Annotation of imach/src/imach.c, revision 1.294
1.294 ! brouard 1: /* $Id: imach.c,v 1.293 2019/05/09 15:17:34 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.294 ! brouard 4: Revision 1.293 2019/05/09 15:17:34 brouard
! 5: *** empty log message ***
! 6:
1.293 brouard 7: Revision 1.292 2019/05/09 14:17:20 brouard
8: Summary: Some updates
9:
1.292 brouard 10: Revision 1.291 2019/05/09 13:44:18 brouard
11: Summary: Before ncovmax
12:
1.291 brouard 13: Revision 1.290 2019/05/09 13:39:37 brouard
14: Summary: 0.99r18 unlimited number of individuals
15:
16: 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.
17:
1.290 brouard 18: Revision 1.289 2018/12/13 09:16:26 brouard
19: Summary: Bug for young ages (<-30) will be in r17
20:
1.289 brouard 21: Revision 1.288 2018/05/02 20:58:27 brouard
22: Summary: Some bugs fixed
23:
1.288 brouard 24: Revision 1.287 2018/05/01 17:57:25 brouard
25: Summary: Bug fixed by providing frequencies only for non missing covariates
26:
1.287 brouard 27: Revision 1.286 2018/04/27 14:27:04 brouard
28: Summary: some minor bugs
29:
1.286 brouard 30: Revision 1.285 2018/04/21 21:02:16 brouard
31: Summary: Some bugs fixed, valgrind tested
32:
1.285 brouard 33: Revision 1.284 2018/04/20 05:22:13 brouard
34: Summary: Computing mean and stdeviation of fixed quantitative variables
35:
1.284 brouard 36: Revision 1.283 2018/04/19 14:49:16 brouard
37: Summary: Some minor bugs fixed
38:
1.283 brouard 39: Revision 1.282 2018/02/27 22:50:02 brouard
40: *** empty log message ***
41:
1.282 brouard 42: Revision 1.281 2018/02/27 19:25:23 brouard
43: Summary: Adding second argument for quitting
44:
1.281 brouard 45: Revision 1.280 2018/02/21 07:58:13 brouard
46: Summary: 0.99r15
47:
48: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
49:
1.280 brouard 50: Revision 1.279 2017/07/20 13:35:01 brouard
51: Summary: temporary working
52:
1.279 brouard 53: Revision 1.278 2017/07/19 14:09:02 brouard
54: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
55:
1.278 brouard 56: Revision 1.277 2017/07/17 08:53:49 brouard
57: Summary: BOM files can be read now
58:
1.277 brouard 59: Revision 1.276 2017/06/30 15:48:31 brouard
60: Summary: Graphs improvements
61:
1.276 brouard 62: Revision 1.275 2017/06/30 13:39:33 brouard
63: Summary: Saito's color
64:
1.275 brouard 65: Revision 1.274 2017/06/29 09:47:08 brouard
66: Summary: Version 0.99r14
67:
1.274 brouard 68: Revision 1.273 2017/06/27 11:06:02 brouard
69: Summary: More documentation on projections
70:
1.273 brouard 71: Revision 1.272 2017/06/27 10:22:40 brouard
72: Summary: Color of backprojection changed from 6 to 5(yellow)
73:
1.272 brouard 74: Revision 1.271 2017/06/27 10:17:50 brouard
75: Summary: Some bug with rint
76:
1.271 brouard 77: Revision 1.270 2017/05/24 05:45:29 brouard
78: *** empty log message ***
79:
1.270 brouard 80: Revision 1.269 2017/05/23 08:39:25 brouard
81: Summary: Code into subroutine, cleanings
82:
1.269 brouard 83: Revision 1.268 2017/05/18 20:09:32 brouard
84: Summary: backprojection and confidence intervals of backprevalence
85:
1.268 brouard 86: Revision 1.267 2017/05/13 10:25:05 brouard
87: Summary: temporary save for backprojection
88:
1.267 brouard 89: Revision 1.266 2017/05/13 07:26:12 brouard
90: Summary: Version 0.99r13 (improvements and bugs fixed)
91:
1.266 brouard 92: Revision 1.265 2017/04/26 16:22:11 brouard
93: Summary: imach 0.99r13 Some bugs fixed
94:
1.265 brouard 95: Revision 1.264 2017/04/26 06:01:29 brouard
96: Summary: Labels in graphs
97:
1.264 brouard 98: Revision 1.263 2017/04/24 15:23:15 brouard
99: Summary: to save
100:
1.263 brouard 101: Revision 1.262 2017/04/18 16:48:12 brouard
102: *** empty log message ***
103:
1.262 brouard 104: Revision 1.261 2017/04/05 10:14:09 brouard
105: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
106:
1.261 brouard 107: Revision 1.260 2017/04/04 17:46:59 brouard
108: Summary: Gnuplot indexations fixed (humm)
109:
1.260 brouard 110: Revision 1.259 2017/04/04 13:01:16 brouard
111: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
112:
1.259 brouard 113: Revision 1.258 2017/04/03 10:17:47 brouard
114: Summary: Version 0.99r12
115:
116: Some cleanings, conformed with updated documentation.
117:
1.258 brouard 118: Revision 1.257 2017/03/29 16:53:30 brouard
119: Summary: Temp
120:
1.257 brouard 121: Revision 1.256 2017/03/27 05:50:23 brouard
122: Summary: Temporary
123:
1.256 brouard 124: Revision 1.255 2017/03/08 16:02:28 brouard
125: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
126:
1.255 brouard 127: Revision 1.254 2017/03/08 07:13:00 brouard
128: Summary: Fixing data parameter line
129:
1.254 brouard 130: Revision 1.253 2016/12/15 11:59:41 brouard
131: Summary: 0.99 in progress
132:
1.253 brouard 133: Revision 1.252 2016/09/15 21:15:37 brouard
134: *** empty log message ***
135:
1.252 brouard 136: Revision 1.251 2016/09/15 15:01:13 brouard
137: Summary: not working
138:
1.251 brouard 139: Revision 1.250 2016/09/08 16:07:27 brouard
140: Summary: continue
141:
1.250 brouard 142: Revision 1.249 2016/09/07 17:14:18 brouard
143: Summary: Starting values from frequencies
144:
1.249 brouard 145: Revision 1.248 2016/09/07 14:10:18 brouard
146: *** empty log message ***
147:
1.248 brouard 148: Revision 1.247 2016/09/02 11:11:21 brouard
149: *** empty log message ***
150:
1.247 brouard 151: Revision 1.246 2016/09/02 08:49:22 brouard
152: *** empty log message ***
153:
1.246 brouard 154: Revision 1.245 2016/09/02 07:25:01 brouard
155: *** empty log message ***
156:
1.245 brouard 157: Revision 1.244 2016/09/02 07:17:34 brouard
158: *** empty log message ***
159:
1.244 brouard 160: Revision 1.243 2016/09/02 06:45:35 brouard
161: *** empty log message ***
162:
1.243 brouard 163: Revision 1.242 2016/08/30 15:01:20 brouard
164: Summary: Fixing a lots
165:
1.242 brouard 166: Revision 1.241 2016/08/29 17:17:25 brouard
167: Summary: gnuplot problem in Back projection to fix
168:
1.241 brouard 169: Revision 1.240 2016/08/29 07:53:18 brouard
170: Summary: Better
171:
1.240 brouard 172: Revision 1.239 2016/08/26 15:51:03 brouard
173: Summary: Improvement in Powell output in order to copy and paste
174:
175: Author:
176:
1.239 brouard 177: Revision 1.238 2016/08/26 14:23:35 brouard
178: Summary: Starting tests of 0.99
179:
1.238 brouard 180: Revision 1.237 2016/08/26 09:20:19 brouard
181: Summary: to valgrind
182:
1.237 brouard 183: Revision 1.236 2016/08/25 10:50:18 brouard
184: *** empty log message ***
185:
1.236 brouard 186: Revision 1.235 2016/08/25 06:59:23 brouard
187: *** empty log message ***
188:
1.235 brouard 189: Revision 1.234 2016/08/23 16:51:20 brouard
190: *** empty log message ***
191:
1.234 brouard 192: Revision 1.233 2016/08/23 07:40:50 brouard
193: Summary: not working
194:
1.233 brouard 195: Revision 1.232 2016/08/22 14:20:21 brouard
196: Summary: not working
197:
1.232 brouard 198: Revision 1.231 2016/08/22 07:17:15 brouard
199: Summary: not working
200:
1.231 brouard 201: Revision 1.230 2016/08/22 06:55:53 brouard
202: Summary: Not working
203:
1.230 brouard 204: Revision 1.229 2016/07/23 09:45:53 brouard
205: Summary: Completing for func too
206:
1.229 brouard 207: Revision 1.228 2016/07/22 17:45:30 brouard
208: Summary: Fixing some arrays, still debugging
209:
1.227 brouard 210: Revision 1.226 2016/07/12 18:42:34 brouard
211: Summary: temp
212:
1.226 brouard 213: Revision 1.225 2016/07/12 08:40:03 brouard
214: Summary: saving but not running
215:
1.225 brouard 216: Revision 1.224 2016/07/01 13:16:01 brouard
217: Summary: Fixes
218:
1.224 brouard 219: Revision 1.223 2016/02/19 09:23:35 brouard
220: Summary: temporary
221:
1.223 brouard 222: Revision 1.222 2016/02/17 08:14:50 brouard
223: Summary: Probably last 0.98 stable version 0.98r6
224:
1.222 brouard 225: Revision 1.221 2016/02/15 23:35:36 brouard
226: Summary: minor bug
227:
1.220 brouard 228: Revision 1.219 2016/02/15 00:48:12 brouard
229: *** empty log message ***
230:
1.219 brouard 231: Revision 1.218 2016/02/12 11:29:23 brouard
232: Summary: 0.99 Back projections
233:
1.218 brouard 234: Revision 1.217 2015/12/23 17:18:31 brouard
235: Summary: Experimental backcast
236:
1.217 brouard 237: Revision 1.216 2015/12/18 17:32:11 brouard
238: Summary: 0.98r4 Warning and status=-2
239:
240: Version 0.98r4 is now:
241: - displaying an error when status is -1, date of interview unknown and date of death known;
242: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
243: Older changes concerning s=-2, dating from 2005 have been supersed.
