */
6279: /* for(j=1; j<=nlstate;j++){ */
6280: /* printf(" %d ",j); */
6281: /* for(theta=1; theta <=npar; theta++) */
6282: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6283: /* printf("\n "); */
6284: /* } */
6285: /* } */
6286: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6287: /* printf("\n gradg %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 ",theta,gradg[theta][j]); */
6292: /* printf("\n "); */
6293: /* } */
6294: /* } */
1.126 brouard 6295:
6296: for(i=1;i<=nlstate;i++)
6297: varpl[i][(int)age] =0.;
1.209 brouard 6298: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6299: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6300: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6301: }else{
1.268 brouard 6302: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6303: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6304: }
1.126 brouard 6305: for(i=1;i<=nlstate;i++)
6306: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6307:
6308: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6309: if(nresult >=1)
6310: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6311: for(i=1; i<=nlstate;i++){
1.126 brouard 6312: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6313: /* for(j=1;j<=nlstate;j++) */
6314: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6315: }
1.126 brouard 6316: fprintf(ficresvpl,"\n");
6317: free_vector(gp,1,nlstate);
6318: free_vector(gm,1,nlstate);
1.208 brouard 6319: free_matrix(mgm,1,npar,1,nlstate);
6320: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6321: free_matrix(gradg,1,npar,1,nlstate);
6322: free_matrix(trgradg,1,nlstate,1,npar);
6323: } /* End age */
6324:
6325: free_vector(xp,1,npar);
6326: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6327: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6328:
6329: }
6330:
6331:
6332: /************ Variance of backprevalence limit ******************/
1.269 brouard 6333: 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 6334: {
6335: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6336: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6337:
6338: double **dnewmpar,**doldm;
6339: int i, j, nhstepm, hstepm;
6340: double *xp;
6341: double *gp, *gm;
6342: double **gradg, **trgradg;
6343: double **mgm, **mgp;
6344: double age,agelim;
6345: int theta;
6346:
6347: pstamp(ficresvbl);
6348: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6349: fprintf(ficresvbl,"# Age ");
6350: if(nresult >=1)
6351: fprintf(ficresvbl," Result# ");
6352: for(i=1; i<=nlstate;i++)
6353: fprintf(ficresvbl," %1d-%1d",i,i);
6354: fprintf(ficresvbl,"\n");
6355:
6356: xp=vector(1,npar);
6357: dnewmpar=matrix(1,nlstate,1,npar);
6358: doldm=matrix(1,nlstate,1,nlstate);
6359:
6360: hstepm=1*YEARM; /* Every year of age */
6361: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6362: agelim = AGEINF;
6363: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6364: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6365: if (stepm >= YEARM) hstepm=1;
6366: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6367: gradg=matrix(1,npar,1,nlstate);
6368: mgp=matrix(1,npar,1,nlstate);
6369: mgm=matrix(1,npar,1,nlstate);
6370: gp=vector(1,nlstate);
6371: gm=vector(1,nlstate);
6372:
6373: for(theta=1; theta <=npar; theta++){
6374: for(i=1; i<=npar; i++){ /* Computes gradient */
6375: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6376: }
6377: if(mobilavproj > 0 )
6378: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6379: else
6380: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6381: for(i=1;i<=nlstate;i++){
6382: gp[i] = bprlim[i][i];
6383: mgp[theta][i] = bprlim[i][i];
6384: }
6385: for(i=1; i<=npar; i++) /* Computes gradient */
6386: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6387: if(mobilavproj > 0 )
6388: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6389: else
6390: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6391: for(i=1;i<=nlstate;i++){
6392: gm[i] = bprlim[i][i];
6393: mgm[theta][i] = bprlim[i][i];
6394: }
6395: for(i=1;i<=nlstate;i++)
6396: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6397: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6398: } /* End theta */
6399:
6400: trgradg =matrix(1,nlstate,1,npar);
6401:
6402: for(j=1; j<=nlstate;j++)
6403: for(theta=1; theta <=npar; theta++)
6404: trgradg[j][theta]=gradg[theta][j];
6405: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6406: /* printf("\nmgm mgp %d ",(int)age); */
6407: /* for(j=1; j<=nlstate;j++){ */
6408: /* printf(" %d ",j); */
6409: /* for(theta=1; theta <=npar; theta++) */
6410: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6411: /* printf("\n "); */
6412: /* } */
6413: /* } */
6414: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6415: /* printf("\n gradg %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 ",theta,gradg[theta][j]); */
6420: /* printf("\n "); */
6421: /* } */
6422: /* } */
6423:
6424: for(i=1;i<=nlstate;i++)
6425: varbpl[i][(int)age] =0.;
6426: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6427: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6428: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6429: }else{
6430: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6431: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6432: }
6433: for(i=1;i<=nlstate;i++)
6434: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6435:
6436: fprintf(ficresvbl,"%.0f ",age );
6437: if(nresult >=1)
6438: fprintf(ficresvbl,"%d ",nres );
6439: for(i=1; i<=nlstate;i++)
6440: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6441: fprintf(ficresvbl,"\n");
6442: free_vector(gp,1,nlstate);
6443: free_vector(gm,1,nlstate);
6444: free_matrix(mgm,1,npar,1,nlstate);
6445: free_matrix(mgp,1,npar,1,nlstate);
6446: free_matrix(gradg,1,npar,1,nlstate);
6447: free_matrix(trgradg,1,nlstate,1,npar);
6448: } /* End age */
6449:
6450: free_vector(xp,1,npar);
6451: free_matrix(doldm,1,nlstate,1,npar);
6452: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6453:
6454: }
6455:
6456: /************ Variance of one-step probabilities ******************/
6457: 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 6458: {
6459: int i, j=0, k1, l1, tj;
6460: int k2, l2, j1, z1;
6461: int k=0, l;
6462: int first=1, first1, first2;
6463: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6464: double **dnewm,**doldm;
6465: double *xp;
6466: double *gp, *gm;
6467: double **gradg, **trgradg;
6468: double **mu;
6469: double age, cov[NCOVMAX+1];
6470: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6471: int theta;
6472: char fileresprob[FILENAMELENGTH];
6473: char fileresprobcov[FILENAMELENGTH];
6474: char fileresprobcor[FILENAMELENGTH];
6475: double ***varpij;
6476:
6477: strcpy(fileresprob,"PROB_");
6478: strcat(fileresprob,fileres);
6479: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6480: printf("Problem with resultfile: %s\n", fileresprob);
6481: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6482: }
6483: strcpy(fileresprobcov,"PROBCOV_");
6484: strcat(fileresprobcov,fileresu);
6485: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6486: printf("Problem with resultfile: %s\n", fileresprobcov);
6487: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6488: }
6489: strcpy(fileresprobcor,"PROBCOR_");
6490: strcat(fileresprobcor,fileresu);
6491: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6492: printf("Problem with resultfile: %s\n", fileresprobcor);
6493: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6494: }
6495: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6496: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6497: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6498: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6499: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6500: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6501: pstamp(ficresprob);
6502: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6503: fprintf(ficresprob,"# Age");
6504: pstamp(ficresprobcov);
6505: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6506: fprintf(ficresprobcov,"# Age");
6507: pstamp(ficresprobcor);
6508: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6509: fprintf(ficresprobcor,"# Age");
1.126 brouard 6510:
6511:
1.222 brouard 6512: for(i=1; i<=nlstate;i++)
6513: for(j=1; j<=(nlstate+ndeath);j++){
6514: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6515: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6516: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6517: }
6518: /* fprintf(ficresprob,"\n");
6519: fprintf(ficresprobcov,"\n");
6520: fprintf(ficresprobcor,"\n");
6521: */
6522: xp=vector(1,npar);
6523: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6524: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6525: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6526: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6527: first=1;
6528: fprintf(ficgp,"\n# Routine varprob");
6529: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6530: fprintf(fichtm,"\n");
6531:
1.288 brouard 6532: 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 6533: 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);
6534: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6535: and drawn. It helps understanding how is the covariance between two incidences.\
6536: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6537: 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 6538: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6539: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6540: standard deviations wide on each axis. <br>\
6541: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6542: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6543: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6544:
1.222 brouard 6545: cov[1]=1;
6546: /* tj=cptcoveff; */
1.225 brouard 6547: tj = (int) pow(2,cptcoveff);
1.222 brouard 6548: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6549: j1=0;
1.224 brouard 6550: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6551: if (cptcovn>0) {
6552: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6553: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6554: fprintf(ficresprob, "**********\n#\n");
6555: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6556: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6557: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6558:
1.222 brouard 6559: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6560: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6561: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6562:
6563:
1.222 brouard 6564: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6565: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6566: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6567:
1.222 brouard 6568: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6569: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6570: fprintf(ficresprobcor, "**********\n#");
6571: if(invalidvarcomb[j1]){
6572: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6573: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6574: continue;
6575: }
6576: }
6577: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6578: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6579: gp=vector(1,(nlstate)*(nlstate+ndeath));
6580: gm=vector(1,(nlstate)*(nlstate+ndeath));
6581: for (age=bage; age<=fage; age ++){
6582: cov[2]=age;
6583: if(nagesqr==1)
6584: cov[3]= age*age;
6585: for (k=1; k<=cptcovn;k++) {
6586: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6587: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6588: * 1 1 1 1 1
6589: * 2 2 1 1 1
6590: * 3 1 2 1 1
6591: */
6592: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6593: }
6594: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6595: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6596: for (k=1; k<=cptcovprod;k++)
6597: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6598:
6599:
1.222 brouard 6600: for(theta=1; theta <=npar; theta++){
6601: for(i=1; i<=npar; i++)
6602: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6603:
1.222 brouard 6604: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6605:
1.222 brouard 6606: k=0;
6607: for(i=1; i<= (nlstate); i++){
6608: for(j=1; j<=(nlstate+ndeath);j++){
6609: k=k+1;
6610: gp[k]=pmmij[i][j];
6611: }
6612: }
1.220 brouard 6613:
1.222 brouard 6614: for(i=1; i<=npar; i++)
6615: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6616:
1.222 brouard 6617: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6618: k=0;
6619: for(i=1; i<=(nlstate); i++){
6620: for(j=1; j<=(nlstate+ndeath);j++){
6621: k=k+1;
6622: gm[k]=pmmij[i][j];
6623: }
6624: }
1.220 brouard 6625:
1.222 brouard 6626: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6627: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6628: }
1.126 brouard 6629:
1.222 brouard 6630: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6631: for(theta=1; theta <=npar; theta++)
6632: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6633:
1.222 brouard 6634: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6635: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6636:
1.222 brouard 6637: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6638:
1.222 brouard 6639: k=0;
6640: for(i=1; i<=(nlstate); i++){
6641: for(j=1; j<=(nlstate+ndeath);j++){
6642: k=k+1;
6643: mu[k][(int) age]=pmmij[i][j];
6644: }
6645: }
6646: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6647: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6648: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6649:
1.222 brouard 6650: /*printf("\n%d ",(int)age);
6651: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6652: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6653: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6654: }*/
1.220 brouard 6655:
1.222 brouard 6656: fprintf(ficresprob,"\n%d ",(int)age);
6657: fprintf(ficresprobcov,"\n%d ",(int)age);
6658: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6659:
1.222 brouard 6660: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6661: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6662: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6663: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6664: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6665: }
6666: i=0;
6667: for (k=1; k<=(nlstate);k++){
6668: for (l=1; l<=(nlstate+ndeath);l++){
6669: i++;
6670: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6671: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6672: for (j=1; j<=i;j++){
6673: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6674: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6675: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6676: }
6677: }
6678: }/* end of loop for state */
6679: } /* end of loop for age */
6680: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6681: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6682: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6683: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6684:
6685: /* Confidence intervalle of pij */
6686: /*
6687: fprintf(ficgp,"\nunset parametric;unset label");
6688: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6689: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6690: 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);
6691: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6692: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6693: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6694: */
6695:
6696: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6697: first1=1;first2=2;
6698: for (k2=1; k2<=(nlstate);k2++){
6699: for (l2=1; l2<=(nlstate+ndeath);l2++){
6700: if(l2==k2) continue;
6701: j=(k2-1)*(nlstate+ndeath)+l2;
6702: for (k1=1; k1<=(nlstate);k1++){
6703: for (l1=1; l1<=(nlstate+ndeath);l1++){
6704: if(l1==k1) continue;
6705: i=(k1-1)*(nlstate+ndeath)+l1;
6706: if(i<=j) continue;
6707: for (age=bage; age<=fage; age ++){
6708: if ((int)age %5==0){
6709: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6710: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6711: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6712: mu1=mu[i][(int) age]/stepm*YEARM ;
6713: mu2=mu[j][(int) age]/stepm*YEARM;
6714: c12=cv12/sqrt(v1*v2);
6715: /* Computing eigen value of matrix of covariance */
6716: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6717: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6718: if ((lc2 <0) || (lc1 <0) ){
6719: if(first2==1){
6720: first1=0;
6721: 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);
6722: }
6723: 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);
6724: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6725: /* lc2=fabs(lc2); */
6726: }
1.220 brouard 6727:
1.222 brouard 6728: /* Eigen vectors */
1.280 brouard 6729: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6730: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6731: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6732: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6733: }else
6734: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6735: /*v21=sqrt(1.-v11*v11); *//* error */
6736: v21=(lc1-v1)/cv12*v11;
6737: v12=-v21;
6738: v22=v11;
6739: tnalp=v21/v11;
6740: if(first1==1){
6741: first1=0;
6742: 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);
6743: }
6744: 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);
6745: /*printf(fignu*/
6746: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6747: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6748: if(first==1){
6749: first=0;
6750: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6751: fprintf(ficgp,"\nset parametric;unset label");
6752: 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);
6753: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6754: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6755: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6756: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6757: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6758: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6759: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6760: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6761: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6762: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6763: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6764: 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 6765: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6766: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6767: }else{
6768: first=0;
6769: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6770: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6771: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6772: 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 6773: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6774: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6775: }/* if first */
6776: } /* age mod 5 */
6777: } /* end loop age */
6778: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6779: first=1;
6780: } /*l12 */
6781: } /* k12 */
6782: } /*l1 */
6783: }/* k1 */
6784: } /* loop on combination of covariates j1 */
6785: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6786: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6787: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6788: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6789: free_vector(xp,1,npar);
6790: fclose(ficresprob);
6791: fclose(ficresprobcov);
6792: fclose(ficresprobcor);
6793: fflush(ficgp);
6794: fflush(fichtmcov);
6795: }
1.126 brouard 6796:
6797:
6798: /******************* Printing html file ***********/
1.201 brouard 6799: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6800: int lastpass, int stepm, int weightopt, char model[],\
6801: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6802: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.273 brouard 6803: double jprev1, double mprev1,double anprev1, double dateprev1, double dateproj1, double dateback1, \
6804: double jprev2, double mprev2,double anprev2, double dateprev2, double dateproj2, double dateback2){
1.237 brouard 6805: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6806:
6807: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6808: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6809: </ul>");
1.237 brouard 6810: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6811: </ul>", model);
1.214 brouard 6812: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6813: 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",
6814: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6815: 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 6816: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6817: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6818: fprintf(fichtm,"\
6819: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6820: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6821: fprintf(fichtm,"\
1.217 brouard 6822: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6823: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6824: fprintf(fichtm,"\
1.288 brouard 6825: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6826: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6827: fprintf(fichtm,"\
1.288 brouard 6828: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6829: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6830: fprintf(fichtm,"\
1.211 brouard 6831: - (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 6832: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6833: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6834: if(prevfcast==1){
6835: fprintf(fichtm,"\
6836: - Prevalence projections by age and states: \
1.201 brouard 6837: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6838: }
1.126 brouard 6839:
6840:
1.225 brouard 6841: m=pow(2,cptcoveff);
1.222 brouard 6842: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6843:
1.264 brouard 6844: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6845:
6846: jj1=0;
6847:
6848: fprintf(fichtm," \n<ul>");
6849: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6850: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6851: if(m != 1 && TKresult[nres]!= k1)
6852: continue;
6853: jj1++;
6854: if (cptcovn > 0) {
6855: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6856: for (cpt=1; cpt<=cptcoveff;cpt++){
6857: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6858: }
6859: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6860: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6861: }
6862: fprintf(fichtm,"\">");
6863:
6864: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6865: fprintf(fichtm,"************ Results for covariates");
6866: for (cpt=1; cpt<=cptcoveff;cpt++){
6867: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6868: }
6869: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6870: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6871: }
6872: if(invalidvarcomb[k1]){
6873: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6874: continue;
6875: }
6876: fprintf(fichtm,"</a></li>");
6877: } /* cptcovn >0 */
6878: }
6879: fprintf(fichtm," \n</ul>");
6880:
1.222 brouard 6881: jj1=0;
1.237 brouard 6882:
6883: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6884: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6885: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6886: continue;
1.220 brouard 6887:
1.222 brouard 6888: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6889: jj1++;
6890: if (cptcovn > 0) {
1.264 brouard 6891: fprintf(fichtm,"\n<p><a name=\"rescov");
6892: for (cpt=1; cpt<=cptcoveff;cpt++){
6893: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6894: }
6895: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6896: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6897: }
6898: fprintf(fichtm,"\"</a>");
6899:
1.222 brouard 6900: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6901: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6902: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6903: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6904: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6905: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6906: }
1.237 brouard 6907: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6908: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6909: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6910: }
6911:
1.230 brouard 6912: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6913: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6914: if(invalidvarcomb[k1]){
6915: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6916: printf("\nCombination (%d) ignored because no cases \n",k1);
6917: continue;
6918: }
6919: }
6920: /* aij, bij */
1.259 brouard 6921: 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 6922: <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 6923: /* Pij */
1.241 brouard 6924: 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> \
6925: <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 6926: /* Quasi-incidences */
6927: 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 6928: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6929: 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 6930: 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> \
6931: <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 6932: /* Survival functions (period) in state j */
6933: for(cpt=1; cpt<=nlstate;cpt++){
1.292 ! brouard 6934: 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 6935: <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 6936: }
6937: /* State specific survival functions (period) */
6938: for(cpt=1; cpt<=nlstate;cpt++){
1.292 ! brouard 6939: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
! 6940: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 6941: <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 6942: }
1.288 brouard 6943: /* Period (forward stable) prevalence in each health state */
1.222 brouard 6944: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6945: 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> \
6946: <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 6947: }
6948: if(backcast==1){
1.288 brouard 6949: /* Backward prevalence in each health state */
1.222 brouard 6950: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6951: 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 6952: <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 6953: }
1.217 brouard 6954: }
1.222 brouard 6955: if(prevfcast==1){
1.288 brouard 6956: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 6957: for(cpt=1; cpt<=nlstate;cpt++){
1.288 brouard 6958: 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 6959: <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 6960: }
6961: }
1.268 brouard 6962: if(backcast==1){
6963: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6964: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6965: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6966: 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 \
6967: 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) \
6968: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6969: <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 6970: }
6971: }
1.220 brouard 6972:
1.222 brouard 6973: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6974: 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> \
6975: <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 6976: }
6977: /* } /\* end i1 *\/ */
6978: }/* End k1 */
6979: fprintf(fichtm,"</ul>");
1.126 brouard 6980:
1.222 brouard 6981: fprintf(fichtm,"\
1.126 brouard 6982: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6983: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6984: - 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 6985: But because parameters are usually highly correlated (a higher incidence of disability \
6986: and a higher incidence of recovery can give very close observed transition) it might \
6987: be very useful to look not only at linear confidence intervals estimated from the \
6988: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6989: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6990: covariance matrix of the one-step probabilities. \
6991: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6992:
1.222 brouard 6993: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6994: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6995: fprintf(fichtm,"\
1.126 brouard 6996: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6997: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6998:
1.222 brouard 6999: fprintf(fichtm,"\
1.126 brouard 7000: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7001: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7002: fprintf(fichtm,"\
1.126 brouard 7003: - 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): \
7004: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7005: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7006: fprintf(fichtm,"\
1.126 brouard 7007: - (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): \
7008: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7009: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7010: fprintf(fichtm,"\
1.288 brouard 7011: - 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 7012: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7013: fprintf(fichtm,"\
1.128 brouard 7014: - 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 7015: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7016: fprintf(fichtm,"\
1.288 brouard 7017: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7018: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7019:
7020: /* if(popforecast==1) fprintf(fichtm,"\n */
7021: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7022: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7023: /* <br>",fileres,fileres,fileres,fileres); */
7024: /* else */
7025: /* 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 7026: fflush(fichtm);
7027: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7028:
1.225 brouard 7029: m=pow(2,cptcoveff);
1.222 brouard 7030: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7031:
1.222 brouard 7032: jj1=0;
1.237 brouard 7033:
1.241 brouard 7034: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7035: for(k1=1; k1<=m;k1++){
1.253 brouard 7036: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7037: continue;
1.222 brouard 7038: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7039: jj1++;
1.126 brouard 7040: if (cptcovn > 0) {
7041: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7042: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7043: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7044: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7045: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7046: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7047: }
7048:
1.126 brouard 7049: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7050:
1.222 brouard 7051: if(invalidvarcomb[k1]){
7052: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7053: continue;
7054: }
1.126 brouard 7055: }
7056: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7057: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7058: 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 7059: <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 7060: }
7061: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7062: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7063: true period expectancies (those weighted with period prevalences are also\
7064: drawn in addition to the population based expectancies computed using\
1.241 brouard 7065: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7066: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7067: /* } /\* end i1 *\/ */
7068: }/* End k1 */
1.241 brouard 7069: }/* End nres */
1.222 brouard 7070: fprintf(fichtm,"</ul>");
7071: fflush(fichtm);
1.126 brouard 7072: }
7073:
7074: /******************* Gnuplot file **************/
1.270 brouard 7075: 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 7076:
7077: char dirfileres[132],optfileres[132];
1.264 brouard 7078: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7079: 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 7080: int lv=0, vlv=0, kl=0;
1.130 brouard 7081: int ng=0;
1.201 brouard 7082: int vpopbased;
1.223 brouard 7083: int ioffset; /* variable offset for columns */
1.270 brouard 7084: int iyearc=1; /* variable column for year of projection */
7085: int iagec=1; /* variable column for age of projection */
1.235 brouard 7086: int nres=0; /* Index of resultline */
1.266 brouard 7087: int istart=1; /* For starting graphs in projections */
1.219 brouard 7088:
1.126 brouard 7089: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7090: /* printf("Problem with file %s",optionfilegnuplot); */
7091: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7092: /* } */
7093:
7094: /*#ifdef windows */
7095: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7096: /*#endif */
1.225 brouard 7097: m=pow(2,cptcoveff);
1.126 brouard 7098:
1.274 brouard 7099: /* diagram of the model */
7100: fprintf(ficgp,"\n#Diagram of the model \n");
7101: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7102: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7103: 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);
7104:
7105: 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);
7106: fprintf(ficgp,"\n#show arrow\nunset label\n");
7107: 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);
7108: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7109: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7110: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7111: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7112:
1.202 brouard 7113: /* Contribution to likelihood */
7114: /* Plot the probability implied in the likelihood */
1.223 brouard 7115: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7116: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7117: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7118: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7119: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7120: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7121: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7122: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7123: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7124: 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));
7125: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7126: 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));
7127: for (i=1; i<= nlstate ; i ++) {
7128: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7129: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7130: 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);
7131: for (j=2; j<= nlstate+ndeath ; j ++) {
7132: 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);
7133: }
7134: fprintf(ficgp,";\nset out; unset ylabel;\n");
7135: }
7136: /* 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 */
7137: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7138: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7139: fprintf(ficgp,"\nset out;unset log\n");
7140: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7141:
1.126 brouard 7142: strcpy(dirfileres,optionfilefiname);
7143: strcpy(optfileres,"vpl");
1.223 brouard 7144: /* 1eme*/
1.238 brouard 7145: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7146: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7147: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7148: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7149: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7150: continue;
7151: /* We are interested in selected combination by the resultline */
1.246 brouard 7152: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7153: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7154: strcpy(gplotlabel,"(");
1.238 brouard 7155: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7156: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7157: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7158: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7159: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7160: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7161: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7162: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7163: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7164: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7165: }
7166: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7167: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7168: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7169: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7170: }
7171: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7172: /* printf("\n#\n"); */
1.238 brouard 7173: fprintf(ficgp,"\n#\n");
7174: if(invalidvarcomb[k1]){
1.260 brouard 7175: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7176: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7177: continue;
7178: }
1.235 brouard 7179:
1.241 brouard 7180: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7181: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7182: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7183: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7184: 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);
7185: /* 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); */
7186: /* k1-1 error should be nres-1*/
1.238 brouard 7187: for (i=1; i<= nlstate ; i ++) {
7188: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7189: else fprintf(ficgp," %%*lf (%%*lf)");
7190: }
1.288 brouard 7191: 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 7192: for (i=1; i<= nlstate ; i ++) {
7193: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7194: else fprintf(ficgp," %%*lf (%%*lf)");
7195: }
1.260 brouard 7196: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7197: for (i=1; i<= nlstate ; i ++) {
7198: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7199: else fprintf(ficgp," %%*lf (%%*lf)");
7200: }
1.265 brouard 7201: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7202:
7203: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7204: if(cptcoveff ==0){
1.271 brouard 7205: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7206: }else{
7207: kl=0;