244:
1.216 brouard 245: Revision 1.215 2015/12/16 08:52:24 brouard
246: Summary: 0.98r4 working
247:
1.215 brouard 248: Revision 1.214 2015/12/16 06:57:54 brouard
249: Summary: temporary not working
250:
1.214 brouard 251: Revision 1.213 2015/12/11 18:22:17 brouard
252: Summary: 0.98r4
253:
1.213 brouard 254: Revision 1.212 2015/11/21 12:47:24 brouard
255: Summary: minor typo
256:
1.212 brouard 257: Revision 1.211 2015/11/21 12:41:11 brouard
258: Summary: 0.98r3 with some graph of projected cross-sectional
259:
260: Author: Nicolas Brouard
261:
1.211 brouard 262: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 263: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 264: Summary: Adding ftolpl parameter
265: Author: N Brouard
266:
267: We had difficulties to get smoothed confidence intervals. It was due
268: to the period prevalence which wasn't computed accurately. The inner
269: parameter ftolpl is now an outer parameter of the .imach parameter
270: file after estepm. If ftolpl is small 1.e-4 and estepm too,
271: computation are long.
272:
1.209 brouard 273: Revision 1.208 2015/11/17 14:31:57 brouard
274: Summary: temporary
275:
1.208 brouard 276: Revision 1.207 2015/10/27 17:36:57 brouard
277: *** empty log message ***
278:
1.207 brouard 279: Revision 1.206 2015/10/24 07:14:11 brouard
280: *** empty log message ***
281:
1.206 brouard 282: Revision 1.205 2015/10/23 15:50:53 brouard
283: Summary: 0.98r3 some clarification for graphs on likelihood contributions
284:
1.205 brouard 285: Revision 1.204 2015/10/01 16:20:26 brouard
286: Summary: Some new graphs of contribution to likelihood
287:
1.204 brouard 288: Revision 1.203 2015/09/30 17:45:14 brouard
289: Summary: looking at better estimation of the hessian
290:
291: Also a better criteria for convergence to the period prevalence And
292: therefore adding the number of years needed to converge. (The
293: prevalence in any alive state shold sum to one
294:
1.203 brouard 295: Revision 1.202 2015/09/22 19:45:16 brouard
296: Summary: Adding some overall graph on contribution to likelihood. Might change
297:
1.202 brouard 298: Revision 1.201 2015/09/15 17:34:58 brouard
299: Summary: 0.98r0
300:
301: - Some new graphs like suvival functions
302: - Some bugs fixed like model=1+age+V2.
303:
1.201 brouard 304: Revision 1.200 2015/09/09 16:53:55 brouard
305: Summary: Big bug thanks to Flavia
306:
307: Even model=1+age+V2. did not work anymore
308:
1.200 brouard 309: Revision 1.199 2015/09/07 14:09:23 brouard
310: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
311:
1.199 brouard 312: Revision 1.198 2015/09/03 07:14:39 brouard
313: Summary: 0.98q5 Flavia
314:
1.198 brouard 315: Revision 1.197 2015/09/01 18:24:39 brouard
316: *** empty log message ***
317:
1.197 brouard 318: Revision 1.196 2015/08/18 23:17:52 brouard
319: Summary: 0.98q5
320:
1.196 brouard 321: Revision 1.195 2015/08/18 16:28:39 brouard
322: Summary: Adding a hack for testing purpose
323:
324: After reading the title, ftol and model lines, if the comment line has
325: a q, starting with #q, the answer at the end of the run is quit. It
326: permits to run test files in batch with ctest. The former workaround was
327: $ echo q | imach foo.imach
328:
1.195 brouard 329: Revision 1.194 2015/08/18 13:32:00 brouard
330: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
331:
1.194 brouard 332: Revision 1.193 2015/08/04 07:17:42 brouard
333: Summary: 0.98q4
334:
1.193 brouard 335: Revision 1.192 2015/07/16 16:49:02 brouard
336: Summary: Fixing some outputs
337:
1.192 brouard 338: Revision 1.191 2015/07/14 10:00:33 brouard
339: Summary: Some fixes
340:
1.191 brouard 341: Revision 1.190 2015/05/05 08:51:13 brouard
342: Summary: Adding digits in output parameters (7 digits instead of 6)
343:
344: Fix 1+age+.
345:
1.190 brouard 346: Revision 1.189 2015/04/30 14:45:16 brouard
347: Summary: 0.98q2
348:
1.189 brouard 349: Revision 1.188 2015/04/30 08:27:53 brouard
350: *** empty log message ***
351:
1.188 brouard 352: Revision 1.187 2015/04/29 09:11:15 brouard
353: *** empty log message ***
354:
1.187 brouard 355: Revision 1.186 2015/04/23 12:01:52 brouard
356: Summary: V1*age is working now, version 0.98q1
357:
358: Some codes had been disabled in order to simplify and Vn*age was
359: working in the optimization phase, ie, giving correct MLE parameters,
360: but, as usual, outputs were not correct and program core dumped.
361:
1.186 brouard 362: Revision 1.185 2015/03/11 13:26:42 brouard
363: Summary: Inclusion of compile and links command line for Intel Compiler
364:
1.185 brouard 365: Revision 1.184 2015/03/11 11:52:39 brouard
366: Summary: Back from Windows 8. Intel Compiler
367:
1.184 brouard 368: Revision 1.183 2015/03/10 20:34:32 brouard
369: Summary: 0.98q0, trying with directest, mnbrak fixed
370:
371: We use directest instead of original Powell test; probably no
372: incidence on the results, but better justifications;
373: We fixed Numerical Recipes mnbrak routine which was wrong and gave
374: wrong results.
375:
1.183 brouard 376: Revision 1.182 2015/02/12 08:19:57 brouard
377: Summary: Trying to keep directest which seems simpler and more general
378: Author: Nicolas Brouard
379:
1.182 brouard 380: Revision 1.181 2015/02/11 23:22:24 brouard
381: Summary: Comments on Powell added
382:
383: Author:
384:
1.181 brouard 385: Revision 1.180 2015/02/11 17:33:45 brouard
386: Summary: Finishing move from main to function (hpijx and prevalence_limit)
387:
1.180 brouard 388: Revision 1.179 2015/01/04 09:57:06 brouard
389: Summary: back to OS/X
390:
1.179 brouard 391: Revision 1.178 2015/01/04 09:35:48 brouard
392: *** empty log message ***
393:
1.178 brouard 394: Revision 1.177 2015/01/03 18:40:56 brouard
395: Summary: Still testing ilc32 on OSX
396:
1.177 brouard 397: Revision 1.176 2015/01/03 16:45:04 brouard
398: *** empty log message ***
399:
1.176 brouard 400: Revision 1.175 2015/01/03 16:33:42 brouard
401: *** empty log message ***
402:
1.175 brouard 403: Revision 1.174 2015/01/03 16:15:49 brouard
404: Summary: Still in cross-compilation
405:
1.174 brouard 406: Revision 1.173 2015/01/03 12:06:26 brouard
407: Summary: trying to detect cross-compilation
408:
1.173 brouard 409: Revision 1.172 2014/12/27 12:07:47 brouard
410: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
411:
1.172 brouard 412: Revision 1.171 2014/12/23 13:26:59 brouard
413: Summary: Back from Visual C
414:
415: Still problem with utsname.h on Windows
416:
1.171 brouard 417: Revision 1.170 2014/12/23 11:17:12 brouard
418: Summary: Cleaning some \%% back to %%
419:
420: The escape was mandatory for a specific compiler (which one?), but too many warnings.
421:
1.170 brouard 422: Revision 1.169 2014/12/22 23:08:31 brouard
423: Summary: 0.98p
424:
425: Outputs some informations on compiler used, OS etc. Testing on different platforms.
426:
1.169 brouard 427: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 428: Summary: update
1.169 brouard 429:
1.168 brouard 430: Revision 1.167 2014/12/22 13:50:56 brouard
431: Summary: Testing uname and compiler version and if compiled 32 or 64
432:
433: Testing on Linux 64
434:
1.167 brouard 435: Revision 1.166 2014/12/22 11:40:47 brouard
436: *** empty log message ***
437:
1.166 brouard 438: Revision 1.165 2014/12/16 11:20:36 brouard
439: Summary: After compiling on Visual C
440:
441: * imach.c (Module): Merging 1.61 to 1.162
442:
1.165 brouard 443: Revision 1.164 2014/12/16 10:52:11 brouard
444: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
445:
446: * imach.c (Module): Merging 1.61 to 1.162
447:
1.164 brouard 448: Revision 1.163 2014/12/16 10:30:11 brouard
449: * imach.c (Module): Merging 1.61 to 1.162
450:
1.163 brouard 451: Revision 1.162 2014/09/25 11:43:39 brouard
452: Summary: temporary backup 0.99!
453:
1.162 brouard 454: Revision 1.1 2014/09/16 11:06:58 brouard
455: Summary: With some code (wrong) for nlopt
456:
457: Author:
458:
459: Revision 1.161 2014/09/15 20:41:41 brouard
460: Summary: Problem with macro SQR on Intel compiler
461:
1.161 brouard 462: Revision 1.160 2014/09/02 09:24:05 brouard
463: *** empty log message ***
464:
1.160 brouard 465: Revision 1.159 2014/09/01 10:34:10 brouard
466: Summary: WIN32
467: Author: Brouard
468:
1.159 brouard 469: Revision 1.158 2014/08/27 17:11:51 brouard
470: *** empty log message ***
471:
1.158 brouard 472: Revision 1.157 2014/08/27 16:26:55 brouard
473: Summary: Preparing windows Visual studio version
474: Author: Brouard
475:
476: In order to compile on Visual studio, time.h is now correct and time_t
477: and tm struct should be used. difftime should be used but sometimes I
478: just make the differences in raw time format (time(&now).
479: Trying to suppress #ifdef LINUX
480: Add xdg-open for __linux in order to open default browser.
481:
1.157 brouard 482: Revision 1.156 2014/08/25 20:10:10 brouard
483: *** empty log message ***
484:
1.156 brouard 485: Revision 1.155 2014/08/25 18:32:34 brouard
486: Summary: New compile, minor changes
487: Author: Brouard
488:
1.155 brouard 489: Revision 1.154 2014/06/20 17:32:08 brouard
490: Summary: Outputs now all graphs of convergence to period prevalence
491:
1.154 brouard 492: Revision 1.153 2014/06/20 16:45:46 brouard
493: Summary: If 3 live state, convergence to period prevalence on same graph
494: Author: Brouard
495:
1.153 brouard 496: Revision 1.152 2014/06/18 17:54:09 brouard
497: Summary: open browser, use gnuplot on same dir than imach if not found in the path
498:
1.152 brouard 499: Revision 1.151 2014/06/18 16:43:30 brouard
500: *** empty log message ***
501:
1.151 brouard 502: Revision 1.150 2014/06/18 16:42:35 brouard
503: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
504: Author: brouard
505:
1.150 brouard 506: Revision 1.149 2014/06/18 15:51:14 brouard
507: Summary: Some fixes in parameter files errors
508: Author: Nicolas Brouard
509:
1.149 brouard 510: Revision 1.148 2014/06/17 17:38:48 brouard
511: Summary: Nothing new
512: Author: Brouard
513:
514: Just a new packaging for OS/X version 0.98nS
515:
1.148 brouard 516: Revision 1.147 2014/06/16 10:33:11 brouard
517: *** empty log message ***
518:
1.147 brouard 519: Revision 1.146 2014/06/16 10:20:28 brouard
520: Summary: Merge
521: Author: Brouard
522:
523: Merge, before building revised version.
524:
1.146 brouard 525: Revision 1.145 2014/06/10 21:23:15 brouard
526: Summary: Debugging with valgrind
527: Author: Nicolas Brouard
528:
529: Lot of changes in order to output the results with some covariates
530: After the Edimburgh REVES conference 2014, it seems mandatory to
531: improve the code.
532: No more memory valgrind error but a lot has to be done in order to
533: continue the work of splitting the code into subroutines.
534: Also, decodemodel has been improved. Tricode is still not
535: optimal. nbcode should be improved. Documentation has been added in
536: the source code.
537:
1.144 brouard 538: Revision 1.143 2014/01/26 09:45:38 brouard
539: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
540:
541: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
542: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
543:
1.143 brouard 544: Revision 1.142 2014/01/26 03:57:36 brouard
545: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
546:
547: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
548:
1.142 brouard 549: Revision 1.141 2014/01/26 02:42:01 brouard
550: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
551:
1.141 brouard 552: Revision 1.140 2011/09/02 10:37:54 brouard
553: Summary: times.h is ok with mingw32 now.
554:
1.140 brouard 555: Revision 1.139 2010/06/14 07:50:17 brouard
556: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
557: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
558:
1.139 brouard 559: Revision 1.138 2010/04/30 18:19:40 brouard
560: *** empty log message ***
561:
1.138 brouard 562: Revision 1.137 2010/04/29 18:11:38 brouard
563: (Module): Checking covariates for more complex models
564: than V1+V2. A lot of change to be done. Unstable.
565:
1.137 brouard 566: Revision 1.136 2010/04/26 20:30:53 brouard
567: (Module): merging some libgsl code. Fixing computation
568: of likelione (using inter/intrapolation if mle = 0) in order to
569: get same likelihood as if mle=1.
570: Some cleaning of code and comments added.
571:
1.136 brouard 572: Revision 1.135 2009/10/29 15:33:14 brouard
573: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
574:
1.135 brouard 575: Revision 1.134 2009/10/29 13:18:53 brouard
576: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
577:
1.134 brouard 578: Revision 1.133 2009/07/06 10:21:25 brouard
579: just nforces
580:
1.133 brouard 581: Revision 1.132 2009/07/06 08:22:05 brouard
582: Many tings
583:
1.132 brouard 584: Revision 1.131 2009/06/20 16:22:47 brouard
585: Some dimensions resccaled
586:
1.131 brouard 587: Revision 1.130 2009/05/26 06:44:34 brouard
588: (Module): Max Covariate is now set to 20 instead of 8. A
589: lot of cleaning with variables initialized to 0. Trying to make
590: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
591:
1.130 brouard 592: Revision 1.129 2007/08/31 13:49:27 lievre
593: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
594:
1.129 lievre 595: Revision 1.128 2006/06/30 13:02:05 brouard
596: (Module): Clarifications on computing e.j
597:
1.128 brouard 598: Revision 1.127 2006/04/28 18:11:50 brouard
599: (Module): Yes the sum of survivors was wrong since
600: imach-114 because nhstepm was no more computed in the age
601: loop. Now we define nhstepma in the age loop.
602: (Module): In order to speed up (in case of numerous covariates) we
603: compute health expectancies (without variances) in a first step
604: and then all the health expectancies with variances or standard
605: deviation (needs data from the Hessian matrices) which slows the
606: computation.
607: In the future we should be able to stop the program is only health
608: expectancies and graph are needed without standard deviations.
609:
1.127 brouard 610: Revision 1.126 2006/04/28 17:23:28 brouard
611: (Module): Yes the sum of survivors was wrong since
612: imach-114 because nhstepm was no more computed in the age
613: loop. Now we define nhstepma in the age loop.
614: Version 0.98h
615:
1.126 brouard 616: Revision 1.125 2006/04/04 15:20:31 lievre
617: Errors in calculation of health expectancies. Age was not initialized.
618: Forecasting file added.
619:
620: Revision 1.124 2006/03/22 17:13:53 lievre
621: Parameters are printed with %lf instead of %f (more numbers after the comma).
622: The log-likelihood is printed in the log file
623:
624: Revision 1.123 2006/03/20 10:52:43 brouard
625: * imach.c (Module): <title> changed, corresponds to .htm file
626: name. <head> headers where missing.