7208: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7209: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7210: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7211: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7212: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7213: vlv= nbcode[Tvaraff[k]][lv];
7214: kl++;
7215: /* 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 *\/ */
7216: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7217: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7218: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7219: if(k==cptcoveff){
7220: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7221: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7222: }else{
7223: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7224: kl++;
7225: }
7226: } /* end covariate */
7227: } /* end if no covariate */
7228:
1.238 brouard 7229: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7230: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7231: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7232: if(cptcoveff ==0){
1.245 brouard 7233: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7234: }else{
7235: kl=0;
7236: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7237: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7238: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7239: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7240: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7241: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7242: kl++;
1.238 brouard 7243: /* 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 *\/ */
7244: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7245: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7246: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7247: if(k==cptcoveff){
1.245 brouard 7248: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7249: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7250: }else{
7251: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7252: kl++;
7253: }
7254: } /* end covariate */
7255: } /* end if no covariate */
1.268 brouard 7256: if(backcast == 1){
7257: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7258: /* k1-1 error should be nres-1*/
7259: for (i=1; i<= nlstate ; i ++) {
7260: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7261: else fprintf(ficgp," %%*lf (%%*lf)");
7262: }
1.271 brouard 7263: 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 7264: for (i=1; i<= nlstate ; i ++) {
7265: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7266: else fprintf(ficgp," %%*lf (%%*lf)");
7267: }
1.276 brouard 7268: 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 7269: for (i=1; i<= nlstate ; i ++) {
7270: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7271: else fprintf(ficgp," %%*lf (%%*lf)");
7272: }
1.274 brouard 7273: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7274: } /* end if backprojcast */
1.238 brouard 7275: } /* end if backcast */
1.276 brouard 7276: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7277: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7278: } /* nres */
1.201 brouard 7279: } /* k1 */
7280: } /* cpt */
1.235 brouard 7281:
7282:
1.126 brouard 7283: /*2 eme*/
1.238 brouard 7284: for (k1=1; k1<= m ; k1 ++){
7285: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7286: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7287: continue;
7288: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7289: strcpy(gplotlabel,"(");
1.238 brouard 7290: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7291: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7292: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7293: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7294: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7295: vlv= nbcode[Tvaraff[k]][lv];
7296: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7297: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7298: }
1.237 brouard 7299: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7300: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7301: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7302: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7303: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7304: }
1.264 brouard 7305: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7306: fprintf(ficgp,"\n#\n");
1.223 brouard 7307: if(invalidvarcomb[k1]){
7308: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7309: continue;
7310: }
1.219 brouard 7311:
1.241 brouard 7312: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7313: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7314: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7315: if(vpopbased==0){
1.238 brouard 7316: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7317: }else
1.238 brouard 7318: fprintf(ficgp,"\nreplot ");
7319: for (i=1; i<= nlstate+1 ; i ++) {
7320: k=2*i;
1.261 brouard 7321: 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 7322: for (j=1; j<= nlstate+1 ; j ++) {
7323: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7324: else fprintf(ficgp," %%*lf (%%*lf)");
7325: }
7326: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7327: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7328: 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 7329: for (j=1; j<= nlstate+1 ; j ++) {
7330: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7331: else fprintf(ficgp," %%*lf (%%*lf)");
7332: }
7333: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7334: 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 7335: for (j=1; j<= nlstate+1 ; j ++) {
7336: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7337: else fprintf(ficgp," %%*lf (%%*lf)");
7338: }
7339: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7340: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7341: } /* state */
7342: } /* vpopbased */
1.264 brouard 7343: 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 7344: } /* end nres */
7345: } /* k1 end 2 eme*/
7346:
7347:
7348: /*3eme*/
7349: for (k1=1; k1<= m ; k1 ++){
7350: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7351: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7352: continue;
7353:
7354: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7355: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7356: strcpy(gplotlabel,"(");
1.238 brouard 7357: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7358: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7359: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7360: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7361: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7362: vlv= nbcode[Tvaraff[k]][lv];
7363: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7364: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7365: }
7366: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7367: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7368: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7369: }
1.264 brouard 7370: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7371: fprintf(ficgp,"\n#\n");
7372: if(invalidvarcomb[k1]){
7373: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7374: continue;
7375: }
7376:
7377: /* k=2+nlstate*(2*cpt-2); */
7378: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7379: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7380: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7381: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7382: 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 7383: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7384: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7385: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7386: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7387: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7388: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7389:
1.238 brouard 7390: */
7391: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7392: 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 7393: /* 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 7394:
1.238 brouard 7395: }
1.261 brouard 7396: 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 7397: }
1.264 brouard 7398: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7399: } /* end nres */
7400: } /* end kl 3eme */
1.126 brouard 7401:
1.223 brouard 7402: /* 4eme */
1.201 brouard 7403: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7404: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7405: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7406: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7407: continue;
1.238 brouard 7408: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7409: strcpy(gplotlabel,"(");
1.238 brouard 7410: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7411: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7412: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7413: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7414: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7415: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7416: vlv= nbcode[Tvaraff[k]][lv];
7417: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7418: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7419: }
7420: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7421: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7422: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7423: }
1.264 brouard 7424: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7425: fprintf(ficgp,"\n#\n");
7426: if(invalidvarcomb[k1]){
7427: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7428: continue;
1.223 brouard 7429: }
1.238 brouard 7430:
1.241 brouard 7431: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7432: 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 7433: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7434: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7435: k=3;
7436: for (i=1; i<= nlstate ; i ++){
7437: if(i==1){
7438: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7439: }else{
7440: fprintf(ficgp,", '' ");
7441: }
7442: l=(nlstate+ndeath)*(i-1)+1;
7443: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7444: for (j=2; j<= nlstate+ndeath ; j ++)
7445: fprintf(ficgp,"+$%d",k+l+j-1);
7446: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7447: } /* nlstate */
1.264 brouard 7448: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7449: } /* end cpt state*/
7450: } /* end nres */
7451: } /* end covariate k1 */
7452:
1.220 brouard 7453: /* 5eme */
1.201 brouard 7454: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7455: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7456: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7457: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7458: continue;
1.238 brouard 7459: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7460: strcpy(gplotlabel,"(");
1.238 brouard 7461: 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);
7462: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7463: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7464: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7465: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7466: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7467: vlv= nbcode[Tvaraff[k]][lv];
7468: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7469: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7470: }
7471: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7472: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7473: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7474: }
1.264 brouard 7475: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7476: fprintf(ficgp,"\n#\n");
7477: if(invalidvarcomb[k1]){
7478: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7479: continue;
7480: }
1.227 brouard 7481:
1.241 brouard 7482: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7483: 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 7484: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7485: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7486: k=3;
7487: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7488: if(j==1)
7489: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7490: else
7491: fprintf(ficgp,", '' ");
7492: l=(nlstate+ndeath)*(cpt-1) +j;
7493: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7494: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7495: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7496: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7497: } /* nlstate */
7498: fprintf(ficgp,", '' ");
7499: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7500: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7501: l=(nlstate+ndeath)*(cpt-1) +j;
7502: if(j < nlstate)
7503: fprintf(ficgp,"$%d +",k+l);
7504: else
7505: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7506: }
1.264 brouard 7507: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7508: } /* end cpt state*/
7509: } /* end covariate */
7510: } /* end nres */
1.227 brouard 7511:
1.220 brouard 7512: /* 6eme */
1.202 brouard 7513: /* CV preval stable (period) for each covariate */
1.237 brouard 7514: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7515: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7516: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7517: continue;
1.255 brouard 7518: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7519: strcpy(gplotlabel,"(");
1.288 brouard 7520: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7521: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7522: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7523: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7524: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7525: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7526: vlv= nbcode[Tvaraff[k]][lv];
7527: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7528: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7529: }
1.237 brouard 7530: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7531: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7532: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7533: }
1.264 brouard 7534: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7535: fprintf(ficgp,"\n#\n");
1.223 brouard 7536: if(invalidvarcomb[k1]){
1.227 brouard 7537: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7538: continue;
1.223 brouard 7539: }
1.227 brouard 7540:
1.241 brouard 7541: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7542: 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 7543: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7544: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7545: k=3; /* Offset */
1.255 brouard 7546: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7547: if(i==1)
7548: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7549: else
7550: fprintf(ficgp,", '' ");
1.255 brouard 7551: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7552: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7553: for (j=2; j<= nlstate ; j ++)
7554: fprintf(ficgp,"+$%d",k+l+j-1);
7555: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7556: } /* nlstate */
1.264 brouard 7557: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7558: } /* end cpt state*/
7559: } /* end covariate */
1.227 brouard 7560:
7561:
1.220 brouard 7562: /* 7eme */
1.218 brouard 7563: if(backcast == 1){
1.288 brouard 7564: /* CV backward prevalence for each covariate */
1.237 brouard 7565: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7566: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7567: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7568: continue;
1.268 brouard 7569: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7570: strcpy(gplotlabel,"(");
1.288 brouard 7571: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7572: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7573: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7574: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7575: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7576: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7577: vlv= nbcode[Tvaraff[k]][lv];
7578: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7579: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7580: }
1.237 brouard 7581: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7582: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7583: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7584: }
1.264 brouard 7585: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7586: fprintf(ficgp,"\n#\n");
7587: if(invalidvarcomb[k1]){
7588: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7589: continue;
7590: }
7591:
1.241 brouard 7592: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7593: 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 7594: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7595: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7596: k=3; /* Offset */
1.268 brouard 7597: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7598: if(i==1)
7599: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7600: else
7601: fprintf(ficgp,", '' ");
7602: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7603: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7604: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7605: /* 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 7606: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7607: /* for (j=2; j<= nlstate ; j ++) */
7608: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7609: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7610: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7611: } /* nlstate */
1.264 brouard 7612: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7613: } /* end cpt state*/
7614: } /* end covariate */
7615: } /* End if backcast */
7616:
1.223 brouard 7617: /* 8eme */
1.218 brouard 7618: if(prevfcast==1){
1.288 brouard 7619: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7620:
1.237 brouard 7621: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7622: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7623: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7624: continue;
1.211 brouard 7625: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7626: strcpy(gplotlabel,"(");
1.288 brouard 7627: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7628: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7629: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7630: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7631: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7632: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7633: vlv= nbcode[Tvaraff[k]][lv];
7634: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7635: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7636: }
1.237 brouard 7637: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7638: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7639: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7640: }
1.264 brouard 7641: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7642: fprintf(ficgp,"\n#\n");
7643: if(invalidvarcomb[k1]){
7644: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7645: continue;
7646: }
7647:
7648: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7649: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7650: 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 7651: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7652: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7653:
7654: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7655: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7656: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7657: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7658: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7659: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7660: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7661: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7662: if(i==istart){
1.227 brouard 7663: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7664: }else{
7665: fprintf(ficgp,",\\\n '' ");
7666: }
7667: if(cptcoveff ==0){ /* No covariate */
7668: ioffset=2; /* Age is in 2 */
7669: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7670: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7671: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7672: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7673: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7674: if(i==nlstate+1){
1.270 brouard 7675: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7676: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7677: fprintf(ficgp,",\\\n '' ");
7678: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7679: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7680: offyear, \
1.268 brouard 7681: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7682: }else
1.227 brouard 7683: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7684: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7685: }else{ /* more than 2 covariates */
1.270 brouard 7686: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7687: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7688: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7689: iyearc=ioffset-1;
7690: iagec=ioffset;
1.227 brouard 7691: fprintf(ficgp," u %d:(",ioffset);
7692: kl=0;
7693: strcpy(gplotcondition,"(");
7694: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7695: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7696: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7697: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7698: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7699: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7700: kl++;
7701: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7702: kl++;
7703: if(k <cptcoveff && cptcoveff>1)
7704: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7705: }
7706: strcpy(gplotcondition+strlen(gplotcondition),")");
7707: /* 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 *\/ */
7708: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7709: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7710: /* '' 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*/
7711: if(i==nlstate+1){
1.270 brouard 7712: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7713: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7714: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7715: fprintf(ficgp," u %d:(",iagec);
7716: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7717: iyearc, iagec, offyear, \
7718: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7719: /* '' 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 7720: }else{
7721: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7722: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7723: }
7724: } /* end if covariate */
7725: } /* nlstate */
1.264 brouard 7726: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7727: } /* end cpt state*/
7728: } /* end covariate */
7729: } /* End if prevfcast */
1.227 brouard 7730:
1.268 brouard 7731: if(backcast==1){
7732: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7733:
7734: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7735: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7736: if(m != 1 && TKresult[nres]!= k1)
7737: continue;
7738: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7739: strcpy(gplotlabel,"(");
7740: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7741: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7742: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7743: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7744: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7745: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7746: vlv= nbcode[Tvaraff[k]][lv];
7747: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7748: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7749: }
7750: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7751: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7752: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7753: }
7754: strcpy(gplotlabel+strlen(gplotlabel),")");
7755: fprintf(ficgp,"\n#\n");
7756: if(invalidvarcomb[k1]){
7757: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7758: continue;
7759: }
7760:
7761: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7762: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7763: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7764: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7765: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7766:
7767: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7768: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7769: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7770: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7771: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7772: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7773: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7774: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7775: if(i==istart){
7776: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7777: }else{
7778: fprintf(ficgp,",\\\n '' ");
7779: }
7780: if(cptcoveff ==0){ /* No covariate */
7781: ioffset=2; /* Age is in 2 */
7782: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7783: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7784: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7785: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7786: fprintf(ficgp," u %d:(", ioffset);
7787: if(i==nlstate+1){
1.270 brouard 7788: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7789: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7790: fprintf(ficgp,",\\\n '' ");
7791: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7792: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7793: offbyear, \
7794: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7795: }else
7796: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7797: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7798: }else{ /* more than 2 covariates */
1.270 brouard 7799: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7800: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7801: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7802: iyearc=ioffset-1;
7803: iagec=ioffset;
1.268 brouard 7804: fprintf(ficgp," u %d:(",ioffset);
7805: kl=0;
7806: strcpy(gplotcondition,"(");
7807: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7808: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7809: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7810: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7811: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7812: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7813: kl++;
7814: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7815: kl++;
7816: if(k <cptcoveff && cptcoveff>1)
7817: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7818: }
7819: strcpy(gplotcondition+strlen(gplotcondition),")");
7820: /* 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 *\/ */
7821: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7822: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7823: /* '' 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*/
7824: if(i==nlstate+1){
1.270 brouard 7825: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7826: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7827: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7828: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7829: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7830: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7831: iyearc,iagec,offbyear, \
7832: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7833: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7834: }else{
7835: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7836: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7837: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7838: }
7839: } /* end if covariate */
7840: } /* nlstate */
7841: fprintf(ficgp,"\nset out; unset label;\n");
7842: } /* end cpt state*/
7843: } /* end covariate */
7844: } /* End if backcast */
7845:
1.227 brouard 7846:
1.238 brouard 7847: /* 9eme writing MLE parameters */
7848: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7849: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7850: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7851: for(k=1; k <=(nlstate+ndeath); k++){
7852: if (k != i) {
1.227 brouard 7853: fprintf(ficgp,"# current state %d\n",k);
7854: for(j=1; j <=ncovmodel; j++){
7855: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7856: jk++;
7857: }
7858: fprintf(ficgp,"\n");
1.126 brouard 7859: }
7860: }
1.223 brouard 7861: }
1.187 brouard 7862: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7863:
1.145 brouard 7864: /*goto avoid;*/
1.238 brouard 7865: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7866: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7867: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7868: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7869: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7870: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7871: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7872: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7873: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7874: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7875: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7876: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7877: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7878: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7879: fprintf(ficgp,"#\n");
1.223 brouard 7880: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7881: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7882: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7883: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7884: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7885: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7886: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7887: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7888: continue;
1.264 brouard 7889: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7890: strcpy(gplotlabel,"(");
1.276 brouard 7891: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7892: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7893: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7894: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7895: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7896: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7897: vlv= nbcode[Tvaraff[k]][lv];
7898: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7899: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7900: }
1.237 brouard 7901: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7902: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7903: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7904: }
1.264 brouard 7905: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7906: fprintf(ficgp,"\n#\n");
1.264 brouard 7907: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7908: fprintf(ficgp,"\nset key outside ");
7909: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7910: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7911: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7912: if (ng==1){
7913: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7914: fprintf(ficgp,"\nunset log y");
7915: }else if (ng==2){
7916: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7917: fprintf(ficgp,"\nset log y");
7918: }else if (ng==3){
7919: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7920: fprintf(ficgp,"\nset log y");
7921: }else
7922: fprintf(ficgp,"\nunset title ");
7923: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7924: i=1;
7925: for(k2=1; k2<=nlstate; k2++) {
7926: k3=i;
7927: for(k=1; k<=(nlstate+ndeath); k++) {
7928: if (k != k2){
7929: switch( ng) {
7930: case 1:
7931: if(nagesqr==0)
7932: fprintf(ficgp," p%d+p%d*x",i,i+1);
7933: else /* nagesqr =1 */
7934: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7935: break;
7936: case 2: /* ng=2 */
7937: if(nagesqr==0)
7938: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7939: else /* nagesqr =1 */
7940: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7941: break;
7942: case 3:
7943: if(nagesqr==0)
7944: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7945: else /* nagesqr =1 */
7946: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7947: break;
7948: }
7949: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7950: ijp=1; /* product no age */
7951: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7952: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7953: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7954: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7955: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7956: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7957: if(DummyV[j]==0){
7958: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7959: }else{ /* quantitative */
7960: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7961: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7962: }
7963: ij++;
1.237 brouard 7964: }
1.268 brouard 7965: }
7966: }else if(cptcovprod >0){
7967: if(j==Tprod[ijp]) { /* */
7968: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7969: if(ijp <=cptcovprod) { /* Product */
7970: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7971: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7972: /* 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)]); */
7973: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7974: }else{ /* Vn is dummy and Vm is quanti */
7975: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7976: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7977: }
7978: }else{ /* Vn*Vm Vn is quanti */
7979: if(DummyV[Tvard[ijp][2]]==0){
7980: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7981: }else{ /* Both quanti */
7982: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7983: }
1.237 brouard 7984: }
1.268 brouard 7985: ijp++;
1.237 brouard 7986: }
1.268 brouard 7987: } /* end Tprod */
1.237 brouard 7988: } else{ /* simple covariate */
1.264 brouard 7989: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7990: if(Dummy[j]==0){
7991: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7992: }else{ /* quantitative */
7993: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7994: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7995: }
1.237 brouard 7996: } /* end simple */
7997: } /* end j */
1.223 brouard 7998: }else{
7999: i=i-ncovmodel;
8000: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8001: fprintf(ficgp," (1.");
8002: }
1.227 brouard 8003:
1.223 brouard 8004: if(ng != 1){
8005: fprintf(ficgp,")/(1");
1.227 brouard 8006:
1.264 brouard 8007: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8008: if(nagesqr==0)
1.264 brouard 8009: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8010: else /* nagesqr =1 */
1.264 brouard 8011: 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 8012:
1.223 brouard 8013: ij=1;
8014: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8015: if(cptcovage >0){
8016: if((j-2)==Tage[ij]) { /* Bug valgrind */
8017: if(ij <=cptcovage) { /* Bug valgrind */
8018: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8019: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8020: ij++;
8021: }
8022: }
8023: }else
8024: 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 8025: }
8026: fprintf(ficgp,")");
8027: }
8028: fprintf(ficgp,")");
8029: if(ng ==2)
1.276 brouard 8030: 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 8031: else /* ng= 3 */
1.276 brouard 8032: 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 8033: }else{ /* end ng <> 1 */
8034: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8035: 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 8036: }
8037: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8038: fprintf(ficgp,",");
8039: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8040: fprintf(ficgp,",");
8041: i=i+ncovmodel;
8042: } /* end k */
8043: } /* end k2 */
1.276 brouard 8044: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8045: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8046: } /* end k1 */
1.223 brouard 8047: } /* end ng */
8048: /* avoid: */
8049: fflush(ficgp);
1.126 brouard 8050: } /* end gnuplot */
8051:
8052:
8053: /*************** Moving average **************/
1.219 brouard 8054: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8055: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8056:
1.222 brouard 8057: int i, cpt, cptcod;
8058: int modcovmax =1;
8059: int mobilavrange, mob;
8060: int iage=0;
1.288 brouard 8061: int firstA1=0, firstA2=0;
1.222 brouard 8062:
1.266 brouard 8063: double sum=0., sumr=0.;
1.222 brouard 8064: double age;
1.266 brouard 8065: double *sumnewp, *sumnewm, *sumnewmr;
8066: double *agemingood, *agemaxgood;
8067: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8068:
8069:
1.278 brouard 8070: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8071: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8072:
8073: sumnewp = vector(1,ncovcombmax);
8074: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8075: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8076: agemingood = vector(1,ncovcombmax);
1.266 brouard 8077: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8078: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8079: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8080:
8081: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8082: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8083: sumnewp[cptcod]=0.;
1.266 brouard 8084: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8085: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8086: }
8087: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8088:
1.266 brouard 8089: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8090: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8091: else mobilavrange=mobilav;
8092: for (age=bage; age<=fage; age++)
8093: for (i=1; i<=nlstate;i++)
8094: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8095: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8096: /* We keep the original values on the extreme ages bage, fage and for
8097: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8098: we use a 5 terms etc. until the borders are no more concerned.