627:
628: * imach.c (Module): Weights can have a decimal point as for
629: English (a comma might work with a correct LC_NUMERIC environment,
630: otherwise the weight is truncated).
631: Modification of warning when the covariates values are not 0 or
632: 1.
633: Version 0.98g
634:
635: Revision 1.122 2006/03/20 09:45:41 brouard
636: (Module): Weights can have a decimal point as for
637: English (a comma might work with a correct LC_NUMERIC environment,
638: otherwise the weight is truncated).
639: Modification of warning when the covariates values are not 0 or
640: 1.
641: Version 0.98g
642:
643: Revision 1.121 2006/03/16 17:45:01 lievre
644: * imach.c (Module): Comments concerning covariates added
645:
646: * imach.c (Module): refinements in the computation of lli if
647: status=-2 in order to have more reliable computation if stepm is
648: not 1 month. Version 0.98f
649:
650: Revision 1.120 2006/03/16 15:10:38 lievre
651: (Module): refinements in the computation of lli if
652: status=-2 in order to have more reliable computation if stepm is
653: not 1 month. Version 0.98f
654:
655: Revision 1.119 2006/03/15 17:42:26 brouard
656: (Module): Bug if status = -2, the loglikelihood was
657: computed as likelihood omitting the logarithm. Version O.98e
658:
659: Revision 1.118 2006/03/14 18:20:07 brouard
660: (Module): varevsij Comments added explaining the second
661: table of variances if popbased=1 .
662: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
663: (Module): Function pstamp added
664: (Module): Version 0.98d
665:
666: Revision 1.117 2006/03/14 17:16:22 brouard
667: (Module): varevsij Comments added explaining the second
668: table of variances if popbased=1 .
669: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
670: (Module): Function pstamp added
671: (Module): Version 0.98d
672:
673: Revision 1.116 2006/03/06 10:29:27 brouard
674: (Module): Variance-covariance wrong links and
675: varian-covariance of ej. is needed (Saito).
676:
677: Revision 1.115 2006/02/27 12:17:45 brouard
678: (Module): One freematrix added in mlikeli! 0.98c
679:
680: Revision 1.114 2006/02/26 12:57:58 brouard
681: (Module): Some improvements in processing parameter
682: filename with strsep.
683:
684: Revision 1.113 2006/02/24 14:20:24 brouard
685: (Module): Memory leaks checks with valgrind and:
686: datafile was not closed, some imatrix were not freed and on matrix
687: allocation too.
688:
689: Revision 1.112 2006/01/30 09:55:26 brouard
690: (Module): Back to gnuplot.exe instead of wgnuplot.exe
691:
692: Revision 1.111 2006/01/25 20:38:18 brouard
693: (Module): Lots of cleaning and bugs added (Gompertz)
694: (Module): Comments can be added in data file. Missing date values
695: can be a simple dot '.'.
696:
697: Revision 1.110 2006/01/25 00:51:50 brouard
698: (Module): Lots of cleaning and bugs added (Gompertz)
699:
700: Revision 1.109 2006/01/24 19:37:15 brouard
701: (Module): Comments (lines starting with a #) are allowed in data.
702:
703: Revision 1.108 2006/01/19 18:05:42 lievre
704: Gnuplot problem appeared...
705: To be fixed
706:
707: Revision 1.107 2006/01/19 16:20:37 brouard
708: Test existence of gnuplot in imach path
709:
710: Revision 1.106 2006/01/19 13:24:36 brouard
711: Some cleaning and links added in html output
712:
713: Revision 1.105 2006/01/05 20:23:19 lievre
714: *** empty log message ***
715:
716: Revision 1.104 2005/09/30 16:11:43 lievre
717: (Module): sump fixed, loop imx fixed, and simplifications.
718: (Module): If the status is missing at the last wave but we know
719: that the person is alive, then we can code his/her status as -2
720: (instead of missing=-1 in earlier versions) and his/her
721: contributions to the likelihood is 1 - Prob of dying from last
722: health status (= 1-p13= p11+p12 in the easiest case of somebody in
723: the healthy state at last known wave). Version is 0.98
724:
725: Revision 1.103 2005/09/30 15:54:49 lievre
726: (Module): sump fixed, loop imx fixed, and simplifications.
727:
728: Revision 1.102 2004/09/15 17:31:30 brouard
729: Add the possibility to read data file including tab characters.
730:
731: Revision 1.101 2004/09/15 10:38:38 brouard
732: Fix on curr_time
733:
734: Revision 1.100 2004/07/12 18:29:06 brouard
735: Add version for Mac OS X. Just define UNIX in Makefile
736:
737: Revision 1.99 2004/06/05 08:57:40 brouard
738: *** empty log message ***
739:
740: Revision 1.98 2004/05/16 15:05:56 brouard
741: New version 0.97 . First attempt to estimate force of mortality
742: directly from the data i.e. without the need of knowing the health
743: state at each age, but using a Gompertz model: log u =a + b*age .
744: This is the basic analysis of mortality and should be done before any
745: other analysis, in order to test if the mortality estimated from the
746: cross-longitudinal survey is different from the mortality estimated
747: from other sources like vital statistic data.
748:
749: The same imach parameter file can be used but the option for mle should be -3.
750:
1.133 brouard 751: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 752: former routines in order to include the new code within the former code.
753:
754: The output is very simple: only an estimate of the intercept and of
755: the slope with 95% confident intervals.
756:
757: Current limitations:
758: A) Even if you enter covariates, i.e. with the
759: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
760: B) There is no computation of Life Expectancy nor Life Table.
761:
762: Revision 1.97 2004/02/20 13:25:42 lievre
763: Version 0.96d. Population forecasting command line is (temporarily)
764: suppressed.
765:
766: Revision 1.96 2003/07/15 15:38:55 brouard
767: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
768: rewritten within the same printf. Workaround: many printfs.
769:
770: Revision 1.95 2003/07/08 07:54:34 brouard
771: * imach.c (Repository):
772: (Repository): Using imachwizard code to output a more meaningful covariance
773: matrix (cov(a12,c31) instead of numbers.
774:
775: Revision 1.94 2003/06/27 13:00:02 brouard
776: Just cleaning
777:
778: Revision 1.93 2003/06/25 16:33:55 brouard
779: (Module): On windows (cygwin) function asctime_r doesn't
780: exist so I changed back to asctime which exists.
781: (Module): Version 0.96b
782:
783: Revision 1.92 2003/06/25 16:30:45 brouard
784: (Module): On windows (cygwin) function asctime_r doesn't
785: exist so I changed back to asctime which exists.
786:
787: Revision 1.91 2003/06/25 15:30:29 brouard
788: * imach.c (Repository): Duplicated warning errors corrected.
789: (Repository): Elapsed time after each iteration is now output. It
790: helps to forecast when convergence will be reached. Elapsed time
791: is stamped in powell. We created a new html file for the graphs
792: concerning matrix of covariance. It has extension -cov.htm.
793:
794: Revision 1.90 2003/06/24 12:34:15 brouard
795: (Module): Some bugs corrected for windows. Also, when
796: mle=-1 a template is output in file "or"mypar.txt with the design
797: of the covariance matrix to be input.
798:
799: Revision 1.89 2003/06/24 12:30:52 brouard
800: (Module): Some bugs corrected for windows. Also, when
801: mle=-1 a template is output in file "or"mypar.txt with the design
802: of the covariance matrix to be input.
803:
804: Revision 1.88 2003/06/23 17:54:56 brouard
805: * 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.
806:
807: Revision 1.87 2003/06/18 12:26:01 brouard
808: Version 0.96
809:
810: Revision 1.86 2003/06/17 20:04:08 brouard
811: (Module): Change position of html and gnuplot routines and added
812: routine fileappend.
813:
814: Revision 1.85 2003/06/17 13:12:43 brouard
815: * imach.c (Repository): Check when date of death was earlier that
816: current date of interview. It may happen when the death was just
817: prior to the death. In this case, dh was negative and likelihood
818: was wrong (infinity). We still send an "Error" but patch by
819: assuming that the date of death was just one stepm after the
820: interview.
821: (Repository): Because some people have very long ID (first column)
822: we changed int to long in num[] and we added a new lvector for
823: memory allocation. But we also truncated to 8 characters (left
824: truncation)
825: (Repository): No more line truncation errors.
826:
827: Revision 1.84 2003/06/13 21:44:43 brouard
828: * imach.c (Repository): Replace "freqsummary" at a correct
829: place. It differs from routine "prevalence" which may be called
830: many times. Probs is memory consuming and must be used with
831: parcimony.
832: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
833:
834: Revision 1.83 2003/06/10 13:39:11 lievre
835: *** empty log message ***
836:
837: Revision 1.82 2003/06/05 15:57:20 brouard
838: Add log in imach.c and fullversion number is now printed.
839:
840: */
841: /*
842: Interpolated Markov Chain
843:
844: Short summary of the programme:
845:
1.227 brouard 846: This program computes Healthy Life Expectancies or State-specific
847: (if states aren't health statuses) Expectancies from
848: cross-longitudinal data. Cross-longitudinal data consist in:
849:
850: -1- a first survey ("cross") where individuals from different ages
851: are interviewed on their health status or degree of disability (in
852: the case of a health survey which is our main interest)
853:
854: -2- at least a second wave of interviews ("longitudinal") which
855: measure each change (if any) in individual health status. Health
856: expectancies are computed from the time spent in each health state
857: according to a model. More health states you consider, more time is
858: necessary to reach the Maximum Likelihood of the parameters involved
859: in the model. The simplest model is the multinomial logistic model
860: where pij is the probability to be observed in state j at the second
861: wave conditional to be observed in state i at the first
862: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
863: etc , where 'age' is age and 'sex' is a covariate. If you want to
864: have a more complex model than "constant and age", you should modify
865: the program where the markup *Covariates have to be included here
866: again* invites you to do it. More covariates you add, slower the
1.126 brouard 867: convergence.
868:
869: The advantage of this computer programme, compared to a simple
870: multinomial logistic model, is clear when the delay between waves is not
871: identical for each individual. Also, if a individual missed an
872: intermediate interview, the information is lost, but taken into
873: account using an interpolation or extrapolation.
874:
875: hPijx is the probability to be observed in state i at age x+h
876: conditional to the observed state i at age x. The delay 'h' can be
877: split into an exact number (nh*stepm) of unobserved intermediate
878: states. This elementary transition (by month, quarter,
879: semester or year) is modelled as a multinomial logistic. The hPx
880: matrix is simply the matrix product of nh*stepm elementary matrices
881: and the contribution of each individual to the likelihood is simply
882: hPijx.
883:
884: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 885: of the life expectancies. It also computes the period (stable) prevalence.
886:
887: Back prevalence and projections:
1.227 brouard 888:
889: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
890: double agemaxpar, double ftolpl, int *ncvyearp, double
891: dateprev1,double dateprev2, int firstpass, int lastpass, int
892: mobilavproj)
893:
894: Computes the back prevalence limit for any combination of
895: covariate values k at any age between ageminpar and agemaxpar and
896: returns it in **bprlim. In the loops,
897:
898: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
899: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
900:
901: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 902: Computes for any combination of covariates k and any age between bage and fage
903: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
904: oldm=oldms;savm=savms;
1.227 brouard 905:
1.267 brouard 906: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 907: Computes the transition matrix starting at age 'age' over
908: 'nhstepm*hstepm*stepm' months (i.e. until
909: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 910: nhstepm*hstepm matrices.
911:
912: Returns p3mat[i][j][h] after calling
913: p3mat[i][j][h]=matprod2(newm,
914: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
915: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
916: oldm);
1.226 brouard 917:
918: Important routines
919:
920: - func (or funcone), computes logit (pij) distinguishing
921: o fixed variables (single or product dummies or quantitative);
922: o varying variables by:
923: (1) wave (single, product dummies, quantitative),
924: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
925: % fixed dummy (treated) or quantitative (not done because time-consuming);
926: % varying dummy (not done) or quantitative (not done);
927: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
928: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
929: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
930: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
931: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 932:
1.226 brouard 933:
934:
1.133 brouard 935: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
936: Institut national d'études démographiques, Paris.
1.126 brouard 937: This software have been partly granted by Euro-REVES, a concerted action
938: from the European Union.
939: It is copyrighted identically to a GNU software product, ie programme and
940: software can be distributed freely for non commercial use. Latest version
941: can be accessed at http://euroreves.ined.fr/imach .
942:
943: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
944: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
945:
946: **********************************************************************/
947: /*
948: main
949: read parameterfile
950: read datafile
951: concatwav
952: freqsummary
953: if (mle >= 1)
954: mlikeli
955: print results files
956: if mle==1
957: computes hessian
958: read end of parameter file: agemin, agemax, bage, fage, estepm
959: begin-prev-date,...
960: open gnuplot file
961: open html file
1.145 brouard 962: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
963: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
964: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
965: freexexit2 possible for memory heap.
966:
967: h Pij x | pij_nom ficrestpij
968: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
969: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
970: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
971:
972: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
973: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
974: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
975: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
976: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
977:
1.126 brouard 978: forecasting if prevfcast==1 prevforecast call prevalence()
979: health expectancies
980: Variance-covariance of DFLE
981: prevalence()
982: movingaverage()
983: varevsij()
984: if popbased==1 varevsij(,popbased)
985: total life expectancies
986: Variance of period (stable) prevalence
987: end
988: */
989:
1.187 brouard 990: /* #define DEBUG */
991: /* #define DEBUGBRENT */
1.203 brouard 992: /* #define DEBUGLINMIN */
993: /* #define DEBUGHESS */
994: #define DEBUGHESSIJ
1.224 brouard 995: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 996: #define POWELL /* Instead of NLOPT */
1.224 brouard 997: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 998: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
999: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 1000:
1001: #include <math.h>
1002: #include <stdio.h>
1003: #include <stdlib.h>
1004: #include <string.h>
1.226 brouard 1005: #include <ctype.h>
1.159 brouard 1006:
1007: #ifdef _WIN32
1008: #include <io.h>
1.172 brouard 1009: #include <windows.h>
1010: #include <tchar.h>
1.159 brouard 1011: #else
1.126 brouard 1012: #include <unistd.h>
1.159 brouard 1013: #endif
1.126 brouard 1014:
1015: #include <limits.h>
1016: #include <sys/types.h>
1.171 brouard 1017:
1018: #if defined(__GNUC__)
1019: #include <sys/utsname.h> /* Doesn't work on Windows */
1020: #endif
1021:
1.126 brouard 1022: #include <sys/stat.h>
1023: #include <errno.h>
1.159 brouard 1024: /* extern int errno; */
1.126 brouard 1025:
1.157 brouard 1026: /* #ifdef LINUX */
1027: /* #include <time.h> */
1028: /* #include "timeval.h" */
1029: /* #else */
1030: /* #include <sys/time.h> */
1031: /* #endif */
1032:
1.126 brouard 1033: #include <time.h>
1034:
1.136 brouard 1035: #ifdef GSL
1036: #include <gsl/gsl_errno.h>
1037: #include <gsl/gsl_multimin.h>
1038: #endif
1039:
1.167 brouard 1040:
1.162 brouard 1041: #ifdef NLOPT
1042: #include <nlopt.h>
1043: typedef struct {
1044: double (* function)(double [] );
1045: } myfunc_data ;
1046: #endif
1047:
1.126 brouard 1048: /* #include <libintl.h> */
1049: /* #define _(String) gettext (String) */
1050:
1.251 brouard 1051: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1052:
1053: #define GNUPLOTPROGRAM "gnuplot"
1054: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1055: #define FILENAMELENGTH 132
1056:
1057: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1058: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1059:
1.144 brouard 1060: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1061: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1062:
1063: #define NINTERVMAX 8
1.144 brouard 1064: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1065: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.291 brouard 1066: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1067: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1068: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1069: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1070: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1071: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1072: /* #define AGESUP 130 */
1.288 brouard 1073: /* #define AGESUP 150 */
1074: #define AGESUP 200
1.268 brouard 1075: #define AGEINF 0
1.218 brouard 1076: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1077: #define AGEBASE 40
1.194 brouard 1078: #define AGEOVERFLOW 1.e20
1.164 brouard 1079: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1080: #ifdef _WIN32
1081: #define DIRSEPARATOR '\\'
1082: #define CHARSEPARATOR "\\"
1083: #define ODIRSEPARATOR '/'
1084: #else
1.126 brouard 1085: #define DIRSEPARATOR '/'
1086: #define CHARSEPARATOR "/"
1087: #define ODIRSEPARATOR '\\'
1088: #endif
1089:
1.294 ! brouard 1090: /* $Id: imach.c,v 1.293 2019/05/09 15:17:34 brouard Exp $ */
1.126 brouard 1091: /* $State: Exp $ */
1.196 brouard 1092: #include "version.h"
1093: char version[]=__IMACH_VERSION__;
1.283 brouard 1094: 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";
1.294 ! brouard 1095: char fullversion[]="$Revision: 1.293 $ $Date: 2019/05/09 15:17:34 $";
1.126 brouard 1096: char strstart[80];
1097: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1098: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1099: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1100: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1101: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1102: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1103: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1104: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1105: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1106: int cptcovprodnoage=0; /**< Number of covariate products without age */