8099: */
8100: for (mob=3;mob <=mobilavrange;mob=mob+2){
8101: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8102: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8103: sumnewm[cptcod]=0.;
8104: for (i=1; i<=nlstate;i++){
1.222 brouard 8105: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8106: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8107: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8108: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8109: }
8110: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8111: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8112: } /* end i */
8113: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8114: } /* end cptcod */
1.222 brouard 8115: }/* end age */
8116: }/* end mob */
1.266 brouard 8117: }else{
8118: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8119: return -1;
1.266 brouard 8120: }
8121:
8122: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8123: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8124: if(invalidvarcomb[cptcod]){
8125: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8126: continue;
8127: }
1.219 brouard 8128:
1.266 brouard 8129: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8130: sumnewm[cptcod]=0.;
8131: sumnewmr[cptcod]=0.;
8132: for (i=1; i<=nlstate;i++){
8133: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8134: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8135: }
8136: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8137: agemingoodr[cptcod]=age;
8138: }
8139: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8140: agemingood[cptcod]=age;
8141: }
8142: } /* age */
8143: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8144: sumnewm[cptcod]=0.;
1.266 brouard 8145: sumnewmr[cptcod]=0.;
1.222 brouard 8146: for (i=1; i<=nlstate;i++){
8147: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8148: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8149: }
8150: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8151: agemaxgoodr[cptcod]=age;
1.222 brouard 8152: }
8153: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8154: agemaxgood[cptcod]=age;
8155: }
8156: } /* age */
8157: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8158: /* but they will change */
1.288 brouard 8159: firstA1=0;firstA2=0;
1.266 brouard 8160: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8161: sumnewm[cptcod]=0.;
8162: sumnewmr[cptcod]=0.;
8163: for (i=1; i<=nlstate;i++){
8164: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8165: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8166: }
8167: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8168: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8169: agemaxgoodr[cptcod]=age; /* age min */
8170: for (i=1; i<=nlstate;i++)
8171: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8172: }else{ /* bad we change the value with the values of good ages */
8173: for (i=1; i<=nlstate;i++){
8174: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8175: } /* i */
8176: } /* end bad */
8177: }else{
8178: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8179: agemaxgood[cptcod]=age;
8180: }else{ /* bad we change the value with the values of good ages */
8181: for (i=1; i<=nlstate;i++){
8182: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8183: } /* i */
8184: } /* end bad */
8185: }/* end else */
8186: sum=0.;sumr=0.;
8187: for (i=1; i<=nlstate;i++){
8188: sum+=mobaverage[(int)age][i][cptcod];
8189: sumr+=probs[(int)age][i][cptcod];
8190: }
8191: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8192: if(!firstA1){
8193: firstA1=1;
8194: 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);
8195: }
8196: 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 8197: } /* end bad */
8198: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8199: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8200: if(!firstA2){
8201: firstA2=1;
8202: 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);
8203: }
8204: 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 8205: } /* end bad */
8206: }/* age */
1.266 brouard 8207:
8208: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8209: sumnewm[cptcod]=0.;
1.266 brouard 8210: sumnewmr[cptcod]=0.;
1.222 brouard 8211: for (i=1; i<=nlstate;i++){
8212: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8213: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8214: }
8215: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8216: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8217: agemingoodr[cptcod]=age;
8218: for (i=1; i<=nlstate;i++)
8219: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8220: }else{ /* bad we change the value with the values of good ages */
8221: for (i=1; i<=nlstate;i++){
8222: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8223: } /* i */
8224: } /* end bad */
8225: }else{
8226: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8227: agemingood[cptcod]=age;
8228: }else{ /* bad */
8229: for (i=1; i<=nlstate;i++){
8230: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8231: } /* i */
8232: } /* end bad */
8233: }/* end else */
8234: sum=0.;sumr=0.;
8235: for (i=1; i<=nlstate;i++){
8236: sum+=mobaverage[(int)age][i][cptcod];
8237: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8238: }
1.266 brouard 8239: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8240: 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 8241: } /* end bad */
8242: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8243: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8244: 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 8245: } /* end bad */
8246: }/* age */
1.266 brouard 8247:
1.222 brouard 8248:
8249: for (age=bage; age<=fage; age++){
1.235 brouard 8250: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8251: sumnewp[cptcod]=0.;
8252: sumnewm[cptcod]=0.;
8253: for (i=1; i<=nlstate;i++){
8254: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8255: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8256: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8257: }
8258: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8259: }
8260: /* printf("\n"); */
8261: /* } */
1.266 brouard 8262:
1.222 brouard 8263: /* brutal averaging */
1.266 brouard 8264: /* for (i=1; i<=nlstate;i++){ */
8265: /* for (age=1; age<=bage; age++){ */
8266: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8267: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8268: /* } */
8269: /* for (age=fage; age<=AGESUP; age++){ */
8270: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8271: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8272: /* } */
8273: /* } /\* end i status *\/ */
8274: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8275: /* for (age=1; age<=AGESUP; age++){ */
8276: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8277: /* mobaverage[(int)age][i][cptcod]=0.; */
8278: /* } */
8279: /* } */
1.222 brouard 8280: }/* end cptcod */
1.266 brouard 8281: free_vector(agemaxgoodr,1, ncovcombmax);
8282: free_vector(agemaxgood,1, ncovcombmax);
8283: free_vector(agemingood,1, ncovcombmax);
8284: free_vector(agemingoodr,1, ncovcombmax);
8285: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8286: free_vector(sumnewm,1, ncovcombmax);
8287: free_vector(sumnewp,1, ncovcombmax);
8288: return 0;
8289: }/* End movingaverage */
1.218 brouard 8290:
1.126 brouard 8291:
8292: /************** Forecasting ******************/
1.269 brouard 8293: 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 8294: /* proj1, year, month, day of starting projection
8295: agemin, agemax range of age
8296: dateprev1 dateprev2 range of dates during which prevalence is computed
8297: anproj2 year of en of projection (same day and month as proj1).
8298: */
1.267 brouard 8299: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8300: double agec; /* generic age */
8301: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8302: double *popeffectif,*popcount;
8303: double ***p3mat;
1.218 brouard 8304: /* double ***mobaverage; */
1.126 brouard 8305: char fileresf[FILENAMELENGTH];
8306:
8307: agelim=AGESUP;
1.211 brouard 8308: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8309: in each health status at the date of interview (if between dateprev1 and dateprev2).
8310: We still use firstpass and lastpass as another selection.
8311: */
1.214 brouard 8312: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8313: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8314:
1.201 brouard 8315: strcpy(fileresf,"F_");
8316: strcat(fileresf,fileresu);
1.126 brouard 8317: if((ficresf=fopen(fileresf,"w"))==NULL) {
8318: printf("Problem with forecast resultfile: %s\n", fileresf);
8319: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8320: }
1.235 brouard 8321: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8322: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8323:
1.225 brouard 8324: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8325:
8326:
8327: stepsize=(int) (stepm+YEARM-1)/YEARM;
8328: if (stepm<=12) stepsize=1;
8329: if(estepm < stepm){
8330: printf ("Problem %d lower than %d\n",estepm, stepm);
8331: }
1.270 brouard 8332: else{
8333: hstepm=estepm;
8334: }
8335: if(estepm > stepm){ /* Yes every two year */
8336: stepsize=2;
8337: }
1.126 brouard 8338:
8339: hstepm=hstepm/stepm;
8340: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8341: fractional in yp1 */
8342: anprojmean=yp;
8343: yp2=modf((yp1*12),&yp);
8344: mprojmean=yp;
8345: yp1=modf((yp2*30.5),&yp);
8346: jprojmean=yp;
8347: if(jprojmean==0) jprojmean=1;
8348: if(mprojmean==0) jprojmean=1;
8349:
1.227 brouard 8350: i1=pow(2,cptcoveff);
1.126 brouard 8351: if (cptcovn < 1){i1=1;}
8352:
8353: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8354:
8355: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8356:
1.126 brouard 8357: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8358: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8359: for(k=1; k<=i1;k++){
1.253 brouard 8360: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8361: continue;
1.227 brouard 8362: if(invalidvarcomb[k]){
8363: printf("\nCombination (%d) projection ignored because no cases \n",k);
8364: continue;
8365: }
8366: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8367: for(j=1;j<=cptcoveff;j++) {
8368: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8369: }
1.235 brouard 8370: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8371: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8372: }
1.227 brouard 8373: fprintf(ficresf," yearproj age");
8374: for(j=1; j<=nlstate+ndeath;j++){
8375: for(i=1; i<=nlstate;i++)
8376: fprintf(ficresf," p%d%d",i,j);
8377: fprintf(ficresf," wp.%d",j);
8378: }
8379: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8380: fprintf(ficresf,"\n");
8381: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8382: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8383: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8384: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8385: nhstepm = nhstepm/hstepm;
8386: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8387: oldm=oldms;savm=savms;
1.268 brouard 8388: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8389: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8390: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8391: for (h=0; h<=nhstepm; h++){
8392: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8393: break;
8394: }
8395: }
8396: fprintf(ficresf,"\n");
8397: for(j=1;j<=cptcoveff;j++)
8398: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8399: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8400:
8401: for(j=1; j<=nlstate+ndeath;j++) {
8402: ppij=0.;
8403: for(i=1; i<=nlstate;i++) {
1.278 brouard 8404: if (mobilav>=1)
8405: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8406: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8407: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8408: }
1.268 brouard 8409: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8410: } /* end i */
8411: fprintf(ficresf," %.3f", ppij);
8412: }/* end j */
1.227 brouard 8413: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8414: } /* end agec */
1.266 brouard 8415: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8416: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8417: } /* end yearp */
8418: } /* end k */
1.219 brouard 8419:
1.126 brouard 8420: fclose(ficresf);
1.215 brouard 8421: printf("End of Computing forecasting \n");
8422: fprintf(ficlog,"End of Computing forecasting\n");
8423:
1.126 brouard 8424: }
8425:
1.269 brouard 8426: /************** Back Forecasting ******************/
8427: 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 8428: /* back1, year, month, day of starting backection
8429: agemin, agemax range of age
8430: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8431: anback2 year of end of backprojection (same day and month as back1).
8432: prevacurrent and prev are prevalences.
1.267 brouard 8433: */
8434: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8435: double agec; /* generic age */
1.268 brouard 8436: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8437: double *popeffectif,*popcount;
8438: double ***p3mat;
8439: /* double ***mobaverage; */
8440: char fileresfb[FILENAMELENGTH];
8441:
1.268 brouard 8442: agelim=AGEINF;
1.267 brouard 8443: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8444: in each health status at the date of interview (if between dateprev1 and dateprev2).
8445: We still use firstpass and lastpass as another selection.
8446: */
8447: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8448: /* firstpass, lastpass, stepm, weightopt, model); */
8449:
8450: /*Do we need to compute prevalence again?*/
8451:
8452: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8453:
8454: strcpy(fileresfb,"FB_");
8455: strcat(fileresfb,fileresu);
8456: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8457: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8458: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8459: }
8460: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8461: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8462:
8463: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8464:
8465:
8466: stepsize=(int) (stepm+YEARM-1)/YEARM;
8467: if (stepm<=12) stepsize=1;
8468: if(estepm < stepm){
8469: printf ("Problem %d lower than %d\n",estepm, stepm);
8470: }
1.270 brouard 8471: else{
8472: hstepm=estepm;
8473: }
8474: if(estepm >= stepm){ /* Yes every two year */
8475: stepsize=2;
8476: }
1.267 brouard 8477:
8478: hstepm=hstepm/stepm;
8479: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8480: fractional in yp1 */
8481: anprojmean=yp;
8482: yp2=modf((yp1*12),&yp);
8483: mprojmean=yp;
8484: yp1=modf((yp2*30.5),&yp);
8485: jprojmean=yp;
8486: if(jprojmean==0) jprojmean=1;
8487: if(mprojmean==0) jprojmean=1;
8488:
8489: i1=pow(2,cptcoveff);
8490: if (cptcovn < 1){i1=1;}
8491:
8492: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8493: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8494:
8495: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8496:
8497: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8498: for(k=1; k<=i1;k++){
8499: if(i1 != 1 && TKresult[nres]!= k)
8500: continue;
8501: if(invalidvarcomb[k]){
8502: printf("\nCombination (%d) projection ignored because no cases \n",k);
8503: continue;
8504: }
1.268 brouard 8505: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8506: for(j=1;j<=cptcoveff;j++) {
8507: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8508: }
8509: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8510: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8511: }
8512: fprintf(ficresfb," yearbproj age");
8513: for(j=1; j<=nlstate+ndeath;j++){
8514: for(i=1; i<=nlstate;i++)
1.268 brouard 8515: fprintf(ficresfb," b%d%d",i,j);
8516: fprintf(ficresfb," b.%d",j);
1.267 brouard 8517: }
8518: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8519: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8520: fprintf(ficresfb,"\n");
8521: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.273 brouard 8522: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8523: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8524: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8525: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8526: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8527: nhstepm = nhstepm/hstepm;
8528: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8529: oldm=oldms;savm=savms;
1.268 brouard 8530: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8531: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8532: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8533: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8534: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8535: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8536: for (h=0; h<=nhstepm; h++){
1.268 brouard 8537: if (h*hstepm/YEARM*stepm ==-yearp) {
8538: break;
8539: }
8540: }
8541: fprintf(ficresfb,"\n");
8542: for(j=1;j<=cptcoveff;j++)
8543: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8544: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8545: for(i=1; i<=nlstate+ndeath;i++) {
8546: ppij=0.;ppi=0.;
8547: for(j=1; j<=nlstate;j++) {
8548: /* if (mobilav==1) */
1.269 brouard 8549: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8550: ppi=ppi+prevacurrent[(int)agec][j][k];
8551: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8552: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8553: /* else { */
8554: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8555: /* } */
1.268 brouard 8556: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8557: } /* end j */
8558: if(ppi <0.99){
8559: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8560: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8561: }
8562: fprintf(ficresfb," %.3f", ppij);
8563: }/* end j */
1.267 brouard 8564: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8565: } /* end agec */
8566: } /* end yearp */
8567: } /* end k */
1.217 brouard 8568:
1.267 brouard 8569: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8570:
1.267 brouard 8571: fclose(ficresfb);
8572: printf("End of Computing Back forecasting \n");
8573: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8574:
1.267 brouard 8575: }
1.217 brouard 8576:
1.269 brouard 8577: /* Variance of prevalence limit: varprlim */
8578: 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 8579: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8580:
8581: char fileresvpl[FILENAMELENGTH];
8582: FILE *ficresvpl;
8583: double **oldm, **savm;
8584: double **varpl; /* Variances of prevalence limits by age */
8585: int i1, k, nres, j ;
8586:
8587: strcpy(fileresvpl,"VPL_");
8588: strcat(fileresvpl,fileresu);
8589: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8590: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8591: exit(0);
8592: }
1.288 brouard 8593: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8594: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8595:
8596: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8597: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8598:
8599: i1=pow(2,cptcoveff);
8600: if (cptcovn < 1){i1=1;}
8601:
8602: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8603: for(k=1; k<=i1;k++){
8604: if(i1 != 1 && TKresult[nres]!= k)
8605: continue;
8606: fprintf(ficresvpl,"\n#****** ");
8607: printf("\n#****** ");
8608: fprintf(ficlog,"\n#****** ");
8609: for(j=1;j<=cptcoveff;j++) {
8610: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8611: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8612: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8613: }
8614: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8615: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8616: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8617: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8618: }
8619: fprintf(ficresvpl,"******\n");
8620: printf("******\n");
8621: fprintf(ficlog,"******\n");
8622:
8623: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8624: oldm=oldms;savm=savms;
8625: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8626: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8627: /*}*/
8628: }
8629:
8630: fclose(ficresvpl);
1.288 brouard 8631: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8632: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8633:
8634: }
8635: /* Variance of back prevalence: varbprlim */
8636: 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){
8637: /*------- Variance of back (stable) prevalence------*/
8638:
8639: char fileresvbl[FILENAMELENGTH];
8640: FILE *ficresvbl;
8641:
8642: double **oldm, **savm;
8643: double **varbpl; /* Variances of back prevalence limits by age */
8644: int i1, k, nres, j ;
8645:
8646: strcpy(fileresvbl,"VBL_");
8647: strcat(fileresvbl,fileresu);
8648: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8649: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8650: exit(0);
8651: }
8652: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8653: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8654:
8655:
8656: i1=pow(2,cptcoveff);
8657: if (cptcovn < 1){i1=1;}
8658:
8659: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8660: for(k=1; k<=i1;k++){
8661: if(i1 != 1 && TKresult[nres]!= k)
8662: continue;
8663: fprintf(ficresvbl,"\n#****** ");
8664: printf("\n#****** ");
8665: fprintf(ficlog,"\n#****** ");
8666: for(j=1;j<=cptcoveff;j++) {
8667: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8668: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8669: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8670: }
8671: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8672: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8673: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8674: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8675: }
8676: fprintf(ficresvbl,"******\n");
8677: printf("******\n");
8678: fprintf(ficlog,"******\n");
8679:
8680: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8681: oldm=oldms;savm=savms;
8682:
8683: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8684: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8685: /*}*/
8686: }
8687:
8688: fclose(ficresvbl);
8689: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8690: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8691:
8692: } /* End of varbprlim */
8693:
1.126 brouard 8694: /************** Forecasting *****not tested NB*************/
1.227 brouard 8695: /* 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 8696:
1.227 brouard 8697: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8698: /* int *popage; */
8699: /* double calagedatem, agelim, kk1, kk2; */
8700: /* double *popeffectif,*popcount; */
8701: /* double ***p3mat,***tabpop,***tabpopprev; */
8702: /* /\* double ***mobaverage; *\/ */
8703: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8704:
1.227 brouard 8705: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8706: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8707: /* agelim=AGESUP; */
8708: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8709:
1.227 brouard 8710: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8711:
8712:
1.227 brouard 8713: /* strcpy(filerespop,"POP_"); */
8714: /* strcat(filerespop,fileresu); */
8715: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8716: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8717: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8718: /* } */
8719: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8720: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8721:
1.227 brouard 8722: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8723:
1.227 brouard 8724: /* /\* if (mobilav!=0) { *\/ */
8725: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8726: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8727: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8728: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8729: /* /\* } *\/ */
8730: /* /\* } *\/ */
1.126 brouard 8731:
1.227 brouard 8732: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8733: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8734:
1.227 brouard 8735: /* agelim=AGESUP; */
1.126 brouard 8736:
1.227 brouard 8737: /* hstepm=1; */
8738: /* hstepm=hstepm/stepm; */
1.218 brouard 8739:
1.227 brouard 8740: /* if (popforecast==1) { */
8741: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8742: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8743: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8744: /* } */
8745: /* popage=ivector(0,AGESUP); */
8746: /* popeffectif=vector(0,AGESUP); */
8747: /* popcount=vector(0,AGESUP); */
1.126 brouard 8748:
1.227 brouard 8749: /* i=1; */
8750: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8751:
1.227 brouard 8752: /* imx=i; */
8753: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8754: /* } */
1.218 brouard 8755:
1.227 brouard 8756: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8757: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8758: /* k=k+1; */
8759: /* fprintf(ficrespop,"\n#******"); */
8760: /* for(j=1;j<=cptcoveff;j++) { */
8761: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8762: /* } */
8763: /* fprintf(ficrespop,"******\n"); */
8764: /* fprintf(ficrespop,"# Age"); */
8765: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8766: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8767:
1.227 brouard 8768: /* for (cpt=0; cpt<=0;cpt++) { */
8769: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8770:
1.227 brouard 8771: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8772: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8773: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8774:
1.227 brouard 8775: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8776: /* oldm=oldms;savm=savms; */
8777: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8778:
1.227 brouard 8779: /* for (h=0; h<=nhstepm; h++){ */
8780: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8781: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8782: /* } */
8783: /* for(j=1; j<=nlstate+ndeath;j++) { */
8784: /* kk1=0.;kk2=0; */
8785: /* for(i=1; i<=nlstate;i++) { */
8786: /* if (mobilav==1) */
8787: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8788: /* else { */
8789: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8790: /* } */
8791: /* } */
8792: /* if (h==(int)(calagedatem+12*cpt)){ */
8793: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8794: /* /\*fprintf(ficrespop," %.3f", kk1); */
8795: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8796: /* } */
8797: /* } */
8798: /* for(i=1; i<=nlstate;i++){ */
8799: /* kk1=0.; */
8800: /* for(j=1; j<=nlstate;j++){ */
8801: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8802: /* } */
8803: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8804: /* } */
1.218 brouard 8805:
1.227 brouard 8806: /* if (h==(int)(calagedatem+12*cpt)) */
8807: /* for(j=1; j<=nlstate;j++) */
8808: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8809: /* } */
8810: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8811: /* } */
8812: /* } */
1.218 brouard 8813:
1.227 brouard 8814: /* /\******\/ */
1.218 brouard 8815:
1.227 brouard 8816: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8817: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8818: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8819: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8820: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8821:
1.227 brouard 8822: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8823: /* oldm=oldms;savm=savms; */
8824: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8825: /* for (h=0; h<=nhstepm; h++){ */
8826: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8827: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8828: /* } */
8829: /* for(j=1; j<=nlstate+ndeath;j++) { */
8830: /* kk1=0.;kk2=0; */
8831: /* for(i=1; i<=nlstate;i++) { */
8832: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8833: /* } */
8834: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8835: /* } */
8836: /* } */
8837: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8838: /* } */
8839: /* } */
8840: /* } */
8841: /* } */
1.218 brouard 8842:
1.227 brouard 8843: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8844:
1.227 brouard 8845: /* if (popforecast==1) { */
8846: /* free_ivector(popage,0,AGESUP); */
8847: /* free_vector(popeffectif,0,AGESUP); */
8848: /* free_vector(popcount,0,AGESUP); */
8849: /* } */