1107: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1108: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1109: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1110: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1111: int nsd=0; /**< Total number of single dummy variables (output) */
1112: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1113: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1114: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1115: int ntveff=0; /**< ntveff number of effective time varying variables */
1116: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1117: int cptcov=0; /* Working variable */
1.290 brouard 1118: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1119: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1120: int npar=NPARMAX;
1121: int nlstate=2; /* Number of live states */
1122: int ndeath=1; /* Number of dead states */
1.130 brouard 1123: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1124: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1125: int popbased=0;
1126:
1127: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1128: int maxwav=0; /* Maxim number of waves */
1129: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1130: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1131: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1132: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1133: int mle=1, weightopt=0;
1.126 brouard 1134: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1135: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1136: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1137: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1138: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1139: int selected(int kvar); /* Is covariate kvar selected for printing results */
1140:
1.130 brouard 1141: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1142: double **matprod2(); /* test */
1.126 brouard 1143: double **oldm, **newm, **savm; /* Working pointers to matrices */
1144: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1145: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1146:
1.136 brouard 1147: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1148: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1149: FILE *ficlog, *ficrespow;
1.130 brouard 1150: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1151: double fretone; /* Only one call to likelihood */
1.130 brouard 1152: long ipmx=0; /* Number of contributions */
1.126 brouard 1153: double sw; /* Sum of weights */
1154: char filerespow[FILENAMELENGTH];
1155: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1156: FILE *ficresilk;
1157: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1158: FILE *ficresprobmorprev;
1159: FILE *fichtm, *fichtmcov; /* Html File */
1160: FILE *ficreseij;
1161: char filerese[FILENAMELENGTH];
1162: FILE *ficresstdeij;
1163: char fileresstde[FILENAMELENGTH];
1164: FILE *ficrescveij;
1165: char filerescve[FILENAMELENGTH];
1166: FILE *ficresvij;
1167: char fileresv[FILENAMELENGTH];
1.269 brouard 1168:
1.126 brouard 1169: char title[MAXLINE];
1.234 brouard 1170: char model[MAXLINE]; /**< The model line */
1.217 brouard 1171: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1172: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1173: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1174: char command[FILENAMELENGTH];
1175: int outcmd=0;
1176:
1.217 brouard 1177: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1178: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1179: char filelog[FILENAMELENGTH]; /* Log file */
1180: char filerest[FILENAMELENGTH];
1181: char fileregp[FILENAMELENGTH];
1182: char popfile[FILENAMELENGTH];
1183:
1184: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1185:
1.157 brouard 1186: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1187: /* struct timezone tzp; */
1188: /* extern int gettimeofday(); */
1189: struct tm tml, *gmtime(), *localtime();
1190:
1191: extern time_t time();
1192:
1193: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1194: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1195: struct tm tm;
1196:
1.126 brouard 1197: char strcurr[80], strfor[80];
1198:
1199: char *endptr;
1200: long lval;
1201: double dval;
1202:
1203: #define NR_END 1
1204: #define FREE_ARG char*
1205: #define FTOL 1.0e-10
1206:
1207: #define NRANSI
1.240 brouard 1208: #define ITMAX 200
1209: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1210:
1211: #define TOL 2.0e-4
1212:
1213: #define CGOLD 0.3819660
1214: #define ZEPS 1.0e-10
1215: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1216:
1217: #define GOLD 1.618034
1218: #define GLIMIT 100.0
1219: #define TINY 1.0e-20
1220:
1221: static double maxarg1,maxarg2;
1222: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1223: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1224:
1225: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1226: #define rint(a) floor(a+0.5)
1.166 brouard 1227: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1228: #define mytinydouble 1.0e-16
1.166 brouard 1229: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1230: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1231: /* static double dsqrarg; */
1232: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1233: static double sqrarg;
1234: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1235: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1236: int agegomp= AGEGOMP;
1237:
1238: int imx;
1239: int stepm=1;
1240: /* Stepm, step in month: minimum step interpolation*/
1241:
1242: int estepm;
1243: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1244:
1245: int m,nb;
1246: long *num;
1.197 brouard 1247: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1248: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1249: covariate for which somebody answered excluding
1250: undefined. Usually 2: 0 and 1. */
1251: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1252: covariate for which somebody answered including
1253: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1254: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1255: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1256: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1257: double *ageexmed,*agecens;
1258: double dateintmean=0;
1259:
1260: double *weight;
1261: int **s; /* Status */
1.141 brouard 1262: double *agedc;
1.145 brouard 1263: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1264: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1265: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1266: double **coqvar; /* Fixed quantitative covariate nqv */
1267: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1268: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1269: double idx;
1270: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1271: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1272: /*k 1 2 3 4 5 6 7 8 9 */
1273: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1274: /* Tndvar[k] 1 2 3 4 5 */
1275: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1276: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1277: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1278: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1279: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1280: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1281: /* Tprod[i]=k 4 7 */
1282: /* Tage[i]=k 5 8 */
1283: /* */
1284: /* Type */
1285: /* V 1 2 3 4 5 */
1286: /* F F V V V */
1287: /* D Q D D Q */
1288: /* */
1289: int *TvarsD;
1290: int *TvarsDind;
1291: int *TvarsQ;
1292: int *TvarsQind;
1293:
1.235 brouard 1294: #define MAXRESULTLINES 10
1295: int nresult=0;
1.258 brouard 1296: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1297: int TKresult[MAXRESULTLINES];
1.237 brouard 1298: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1299: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1300: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1301: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1302: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1303: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1304:
1.234 brouard 1305: /* 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 1306: 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 */
1307: 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 */
1308: 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 */
1309: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1310: 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 */
1311: 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 1312: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1313: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1314: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1315: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1316: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1317: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1318: 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 */
1319: 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 */
1320:
1.230 brouard 1321: int *Tvarsel; /**< Selected covariates for output */
1322: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1323: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1324: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1325: 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 1326: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1327: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1328: int *Tage;
1.227 brouard 1329: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1330: 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 1331: 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*/
1332: 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 1333: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1334: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1335: int **Tvard;
1336: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1337: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1338: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1339: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1340: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1341: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1342: double *lsurv, *lpop, *tpop;
1343:
1.231 brouard 1344: #define FD 1; /* Fixed dummy covariate */
1345: #define FQ 2; /* Fixed quantitative covariate */
1346: #define FP 3; /* Fixed product covariate */