8850: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8851: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8852: /* fclose(ficrespop); */
8853: /* } /\* End of popforecast *\/ */
1.218 brouard 8854:
1.126 brouard 8855: int fileappend(FILE *fichier, char *optionfich)
8856: {
8857: if((fichier=fopen(optionfich,"a"))==NULL) {
8858: printf("Problem with file: %s\n", optionfich);
8859: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8860: return (0);
8861: }
8862: fflush(fichier);
8863: return (1);
8864: }
8865:
8866:
8867: /**************** function prwizard **********************/
8868: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8869: {
8870:
8871: /* Wizard to print covariance matrix template */
8872:
1.164 brouard 8873: char ca[32], cb[32];
8874: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8875: int numlinepar;
8876:
8877: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8878: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8879: for(i=1; i <=nlstate; i++){
8880: jj=0;
8881: for(j=1; j <=nlstate+ndeath; j++){
8882: if(j==i) continue;
8883: jj++;
8884: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8885: printf("%1d%1d",i,j);
8886: fprintf(ficparo,"%1d%1d",i,j);
8887: for(k=1; k<=ncovmodel;k++){
8888: /* printf(" %lf",param[i][j][k]); */
8889: /* fprintf(ficparo," %lf",param[i][j][k]); */
8890: printf(" 0.");
8891: fprintf(ficparo," 0.");
8892: }
8893: printf("\n");
8894: fprintf(ficparo,"\n");
8895: }
8896: }
8897: printf("# Scales (for hessian or gradient estimation)\n");
8898: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8899: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8900: for(i=1; i <=nlstate; i++){
8901: jj=0;
8902: for(j=1; j <=nlstate+ndeath; j++){
8903: if(j==i) continue;
8904: jj++;
8905: fprintf(ficparo,"%1d%1d",i,j);
8906: printf("%1d%1d",i,j);
8907: fflush(stdout);
8908: for(k=1; k<=ncovmodel;k++){
8909: /* printf(" %le",delti3[i][j][k]); */
8910: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8911: printf(" 0.");
8912: fprintf(ficparo," 0.");
8913: }
8914: numlinepar++;
8915: printf("\n");
8916: fprintf(ficparo,"\n");
8917: }
8918: }
8919: printf("# Covariance matrix\n");
8920: /* # 121 Var(a12)\n\ */
8921: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8922: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8923: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8924: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8925: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8926: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8927: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8928: fflush(stdout);
8929: fprintf(ficparo,"# Covariance matrix\n");
8930: /* # 121 Var(a12)\n\ */
8931: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8932: /* # ...\n\ */
8933: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8934:
8935: for(itimes=1;itimes<=2;itimes++){
8936: jj=0;
8937: for(i=1; i <=nlstate; i++){
8938: for(j=1; j <=nlstate+ndeath; j++){
8939: if(j==i) continue;
8940: for(k=1; k<=ncovmodel;k++){
8941: jj++;
8942: ca[0]= k+'a'-1;ca[1]='\0';
8943: if(itimes==1){
8944: printf("#%1d%1d%d",i,j,k);
8945: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8946: }else{
8947: printf("%1d%1d%d",i,j,k);
8948: fprintf(ficparo,"%1d%1d%d",i,j,k);
8949: /* printf(" %.5le",matcov[i][j]); */
8950: }
8951: ll=0;
8952: for(li=1;li <=nlstate; li++){
8953: for(lj=1;lj <=nlstate+ndeath; lj++){
8954: if(lj==li) continue;
8955: for(lk=1;lk<=ncovmodel;lk++){
8956: ll++;
8957: if(ll<=jj){
8958: cb[0]= lk +'a'-1;cb[1]='\0';
8959: if(ll<jj){
8960: if(itimes==1){
8961: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8962: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8963: }else{
8964: printf(" 0.");
8965: fprintf(ficparo," 0.");
8966: }
8967: }else{
8968: if(itimes==1){
8969: printf(" Var(%s%1d%1d)",ca,i,j);
8970: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8971: }else{
8972: printf(" 0.");
8973: fprintf(ficparo," 0.");
8974: }
8975: }
8976: }
8977: } /* end lk */
8978: } /* end lj */
8979: } /* end li */
8980: printf("\n");
8981: fprintf(ficparo,"\n");
8982: numlinepar++;
8983: } /* end k*/
8984: } /*end j */
8985: } /* end i */
8986: } /* end itimes */
8987:
8988: } /* end of prwizard */
8989: /******************* Gompertz Likelihood ******************************/
8990: double gompertz(double x[])
8991: {
8992: double A,B,L=0.0,sump=0.,num=0.;
8993: int i,n=0; /* n is the size of the sample */
8994:
1.220 brouard 8995: for (i=1;i<=imx ; i++) {
1.126 brouard 8996: sump=sump+weight[i];
8997: /* sump=sump+1;*/
8998: num=num+1;
8999: }
9000:
9001:
9002: /* for (i=0; i<=imx; i++)
9003: 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]);*/
9004:
9005: for (i=1;i<=imx ; i++)
9006: {
9007: if (cens[i] == 1 && wav[i]>1)
9008: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9009:
9010: if (cens[i] == 0 && wav[i]>1)
9011: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
9012: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
9013:
9014: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9015: if (wav[i] > 1 ) { /* ??? */
9016: L=L+A*weight[i];
9017: /* 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]);*/
9018: }
9019: }
9020:
9021: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9022:
9023: return -2*L*num/sump;
9024: }
9025:
1.136 brouard 9026: #ifdef GSL
9027: /******************* Gompertz_f Likelihood ******************************/
9028: double gompertz_f(const gsl_vector *v, void *params)
9029: {
9030: double A,B,LL=0.0,sump=0.,num=0.;
9031: double *x= (double *) v->data;
9032: int i,n=0; /* n is the size of the sample */
9033:
9034: for (i=0;i<=imx-1 ; i++) {
9035: sump=sump+weight[i];
9036: /* sump=sump+1;*/
9037: num=num+1;
9038: }
9039:
9040:
9041: /* for (i=0; i<=imx; i++)
9042: 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]);*/
9043: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9044: for (i=1;i<=imx ; i++)
9045: {
9046: if (cens[i] == 1 && wav[i]>1)
9047: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9048:
9049: if (cens[i] == 0 && wav[i]>1)
9050: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9051: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9052:
9053: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9054: if (wav[i] > 1 ) { /* ??? */
9055: LL=LL+A*weight[i];
9056: /* 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]);*/
9057: }
9058: }
9059:
9060: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9061: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9062:
9063: return -2*LL*num/sump;
9064: }
9065: #endif
9066:
1.126 brouard 9067: /******************* Printing html file ***********/
1.201 brouard 9068: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9069: int lastpass, int stepm, int weightopt, char model[],\
9070: int imx, double p[],double **matcov,double agemortsup){
9071: int i,k;
9072:
9073: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9074: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9075: for (i=1;i<=2;i++)
9076: 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 9077: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9078: fprintf(fichtm,"</ul>");
9079:
9080: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9081:
9082: 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>");
9083:
9084: for (k=agegomp;k<(agemortsup-2);k++)
9085: 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]);
9086:
9087:
9088: fflush(fichtm);
9089: }
9090:
9091: /******************* Gnuplot file **************/
1.201 brouard 9092: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9093:
9094: char dirfileres[132],optfileres[132];
1.164 brouard 9095:
1.126 brouard 9096: int ng;
9097:
9098:
9099: /*#ifdef windows */
9100: fprintf(ficgp,"cd \"%s\" \n",pathc);
9101: /*#endif */
9102:
9103:
9104: strcpy(dirfileres,optionfilefiname);
9105: strcpy(optfileres,"vpl");
1.199 brouard 9106: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9107: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9108: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9109: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9110: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9111:
9112: }
9113:
1.136 brouard 9114: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9115: {
1.126 brouard 9116:
1.136 brouard 9117: /*-------- data file ----------*/
9118: FILE *fic;
9119: char dummy[]=" ";
1.240 brouard 9120: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9121: int lstra;
1.136 brouard 9122: int linei, month, year,iout;
9123: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9124: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9125: char *stratrunc;
1.223 brouard 9126:
1.240 brouard 9127: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9128: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9129:
1.240 brouard 9130: for(v=1; v <=ncovcol;v++){
9131: DummyV[v]=0;
9132: FixedV[v]=0;
9133: }
9134: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9135: DummyV[v]=1;
9136: FixedV[v]=0;
9137: }
9138: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9139: DummyV[v]=0;
9140: FixedV[v]=1;
9141: }
9142: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9143: DummyV[v]=1;
9144: FixedV[v]=1;
9145: }
9146: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9147: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9148: 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]);
9149: }
1.126 brouard 9150:
1.136 brouard 9151: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9152: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9153: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9154: }
1.126 brouard 9155:
1.136 brouard 9156: i=1;
9157: linei=0;
9158: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9159: linei=linei+1;
9160: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9161: if(line[j] == '\t')
9162: line[j] = ' ';
9163: }
9164: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9165: ;
9166: };
9167: line[j+1]=0; /* Trims blanks at end of line */
9168: if(line[0]=='#'){
9169: fprintf(ficlog,"Comment line\n%s\n",line);
9170: printf("Comment line\n%s\n",line);
9171: continue;
9172: }
9173: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9174: strcpy(line, linetmp);
1.223 brouard 9175:
9176: /* Loops on waves */
9177: for (j=maxwav;j>=1;j--){
9178: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9179: cutv(stra, strb, line, ' ');
9180: if(strb[0]=='.') { /* Missing value */
9181: lval=-1;
9182: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9183: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9184: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9185: 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);
9186: 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);
9187: return 1;
9188: }
9189: }else{
9190: errno=0;
9191: /* what_kind_of_number(strb); */
9192: dval=strtod(strb,&endptr);
9193: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9194: /* if(strb != endptr && *endptr == '\0') */
9195: /* dval=dlval; */
9196: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9197: if( strb[0]=='\0' || (*endptr != '\0')){
9198: 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);
9199: 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);
9200: return 1;
9201: }
9202: cotqvar[j][iv][i]=dval;
9203: cotvar[j][ntv+iv][i]=dval;
9204: }
9205: strcpy(line,stra);
1.223 brouard 9206: }/* end loop ntqv */
1.225 brouard 9207:
1.223 brouard 9208: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9209: cutv(stra, strb, line, ' ');
9210: if(strb[0]=='.') { /* Missing value */
9211: lval=-1;
9212: }else{
9213: errno=0;
9214: lval=strtol(strb,&endptr,10);
9215: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9216: if( strb[0]=='\0' || (*endptr != '\0')){
9217: 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);
9218: 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);
9219: return 1;
9220: }
9221: }
9222: if(lval <-1 || lval >1){
9223: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9224: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9225: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9226: For example, for multinomial values like 1, 2 and 3,\n \
9227: build V1=0 V2=0 for the reference value (1),\n \
9228: V1=1 V2=0 for (2) \n \
1.223 brouard 9229: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9230: output of IMaCh is often meaningless.\n \
1.223 brouard 9231: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9232: fprintf(ficlog,"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);fflush(ficlog);
1.238 brouard 9241: return 1;
9242: }
9243: cotvar[j][iv][i]=(double)(lval);
9244: strcpy(line,stra);
1.223 brouard 9245: }/* end loop ntv */
1.225 brouard 9246:
1.223 brouard 9247: /* Statuses at wave */
1.137 brouard 9248: cutv(stra, strb, line, ' ');
1.223 brouard 9249: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9250: lval=-1;
1.136 brouard 9251: }else{
1.238 brouard 9252: errno=0;
9253: lval=strtol(strb,&endptr,10);
9254: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9255: if( strb[0]=='\0' || (*endptr != '\0')){
9256: 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);
9257: 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);
9258: return 1;
9259: }
1.136 brouard 9260: }
1.225 brouard 9261:
1.136 brouard 9262: s[j][i]=lval;
1.225 brouard 9263:
1.223 brouard 9264: /* Date of Interview */
1.136 brouard 9265: strcpy(line,stra);
9266: cutv(stra, strb,line,' ');
1.169 brouard 9267: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9268: }
1.169 brouard 9269: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9270: month=99;
9271: year=9999;
1.136 brouard 9272: }else{
1.225 brouard 9273: 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);
9274: 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);
9275: return 1;
1.136 brouard 9276: }
9277: anint[j][i]= (double) year;
9278: mint[j][i]= (double)month;
9279: strcpy(line,stra);
1.223 brouard 9280: } /* End loop on waves */
1.225 brouard 9281:
1.223 brouard 9282: /* Date of death */
1.136 brouard 9283: cutv(stra, strb,line,' ');
1.169 brouard 9284: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9285: }
1.169 brouard 9286: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9287: month=99;
9288: year=9999;
9289: }else{
1.141 brouard 9290: 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 9291: 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);
9292: return 1;
1.136 brouard 9293: }
9294: andc[i]=(double) year;
9295: moisdc[i]=(double) month;
9296: strcpy(line,stra);
9297:
1.223 brouard 9298: /* Date of birth */
1.136 brouard 9299: cutv(stra, strb,line,' ');
1.169 brouard 9300: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9301: }
1.169 brouard 9302: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9303: month=99;
9304: year=9999;
9305: }else{
1.141 brouard 9306: 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);
9307: 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 9308: return 1;
1.136 brouard 9309: }
9310: if (year==9999) {
1.141 brouard 9311: 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);
9312: 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 9313: return 1;
9314:
1.136 brouard 9315: }
9316: annais[i]=(double)(year);
9317: moisnais[i]=(double)(month);
9318: strcpy(line,stra);
1.225 brouard 9319:
1.223 brouard 9320: /* Sample weight */
1.136 brouard 9321: cutv(stra, strb,line,' ');
9322: errno=0;
9323: dval=strtod(strb,&endptr);
9324: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9325: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9326: 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 9327: fflush(ficlog);
9328: return 1;
9329: }
9330: weight[i]=dval;
9331: strcpy(line,stra);
1.225 brouard 9332:
1.223 brouard 9333: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9334: cutv(stra, strb, line, ' ');
9335: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9336: lval=-1;
1.223 brouard 9337: }else{
1.225 brouard 9338: errno=0;
9339: /* what_kind_of_number(strb); */
9340: dval=strtod(strb,&endptr);
9341: /* if(strb != endptr && *endptr == '\0') */
9342: /* dval=dlval; */
9343: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9344: if( strb[0]=='\0' || (*endptr != '\0')){
9345: 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);
9346: 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);
9347: return 1;
9348: }
9349: coqvar[iv][i]=dval;
1.226 brouard 9350: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9351: }
9352: strcpy(line,stra);
9353: }/* end loop nqv */
1.136 brouard 9354:
1.223 brouard 9355: /* Covariate values */
1.136 brouard 9356: for (j=ncovcol;j>=1;j--){
9357: cutv(stra, strb,line,' ');
1.223 brouard 9358: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9359: lval=-1;
1.136 brouard 9360: }else{
1.225 brouard 9361: errno=0;
9362: lval=strtol(strb,&endptr,10);
9363: if( strb[0]=='\0' || (*endptr != '\0')){
9364: 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);
9365: 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);
9366: return 1;
9367: }
1.136 brouard 9368: }
9369: if(lval <-1 || lval >1){
1.225 brouard 9370: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9371: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9372: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9373: For example, for multinomial values like 1, 2 and 3,\n \
9374: build V1=0 V2=0 for the reference value (1),\n \
9375: V1=1 V2=0 for (2) \n \
1.136 brouard 9376: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9377: output of IMaCh is often meaningless.\n \
1.136 brouard 9378: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9379: fprintf(ficlog,"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);fflush(ficlog);
1.225 brouard 9388: return 1;
1.136 brouard 9389: }
9390: covar[j][i]=(double)(lval);
9391: strcpy(line,stra);
9392: }
9393: lstra=strlen(stra);
1.225 brouard 9394:
1.136 brouard 9395: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9396: stratrunc = &(stra[lstra-9]);
9397: num[i]=atol(stratrunc);
9398: }
9399: else
9400: num[i]=atol(stra);
9401: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9402: 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;}*/
9403:
9404: i=i+1;
9405: } /* End loop reading data */
1.225 brouard 9406:
1.136 brouard 9407: *imax=i-1; /* Number of individuals */
9408: fclose(fic);
1.225 brouard 9409:
1.136 brouard 9410: return (0);
1.164 brouard 9411: /* endread: */
1.225 brouard 9412: printf("Exiting readdata: ");
9413: fclose(fic);
9414: return (1);
1.223 brouard 9415: }
1.126 brouard 9416:
1.234 brouard 9417: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9418: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9419: while (*p2 == ' ')
1.234 brouard 9420: p2++;
9421: /* while ((*p1++ = *p2++) !=0) */
9422: /* ; */
9423: /* do */
9424: /* while (*p2 == ' ') */
9425: /* p2++; */
9426: /* while (*p1++ == *p2++); */
9427: *stri=p2;
1.145 brouard 9428: }
9429:
1.235 brouard 9430: int decoderesult ( char resultline[], int nres)
1.230 brouard 9431: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9432: {
1.235 brouard 9433: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9434: char resultsav[MAXLINE];
1.234 brouard 9435: int resultmodel[MAXLINE];
9436: int modelresult[MAXLINE];
1.230 brouard 9437: char stra[80], strb[80], strc[80], strd[80],stre[80];
9438:
1.234 brouard 9439: removefirstspace(&resultline);
1.233 brouard 9440: printf("decoderesult:%s\n",resultline);
1.230 brouard 9441:
9442: if (strstr(resultline,"v") !=0){
9443: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9444: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9445: return 1;
9446: }
9447: trimbb(resultsav, resultline);
9448: if (strlen(resultsav) >1){
9449: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9450: }
1.253 brouard 9451: if(j == 0){ /* Resultline but no = */
9452: TKresult[nres]=0; /* Combination for the nresult and the model */
9453: return (0);
9454: }
9455:
1.234 brouard 9456: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9457: 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);
9458: 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);
9459: }
9460: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9461: if(nbocc(resultsav,'=') >1){
9462: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9463: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9464: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9465: }else
9466: cutl(strc,strd,resultsav,'=');
1.230 brouard 9467: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9468:
1.230 brouard 9469: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9470: Tvarsel[k]=atoi(strc);
9471: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9472: /* cptcovsel++; */
9473: if (nbocc(stra,'=') >0)
9474: strcpy(resultsav,stra); /* and analyzes it */
9475: }
1.235 brouard 9476: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9477: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9478: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9479: match=0;
1.236 brouard 9480: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9481: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9482: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9483: match=1;
9484: break;
9485: }
9486: }
9487: if(match == 0){
9488: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9489: }
9490: }
9491: }
1.235 brouard 9492: /* Checking for missing or useless values in comparison of current model needs */
9493: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9494: match=0;
1.235 brouard 9495: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9496: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9497: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9498: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9499: ++match;
9500: }
9501: }
9502: }
9503: if(match == 0){
9504: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9505: }else if(match > 1){
9506: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9507: }
9508: }
1.235 brouard 9509:
1.234 brouard 9510: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9511: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9512: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9513: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9514: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9515: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9516: /* 1 0 0 0 */
9517: /* 2 1 0 0 */
9518: /* 3 0 1 0 */
9519: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9520: /* 5 0 0 1 */
9521: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9522: /* 7 0 1 1 */
9523: /* 8 1 1 1 */
1.237 brouard 9524: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9525: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9526: /* V5*age V5 known which value for nres? */
9527: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9528: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9529: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9530: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9531: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9532: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9533: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9534: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9535: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9536: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9537: k4++;;
9538: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9539: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9540: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9541: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9542: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9543: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9544: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9545: k4q++;;
9546: }
9547: }
1.234 brouard 9548:
1.235 brouard 9549: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9550: return (0);
9551: }
1.235 brouard 9552:
1.230 brouard 9553: int decodemodel( char model[], int lastobs)
9554: /**< This routine decodes the model and returns:
1.224 brouard 9555: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9556: * - nagesqr = 1 if age*age in the model, otherwise 0.
9557: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9558: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9559: * - cptcovage number of covariates with age*products =2
9560: * - cptcovs number of simple covariates
9561: * - 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
9562: * which is a new column after the 9 (ncovcol) variables.
9563: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9564: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9565: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9566: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9567: */
1.136 brouard 9568: {
1.238 brouard 9569: int i, j, k, ks, v;
1.227 brouard 9570: int j1, k1, k2, k3, k4;
1.136 brouard 9571: char modelsav[80];
1.145 brouard 9572: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9573: char *strpt;
1.136 brouard 9574:
1.145 brouard 9575: /*removespace(model);*/
1.136 brouard 9576: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9577: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9578: if (strstr(model,"AGE") !=0){
1.192 brouard 9579: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9580: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9581: return 1;
9582: }
1.141 brouard 9583: if (strstr(model,"v") !=0){
9584: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9585: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9586: return 1;
9587: }
1.187 brouard 9588: strcpy(modelsav,model);
9589: if ((strpt=strstr(model,"age*age")) !=0){
9590: printf(" strpt=%s, model=%s\n",strpt, model);
9591: if(strpt != model){
1.234 brouard 9592: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9593: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9594: corresponding column of parameters.\n",model);
1.234 brouard 9595: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9596: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9597: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9598: return 1;
1.225 brouard 9599: }
1.187 brouard 9600: nagesqr=1;
9601: if (strstr(model,"+age*age") !=0)
1.234 brouard 9602: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9603: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9604: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9605: else
1.234 brouard 9606: substrchaine(modelsav, model, "age*age");
1.187 brouard 9607: }else
9608: nagesqr=0;
9609: if (strlen(modelsav) >1){
9610: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9611: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9612: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9613: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9614: * cst, age and age*age
9615: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9616: /* including age products which are counted in cptcovage.
9617: * but the covariates which are products must be treated
9618: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9619: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9620: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9621:
9622:
1.187 brouard 9623: /* Design
9624: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9625: * < ncovcol=8 >
9626: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9627: * k= 1 2 3 4 5 6 7 8
9628: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9629: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9630: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9631: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9632: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9633: * Tage[++cptcovage]=k
9634: * if products, new covar are created after ncovcol with k1
9635: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9636: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9637: * 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
9638: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9639: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9640: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9641: * < ncovcol=8 >
9642: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9643: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9644: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9645: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9646: * p Tprod[1]@2={ 6, 5}
9647: *p Tvard[1][1]@4= {7, 8, 5, 6}
9648: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9649: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9650: *How to reorganize?
9651: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9652: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9653: * {2, 1, 4, 8, 5, 6, 3, 7}
9654: * Struct []
9655: */
1.225 brouard 9656:
1.187 brouard 9657: /* This loop fills the array Tvar from the string 'model'.*/
9658: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9659: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9660: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9661: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9662: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9663: /* k=1 Tvar[1]=2 (from V2) */
9664: /* k=5 Tvar[5] */
9665: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9666: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9667: /* } */
1.198 brouard 9668: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9669: /*
9670: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9671: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9672: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9673: }
1.187 brouard 9674: cptcovage=0;
9675: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9676: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9677: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9678: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9679: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9680: /*scanf("%d",i);*/
9681: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9682: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9683: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9684: /* covar is not filled and then is empty */
9685: cptcovprod--;
9686: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9687: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9688: Typevar[k]=1; /* 1 for age product */
9689: cptcovage++; /* Sums the number of covariates which include age as a product */
9690: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9691: /*printf("stre=%s ", stre);*/
9692: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9693: cptcovprod--;
9694: cutl(stre,strb,strc,'V');
9695: Tvar[k]=atoi(stre);
9696: Typevar[k]=1; /* 1 for age product */
9697: cptcovage++;
9698: Tage[cptcovage]=k;
9699: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9700: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9701: cptcovn++;
9702: cptcovprodnoage++;k1++;
9703: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9704: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9705: because this model-covariate is a construction we invent a new column
9706: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9707: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9708: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9709: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9710: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9711: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9712: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9713: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9714: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9715: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9716: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9717: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9718: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9719: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9720: for (i=1; i<=lastobs;i++){
9721: /* Computes the new covariate which is a product of
9722: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9723: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9724: }
9725: } /* End age is not in the model */
9726: } /* End if model includes a product */
9727: else { /* no more sum */
9728: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9729: /* scanf("%d",i);*/
9730: cutl(strd,strc,strb,'V');
9731: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9732: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9733: Tvar[k]=atoi(strd);
9734: Typevar[k]=0; /* 0 for simple covariates */
9735: }
9736: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9737: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9738: scanf("%d",i);*/
1.187 brouard 9739: } /* end of loop + on total covariates */
9740: } /* end if strlen(modelsave == 0) age*age might exist */
9741: } /* end if strlen(model == 0) */
1.136 brouard 9742:
9743: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9744: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9745:
1.136 brouard 9746: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9747: printf("cptcovprod=%d ", cptcovprod);
9748: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9749: scanf("%d ",i);*/
9750:
9751:
1.230 brouard 9752: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9753: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9754: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9755: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9756: k = 1 2 3 4 5 6 7 8 9
9757: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9758: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9759: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9760: Dummy[k] 1 0 0 0 3 1 1 2 3
9761: Tmodelind[combination of covar]=k;
1.225 brouard 9762: */
9763: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9764: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9765: /* 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 9766: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9767: printf("Model=%s\n\
9768: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9769: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9770: 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);
9771: fprintf(ficlog,"Model=%s\n\
9772: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9773: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9774: 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 9775: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9776: 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 */
9777: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9778: Fixed[k]= 0;
9779: Dummy[k]= 0;
1.225 brouard 9780: ncoveff++;
1.232 brouard 9781: ncovf++;
1.234 brouard 9782: nsd++;
9783: modell[k].maintype= FTYPE;
9784: TvarsD[nsd]=Tvar[k];
9785: TvarsDind[nsd]=k;
9786: TvarF[ncovf]=Tvar[k];
9787: TvarFind[ncovf]=k;
9788: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9789: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9790: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9791: Fixed[k]= 0;
9792: Dummy[k]= 0;
9793: ncoveff++;
9794: ncovf++;
9795: modell[k].maintype= FTYPE;
9796: TvarF[ncovf]=Tvar[k];
9797: TvarFind[ncovf]=k;
1.230 brouard 9798: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9799: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9800: }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 9801: Fixed[k]= 0;
9802: Dummy[k]= 1;
1.230 brouard 9803: nqfveff++;
1.234 brouard 9804: modell[k].maintype= FTYPE;
9805: modell[k].subtype= FQ;
9806: nsq++;
9807: TvarsQ[nsq]=Tvar[k];
9808: TvarsQind[nsq]=k;
1.232 brouard 9809: ncovf++;
1.234 brouard 9810: TvarF[ncovf]=Tvar[k];
9811: TvarFind[ncovf]=k;
1.231 brouard 9812: 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 9813: 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 9814: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9815: Fixed[k]= 1;
9816: Dummy[k]= 0;
1.225 brouard 9817: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9818: modell[k].maintype= VTYPE;
9819: modell[k].subtype= VD;
9820: nsd++;
9821: TvarsD[nsd]=Tvar[k];
9822: TvarsDind[nsd]=k;
9823: ncovv++; /* Only simple time varying variables */
9824: TvarV[ncovv]=Tvar[k];
1.242 brouard 9825: 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 9826: 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 */
9827: 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 9828: 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);
9829: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9830: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9831: Fixed[k]= 1;
9832: Dummy[k]= 1;
9833: nqtveff++;
9834: modell[k].maintype= VTYPE;
9835: modell[k].subtype= VQ;
9836: ncovv++; /* Only simple time varying variables */
9837: nsq++;
9838: TvarsQ[nsq]=Tvar[k];
9839: TvarsQind[nsq]=k;
9840: TvarV[ncovv]=Tvar[k];
1.242 brouard 9841: 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 9842: 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 */
9843: 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 9844: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9845: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9846: 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 9847: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9848: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9849: ncova++;
9850: TvarA[ncova]=Tvar[k];
9851: TvarAind[ncova]=k;
1.231 brouard 9852: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9853: Fixed[k]= 2;
9854: Dummy[k]= 2;
9855: modell[k].maintype= ATYPE;
9856: modell[k].subtype= APFD;
9857: /* ncoveff++; */
1.227 brouard 9858: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9859: Fixed[k]= 2;
9860: Dummy[k]= 3;
9861: modell[k].maintype= ATYPE;
9862: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9863: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9864: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9865: Fixed[k]= 3;
9866: Dummy[k]= 2;
9867: modell[k].maintype= ATYPE;
9868: modell[k].subtype= APVD; /* Product age * varying dummy */
9869: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9870: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9871: Fixed[k]= 3;
9872: Dummy[k]= 3;
9873: modell[k].maintype= ATYPE;
9874: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9875: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9876: }
9877: }else if (Typevar[k] == 2) { /* product without age */
9878: k1=Tposprod[k];
9879: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9880: if(Tvard[k1][2] <=ncovcol){
9881: Fixed[k]= 1;
9882: Dummy[k]= 0;
9883: modell[k].maintype= FTYPE;
9884: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9885: ncovf++; /* Fixed variables without age */
9886: TvarF[ncovf]=Tvar[k];
9887: TvarFind[ncovf]=k;
9888: }else if(Tvard[k1][2] <=ncovcol+nqv){
9889: Fixed[k]= 0; /* or 2 ?*/
9890: Dummy[k]= 1;
9891: modell[k].maintype= FTYPE;
9892: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9893: ncovf++; /* Varying variables without age */
9894: TvarF[ncovf]=Tvar[k];
9895: TvarFind[ncovf]=k;
9896: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9897: Fixed[k]= 1;
9898: Dummy[k]= 0;
9899: modell[k].maintype= VTYPE;
9900: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9901: ncovv++; /* Varying variables without age */
9902: TvarV[ncovv]=Tvar[k];
9903: TvarVind[ncovv]=k;
9904: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9905: Fixed[k]= 1;
9906: Dummy[k]= 1;
9907: modell[k].maintype= VTYPE;
9908: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9909: ncovv++; /* Varying variables without age */
9910: TvarV[ncovv]=Tvar[k];
9911: TvarVind[ncovv]=k;
9912: }
1.227 brouard 9913: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9914: if(Tvard[k1][2] <=ncovcol){
9915: Fixed[k]= 0; /* or 2 ?*/
9916: Dummy[k]= 1;
9917: modell[k].maintype= FTYPE;
9918: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9919: ncovf++; /* Fixed variables without age */
9920: TvarF[ncovf]=Tvar[k];
9921: TvarFind[ncovf]=k;
9922: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9923: Fixed[k]= 1;
9924: Dummy[k]= 1;
9925: modell[k].maintype= VTYPE;
9926: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9927: ncovv++; /* Varying variables without age */
9928: TvarV[ncovv]=Tvar[k];
9929: TvarVind[ncovv]=k;
9930: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9931: Fixed[k]= 1;
9932: Dummy[k]= 1;
9933: modell[k].maintype= VTYPE;
9934: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9935: ncovv++; /* Varying variables without age */
9936: TvarV[ncovv]=Tvar[k];
9937: TvarVind[ncovv]=k;
9938: ncovv++; /* Varying variables without age */
9939: TvarV[ncovv]=Tvar[k];
9940: TvarVind[ncovv]=k;
9941: }
1.227 brouard 9942: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9943: if(Tvard[k1][2] <=ncovcol){
9944: Fixed[k]= 1;
9945: Dummy[k]= 1;
9946: modell[k].maintype= VTYPE;
9947: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9948: ncovv++; /* Varying variables without age */
9949: TvarV[ncovv]=Tvar[k];
9950: TvarVind[ncovv]=k;
9951: }else if(Tvard[k1][2] <=ncovcol+nqv){
9952: Fixed[k]= 1;
9953: Dummy[k]= 1;
9954: modell[k].maintype= VTYPE;
9955: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9956: ncovv++; /* Varying variables without age */
9957: TvarV[ncovv]=Tvar[k];
9958: TvarVind[ncovv]=k;
9959: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9960: Fixed[k]= 1;
9961: Dummy[k]= 0;
9962: modell[k].maintype= VTYPE;
9963: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9964: ncovv++; /* Varying variables without age */
9965: TvarV[ncovv]=Tvar[k];
9966: TvarVind[ncovv]=k;
9967: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9968: Fixed[k]= 1;
9969: Dummy[k]= 1;
9970: modell[k].maintype= VTYPE;
9971: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9972: ncovv++; /* Varying variables without age */
9973: TvarV[ncovv]=Tvar[k];
9974: TvarVind[ncovv]=k;
9975: }
1.227 brouard 9976: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9977: if(Tvard[k1][2] <=ncovcol){
9978: Fixed[k]= 1;
9979: Dummy[k]= 1;
9980: modell[k].maintype= VTYPE;
9981: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9982: ncovv++; /* Varying variables without age */
9983: TvarV[ncovv]=Tvar[k];
9984: TvarVind[ncovv]=k;
9985: }else if(Tvard[k1][2] <=ncovcol+nqv){
9986: Fixed[k]= 1;
9987: Dummy[k]= 1;
9988: modell[k].maintype= VTYPE;
9989: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9990: ncovv++; /* Varying variables without age */
9991: TvarV[ncovv]=Tvar[k];
9992: TvarVind[ncovv]=k;
9993: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9994: Fixed[k]= 1;
9995: Dummy[k]= 1;
9996: modell[k].maintype= VTYPE;
9997: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9998: ncovv++; /* Varying variables without age */
9999: TvarV[ncovv]=Tvar[k];
10000: TvarVind[ncovv]=k;
10001: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10002: Fixed[k]= 1;
10003: Dummy[k]= 1;
10004: modell[k].maintype= VTYPE;
10005: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10006: ncovv++; /* Varying variables without age */
10007: TvarV[ncovv]=Tvar[k];
10008: TvarVind[ncovv]=k;
10009: }
1.227 brouard 10010: }else{
1.240 brouard 10011: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10012: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10013: } /*end k1*/
1.225 brouard 10014: }else{
1.226 brouard 10015: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10016: 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 10017: }
1.227 brouard 10018: 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 10019: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10020: 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]);
10021: }
10022: /* Searching for doublons in the model */
10023: for(k1=1; k1<= cptcovt;k1++){
10024: for(k2=1; k2 <k1;k2++){
1.285 brouard 10025: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10026: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10027: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10028: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10029: 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]);
10030: 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 10031: return(1);
10032: }
10033: }else if (Typevar[k1] ==2){
10034: k3=Tposprod[k1];
10035: k4=Tposprod[k2];
10036: 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])) ){
10037: 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]]);
10038: 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);
10039: return(1);
10040: }
10041: }
1.227 brouard 10042: }
10043: }
1.225 brouard 10044: }
10045: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10046: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10047: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10048: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10049: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10050: /*endread:*/
1.225 brouard 10051: printf("Exiting decodemodel: ");
10052: return (1);
1.136 brouard 10053: }
10054:
1.169 brouard 10055: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10056: {/* Check ages at death */
1.136 brouard 10057: int i, m;
1.218 brouard 10058: int firstone=0;
10059:
1.136 brouard 10060: for (i=1; i<=imx; i++) {
10061: for(m=2; (m<= maxwav); m++) {
10062: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10063: anint[m][i]=9999;
1.216 brouard 10064: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10065: s[m][i]=-1;
1.136 brouard 10066: }
10067: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10068: *nberr = *nberr + 1;
1.218 brouard 10069: if(firstone == 0){
10070: firstone=1;
1.260 brouard 10071: 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 10072: }
1.262 brouard 10073: 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 10074: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10075: }
10076: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10077: (*nberr)++;
1.259 brouard 10078: 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 10079: 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 10080: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10081: }
10082: }
10083: }
10084:
10085: for (i=1; i<=imx; i++) {
10086: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10087: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10088: 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 10089: if (s[m][i] >= nlstate+1) {
1.169 brouard 10090: if(agedc[i]>0){
10091: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10092: agev[m][i]=agedc[i];
1.214 brouard 10093: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10094: }else {
1.136 brouard 10095: if ((int)andc[i]!=9999){
10096: nbwarn++;
10097: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10098: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10099: agev[m][i]=-1;
10100: }
10101: }
1.169 brouard 10102: } /* agedc > 0 */
1.214 brouard 10103: } /* end if */
1.136 brouard 10104: else if(s[m][i] !=9){ /* Standard case, age in fractional
10105: years but with the precision of a month */
10106: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10107: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10108: agev[m][i]=1;
10109: else if(agev[m][i] < *agemin){
10110: *agemin=agev[m][i];
10111: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10112: }
10113: else if(agev[m][i] >*agemax){
10114: *agemax=agev[m][i];
1.156 brouard 10115: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10116: }
10117: /*agev[m][i]=anint[m][i]-annais[i];*/
10118: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10119: } /* en if 9*/
1.136 brouard 10120: else { /* =9 */
1.214 brouard 10121: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10122: agev[m][i]=1;
10123: s[m][i]=-1;
10124: }
10125: }
1.214 brouard 10126: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10127: agev[m][i]=1;
1.214 brouard 10128: else{
10129: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10130: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10131: agev[m][i]=0;
10132: }
10133: } /* End for lastpass */
10134: }
1.136 brouard 10135:
10136: for (i=1; i<=imx; i++) {
10137: for(m=firstpass; (m<=lastpass); m++){
10138: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10139: (*nberr)++;
1.136 brouard 10140: 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);
10141: 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);
10142: return 1;
10143: }
10144: }
10145: }
10146:
10147: /*for (i=1; i<=imx; i++){
10148: for (m=firstpass; (m<lastpass); m++){
10149: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10150: }
10151:
10152: }*/
10153:
10154:
1.139 brouard 10155: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10156: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10157:
10158: return (0);
1.164 brouard 10159: /* endread:*/
1.136 brouard 10160: printf("Exiting calandcheckages: ");
10161: return (1);
10162: }
10163:
1.172 brouard 10164: #if defined(_MSC_VER)
10165: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10166: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10167: //#include "stdafx.h"
10168: //#include <stdio.h>
10169: //#include <tchar.h>
10170: //#include <windows.h>
10171: //#include <iostream>
10172: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10173:
10174: LPFN_ISWOW64PROCESS fnIsWow64Process;
10175:
10176: BOOL IsWow64()
10177: {
10178: BOOL bIsWow64 = FALSE;
10179:
10180: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10181: // (HANDLE, PBOOL);
10182:
10183: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10184:
10185: HMODULE module = GetModuleHandle(_T("kernel32"));
10186: const char funcName[] = "IsWow64Process";
10187: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10188: GetProcAddress(module, funcName);
10189:
10190: if (NULL != fnIsWow64Process)
10191: {
10192: if (!fnIsWow64Process(GetCurrentProcess(),
10193: &bIsWow64))
10194: //throw std::exception("Unknown error");
10195: printf("Unknown error\n");
10196: }
10197: return bIsWow64 != FALSE;
10198: }
10199: #endif
1.177 brouard 10200:
1.191 brouard 10201: void syscompilerinfo(int logged)
1.292 ! brouard 10202: {
! 10203: #include <stdint.h>
! 10204:
! 10205: /* #include "syscompilerinfo.h"*/
1.185 brouard 10206: /* command line Intel compiler 32bit windows, XP compatible:*/
10207: /* /GS /W3 /Gy
10208: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10209: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10210: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10211: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10212: */
10213: /* 64 bits */
1.185 brouard 10214: /*
10215: /GS /W3 /Gy
10216: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10217: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10218: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10219: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10220: /* Optimization are useless and O3 is slower than O2 */
10221: /*
10222: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10223: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10224: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10225: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10226: */
1.186 brouard 10227: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10228: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10229: /PDB:"visual studio
10230: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10231: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10232: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10233: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10234: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10235: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10236: uiAccess='false'"
10237: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10238: /NOLOGO /TLBID:1
10239: */
1.292 ! brouard 10240:
! 10241:
1.177 brouard 10242: #if defined __INTEL_COMPILER
1.178 brouard 10243: #if defined(__GNUC__)
10244: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10245: #endif
1.177 brouard 10246: #elif defined(__GNUC__)
1.179 brouard 10247: #ifndef __APPLE__
1.174 brouard 10248: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10249: #endif
1.177 brouard 10250: struct utsname sysInfo;
1.178 brouard 10251: int cross = CROSS;
10252: if (cross){
10253: printf("Cross-");
1.191 brouard 10254: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10255: }
1.174 brouard 10256: #endif
10257:
1.191 brouard 10258: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10259: #if defined(__clang__)
1.191 brouard 10260: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10261: #endif
10262: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10263: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10264: #endif
10265: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10266: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10267: #endif
10268: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10269: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10270: #endif
10271: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10272: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10273: #endif
10274: #if defined(_MSC_VER)
1.191 brouard 10275: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10276: #endif
10277: #if defined(__PGI)
1.191 brouard 10278: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10279: #endif
10280: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10281: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10282: #endif
1.191 brouard 10283: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10284:
1.167 brouard 10285: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10286: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10287: // Windows (x64 and x86)
1.191 brouard 10288: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10289: #elif __unix__ // all unices, not all compilers
10290: // Unix
1.191 brouard 10291: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10292: #elif __linux__
10293: // linux
1.191 brouard 10294: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10295: #elif __APPLE__
1.174 brouard 10296: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10297: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10298: #endif
10299:
10300: /* __MINGW32__ */
10301: /* __CYGWIN__ */
10302: /* __MINGW64__ */
10303: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10304: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10305: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10306: /* _WIN64 // Defined for applications for Win64. */
10307: /* _M_X64 // Defined for compilations that target x64 processors. */
10308: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10309:
1.167 brouard 10310: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10311: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10312: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10313: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10314: #else
1.191 brouard 10315: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10316: #endif
10317:
1.169 brouard 10318: #if defined(__GNUC__)
10319: # if defined(__GNUC_PATCHLEVEL__)
10320: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10321: + __GNUC_MINOR__ * 100 \
10322: + __GNUC_PATCHLEVEL__)
10323: # else
10324: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10325: + __GNUC_MINOR__ * 100)
10326: # endif
1.174 brouard 10327: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10328: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10329:
10330: if (uname(&sysInfo) != -1) {
10331: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10332: 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 10333: }
10334: else
10335: perror("uname() error");
1.179 brouard 10336: //#ifndef __INTEL_COMPILER
10337: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10338: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10339: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10340: #endif
1.169 brouard 10341: #endif
1.172 brouard 10342:
1.286 brouard 10343: // void main ()
1.172 brouard 10344: // {
1.169 brouard 10345: #if defined(_MSC_VER)
1.174 brouard 10346: if (IsWow64()){
1.191 brouard 10347: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10348: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10349: }
10350: else{
1.191 brouard 10351: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10352: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10353: }
1.172 brouard 10354: // printf("\nPress Enter to continue...");
10355: // getchar();
10356: // }
10357:
1.169 brouard 10358: #endif
10359:
1.167 brouard 10360:
1.219 brouard 10361: }
1.136 brouard 10362:
1.219 brouard 10363: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10364: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10365: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10366: /* double ftolpl = 1.e-10; */
1.180 brouard 10367: double age, agebase, agelim;
1.203 brouard 10368: double tot;
1.180 brouard 10369:
1.202 brouard 10370: strcpy(filerespl,"PL_");
10371: strcat(filerespl,fileresu);
10372: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10373: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10374: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10375: }
1.288 brouard 10376: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10377: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10378: pstamp(ficrespl);
1.288 brouard 10379: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10380: fprintf(ficrespl,"#Age ");
10381: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10382: fprintf(ficrespl,"\n");
1.180 brouard 10383:
1.219 brouard 10384: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10385:
1.219 brouard 10386: agebase=ageminpar;
10387: agelim=agemaxpar;
1.180 brouard 10388:
1.227 brouard 10389: /* i1=pow(2,ncoveff); */
1.234 brouard 10390: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10391: if (cptcovn < 1){i1=1;}
1.180 brouard 10392:
1.238 brouard 10393: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10394: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10395: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10396: continue;
1.235 brouard 10397:
1.238 brouard 10398: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10399: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10400: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10401: /* k=k+1; */
10402: /* to clean */
10403: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10404: fprintf(ficrespl,"#******");
10405: printf("#******");
10406: fprintf(ficlog,"#******");
10407: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10408: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10409: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10410: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10411: }
10412: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10413: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10414: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10415: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10416: }
10417: fprintf(ficrespl,"******\n");
10418: printf("******\n");
10419: fprintf(ficlog,"******\n");
10420: if(invalidvarcomb[k]){
10421: printf("\nCombination (%d) ignored because no case \n",k);
10422: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10423: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10424: continue;
10425: }
1.219 brouard 10426:
1.238 brouard 10427: fprintf(ficrespl,"#Age ");
10428: for(j=1;j<=cptcoveff;j++) {
10429: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10430: }
10431: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10432: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10433:
1.238 brouard 10434: for (age=agebase; age<=agelim; age++){
10435: /* for (age=agebase; age<=agebase; age++){ */
10436: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10437: fprintf(ficrespl,"%.0f ",age );
10438: for(j=1;j<=cptcoveff;j++)
10439: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10440: tot=0.;
10441: for(i=1; i<=nlstate;i++){
10442: tot += prlim[i][i];
10443: fprintf(ficrespl," %.5f", prlim[i][i]);
10444: }
10445: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10446: } /* Age */
10447: /* was end of cptcod */
10448: } /* cptcov */
10449: } /* nres */
1.219 brouard 10450: return 0;
1.180 brouard 10451: }
10452:
1.218 brouard 10453: 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 10454: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10455:
10456: /* Computes the back prevalence limit for any combination of covariate values
10457: * at any age between ageminpar and agemaxpar
10458: */
1.235 brouard 10459: int i, j, k, i1, nres=0 ;
1.217 brouard 10460: /* double ftolpl = 1.e-10; */
10461: double age, agebase, agelim;
10462: double tot;
1.218 brouard 10463: /* double ***mobaverage; */
10464: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10465:
10466: strcpy(fileresplb,"PLB_");
10467: strcat(fileresplb,fileresu);
10468: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10469: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10470: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10471: }
1.288 brouard 10472: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10473: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10474: pstamp(ficresplb);
1.288 brouard 10475: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10476: fprintf(ficresplb,"#Age ");
10477: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10478: fprintf(ficresplb,"\n");
10479:
1.218 brouard 10480:
10481: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10482:
10483: agebase=ageminpar;
10484: agelim=agemaxpar;
10485:
10486:
1.227 brouard 10487: i1=pow(2,cptcoveff);
1.218 brouard 10488: if (cptcovn < 1){i1=1;}
1.227 brouard 10489:
1.238 brouard 10490: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10491: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10492: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10493: continue;
10494: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10495: fprintf(ficresplb,"#******");
10496: printf("#******");
10497: fprintf(ficlog,"#******");
10498: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10499: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10500: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10501: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10502: }
10503: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10504: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10505: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10506: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10507: }
10508: fprintf(ficresplb,"******\n");
10509: printf("******\n");
10510: fprintf(ficlog,"******\n");
10511: if(invalidvarcomb[k]){
10512: printf("\nCombination (%d) ignored because no cases \n",k);
10513: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10514: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10515: continue;
10516: }
1.218 brouard 10517:
1.238 brouard 10518: fprintf(ficresplb,"#Age ");
10519: for(j=1;j<=cptcoveff;j++) {
10520: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10521: }
10522: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10523: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10524:
10525:
1.238 brouard 10526: for (age=agebase; age<=agelim; age++){
10527: /* for (age=agebase; age<=agebase; age++){ */
10528: if(mobilavproj > 0){
10529: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10530: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10531: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10532: }else if (mobilavproj == 0){
10533: 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);
10534: 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);
10535: exit(1);
10536: }else{
10537: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10538: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10539: /* printf("TOTOT\n"); */
10540: /* exit(1); */
1.238 brouard 10541: }
10542: fprintf(ficresplb,"%.0f ",age );
10543: for(j=1;j<=cptcoveff;j++)
10544: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10545: tot=0.;
10546: for(i=1; i<=nlstate;i++){
10547: tot += bprlim[i][i];
10548: fprintf(ficresplb," %.5f", bprlim[i][i]);
10549: }
10550: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10551: } /* Age */
10552: /* was end of cptcod */
1.255 brouard 10553: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10554: } /* end of any combination */
10555: } /* end of nres */
1.218 brouard 10556: /* hBijx(p, bage, fage); */
10557: /* fclose(ficrespijb); */
10558:
10559: return 0;
1.217 brouard 10560: }
1.218 brouard 10561:
1.180 brouard 10562: int hPijx(double *p, int bage, int fage){
10563: /*------------- h Pij x at various ages ------------*/
10564:
10565: int stepsize;
10566: int agelim;
10567: int hstepm;
10568: int nhstepm;
1.235 brouard 10569: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10570:
10571: double agedeb;
10572: double ***p3mat;
10573:
1.201 brouard 10574: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10575: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10576: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10577: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10578: }
10579: printf("Computing pij: result on file '%s' \n", filerespij);
10580: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10581:
10582: stepsize=(int) (stepm+YEARM-1)/YEARM;
10583: /*if (stepm<=24) stepsize=2;*/
10584:
10585: agelim=AGESUP;