1347: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1348: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1349: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1350: #define VD 10; /* Varying dummy covariate */
1351: #define VQ 11; /* Varying quantitative covariate */
1352: #define VP 12; /* Varying product covariate */
1353: #define VPDD 13; /* Varying product dummy*dummy covariate */
1354: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1355: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1356: #define APFD 16; /* Age product * fixed dummy covariate */
1357: #define APFQ 17; /* Age product * fixed quantitative covariate */
1358: #define APVD 18; /* Age product * varying dummy covariate */
1359: #define APVQ 19; /* Age product * varying quantitative covariate */
1360:
1361: #define FTYPE 1; /* Fixed covariate */
1362: #define VTYPE 2; /* Varying covariate (loop in wave) */
1363: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1364:
1365: struct kmodel{
1366: int maintype; /* main type */
1367: int subtype; /* subtype */
1368: };
1369: struct kmodel modell[NCOVMAX];
1370:
1.143 brouard 1371: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1372: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1373:
1374: /**************** split *************************/
1375: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1376: {
1377: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1378: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1379: */
1380: char *ss; /* pointer */
1.186 brouard 1381: int l1=0, l2=0; /* length counters */
1.126 brouard 1382:
1383: l1 = strlen(path ); /* length of path */
1384: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1385: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1386: if ( ss == NULL ) { /* no directory, so determine current directory */
1387: strcpy( name, path ); /* we got the fullname name because no directory */
1388: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1389: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1390: /* get current working directory */
1391: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1392: #ifdef WIN32
1393: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1394: #else
1395: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1396: #endif
1.126 brouard 1397: return( GLOCK_ERROR_GETCWD );
1398: }
1399: /* got dirc from getcwd*/
1400: printf(" DIRC = %s \n",dirc);
1.205 brouard 1401: } else { /* strip directory from path */
1.126 brouard 1402: ss++; /* after this, the filename */
1403: l2 = strlen( ss ); /* length of filename */
1404: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1405: strcpy( name, ss ); /* save file name */
1406: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1407: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1408: printf(" DIRC2 = %s \n",dirc);
1409: }
1410: /* We add a separator at the end of dirc if not exists */
1411: l1 = strlen( dirc ); /* length of directory */
1412: if( dirc[l1-1] != DIRSEPARATOR ){
1413: dirc[l1] = DIRSEPARATOR;
1414: dirc[l1+1] = 0;
1415: printf(" DIRC3 = %s \n",dirc);
1416: }
1417: ss = strrchr( name, '.' ); /* find last / */
1418: if (ss >0){
1419: ss++;
1420: strcpy(ext,ss); /* save extension */
1421: l1= strlen( name);
1422: l2= strlen(ss)+1;
1423: strncpy( finame, name, l1-l2);
1424: finame[l1-l2]= 0;
1425: }
1426:
1427: return( 0 ); /* we're done */
1428: }
1429:
1430:
1431: /******************************************/
1432:
1433: void replace_back_to_slash(char *s, char*t)
1434: {
1435: int i;
1436: int lg=0;
1437: i=0;
1438: lg=strlen(t);
1439: for(i=0; i<= lg; i++) {
1440: (s[i] = t[i]);
1441: if (t[i]== '\\') s[i]='/';
1442: }
1443: }
1444:
1.132 brouard 1445: char *trimbb(char *out, char *in)
1.137 brouard 1446: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1447: char *s;
1448: s=out;
1449: while (*in != '\0'){
1.137 brouard 1450: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1451: in++;
1452: }
1453: *out++ = *in++;
1454: }
1455: *out='\0';
1456: return s;
1457: }
1458:
1.187 brouard 1459: /* char *substrchaine(char *out, char *in, char *chain) */
1460: /* { */
1461: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1462: /* char *s, *t; */
1463: /* t=in;s=out; */
1464: /* while ((*in != *chain) && (*in != '\0')){ */
1465: /* *out++ = *in++; */
1466: /* } */
1467:
1468: /* /\* *in matches *chain *\/ */
1469: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1470: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1471: /* } */
1472: /* in--; chain--; */
1473: /* while ( (*in != '\0')){ */
1474: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1475: /* *out++ = *in++; */
1476: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1477: /* } */
1478: /* *out='\0'; */
1479: /* out=s; */
1480: /* return out; */
1481: /* } */
1482: char *substrchaine(char *out, char *in, char *chain)
1483: {
1484: /* Substract chain 'chain' from 'in', return and output 'out' */
1485: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1486:
1487: char *strloc;
1488:
1489: strcpy (out, in);
1490: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1491: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1492: if(strloc != NULL){
1493: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1494: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1495: /* strcpy (strloc, strloc +strlen(chain));*/
1496: }
1497: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1498: return out;
1499: }
1500:
1501:
1.145 brouard 1502: char *cutl(char *blocc, char *alocc, char *in, char occ)
1503: {
1.187 brouard 1504: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1505: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1506: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1507: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1508: */
1.160 brouard 1509: char *s, *t;
1.145 brouard 1510: t=in;s=in;
1511: while ((*in != occ) && (*in != '\0')){
1512: *alocc++ = *in++;
1513: }
1514: if( *in == occ){
1515: *(alocc)='\0';
1516: s=++in;
1517: }
1518:
1519: if (s == t) {/* occ not found */
1520: *(alocc-(in-s))='\0';
1521: in=s;
1522: }
1523: while ( *in != '\0'){
1524: *blocc++ = *in++;
1525: }
1526:
1527: *blocc='\0';
1528: return t;
1529: }
1.137 brouard 1530: char *cutv(char *blocc, char *alocc, char *in, char occ)
1531: {
1.187 brouard 1532: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1533: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1534: gives blocc="abcdef2ghi" and alocc="j".
1535: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1536: */
1537: char *s, *t;
1538: t=in;s=in;
1539: while (*in != '\0'){
1540: while( *in == occ){
1541: *blocc++ = *in++;
1542: s=in;
1543: }
1544: *blocc++ = *in++;
1545: }
1546: if (s == t) /* occ not found */
1547: *(blocc-(in-s))='\0';
1548: else
1549: *(blocc-(in-s)-1)='\0';
1550: in=s;
1551: while ( *in != '\0'){
1552: *alocc++ = *in++;
1553: }
1554:
1555: *alocc='\0';
1556: return s;
1557: }
1558:
1.126 brouard 1559: int nbocc(char *s, char occ)
1560: {
1561: int i,j=0;
1562: int lg=20;
1563: i=0;
1564: lg=strlen(s);
1565: for(i=0; i<= lg; i++) {
1.234 brouard 1566: if (s[i] == occ ) j++;
1.126 brouard 1567: }
1568: return j;
1569: }
1570:
1.137 brouard 1571: /* void cutv(char *u,char *v, char*t, char occ) */
1572: /* { */
1573: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1574: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1575: /* gives u="abcdef2ghi" and v="j" *\/ */
1576: /* int i,lg,j,p=0; */
1577: /* i=0; */
1578: /* lg=strlen(t); */
1579: /* for(j=0; j<=lg-1; j++) { */
1580: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1581: /* } */
1.126 brouard 1582:
1.137 brouard 1583: /* for(j=0; j<p; j++) { */
1584: /* (u[j] = t[j]); */
1585: /* } */
1586: /* u[p]='\0'; */
1.126 brouard 1587:
1.137 brouard 1588: /* for(j=0; j<= lg; j++) { */
1589: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1590: /* } */
1591: /* } */
1.126 brouard 1592:
1.160 brouard 1593: #ifdef _WIN32
1594: char * strsep(char **pp, const char *delim)
1595: {
1596: char *p, *q;
1597:
1598: if ((p = *pp) == NULL)
1599: return 0;
1600: if ((q = strpbrk (p, delim)) != NULL)
1601: {
1602: *pp = q + 1;
1603: *q = '\0';
1604: }
1605: else
1606: *pp = 0;
1607: return p;
1608: }
1609: #endif
1610:
1.126 brouard 1611: /********************** nrerror ********************/
1612:
1613: void nrerror(char error_text[])
1614: {
1615: fprintf(stderr,"ERREUR ...\n");
1616: fprintf(stderr,"%s\n",error_text);
1617: exit(EXIT_FAILURE);
1618: }
1619: /*********************** vector *******************/
1620: double *vector(int nl, int nh)
1621: {
1622: double *v;
1623: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1624: if (!v) nrerror("allocation failure in vector");
1625: return v-nl+NR_END;
1626: }
1627:
1628: /************************ free vector ******************/
1629: void free_vector(double*v, int nl, int nh)
1630: {
1631: free((FREE_ARG)(v+nl-NR_END));
1632: }
1633:
1634: /************************ivector *******************************/
1635: int *ivector(long nl,long nh)
1636: {
1637: int *v;
1638: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1639: if (!v) nrerror("allocation failure in ivector");
1640: return v-nl+NR_END;
1641: }
1642:
1643: /******************free ivector **************************/
1644: void free_ivector(int *v, long nl, long nh)
1645: {
1646: free((FREE_ARG)(v+nl-NR_END));
1647: }
1648:
1649: /************************lvector *******************************/
1650: long *lvector(long nl,long nh)
1651: {
1652: long *v;
1653: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1654: if (!v) nrerror("allocation failure in ivector");
1655: return v-nl+NR_END;
1656: }
1657:
1658: /******************free lvector **************************/
1659: void free_lvector(long *v, long nl, long nh)
1660: {
1661: free((FREE_ARG)(v+nl-NR_END));
1662: }
1663:
1664: /******************* imatrix *******************************/
1665: int **imatrix(long nrl, long nrh, long ncl, long nch)
1666: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1667: {
1668: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1669: int **m;
1670:
1671: /* allocate pointers to rows */
1672: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1673: if (!m) nrerror("allocation failure 1 in matrix()");
1674: m += NR_END;
1675: m -= nrl;
1676:
1677:
1678: /* allocate rows and set pointers to them */
1679: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1680: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1681: m[nrl] += NR_END;
1682: m[nrl] -= ncl;
1683:
1684: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1685:
1686: /* return pointer to array of pointers to rows */
1687: return m;
1688: }
1689:
1690: /****************** free_imatrix *************************/
1691: void free_imatrix(m,nrl,nrh,ncl,nch)
1692: int **m;
1693: long nch,ncl,nrh,nrl;