10586: hstepm=stepsize*YEARM; /* Every year of age */
10587: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10588:
1.180 brouard 10589: /* hstepm=1; aff par mois*/
10590: pstamp(ficrespij);
10591: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10592: i1= pow(2,cptcoveff);
1.218 brouard 10593: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10594: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10595: /* k=k+1; */
1.235 brouard 10596: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10597: for(k=1; k<=i1;k++){
1.253 brouard 10598: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10599: continue;
1.183 brouard 10600: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10601: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10602: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10603: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10604: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10605: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10606: }
1.183 brouard 10607: fprintf(ficrespij,"******\n");
10608:
10609: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10610: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10611: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10612:
10613: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10614:
1.183 brouard 10615: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10616: oldm=oldms;savm=savms;
1.235 brouard 10617: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10618: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10619: for(i=1; i<=nlstate;i++)
10620: for(j=1; j<=nlstate+ndeath;j++)
10621: fprintf(ficrespij," %1d-%1d",i,j);
10622: fprintf(ficrespij,"\n");
10623: for (h=0; h<=nhstepm; h++){
10624: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10625: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10626: for(i=1; i<=nlstate;i++)
10627: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10628: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10629: fprintf(ficrespij,"\n");
10630: }
1.183 brouard 10631: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10632: fprintf(ficrespij,"\n");
10633: }
1.180 brouard 10634: /*}*/
10635: }
1.218 brouard 10636: return 0;
1.180 brouard 10637: }
1.218 brouard 10638:
10639: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10640: /*------------- h Bij x at various ages ------------*/
10641:
10642: int stepsize;
1.218 brouard 10643: /* int agelim; */
10644: int ageminl;
1.217 brouard 10645: int hstepm;
10646: int nhstepm;
1.238 brouard 10647: int h, i, i1, j, k, nres;
1.218 brouard 10648:
1.217 brouard 10649: double agedeb;
10650: double ***p3mat;
1.218 brouard 10651:
10652: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10653: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10654: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10655: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10656: }
10657: printf("Computing pij back: result on file '%s' \n", filerespijb);
10658: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10659:
10660: stepsize=(int) (stepm+YEARM-1)/YEARM;
10661: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10662:
1.218 brouard 10663: /* agelim=AGESUP; */
1.289 brouard 10664: ageminl=AGEINF; /* was 30 */
1.218 brouard 10665: hstepm=stepsize*YEARM; /* Every year of age */
10666: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10667:
10668: /* hstepm=1; aff par mois*/
10669: pstamp(ficrespijb);
1.255 brouard 10670: 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 10671: i1= pow(2,cptcoveff);
1.218 brouard 10672: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10673: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10674: /* k=k+1; */
1.238 brouard 10675: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10676: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10677: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10678: continue;
10679: fprintf(ficrespijb,"\n#****** ");
10680: for(j=1;j<=cptcoveff;j++)
10681: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10682: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10683: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10684: }
10685: fprintf(ficrespijb,"******\n");
1.264 brouard 10686: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10687: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10688: continue;
10689: }
10690:
10691: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10692: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10693: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10694: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10695: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10696:
10697: /* nhstepm=nhstepm*YEARM; aff par mois*/
10698:
1.266 brouard 10699: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10700: /* and memory limitations if stepm is small */
10701:
1.238 brouard 10702: /* oldm=oldms;savm=savms; */
10703: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10704: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10705: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10706: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10707: for(i=1; i<=nlstate;i++)
10708: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10709: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10710: fprintf(ficrespijb,"\n");
1.238 brouard 10711: for (h=0; h<=nhstepm; h++){
10712: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10713: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10714: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10715: for(i=1; i<=nlstate;i++)
10716: for(j=1; j<=nlstate+ndeath;j++)
10717: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10718: fprintf(ficrespijb,"\n");
10719: }
10720: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10721: fprintf(ficrespijb,"\n");
10722: } /* end age deb */
10723: } /* end combination */
10724: } /* end nres */
1.218 brouard 10725: return 0;
10726: } /* hBijx */
1.217 brouard 10727:
1.180 brouard 10728:
1.136 brouard 10729: /***********************************************/
10730: /**************** Main Program *****************/
10731: /***********************************************/
10732:
10733: int main(int argc, char *argv[])
10734: {
10735: #ifdef GSL
10736: const gsl_multimin_fminimizer_type *T;
10737: size_t iteri = 0, it;
10738: int rval = GSL_CONTINUE;
10739: int status = GSL_SUCCESS;
10740: double ssval;
10741: #endif
10742: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 10743: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
10744: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 10745: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10746: int jj, ll, li, lj, lk;
1.136 brouard 10747: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10748: int num_filled;
1.136 brouard 10749: int itimes;
10750: int NDIM=2;
10751: int vpopbased=0;
1.235 brouard 10752: int nres=0;
1.258 brouard 10753: int endishere=0;
1.277 brouard 10754: int noffset=0;
1.274 brouard 10755: int ncurrv=0; /* Temporary variable */
10756:
1.164 brouard 10757: char ca[32], cb[32];
1.136 brouard 10758: /* FILE *fichtm; *//* Html File */
10759: /* FILE *ficgp;*/ /*Gnuplot File */
10760: struct stat info;
1.191 brouard 10761: double agedeb=0.;
1.194 brouard 10762:
10763: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10764: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10765:
1.165 brouard 10766: double fret;
1.191 brouard 10767: double dum=0.; /* Dummy variable */
1.136 brouard 10768: double ***p3mat;
1.218 brouard 10769: /* double ***mobaverage; */
1.164 brouard 10770:
10771: char line[MAXLINE];
1.197 brouard 10772: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10773:
1.234 brouard 10774: char modeltemp[MAXLINE];
1.230 brouard 10775: char resultline[MAXLINE];
10776:
1.136 brouard 10777: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10778: char *tok, *val; /* pathtot */
1.290 brouard 10779: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 10780: int c, h , cpt, c2;
1.191 brouard 10781: int jl=0;
10782: int i1, j1, jk, stepsize=0;
1.194 brouard 10783: int count=0;
10784:
1.164 brouard 10785: int *tab;
1.136 brouard 10786: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.292 ! brouard 10787: /* int backcast=0; */ /* defined as global for mlikeli and mle */
1.136 brouard 10788: int mobilav=0,popforecast=0;
1.191 brouard 10789: int hstepm=0, nhstepm=0;
1.136 brouard 10790: int agemortsup;
10791: float sumlpop=0.;
10792: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10793: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10794:
1.191 brouard 10795: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10796: double ftolpl=FTOL;
10797: double **prlim;
1.217 brouard 10798: double **bprlim;
1.136 brouard 10799: double ***param; /* Matrix of parameters */
1.251 brouard 10800: double ***paramstart; /* Matrix of starting parameter values */
10801: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10802: double **matcov; /* Matrix of covariance */
1.203 brouard 10803: double **hess; /* Hessian matrix */
1.136 brouard 10804: double ***delti3; /* Scale */
10805: double *delti; /* Scale */
10806: double ***eij, ***vareij;
10807: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10808:
1.136 brouard 10809: double *epj, vepp;
1.164 brouard 10810:
1.273 brouard 10811: double dateprev1, dateprev2;
10812: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0;
10813: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0;
1.217 brouard 10814:
1.136 brouard 10815: double **ximort;
1.145 brouard 10816: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10817: int *dcwave;
10818:
1.164 brouard 10819: char z[1]="c";
1.136 brouard 10820:
10821: /*char *strt;*/
10822: char strtend[80];
1.126 brouard 10823:
1.164 brouard 10824:
1.126 brouard 10825: /* setlocale (LC_ALL, ""); */
10826: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10827: /* textdomain (PACKAGE); */
10828: /* setlocale (LC_CTYPE, ""); */
10829: /* setlocale (LC_MESSAGES, ""); */
10830:
10831: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10832: rstart_time = time(NULL);
10833: /* (void) gettimeofday(&start_time,&tzp);*/
10834: start_time = *localtime(&rstart_time);
1.126 brouard 10835: curr_time=start_time;
1.157 brouard 10836: /*tml = *localtime(&start_time.tm_sec);*/
10837: /* strcpy(strstart,asctime(&tml)); */
10838: strcpy(strstart,asctime(&start_time));
1.126 brouard 10839:
10840: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10841: /* tp.tm_sec = tp.tm_sec +86400; */
10842: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10843: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10844: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10845: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10846: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10847: /* strt=asctime(&tmg); */
10848: /* printf("Time(after) =%s",strstart); */
10849: /* (void) time (&time_value);
10850: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10851: * tm = *localtime(&time_value);
10852: * strstart=asctime(&tm);
10853: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10854: */
10855:
10856: nberr=0; /* Number of errors and warnings */
10857: nbwarn=0;
1.184 brouard 10858: #ifdef WIN32
10859: _getcwd(pathcd, size);
10860: #else
1.126 brouard 10861: getcwd(pathcd, size);
1.184 brouard 10862: #endif
1.191 brouard 10863: syscompilerinfo(0);
1.196 brouard 10864: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10865: if(argc <=1){
10866: printf("\nEnter the parameter file name: ");
1.205 brouard 10867: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10868: printf("ERROR Empty parameter file name\n");
10869: goto end;
10870: }
1.126 brouard 10871: i=strlen(pathr);
10872: if(pathr[i-1]=='\n')
10873: pathr[i-1]='\0';
1.156 brouard 10874: i=strlen(pathr);
1.205 brouard 10875: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10876: pathr[i-1]='\0';
1.205 brouard 10877: }
10878: i=strlen(pathr);
10879: if( i==0 ){
10880: printf("ERROR Empty parameter file name\n");
10881: goto end;
10882: }
10883: for (tok = pathr; tok != NULL; ){
1.126 brouard 10884: printf("Pathr |%s|\n",pathr);
10885: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10886: printf("val= |%s| pathr=%s\n",val,pathr);
10887: strcpy (pathtot, val);
10888: if(pathr[0] == '\0') break; /* Dirty */
10889: }
10890: }
1.281 brouard 10891: else if (argc<=2){
10892: strcpy(pathtot,argv[1]);
10893: }
1.126 brouard 10894: else{
10895: strcpy(pathtot,argv[1]);
1.281 brouard 10896: strcpy(z,argv[2]);
10897: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10898: }
10899: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10900: /*cygwin_split_path(pathtot,path,optionfile);
10901: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10902: /* cutv(path,optionfile,pathtot,'\\');*/
10903:
10904: /* Split argv[0], imach program to get pathimach */
10905: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10906: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10907: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10908: /* strcpy(pathimach,argv[0]); */
10909: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10910: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10911: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10912: #ifdef WIN32
10913: _chdir(path); /* Can be a relative path */
10914: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10915: #else
1.126 brouard 10916: chdir(path); /* Can be a relative path */
1.184 brouard 10917: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10918: #endif
10919: printf("Current directory %s!\n",pathcd);
1.126 brouard 10920: strcpy(command,"mkdir ");
10921: strcat(command,optionfilefiname);
10922: if((outcmd=system(command)) != 0){
1.169 brouard 10923: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10924: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10925: /* fclose(ficlog); */
10926: /* exit(1); */
10927: }
10928: /* if((imk=mkdir(optionfilefiname))<0){ */
10929: /* perror("mkdir"); */
10930: /* } */
10931:
10932: /*-------- arguments in the command line --------*/
10933:
1.186 brouard 10934: /* Main Log file */
1.126 brouard 10935: strcat(filelog, optionfilefiname);
10936: strcat(filelog,".log"); /* */
10937: if((ficlog=fopen(filelog,"w"))==NULL) {
10938: printf("Problem with logfile %s\n",filelog);
10939: goto end;
10940: }
10941: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10942: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10943: fprintf(ficlog,"\nEnter the parameter file name: \n");
10944: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10945: path=%s \n\
10946: optionfile=%s\n\
10947: optionfilext=%s\n\
1.156 brouard 10948: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10949:
1.197 brouard 10950: syscompilerinfo(1);
1.167 brouard 10951:
1.126 brouard 10952: printf("Local time (at start):%s",strstart);
10953: fprintf(ficlog,"Local time (at start): %s",strstart);
10954: fflush(ficlog);
10955: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10956: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10957:
10958: /* */
10959: strcpy(fileres,"r");
10960: strcat(fileres, optionfilefiname);
1.201 brouard 10961: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10962: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10963: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10964:
1.186 brouard 10965: /* Main ---------arguments file --------*/
1.126 brouard 10966:
10967: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10968: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10969: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10970: fflush(ficlog);
1.149 brouard 10971: /* goto end; */
10972: exit(70);
1.126 brouard 10973: }
10974:
10975: strcpy(filereso,"o");
1.201 brouard 10976: strcat(filereso,fileresu);
1.126 brouard 10977: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10978: printf("Problem with Output resultfile: %s\n", filereso);
10979: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10980: fflush(ficlog);
10981: goto end;
10982: }
1.278 brouard 10983: /*-------- Rewriting parameter file ----------*/
10984: strcpy(rfileres,"r"); /* "Rparameterfile */
10985: strcat(rfileres,optionfilefiname); /* Parameter file first name */
10986: strcat(rfileres,"."); /* */
10987: strcat(rfileres,optionfilext); /* Other files have txt extension */
10988: if((ficres =fopen(rfileres,"w"))==NULL) {
10989: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10990: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
10991: fflush(ficlog);
10992: goto end;
10993: }
10994: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 10995:
1.278 brouard 10996:
1.126 brouard 10997: /* Reads comments: lines beginning with '#' */
10998: numlinepar=0;
1.277 brouard 10999: /* Is it a BOM UTF-8 Windows file? */
11000: /* First parameter line */
1.197 brouard 11001: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11002: noffset=0;
11003: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11004: {
11005: noffset=noffset+3;
11006: printf("# File is an UTF8 Bom.\n"); // 0xBF
11007: }
11008: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
11009: {
11010: noffset=noffset+2;
11011: printf("# File is an UTF16BE BOM file\n");
11012: }
11013: else if( line[0] == 0 && line[1] == 0)
11014: {
11015: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11016: noffset=noffset+4;
11017: printf("# File is an UTF16BE BOM file\n");
11018: }
11019: } else{
11020: ;/*printf(" Not a BOM file\n");*/
11021: }
11022:
1.197 brouard 11023: /* If line starts with a # it is a comment */
1.277 brouard 11024: if (line[noffset] == '#') {
1.197 brouard 11025: numlinepar++;
11026: fputs(line,stdout);
11027: fputs(line,ficparo);
1.278 brouard 11028: fputs(line,ficres);
1.197 brouard 11029: fputs(line,ficlog);
11030: continue;
11031: }else
11032: break;
11033: }
11034: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11035: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11036: if (num_filled != 5) {
11037: printf("Should be 5 parameters\n");
1.283 brouard 11038: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11039: }
1.126 brouard 11040: numlinepar++;
1.197 brouard 11041: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11042: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11043: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11044: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11045: }
11046: /* Second parameter line */
11047: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11048: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11049: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11050: if (line[0] == '#') {
11051: numlinepar++;
1.283 brouard 11052: printf("%s",line);
11053: fprintf(ficres,"%s",line);
11054: fprintf(ficparo,"%s",line);
11055: fprintf(ficlog,"%s",line);
1.197 brouard 11056: continue;
11057: }else
11058: break;
11059: }
1.223 brouard 11060: 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", \
11061: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11062: if (num_filled != 11) {
11063: 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 11064: printf("but line=%s\n",line);
1.283 brouard 11065: 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");
11066: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11067: }
1.286 brouard 11068: if( lastpass > maxwav){
11069: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11070: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11071: fflush(ficlog);
11072: goto end;
11073: }
11074: 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 11075: 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 11076: 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 11077: 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 11078: }
1.203 brouard 11079: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11080: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11081: /* Third parameter line */
11082: while(fgets(line, MAXLINE, ficpar)) {
11083: /* If line starts with a # it is a comment */
11084: if (line[0] == '#') {
11085: numlinepar++;
1.283 brouard 11086: printf("%s",line);
11087: fprintf(ficres,"%s",line);
11088: fprintf(ficparo,"%s",line);
11089: fprintf(ficlog,"%s",line);
1.197 brouard 11090: continue;
11091: }else
11092: break;
11093: }
1.201 brouard 11094: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11095: if (num_filled != 1){
11096: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11097: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11098: model[0]='\0';
11099: goto end;
11100: }
11101: else{
11102: if (model[0]=='+'){
11103: for(i=1; i<=strlen(model);i++)
11104: modeltemp[i-1]=model[i];
1.201 brouard 11105: strcpy(model,modeltemp);
1.197 brouard 11106: }
11107: }
1.199 brouard 11108: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11109: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11110: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11111: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11112: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11113: }
11114: /* 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); */
11115: /* numlinepar=numlinepar+3; /\* In general *\/ */
11116: /* 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 11117: /* 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); */
11118: /* 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 11119: fflush(ficlog);
1.190 brouard 11120: /* if(model[0]=='#'|| model[0]== '\0'){ */
11121: if(model[0]=='#'){
1.279 brouard 11122: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11123: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11124: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11125: if(mle != -1){
1.279 brouard 11126: 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 11127: exit(1);
11128: }
11129: }
1.126 brouard 11130: while((c=getc(ficpar))=='#' && c!= EOF){
11131: ungetc(c,ficpar);
11132: fgets(line, MAXLINE, ficpar);
11133: numlinepar++;
1.195 brouard 11134: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11135: z[0]=line[1];
11136: }
11137: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11138: fputs(line, stdout);
11139: //puts(line);
1.126 brouard 11140: fputs(line,ficparo);
11141: fputs(line,ficlog);
11142: }
11143: ungetc(c,ficpar);
11144:
11145:
1.290 brouard 11146: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11147: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11148: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11149: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11150: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11151: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11152: v1+v2*age+v2*v3 makes cptcovn = 3
11153: */
11154: if (strlen(model)>1)
1.187 brouard 11155: 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 11156: else
1.187 brouard 11157: ncovmodel=2; /* Constant and age */
1.133 brouard 11158: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11159: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11160: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11161: 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);
11162: 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);
11163: fflush(stdout);
11164: fclose (ficlog);
11165: goto end;
11166: }
1.126 brouard 11167: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11168: delti=delti3[1][1];
11169: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11170: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11171: /* We could also provide initial parameters values giving by simple logistic regression
11172: * only one way, that is without matrix product. We will have nlstate maximizations */
11173: /* for(i=1;i<nlstate;i++){ */
11174: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11175: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11176: /* } */
1.126 brouard 11177: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11178: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11179: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11180: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11181: fclose (ficparo);
11182: fclose (ficlog);
11183: goto end;
11184: exit(0);
1.220 brouard 11185: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11186: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11187: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11188: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11189: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11190: matcov=matrix(1,npar,1,npar);
1.203 brouard 11191: hess=matrix(1,npar,1,npar);
1.220 brouard 11192: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11193: /* Read guessed parameters */
1.126 brouard 11194: /* Reads comments: lines beginning with '#' */
11195: while((c=getc(ficpar))=='#' && c!= EOF){
11196: ungetc(c,ficpar);
11197: fgets(line, MAXLINE, ficpar);
11198: numlinepar++;
1.141 brouard 11199: fputs(line,stdout);
1.126 brouard 11200: fputs(line,ficparo);
11201: fputs(line,ficlog);
11202: }
11203: ungetc(c,ficpar);
11204:
11205: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11206: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11207: for(i=1; i <=nlstate; i++){
1.234 brouard 11208: j=0;
1.126 brouard 11209: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11210: if(jj==i) continue;
11211: j++;
1.292 ! brouard 11212: while((c=getc(ficpar))=='#' && c!= EOF){
! 11213: ungetc(c,ficpar);
! 11214: fgets(line, MAXLINE, ficpar);
! 11215: numlinepar++;
! 11216: fputs(line,stdout);
! 11217: fputs(line,ficparo);
! 11218: fputs(line,ficlog);
! 11219: }
! 11220: ungetc(c,ficpar);
1.234 brouard 11221: fscanf(ficpar,"%1d%1d",&i1,&j1);
11222: if ((i1 != i) || (j1 != jj)){
11223: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11224: It might be a problem of design; if ncovcol and the model are correct\n \
11225: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11226: exit(1);
11227: }
11228: fprintf(ficparo,"%1d%1d",i1,j1);
11229: if(mle==1)
11230: printf("%1d%1d",i,jj);
11231: fprintf(ficlog,"%1d%1d",i,jj);
11232: for(k=1; k<=ncovmodel;k++){
11233: fscanf(ficpar," %lf",¶m[i][j][k]);
11234: if(mle==1){
11235: printf(" %lf",param[i][j][k]);
11236: fprintf(ficlog," %lf",param[i][j][k]);
11237: }
11238: else
11239: fprintf(ficlog," %lf",param[i][j][k]);
11240: fprintf(ficparo," %lf",param[i][j][k]);
11241: }
11242: fscanf(ficpar,"\n");
11243: numlinepar++;
11244: if(mle==1)
11245: printf("\n");
11246: fprintf(ficlog,"\n");
11247: fprintf(ficparo,"\n");
1.126 brouard 11248: }
11249: }
11250: fflush(ficlog);
1.234 brouard 11251:
1.251 brouard 11252: /* Reads parameters values */
1.126 brouard 11253: p=param[1][1];
1.251 brouard 11254: pstart=paramstart[1][1];
1.126 brouard 11255:
11256: /* Reads comments: lines beginning with '#' */
11257: while((c=getc(ficpar))=='#' && c!= EOF){
11258: ungetc(c,ficpar);
11259: fgets(line, MAXLINE, ficpar);
11260: numlinepar++;
1.141 brouard 11261: fputs(line,stdout);
1.126 brouard 11262: fputs(line,ficparo);
11263: fputs(line,ficlog);
11264: }
11265: ungetc(c,ficpar);
11266:
11267: for(i=1; i <=nlstate; i++){
11268: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11269: fscanf(ficpar,"%1d%1d",&i1,&j1);
11270: if ( (i1-i) * (j1-j) != 0){
11271: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11272: exit(1);
11273: }
11274: printf("%1d%1d",i,j);
11275: fprintf(ficparo,"%1d%1d",i1,j1);
11276: fprintf(ficlog,"%1d%1d",i1,j1);
11277: for(k=1; k<=ncovmodel;k++){
11278: fscanf(ficpar,"%le",&delti3[i][j][k]);
11279: printf(" %le",delti3[i][j][k]);
11280: fprintf(ficparo," %le",delti3[i][j][k]);
11281: fprintf(ficlog," %le",delti3[i][j][k]);
11282: }
11283: fscanf(ficpar,"\n");
11284: numlinepar++;
11285: printf("\n");
11286: fprintf(ficparo,"\n");
11287: fprintf(ficlog,"\n");
1.126 brouard 11288: }
11289: }
11290: fflush(ficlog);
1.234 brouard 11291:
1.145 brouard 11292: /* Reads covariance matrix */
1.126 brouard 11293: delti=delti3[1][1];
1.220 brouard 11294:
11295:
1.126 brouard 11296: /* 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 11297:
1.126 brouard 11298: /* Reads comments: lines beginning with '#' */
11299: while((c=getc(ficpar))=='#' && c!= EOF){
11300: ungetc(c,ficpar);
11301: fgets(line, MAXLINE, ficpar);
11302: numlinepar++;
1.141 brouard 11303: fputs(line,stdout);
1.126 brouard 11304: fputs(line,ficparo);
11305: fputs(line,ficlog);
11306: }
11307: ungetc(c,ficpar);
1.220 brouard 11308:
1.126 brouard 11309: matcov=matrix(1,npar,1,npar);
1.203 brouard 11310: hess=matrix(1,npar,1,npar);
1.131 brouard 11311: for(i=1; i <=npar; i++)
11312: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11313:
1.194 brouard 11314: /* Scans npar lines */
1.126 brouard 11315: for(i=1; i <=npar; i++){
1.226 brouard 11316: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11317: if(count != 3){
1.226 brouard 11318: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11319: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11320: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11321: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11322: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11323: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11324: exit(1);
1.220 brouard 11325: }else{
1.226 brouard 11326: if(mle==1)
11327: printf("%1d%1d%d",i1,j1,jk);
11328: }
11329: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11330: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11331: for(j=1; j <=i; j++){
1.226 brouard 11332: fscanf(ficpar," %le",&matcov[i][j]);
11333: if(mle==1){
11334: printf(" %.5le",matcov[i][j]);
11335: }
11336: fprintf(ficlog," %.5le",matcov[i][j]);
11337: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11338: }
11339: fscanf(ficpar,"\n");
11340: numlinepar++;
11341: if(mle==1)
1.220 brouard 11342: printf("\n");
1.126 brouard 11343: fprintf(ficlog,"\n");
11344: fprintf(ficparo,"\n");
11345: }
1.194 brouard 11346: /* End of read covariance matrix npar lines */
1.126 brouard 11347: for(i=1; i <=npar; i++)
11348: for(j=i+1;j<=npar;j++)
1.226 brouard 11349: matcov[i][j]=matcov[j][i];
1.126 brouard 11350:
11351: if(mle==1)
11352: printf("\n");
11353: fprintf(ficlog,"\n");
11354:
11355: fflush(ficlog);
11356:
11357: } /* End of mle != -3 */
1.218 brouard 11358:
1.186 brouard 11359: /* Main data
11360: */
1.290 brouard 11361: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11362: /* num=lvector(1,n); */
11363: /* moisnais=vector(1,n); */
11364: /* annais=vector(1,n); */
11365: /* moisdc=vector(1,n); */
11366: /* andc=vector(1,n); */
11367: /* weight=vector(1,n); */
11368: /* agedc=vector(1,n); */
11369: /* cod=ivector(1,n); */
11370: /* for(i=1;i<=n;i++){ */
11371: num=lvector(firstobs,lastobs);
11372: moisnais=vector(firstobs,lastobs);
11373: annais=vector(firstobs,lastobs);
11374: moisdc=vector(firstobs,lastobs);
11375: andc=vector(firstobs,lastobs);
11376: weight=vector(firstobs,lastobs);
11377: agedc=vector(firstobs,lastobs);
11378: cod=ivector(firstobs,lastobs);
11379: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11380: num[i]=0;
11381: moisnais[i]=0;
11382: annais[i]=0;
11383: moisdc[i]=0;
11384: andc[i]=0;
11385: agedc[i]=0;
11386: cod[i]=0;
11387: weight[i]=1.0; /* Equal weights, 1 by default */
11388: }
1.290 brouard 11389: mint=matrix(1,maxwav,firstobs,lastobs);
11390: anint=matrix(1,maxwav,firstobs,lastobs);
11391: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11392: tab=ivector(1,NCOVMAX);
1.144 brouard 11393: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11394: 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 11395:
1.136 brouard 11396: /* Reads data from file datafile */
11397: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11398: goto end;
11399:
11400: /* Calculation of the number of parameters from char model */
1.234 brouard 11401: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11402: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11403: k=3 V4 Tvar[k=3]= 4 (from V4)
11404: k=2 V1 Tvar[k=2]= 1 (from V1)
11405: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11406: */
11407:
11408: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11409: TvarsDind=ivector(1,NCOVMAX); /* */
11410: TvarsD=ivector(1,NCOVMAX); /* */
11411: TvarsQind=ivector(1,NCOVMAX); /* */
11412: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11413: TvarF=ivector(1,NCOVMAX); /* */
11414: TvarFind=ivector(1,NCOVMAX); /* */
11415: TvarV=ivector(1,NCOVMAX); /* */
11416: TvarVind=ivector(1,NCOVMAX); /* */
11417: TvarA=ivector(1,NCOVMAX); /* */
11418: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11419: TvarFD=ivector(1,NCOVMAX); /* */
11420: TvarFDind=ivector(1,NCOVMAX); /* */
11421: TvarFQ=ivector(1,NCOVMAX); /* */
11422: TvarFQind=ivector(1,NCOVMAX); /* */
11423: TvarVD=ivector(1,NCOVMAX); /* */
11424: TvarVDind=ivector(1,NCOVMAX); /* */
11425: TvarVQ=ivector(1,NCOVMAX); /* */
11426: TvarVQind=ivector(1,NCOVMAX); /* */
11427:
1.230 brouard 11428: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11429: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11430: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11431: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11432: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11433: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11434: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11435: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11436: */
11437: /* For model-covariate k tells which data-covariate to use but
11438: because this model-covariate is a construction we invent a new column
11439: ncovcol + k1
11440: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11441: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11442: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11443: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11444: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11445: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11446: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11447: */
1.145 brouard 11448: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11449: 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 11450: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11451: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11452: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11453: 4 covariates (3 plus signs)
11454: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11455: */
1.230 brouard 11456: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11457: * individual dummy, fixed or varying:
11458: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11459: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11460: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11461: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11462: * Tmodelind[1]@9={9,0,3,2,}*/
11463: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11464: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11465: * individual quantitative, fixed or varying:
11466: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11467: * 3, 1, 0, 0, 0, 0, 0, 0},
11468: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11469: /* Main decodemodel */
11470:
1.187 brouard 11471:
1.223 brouard 11472: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11473: goto end;
11474:
1.137 brouard 11475: if((double)(lastobs-imx)/(double)imx > 1.10){
11476: nbwarn++;
11477: 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);
11478: 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);
11479: }
1.136 brouard 11480: /* if(mle==1){*/
1.137 brouard 11481: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11482: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11483: }
11484:
11485: /*-calculation of age at interview from date of interview and age at death -*/
11486: agev=matrix(1,maxwav,1,imx);
11487:
11488: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11489: goto end;
11490:
1.126 brouard 11491:
1.136 brouard 11492: agegomp=(int)agemin;
1.290 brouard 11493: free_vector(moisnais,firstobs,lastobs);
11494: free_vector(annais,firstobs,lastobs);
1.126 brouard 11495: /* free_matrix(mint,1,maxwav,1,n);
11496: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11497: /* free_vector(moisdc,1,n); */
11498: /* free_vector(andc,1,n); */
1.145 brouard 11499: /* */
11500:
1.126 brouard 11501: wav=ivector(1,imx);
1.214 brouard 11502: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11503: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11504: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11505: 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.*/
11506: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11507: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11508:
11509: /* Concatenates waves */
1.214 brouard 11510: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11511: Death is a valid wave (if date is known).
11512: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11513: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11514: and mw[mi+1][i]. dh depends on stepm.
11515: */
11516:
1.126 brouard 11517: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11518: /* Concatenates waves */
1.145 brouard 11519:
1.290 brouard 11520: free_vector(moisdc,firstobs,lastobs);
11521: free_vector(andc,firstobs,lastobs);
1.215 brouard 11522:
1.126 brouard 11523: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11524: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11525: ncodemax[1]=1;
1.145 brouard 11526: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11527: cptcoveff=0;
1.220 brouard 11528: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11529: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11530: }
11531:
11532: ncovcombmax=pow(2,cptcoveff);
11533: invalidvarcomb=ivector(1, ncovcombmax);
11534: for(i=1;i<ncovcombmax;i++)
11535: invalidvarcomb[i]=0;
11536:
1.211 brouard 11537: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11538: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11539: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11540:
1.200 brouard 11541: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11542: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11543: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11544: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11545: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11546: * (currently 0 or 1) in the data.
11547: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11548: * corresponding modality (h,j).
11549: */
11550:
1.145 brouard 11551: h=0;
11552: /*if (cptcovn > 0) */
1.126 brouard 11553: m=pow(2,cptcoveff);
11554:
1.144 brouard 11555: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11556: * For k=4 covariates, h goes from 1 to m=2**k
11557: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11558: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11559: * h\k 1 2 3 4
1.143 brouard 11560: *______________________________
11561: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11562: * 2 2 1 1 1
11563: * 3 i=2 1 2 1 1
11564: * 4 2 2 1 1
11565: * 5 i=3 1 i=2 1 2 1
11566: * 6 2 1 2 1
11567: * 7 i=4 1 2 2 1
11568: * 8 2 2 2 1
1.197 brouard 11569: * 9 i=5 1 i=3 1 i=2 1 2
11570: * 10 2 1 1 2
11571: * 11 i=6 1 2 1 2
11572: * 12 2 2 1 2
11573: * 13 i=7 1 i=4 1 2 2
11574: * 14 2 1 2 2
11575: * 15 i=8 1 2 2 2
11576: * 16 2 2 2 2
1.143 brouard 11577: */
1.212 brouard 11578: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11579: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11580: * and the value of each covariate?
11581: * V1=1, V2=1, V3=2, V4=1 ?
11582: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11583: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11584: * In order to get the real value in the data, we use nbcode
11585: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11586: * We are keeping this crazy system in order to be able (in the future?)
11587: * to have more than 2 values (0 or 1) for a covariate.
11588: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11589: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11590: * bbbbbbbb
11591: * 76543210
11592: * h-1 00000101 (6-1=5)
1.219 brouard 11593: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11594: * &
11595: * 1 00000001 (1)
1.219 brouard 11596: * 00000000 = 1 & ((h-1) >> (k-1))
11597: * +1= 00000001 =1
1.211 brouard 11598: *
11599: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11600: * h' 1101 =2^3+2^2+0x2^1+2^0
11601: * >>k' 11
11602: * & 00000001
11603: * = 00000001
11604: * +1 = 00000010=2 = codtabm(14,3)
11605: * Reverse h=6 and m=16?
11606: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11607: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11608: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11609: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11610: * V3=decodtabm(14,3,2**4)=2
11611: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11612: *(h-1) >> (j-1) 0011 =13 >> 2
11613: * &1 000000001
11614: * = 000000001
11615: * +1= 000000010 =2
11616: * 2211
11617: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11618: * V3=2
1.220 brouard 11619: * codtabm and decodtabm are identical
1.211 brouard 11620: */
11621:
1.145 brouard 11622:
11623: free_ivector(Ndum,-1,NCOVMAX);
11624:
11625:
1.126 brouard 11626:
1.186 brouard 11627: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11628: strcpy(optionfilegnuplot,optionfilefiname);
11629: if(mle==-3)
1.201 brouard 11630: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11631: strcat(optionfilegnuplot,".gp");
11632:
11633: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11634: printf("Problem with file %s",optionfilegnuplot);
11635: }
11636: else{
1.204 brouard 11637: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11638: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11639: //fprintf(ficgp,"set missing 'NaNq'\n");
11640: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11641: }
11642: /* fclose(ficgp);*/
1.186 brouard 11643:
11644:
11645: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11646:
11647: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11648: if(mle==-3)
1.201 brouard 11649: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11650: strcat(optionfilehtm,".htm");
11651: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11652: printf("Problem with %s \n",optionfilehtm);
11653: exit(0);
1.126 brouard 11654: }
11655:
11656: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11657: strcat(optionfilehtmcov,"-cov.htm");
11658: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11659: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11660: }
11661: else{
11662: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11663: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11664: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11665: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11666: }
11667:
1.213 brouard 11668: 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 11669: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11670: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11671: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11672: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11673: \n\
11674: <hr size=\"2\" color=\"#EC5E5E\">\
11675: <ul><li><h4>Parameter files</h4>\n\
11676: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11677: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11678: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11679: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11680: - Date and time at start: %s</ul>\n",\
11681: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11682: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11683: fileres,fileres,\
11684: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11685: fflush(fichtm);
11686:
11687: strcpy(pathr,path);
11688: strcat(pathr,optionfilefiname);
1.184 brouard 11689: #ifdef WIN32
11690: _chdir(optionfilefiname); /* Move to directory named optionfile */
11691: #else
1.126 brouard 11692: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11693: #endif
11694:
1.126 brouard 11695:
1.220 brouard 11696: /* Calculates basic frequencies. Computes observed prevalence at single age
11697: and for any valid combination of covariates
1.126 brouard 11698: and prints on file fileres'p'. */
1.251 brouard 11699: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11700: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11701:
11702: fprintf(fichtm,"\n");
1.286 brouard 11703: 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 11704: ftol, stepm);
11705: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11706: ncurrv=1;
11707: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11708: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11709: ncurrv=i;
11710: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11711: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 11712: ncurrv=i;
11713: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11714: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 11715: ncurrv=i;
11716: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11717: 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", \
11718: nlstate, ndeath, maxwav, mle, weightopt);
11719:
11720: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11721: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11722:
11723:
11724: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11725: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11726: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11727: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11728: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11729: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11730: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11731: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11732: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11733:
1.126 brouard 11734: /* For Powell, parameters are in a vector p[] starting at p[1]
11735: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11736: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11737:
11738: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11739: /* For mortality only */
1.126 brouard 11740: if (mle==-3){
1.136 brouard 11741: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11742: for(i=1;i<=NDIM;i++)
11743: for(j=1;j<=NDIM;j++)
11744: ximort[i][j]=0.;
1.186 brouard 11745: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 11746: cens=ivector(firstobs,lastobs);
11747: ageexmed=vector(firstobs,lastobs);
11748: agecens=vector(firstobs,lastobs);
11749: dcwave=ivector(firstobs,lastobs);
1.223 brouard 11750:
1.126 brouard 11751: for (i=1; i<=imx; i++){
11752: dcwave[i]=-1;
11753: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11754: if (s[m][i]>nlstate) {
11755: dcwave[i]=m;
11756: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11757: break;
11758: }
1.126 brouard 11759: }
1.226 brouard 11760:
1.126 brouard 11761: for (i=1; i<=imx; i++) {
11762: if (wav[i]>0){
1.226 brouard 11763: ageexmed[i]=agev[mw[1][i]][i];
11764: j=wav[i];
11765: agecens[i]=1.;
11766:
11767: if (ageexmed[i]> 1 && wav[i] > 0){
11768: agecens[i]=agev[mw[j][i]][i];
11769: cens[i]= 1;
11770: }else if (ageexmed[i]< 1)
11771: cens[i]= -1;
11772: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11773: cens[i]=0 ;
1.126 brouard 11774: }
11775: else cens[i]=-1;
11776: }
11777:
11778: for (i=1;i<=NDIM;i++) {
11779: for (j=1;j<=NDIM;j++)
1.226 brouard 11780: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11781: }
11782:
1.145 brouard 11783: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11784: /*printf("%lf %lf", p[1], p[2]);*/
11785:
11786:
1.136 brouard 11787: #ifdef GSL
11788: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11789: #else
1.126 brouard 11790: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11791: #endif
1.201 brouard 11792: strcpy(filerespow,"POW-MORT_");
11793: strcat(filerespow,fileresu);
1.126 brouard 11794: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11795: printf("Problem with resultfile: %s\n", filerespow);
11796: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11797: }
1.136 brouard 11798: #ifdef GSL
11799: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11800: #else
1.126 brouard 11801: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11802: #endif
1.126 brouard 11803: /* for (i=1;i<=nlstate;i++)
11804: for(j=1;j<=nlstate+ndeath;j++)
11805: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11806: */
11807: fprintf(ficrespow,"\n");
1.136 brouard 11808: #ifdef GSL
11809: /* gsl starts here */
11810: T = gsl_multimin_fminimizer_nmsimplex;
11811: gsl_multimin_fminimizer *sfm = NULL;
11812: gsl_vector *ss, *x;
11813: gsl_multimin_function minex_func;
11814:
11815: /* Initial vertex size vector */
11816: ss = gsl_vector_alloc (NDIM);
11817:
11818: if (ss == NULL){
11819: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11820: }
11821: /* Set all step sizes to 1 */
11822: gsl_vector_set_all (ss, 0.001);
11823:
11824: /* Starting point */
1.126 brouard 11825:
1.136 brouard 11826: x = gsl_vector_alloc (NDIM);
11827:
11828: if (x == NULL){
11829: gsl_vector_free(ss);
11830: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11831: }
11832:
11833: /* Initialize method and iterate */
11834: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11835: /* gsl_vector_set(x, 0, 0.0268); */
11836: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11837: gsl_vector_set(x, 0, p[1]);
11838: gsl_vector_set(x, 1, p[2]);
11839:
11840: minex_func.f = &gompertz_f;
11841: minex_func.n = NDIM;
11842: minex_func.params = (void *)&p; /* ??? */
11843:
11844: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11845: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11846:
11847: printf("Iterations beginning .....\n\n");
11848: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11849:
11850: iteri=0;
11851: while (rval == GSL_CONTINUE){
11852: iteri++;
11853: status = gsl_multimin_fminimizer_iterate(sfm);
11854:
11855: if (status) printf("error: %s\n", gsl_strerror (status));
11856: fflush(0);
11857:
11858: if (status)
11859: break;
11860:
11861: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11862: ssval = gsl_multimin_fminimizer_size (sfm);
11863:
11864: if (rval == GSL_SUCCESS)
11865: printf ("converged to a local maximum at\n");
11866:
11867: printf("%5d ", iteri);
11868: for (it = 0; it < NDIM; it++){
11869: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11870: }
11871: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11872: }
11873:
11874: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11875:
11876: gsl_vector_free(x); /* initial values */
11877: gsl_vector_free(ss); /* inital step size */
11878: for (it=0; it<NDIM; it++){
11879: p[it+1]=gsl_vector_get(sfm->x,it);
11880: fprintf(ficrespow," %.12lf", p[it]);
11881: }
11882: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11883: #endif
11884: #ifdef POWELL
11885: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11886: #endif
1.126 brouard 11887: fclose(ficrespow);
11888:
1.203 brouard 11889: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11890:
11891: for(i=1; i <=NDIM; i++)
11892: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11893: matcov[i][j]=matcov[j][i];
1.126 brouard 11894:
11895: printf("\nCovariance matrix\n ");
1.203 brouard 11896: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11897: for(i=1; i <=NDIM; i++) {
11898: for(j=1;j<=NDIM;j++){
1.220 brouard 11899: printf("%f ",matcov[i][j]);
11900: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11901: }
1.203 brouard 11902: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11903: }
11904:
11905: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11906: for (i=1;i<=NDIM;i++) {
1.126 brouard 11907: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11908: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11909: }
1.126 brouard 11910: lsurv=vector(1,AGESUP);
11911: lpop=vector(1,AGESUP);
11912: tpop=vector(1,AGESUP);
11913: lsurv[agegomp]=100000;
11914:
11915: for (k=agegomp;k<=AGESUP;k++) {
11916: agemortsup=k;
11917: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11918: }
11919:
11920: for (k=agegomp;k<agemortsup;k++)
11921: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11922:
11923: for (k=agegomp;k<agemortsup;k++){
11924: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11925: sumlpop=sumlpop+lpop[k];
11926: }
11927:
11928: tpop[agegomp]=sumlpop;
11929: for (k=agegomp;k<(agemortsup-3);k++){
11930: /* tpop[k+1]=2;*/
11931: tpop[k+1]=tpop[k]-lpop[k];
11932: }
11933:
11934:
11935: printf("\nAge lx qx dx Lx Tx e(x)\n");
11936: for (k=agegomp;k<(agemortsup-2);k++)
11937: 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]);
11938:
11939:
11940: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11941: ageminpar=50;
11942: agemaxpar=100;
1.194 brouard 11943: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11944: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11945: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11946: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11947: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11948: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11949: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11950: }else{
11951: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11952: 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 11953: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11954: }
1.201 brouard 11955: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11956: stepm, weightopt,\
11957: model,imx,p,matcov,agemortsup);
11958:
11959: free_vector(lsurv,1,AGESUP);
11960: free_vector(lpop,1,AGESUP);
11961: free_vector(tpop,1,AGESUP);
1.220 brouard 11962: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 11963: free_ivector(dcwave,firstobs,lastobs);
11964: free_vector(agecens,firstobs,lastobs);
11965: free_vector(ageexmed,firstobs,lastobs);
11966: free_ivector(cens,firstobs,lastobs);
1.220 brouard 11967: #ifdef GSL
1.136 brouard 11968: #endif
1.186 brouard 11969: } /* Endof if mle==-3 mortality only */
1.205 brouard 11970: /* Standard */
11971: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11972: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11973: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11974: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11975: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11976: for (k=1; k<=npar;k++)
11977: printf(" %d %8.5f",k,p[k]);
11978: printf("\n");
1.205 brouard 11979: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11980: /* mlikeli uses func not funcone */
1.247 brouard 11981: /* for(i=1;i<nlstate;i++){ */
11982: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11983: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11984: /* } */
1.205 brouard 11985: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11986: }
11987: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11988: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11989: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11990: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11991: }
11992: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11993: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11994: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11995: for (k=1; k<=npar;k++)
11996: printf(" %d %8.5f",k,p[k]);
11997: printf("\n");
11998:
11999: /*--------- results files --------------*/
1.283 brouard 12000: /* 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 12001:
12002:
12003: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12004: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12005: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12006: for(i=1,jk=1; i <=nlstate; i++){
12007: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12008: if (k != i) {
12009: printf("%d%d ",i,k);
12010: fprintf(ficlog,"%d%d ",i,k);
12011: fprintf(ficres,"%1d%1d ",i,k);
12012: for(j=1; j <=ncovmodel; j++){
12013: printf("%12.7f ",p[jk]);
12014: fprintf(ficlog,"%12.7f ",p[jk]);
12015: fprintf(ficres,"%12.7f ",p[jk]);
12016: jk++;
12017: }
12018: printf("\n");
12019: fprintf(ficlog,"\n");
12020: fprintf(ficres,"\n");
12021: }
1.126 brouard 12022: }
12023: }
1.203 brouard 12024: if(mle != 0){
12025: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12026: ftolhess=ftol; /* Usually correct */
1.203 brouard 12027: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12028: 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");
12029: 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");
12030: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12031: for(k=1; k <=(nlstate+ndeath); k++){
12032: if (k != i) {
12033: printf("%d%d ",i,k);
12034: fprintf(ficlog,"%d%d ",i,k);
12035: for(j=1; j <=ncovmodel; j++){
12036: 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]));
12037: 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]));
12038: jk++;
12039: }
12040: printf("\n");
12041: fprintf(ficlog,"\n");
12042: }
12043: }
1.193 brouard 12044: }
1.203 brouard 12045: } /* end of hesscov and Wald tests */
1.225 brouard 12046:
1.203 brouard 12047: /* */
1.126 brouard 12048: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12049: printf("# Scales (for hessian or gradient estimation)\n");
12050: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12051: for(i=1,jk=1; i <=nlstate; i++){
12052: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12053: if (j!=i) {
12054: fprintf(ficres,"%1d%1d",i,j);
12055: printf("%1d%1d",i,j);
12056: fprintf(ficlog,"%1d%1d",i,j);
12057: for(k=1; k<=ncovmodel;k++){
12058: printf(" %.5e",delti[jk]);
12059: fprintf(ficlog," %.5e",delti[jk]);
12060: fprintf(ficres," %.5e",delti[jk]);
12061: jk++;
12062: }
12063: printf("\n");
12064: fprintf(ficlog,"\n");
12065: fprintf(ficres,"\n");
12066: }
1.126 brouard 12067: }
12068: }
12069:
12070: 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 12071: if(mle >= 1) /* To big for the screen */
1.126 brouard 12072: 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");
12073: 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");
12074: /* # 121 Var(a12)\n\ */
12075: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12076: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12077: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12078: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12079: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12080: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12081: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12082:
12083:
12084: /* Just to have a covariance matrix which will be more understandable
12085: even is we still don't want to manage dictionary of variables
12086: */
12087: for(itimes=1;itimes<=2;itimes++){
12088: jj=0;
12089: for(i=1; i <=nlstate; i++){
1.225 brouard 12090: for(j=1; j <=nlstate+ndeath; j++){
12091: if(j==i) continue;
12092: for(k=1; k<=ncovmodel;k++){
12093: jj++;
12094: ca[0]= k+'a'-1;ca[1]='\0';
12095: if(itimes==1){
12096: if(mle>=1)
12097: printf("#%1d%1d%d",i,j,k);
12098: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12099: fprintf(ficres,"#%1d%1d%d",i,j,k);
12100: }else{
12101: if(mle>=1)
12102: printf("%1d%1d%d",i,j,k);
12103: fprintf(ficlog,"%1d%1d%d",i,j,k);
12104: fprintf(ficres,"%1d%1d%d",i,j,k);
12105: }
12106: ll=0;
12107: for(li=1;li <=nlstate; li++){
12108: for(lj=1;lj <=nlstate+ndeath; lj++){
12109: if(lj==li) continue;
12110: for(lk=1;lk<=ncovmodel;lk++){
12111: ll++;
12112: if(ll<=jj){
12113: cb[0]= lk +'a'-1;cb[1]='\0';
12114: if(ll<jj){
12115: if(itimes==1){
12116: if(mle>=1)
12117: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12118: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12119: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12120: }else{
12121: if(mle>=1)
12122: printf(" %.5e",matcov[jj][ll]);
12123: fprintf(ficlog," %.5e",matcov[jj][ll]);
12124: fprintf(ficres," %.5e",matcov[jj][ll]);
12125: }
12126: }else{
12127: if(itimes==1){
12128: if(mle>=1)
12129: printf(" Var(%s%1d%1d)",ca,i,j);
12130: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12131: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12132: }else{
12133: if(mle>=1)
12134: printf(" %.7e",matcov[jj][ll]);
12135: fprintf(ficlog," %.7e",matcov[jj][ll]);
12136: fprintf(ficres," %.7e",matcov[jj][ll]);
12137: }
12138: }
12139: }
12140: } /* end lk */
12141: } /* end lj */
12142: } /* end li */
12143: if(mle>=1)
12144: printf("\n");
12145: fprintf(ficlog,"\n");
12146: fprintf(ficres,"\n");
12147: numlinepar++;
12148: } /* end k*/
12149: } /*end j */
1.126 brouard 12150: } /* end i */
12151: } /* end itimes */
12152:
12153: fflush(ficlog);
12154: fflush(ficres);
1.225 brouard 12155: while(fgets(line, MAXLINE, ficpar)) {
12156: /* If line starts with a # it is a comment */
12157: if (line[0] == '#') {
12158: numlinepar++;
12159: fputs(line,stdout);
12160: fputs(line,ficparo);
12161: fputs(line,ficlog);
12162: continue;
12163: }else
12164: break;
12165: }
12166:
1.209 brouard 12167: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12168: /* ungetc(c,ficpar); */
12169: /* fgets(line, MAXLINE, ficpar); */
12170: /* fputs(line,stdout); */
12171: /* fputs(line,ficparo); */
12172: /* } */
12173: /* ungetc(c,ficpar); */
1.126 brouard 12174:
12175: estepm=0;
1.209 brouard 12176: 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 12177:
12178: if (num_filled != 6) {
12179: 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);
12180: 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);
12181: goto end;
12182: }
12183: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12184: }
12185: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12186: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12187:
1.209 brouard 12188: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12189: if (estepm==0 || estepm < stepm) estepm=stepm;
12190: if (fage <= 2) {
12191: bage = ageminpar;
12192: fage = agemaxpar;
12193: }
12194:
12195: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12196: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12197: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12198:
1.186 brouard 12199: /* Other stuffs, more or less useful */
1.254 brouard 12200: while(fgets(line, MAXLINE, ficpar)) {
12201: /* If line starts with a # it is a comment */
12202: if (line[0] == '#') {
12203: numlinepar++;
12204: fputs(line,stdout);
12205: fputs(line,ficparo);
12206: fputs(line,ficlog);
12207: continue;
12208: }else
12209: break;
12210: }
12211:
12212: 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){
12213:
12214: if (num_filled != 7) {
12215: 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);
12216: 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);
12217: goto end;
12218: }
12219: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12220: 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);
12221: 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);
12222: 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 12223: }
1.254 brouard 12224:
12225: while(fgets(line, MAXLINE, ficpar)) {
12226: /* If line starts with a # it is a comment */
12227: if (line[0] == '#') {
12228: numlinepar++;
12229: fputs(line,stdout);
12230: fputs(line,ficparo);
12231: fputs(line,ficlog);
12232: continue;
12233: }else
12234: break;
1.126 brouard 12235: }
12236:
12237:
12238: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12239: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12240:
1.254 brouard 12241: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12242: if (num_filled != 1) {
12243: 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);
12244: 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);
12245: goto end;
12246: }
12247: printf("pop_based=%d\n",popbased);
12248: fprintf(ficlog,"pop_based=%d\n",popbased);
12249: fprintf(ficparo,"pop_based=%d\n",popbased);
12250: fprintf(ficres,"pop_based=%d\n",popbased);
12251: }
12252:
1.258 brouard 12253: /* Results */
12254: nresult=0;
12255: do{
12256: if(!fgets(line, MAXLINE, ficpar)){
12257: endishere=1;
12258: parameterline=14;
12259: }else if (line[0] == '#') {
12260: /* If line starts with a # it is a comment */
1.254 brouard 12261: numlinepar++;
12262: fputs(line,stdout);
12263: fputs(line,ficparo);
12264: fputs(line,ficlog);
12265: continue;
1.258 brouard 12266: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12267: parameterline=11;
12268: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12269: parameterline=12;
12270: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12271: parameterline=13;
12272: else{
12273: parameterline=14;
1.254 brouard 12274: }
1.258 brouard 12275: switch (parameterline){
12276: case 11:
12277: 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){
12278: if (num_filled != 8) {
12279: 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);
12280: 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);
12281: goto end;
12282: }
12283: 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);
12284: 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);
12285: 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);
12286: 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);
12287: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12288: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12289: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
12290:
1.258 brouard 12291: }
1.254 brouard 12292: break;
1.258 brouard 12293: case 12:
12294: /*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);*/
12295: 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){
12296: if (num_filled != 8) {
1.262 brouard 12297: 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);
12298: 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 12299: goto end;
12300: }
12301: 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);
12302: 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);
12303: 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);
12304: 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);
12305: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12306: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12307: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.258 brouard 12308: }
1.230 brouard 12309: break;
1.258 brouard 12310: case 13:
12311: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12312: if (num_filled == 0){
12313: resultline[0]='\0';
12314: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12315: 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);
12316: break;
12317: } else if (num_filled != 1){
12318: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12319: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12320: }
12321: nresult++; /* Sum of resultlines */
12322: printf("Result %d: result=%s\n",nresult, resultline);
12323: if(nresult > MAXRESULTLINES){
12324: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12325: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12326: goto end;
12327: }
12328: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12329: fprintf(ficparo,"result: %s\n",resultline);
12330: fprintf(ficres,"result: %s\n",resultline);
12331: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12332: break;
1.258 brouard 12333: case 14:
1.259 brouard 12334: if(ncovmodel >2 && nresult==0 ){
12335: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12336: goto end;
12337: }
1.259 brouard 12338: break;
1.258 brouard 12339: default:
12340: nresult=1;
12341: decoderesult(".",nresult ); /* No covariate */
12342: }
12343: } /* End switch parameterline */
12344: }while(endishere==0); /* End do */
1.126 brouard 12345:
1.230 brouard 12346: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12347: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12348:
12349: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12350: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12351: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12352: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12353: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12354: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12355: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12356: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12357: }else{
1.270 brouard 12358: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12359: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12360: }
12361: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12362: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.273 brouard 12363: jprev1,mprev1,anprev1,dateprev1, dateproj1, dateback1,jprev2,mprev2,anprev2,dateprev2,dateproj2, dateback2);
1.220 brouard 12364:
1.225 brouard 12365: /*------------ free_vector -------------*/
12366: /* chdir(path); */
1.220 brouard 12367:
1.215 brouard 12368: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12369: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12370: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12371: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12372: free_lvector(num,firstobs,lastobs);
12373: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12374: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12375: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12376: fclose(ficparo);
12377: fclose(ficres);
1.220 brouard 12378:
12379:
1.186 brouard 12380: /* Other results (useful)*/
1.220 brouard 12381:
12382:
1.126 brouard 12383: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12384: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12385: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12386: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12387: fclose(ficrespl);
12388:
12389: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12390: /*#include "hpijx.h"*/
12391: hPijx(p, bage, fage);
1.145 brouard 12392: fclose(ficrespij);
1.227 brouard 12393:
1.220 brouard 12394: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12395: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12396: k=1;
1.126 brouard 12397: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12398:
1.269 brouard 12399: /* Prevalence for each covariate combination in probs[age][status][cov] */
12400: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12401: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12402: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12403: for(k=1;k<=ncovcombmax;k++)
12404: probs[i][j][k]=0.;
1.269 brouard 12405: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12406: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12407: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12408: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12409: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12410: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12411: for(k=1;k<=ncovcombmax;k++)
12412: mobaverages[i][j][k]=0.;
1.219 brouard 12413: mobaverage=mobaverages;
12414: if (mobilav!=0) {
1.235 brouard 12415: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12416: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12417: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12418: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12419: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12420: }
1.269 brouard 12421: } else if (mobilavproj !=0) {
1.235 brouard 12422: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12423: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12424: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12425: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12426: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12427: }
1.269 brouard 12428: }else{
12429: printf("Internal error moving average\n");
12430: fflush(stdout);
12431: exit(1);
1.219 brouard 12432: }
12433: }/* end if moving average */
1.227 brouard 12434:
1.126 brouard 12435: /*---------- Forecasting ------------------*/
12436: if(prevfcast==1){
12437: /* if(stepm ==1){*/
1.269 brouard 12438: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12439: }
1.269 brouard 12440:
12441: /* Backcasting */
1.217 brouard 12442: if(backcast==1){
1.219 brouard 12443: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12444: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12445: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12446:
12447: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12448:
12449: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12450:
1.219 brouard 12451: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12452: fclose(ficresplb);
12453:
1.222 brouard 12454: hBijx(p, bage, fage, mobaverage);
12455: fclose(ficrespijb);
1.219 brouard 12456:
1.269 brouard 12457: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12458: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12459: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12460:
12461:
1.269 brouard 12462: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12463: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12464: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12465: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12466: } /* end Backcasting */
1.268 brouard 12467:
1.186 brouard 12468:
12469: /* ------ Other prevalence ratios------------ */
1.126 brouard 12470:
1.215 brouard 12471: free_ivector(wav,1,imx);
12472: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12473: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12474: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12475:
12476:
1.127 brouard 12477: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12478:
1.201 brouard 12479: strcpy(filerese,"E_");
12480: strcat(filerese,fileresu);
1.126 brouard 12481: if((ficreseij=fopen(filerese,"w"))==NULL) {
12482: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12483: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12484: }
1.208 brouard 12485: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12486: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12487:
12488: pstamp(ficreseij);
1.219 brouard 12489:
1.235 brouard 12490: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12491: if (cptcovn < 1){i1=1;}
12492:
12493: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12494: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12495: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12496: continue;
1.219 brouard 12497: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12498: printf("\n#****** ");
1.225 brouard 12499: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12500: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12501: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12502: }
12503: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12504: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12505: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12506: }
12507: fprintf(ficreseij,"******\n");
1.235 brouard 12508: printf("******\n");
1.219 brouard 12509:
12510: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12511: oldm=oldms;savm=savms;
1.235 brouard 12512: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12513:
1.219 brouard 12514: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12515: }
12516: fclose(ficreseij);
1.208 brouard 12517: printf("done evsij\n");fflush(stdout);
12518: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12519:
1.218 brouard 12520:
1.227 brouard 12521: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12522:
1.201 brouard 12523: strcpy(filerest,"T_");
12524: strcat(filerest,fileresu);
1.127 brouard 12525: if((ficrest=fopen(filerest,"w"))==NULL) {
12526: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12527: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12528: }
1.208 brouard 12529: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12530: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12531: strcpy(fileresstde,"STDE_");
12532: strcat(fileresstde,fileresu);
1.126 brouard 12533: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12534: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12535: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12536: }
1.227 brouard 12537: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12538: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12539:
1.201 brouard 12540: strcpy(filerescve,"CVE_");
12541: strcat(filerescve,fileresu);
1.126 brouard 12542: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12543: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12544: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12545: }
1.227 brouard 12546: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12547: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12548:
1.201 brouard 12549: strcpy(fileresv,"V_");
12550: strcat(fileresv,fileresu);
1.126 brouard 12551: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12552: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12553: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12554: }
1.227 brouard 12555: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12556: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12557:
1.235 brouard 12558: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12559: if (cptcovn < 1){i1=1;}
12560:
12561: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12562: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12563: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12564: continue;
1.242 brouard 12565: printf("\n#****** Result for:");
12566: fprintf(ficrest,"\n#****** Result for:");
12567: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12568: for(j=1;j<=cptcoveff;j++){
12569: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12570: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12571: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12572: }
1.235 brouard 12573: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12574: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12575: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12576: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12577: }
1.208 brouard 12578: fprintf(ficrest,"******\n");
1.227 brouard 12579: fprintf(ficlog,"******\n");
12580: printf("******\n");
1.208 brouard 12581:
12582: fprintf(ficresstdeij,"\n#****** ");
12583: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12584: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12585: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12586: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12587: }
1.235 brouard 12588: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12589: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12590: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12591: }
1.208 brouard 12592: fprintf(ficresstdeij,"******\n");
12593: fprintf(ficrescveij,"******\n");
12594:
12595: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12596: /* pstamp(ficresvij); */
1.225 brouard 12597: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12598: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12599: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12600: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12601: }
1.208 brouard 12602: fprintf(ficresvij,"******\n");
12603:
12604: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12605: oldm=oldms;savm=savms;
1.235 brouard 12606: printf(" cvevsij ");
12607: fprintf(ficlog, " cvevsij ");
12608: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12609: printf(" end cvevsij \n ");
12610: fprintf(ficlog, " end cvevsij \n ");
12611:
12612: /*
12613: */
12614: /* goto endfree; */
12615:
12616: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12617: pstamp(ficrest);
12618:
1.269 brouard 12619: epj=vector(1,nlstate+1);
1.208 brouard 12620: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12621: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12622: cptcod= 0; /* To be deleted */
12623: printf("varevsij vpopbased=%d \n",vpopbased);
12624: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12625: 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 12626: 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 ");
12627: if(vpopbased==1)
12628: 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);
12629: else
1.288 brouard 12630: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12631: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12632: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12633: fprintf(ficrest,"\n");
12634: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 12635: printf("Computing age specific forward period (stable) prevalences in each health state \n");
12636: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12637: for(age=bage; age <=fage ;age++){
1.235 brouard 12638: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12639: if (vpopbased==1) {
12640: if(mobilav ==0){
12641: for(i=1; i<=nlstate;i++)
12642: prlim[i][i]=probs[(int)age][i][k];
12643: }else{ /* mobilav */
12644: for(i=1; i<=nlstate;i++)
12645: prlim[i][i]=mobaverage[(int)age][i][k];
12646: }
12647: }
1.219 brouard 12648:
1.227 brouard 12649: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12650: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12651: /* printf(" age %4.0f ",age); */
12652: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12653: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12654: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12655: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12656: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12657: }
12658: epj[nlstate+1] +=epj[j];
12659: }
12660: /* printf(" age %4.0f \n",age); */
1.219 brouard 12661:
1.227 brouard 12662: for(i=1, vepp=0.;i <=nlstate;i++)
12663: for(j=1;j <=nlstate;j++)
12664: vepp += vareij[i][j][(int)age];
12665: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12666: for(j=1;j <=nlstate;j++){
12667: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12668: }
12669: fprintf(ficrest,"\n");
12670: }
1.208 brouard 12671: } /* End vpopbased */
1.269 brouard 12672: free_vector(epj,1,nlstate+1);
1.208 brouard 12673: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12674: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12675: printf("done selection\n");fflush(stdout);
12676: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12677:
1.235 brouard 12678: } /* End k selection */
1.227 brouard 12679:
12680: printf("done State-specific expectancies\n");fflush(stdout);
12681: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12682:
1.288 brouard 12683: /* variance-covariance of forward period prevalence*/
1.269 brouard 12684: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12685:
1.227 brouard 12686:
1.290 brouard 12687: free_vector(weight,firstobs,lastobs);
1.227 brouard 12688: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 12689: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
12690: free_matrix(anint,1,maxwav,firstobs,lastobs);
12691: free_matrix(mint,1,maxwav,firstobs,lastobs);
12692: free_ivector(cod,firstobs,lastobs);
1.227 brouard 12693: free_ivector(tab,1,NCOVMAX);
12694: fclose(ficresstdeij);
12695: fclose(ficrescveij);
12696: fclose(ficresvij);
12697: fclose(ficrest);
12698: fclose(ficpar);
12699:
12700:
1.126 brouard 12701: /*---------- End : free ----------------*/
1.219 brouard 12702: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12703: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12704: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12705: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12706: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12707: } /* mle==-3 arrives here for freeing */
1.227 brouard 12708: /* endfree:*/
12709: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12710: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12711: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 12712: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
12713: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
12714: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
12715: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 12716: free_matrix(matcov,1,npar,1,npar);
12717: free_matrix(hess,1,npar,1,npar);
12718: /*free_vector(delti,1,npar);*/
12719: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12720: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12721: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12722: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12723:
12724: free_ivector(ncodemax,1,NCOVMAX);
12725: free_ivector(ncodemaxwundef,1,NCOVMAX);
12726: free_ivector(Dummy,-1,NCOVMAX);
12727: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12728: free_ivector(DummyV,1,NCOVMAX);
12729: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12730: free_ivector(Typevar,-1,NCOVMAX);
12731: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12732: free_ivector(TvarsQ,1,NCOVMAX);
12733: free_ivector(TvarsQind,1,NCOVMAX);
12734: free_ivector(TvarsD,1,NCOVMAX);
12735: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12736: free_ivector(TvarFD,1,NCOVMAX);
12737: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12738: free_ivector(TvarF,1,NCOVMAX);
12739: free_ivector(TvarFind,1,NCOVMAX);
12740: free_ivector(TvarV,1,NCOVMAX);
12741: free_ivector(TvarVind,1,NCOVMAX);
12742: free_ivector(TvarA,1,NCOVMAX);
12743: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12744: free_ivector(TvarFQ,1,NCOVMAX);
12745: free_ivector(TvarFQind,1,NCOVMAX);
12746: free_ivector(TvarVD,1,NCOVMAX);
12747: free_ivector(TvarVDind,1,NCOVMAX);
12748: free_ivector(TvarVQ,1,NCOVMAX);
12749: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12750: free_ivector(Tvarsel,1,NCOVMAX);
12751: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12752: free_ivector(Tposprod,1,NCOVMAX);
12753: free_ivector(Tprod,1,NCOVMAX);
12754: free_ivector(Tvaraff,1,NCOVMAX);
12755: free_ivector(invalidvarcomb,1,ncovcombmax);
12756: free_ivector(Tage,1,NCOVMAX);
12757: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12758: free_ivector(TmodelInvind,1,NCOVMAX);
12759: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12760:
12761: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12762: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12763: fflush(fichtm);
12764: fflush(ficgp);
12765:
1.227 brouard 12766:
1.126 brouard 12767: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12768: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12769: 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 12770: }else{
12771: printf("End of Imach\n");
12772: fprintf(ficlog,"End of Imach\n");
12773: }
12774: printf("See log file on %s\n",filelog);
12775: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12776: /*(void) gettimeofday(&end_time,&tzp);*/
12777: rend_time = time(NULL);
12778: end_time = *localtime(&rend_time);
12779: /* tml = *localtime(&end_time.tm_sec); */
12780: strcpy(strtend,asctime(&end_time));
1.126 brouard 12781: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12782: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12783: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12784:
1.157 brouard 12785: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12786: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12787: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12788: /* printf("Total time was %d uSec.\n", total_usecs);*/
12789: /* if(fileappend(fichtm,optionfilehtm)){ */
12790: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12791: fclose(fichtm);
12792: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12793: fclose(fichtmcov);
12794: fclose(ficgp);
12795: fclose(ficlog);
12796: /*------ End -----------*/
1.227 brouard 12797:
1.281 brouard 12798:
12799: /* Executes gnuplot */
1.227 brouard 12800:
12801: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12802: #ifdef WIN32
1.227 brouard 12803: if (_chdir(pathcd) != 0)
12804: printf("Can't move to directory %s!\n",path);
12805: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12806: #else
1.227 brouard 12807: if(chdir(pathcd) != 0)
12808: printf("Can't move to directory %s!\n", path);
12809: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12810: #endif
1.126 brouard 12811: printf("Current directory %s!\n",pathcd);
12812: /*strcat(plotcmd,CHARSEPARATOR);*/
12813: sprintf(plotcmd,"gnuplot");
1.157 brouard 12814: #ifdef _WIN32
1.126 brouard 12815: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12816: #endif
12817: if(!stat(plotcmd,&info)){
1.158 brouard 12818: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12819: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12820: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12821: }else
12822: strcpy(pplotcmd,plotcmd);
1.157 brouard 12823: #ifdef __unix
1.126 brouard 12824: strcpy(plotcmd,GNUPLOTPROGRAM);
12825: if(!stat(plotcmd,&info)){
1.158 brouard 12826: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12827: }else
12828: strcpy(pplotcmd,plotcmd);
12829: #endif
12830: }else
12831: strcpy(pplotcmd,plotcmd);
12832:
12833: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12834: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 ! brouard 12835: strcpy(pplotcmd,plotcmd);
1.227 brouard 12836:
1.126 brouard 12837: if((outcmd=system(plotcmd)) != 0){
1.292 ! brouard 12838: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12839: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12840: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 ! brouard 12841: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 12842: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 ! brouard 12843: strcpy(plotcmd,pplotcmd);
! 12844: }
1.126 brouard 12845: }
1.158 brouard 12846: printf(" Successful, please wait...");
1.126 brouard 12847: while (z[0] != 'q') {
12848: /* chdir(path); */
1.154 brouard 12849: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12850: scanf("%s",z);
12851: /* if (z[0] == 'c') system("./imach"); */
12852: if (z[0] == 'e') {
1.158 brouard 12853: #ifdef __APPLE__
1.152 brouard 12854: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12855: #elif __linux
12856: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12857: #else
1.152 brouard 12858: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12859: #endif
12860: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12861: system(pplotcmd);
1.126 brouard 12862: }
12863: else if (z[0] == 'g') system(plotcmd);
12864: else if (z[0] == 'q') exit(0);
12865: }
1.227 brouard 12866: end:
1.126 brouard 12867: while (z[0] != 'q') {
1.195 brouard 12868: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12869: scanf("%s",z);
12870: }
1.283 brouard 12871: printf("End\n");
1.282 brouard 12872: exit(0);
1.126 brouard 12873: }
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