1694: /* free an int matrix allocated by imatrix() */
1695: {
1696: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1697: free((FREE_ARG) (m+nrl-NR_END));
1698: }
1699:
1700: /******************* matrix *******************************/
1701: double **matrix(long nrl, long nrh, long ncl, long nch)
1702: {
1703: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1704: double **m;
1705:
1706: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1707: if (!m) nrerror("allocation failure 1 in matrix()");
1708: m += NR_END;
1709: m -= nrl;
1710:
1711: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1712: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1713: m[nrl] += NR_END;
1714: m[nrl] -= ncl;
1715:
1716: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1717: return m;
1.145 brouard 1718: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1719: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1720: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1721: */
1722: }
1723:
1724: /*************************free matrix ************************/
1725: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1726: {
1727: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1728: free((FREE_ARG)(m+nrl-NR_END));
1729: }
1730:
1731: /******************* ma3x *******************************/
1732: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1733: {
1734: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1735: double ***m;
1736:
1737: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1738: if (!m) nrerror("allocation failure 1 in matrix()");
1739: m += NR_END;
1740: m -= nrl;
1741:
1742: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1743: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1744: m[nrl] += NR_END;
1745: m[nrl] -= ncl;
1746:
1747: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1748:
1749: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1750: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1751: m[nrl][ncl] += NR_END;
1752: m[nrl][ncl] -= nll;
1753: for (j=ncl+1; j<=nch; j++)
1754: m[nrl][j]=m[nrl][j-1]+nlay;
1755:
1756: for (i=nrl+1; i<=nrh; i++) {
1757: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1758: for (j=ncl+1; j<=nch; j++)
1759: m[i][j]=m[i][j-1]+nlay;
1760: }
1761: return m;
1762: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1763: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1764: */
1765: }
1766:
1767: /*************************free ma3x ************************/
1768: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1769: {
1770: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1771: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1772: free((FREE_ARG)(m+nrl-NR_END));
1773: }
1774:
1775: /*************** function subdirf ***********/
1776: char *subdirf(char fileres[])
1777: {
1778: /* Caution optionfilefiname is hidden */
1779: strcpy(tmpout,optionfilefiname);
1780: strcat(tmpout,"/"); /* Add to the right */
1781: strcat(tmpout,fileres);
1782: return tmpout;
1783: }
1784:
1785: /*************** function subdirf2 ***********/
1786: char *subdirf2(char fileres[], char *preop)
1787: {
1788:
1789: /* Caution optionfilefiname is hidden */
1790: strcpy(tmpout,optionfilefiname);
1791: strcat(tmpout,"/");
1792: strcat(tmpout,preop);
1793: strcat(tmpout,fileres);
1794: return tmpout;
1795: }
1796:
1797: /*************** function subdirf3 ***********/
1798: char *subdirf3(char fileres[], char *preop, char *preop2)
1799: {
1800:
1801: /* Caution optionfilefiname is hidden */
1802: strcpy(tmpout,optionfilefiname);
1803: strcat(tmpout,"/");
1804: strcat(tmpout,preop);
1805: strcat(tmpout,preop2);
1806: strcat(tmpout,fileres);
1807: return tmpout;
1808: }
1.213 brouard 1809:
1810: /*************** function subdirfext ***********/
1811: char *subdirfext(char fileres[], char *preop, char *postop)
1812: {
1813:
1814: strcpy(tmpout,preop);
1815: strcat(tmpout,fileres);
1816: strcat(tmpout,postop);
1817: return tmpout;
1818: }
1.126 brouard 1819:
1.213 brouard 1820: /*************** function subdirfext3 ***********/
1821: char *subdirfext3(char fileres[], char *preop, char *postop)
1822: {
1823:
1824: /* Caution optionfilefiname is hidden */
1825: strcpy(tmpout,optionfilefiname);
1826: strcat(tmpout,"/");
1827: strcat(tmpout,preop);
1828: strcat(tmpout,fileres);
1829: strcat(tmpout,postop);
1830: return tmpout;
1831: }
1832:
1.162 brouard 1833: char *asc_diff_time(long time_sec, char ascdiff[])
1834: {
1835: long sec_left, days, hours, minutes;
1836: days = (time_sec) / (60*60*24);
1837: sec_left = (time_sec) % (60*60*24);
1838: hours = (sec_left) / (60*60) ;
1839: sec_left = (sec_left) %(60*60);
1840: minutes = (sec_left) /60;
1841: sec_left = (sec_left) % (60);
1842: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1843: return ascdiff;
1844: }
1845:
1.126 brouard 1846: /***************** f1dim *************************/
1847: extern int ncom;
1848: extern double *pcom,*xicom;
1849: extern double (*nrfunc)(double []);
1850:
1851: double f1dim(double x)
1852: {
1853: int j;
1854: double f;
1855: double *xt;
1856:
1857: xt=vector(1,ncom);
1858: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1859: f=(*nrfunc)(xt);
1860: free_vector(xt,1,ncom);
1861: return f;
1862: }
1863:
1864: /*****************brent *************************/
1865: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1866: {
1867: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1868: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1869: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1870: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1871: * returned function value.
1872: */
1.126 brouard 1873: int iter;
1874: double a,b,d,etemp;
1.159 brouard 1875: double fu=0,fv,fw,fx;
1.164 brouard 1876: double ftemp=0.;
1.126 brouard 1877: double p,q,r,tol1,tol2,u,v,w,x,xm;
1878: double e=0.0;
1879:
1880: a=(ax < cx ? ax : cx);
1881: b=(ax > cx ? ax : cx);
1882: x=w=v=bx;
1883: fw=fv=fx=(*f)(x);
1884: for (iter=1;iter<=ITMAX;iter++) {
1885: xm=0.5*(a+b);
1886: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1887: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1888: printf(".");fflush(stdout);
1889: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1890: #ifdef DEBUGBRENT
1.126 brouard 1891: 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);
1892: 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);
1893: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1894: #endif
1895: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1896: *xmin=x;
1897: return fx;
1898: }
1899: ftemp=fu;
1900: if (fabs(e) > tol1) {
1901: r=(x-w)*(fx-fv);
1902: q=(x-v)*(fx-fw);
1903: p=(x-v)*q-(x-w)*r;
1904: q=2.0*(q-r);
1905: if (q > 0.0) p = -p;
1906: q=fabs(q);
1907: etemp=e;
1908: e=d;
1909: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1910: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1911: else {
1.224 brouard 1912: d=p/q;
1913: u=x+d;
1914: if (u-a < tol2 || b-u < tol2)
1915: d=SIGN(tol1,xm-x);
1.126 brouard 1916: }
1917: } else {
1918: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1919: }
1920: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1921: fu=(*f)(u);
1922: if (fu <= fx) {
1923: if (u >= x) a=x; else b=x;
1924: SHFT(v,w,x,u)
1.183 brouard 1925: SHFT(fv,fw,fx,fu)
1926: } else {
1927: if (u < x) a=u; else b=u;
1928: if (fu <= fw || w == x) {
1.224 brouard 1929: v=w;
1930: w=u;
1931: fv=fw;
1932: fw=fu;
1.183 brouard 1933: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1934: v=u;
1935: fv=fu;
1.183 brouard 1936: }
1937: }
1.126 brouard 1938: }
1939: nrerror("Too many iterations in brent");
1940: *xmin=x;
1941: return fx;
1942: }
1943:
1944: /****************** mnbrak ***********************/
1945:
1946: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1947: double (*func)(double))
1.183 brouard 1948: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1949: the downhill direction (defined by the function as evaluated at the initial points) and returns
1950: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1951: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1952: */
1.126 brouard 1953: double ulim,u,r,q, dum;
1954: double fu;
1.187 brouard 1955:
1956: double scale=10.;
1957: int iterscale=0;
1958:
1959: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1960: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1961:
1962:
1963: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1964: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1965: /* *bx = *ax - (*ax - *bx)/scale; */
1966: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1967: /* } */
1968:
1.126 brouard 1969: if (*fb > *fa) {
1970: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1971: SHFT(dum,*fb,*fa,dum)
1972: }
1.126 brouard 1973: *cx=(*bx)+GOLD*(*bx-*ax);
1974: *fc=(*func)(*cx);
1.183 brouard 1975: #ifdef DEBUG
1.224 brouard 1976: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1977: 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 1978: #endif
1.224 brouard 1979: 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 1980: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1981: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1982: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1983: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1984: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1985: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1986: fu=(*func)(u);
1.163 brouard 1987: #ifdef DEBUG
1988: /* f(x)=A(x-u)**2+f(u) */
1989: double A, fparabu;
1990: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1991: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1992: 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);
1993: 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 1994: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1995: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1996: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1997: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1998: #endif
1.184 brouard 1999: #ifdef MNBRAKORIGINAL
1.183 brouard 2000: #else
1.191 brouard 2001: /* if (fu > *fc) { */
2002: /* #ifdef DEBUG */
2003: /* printf("mnbrak4 fu > fc \n"); */
2004: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2005: /* #endif */
2006: /* /\* 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 *\\/ *\/ */
2007: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2008: /* dum=u; /\* Shifting c and u *\/ */
2009: /* u = *cx; */
2010: /* *cx = dum; */
2011: /* dum = fu; */
2012: /* fu = *fc; */
2013: /* *fc =dum; */
2014: /* } else { /\* end *\/ */
2015: /* #ifdef DEBUG */
2016: /* printf("mnbrak3 fu < fc \n"); */
2017: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2018: /* #endif */
2019: /* dum=u; /\* Shifting c and u *\/ */
2020: /* u = *cx; */
2021: /* *cx = dum; */
2022: /* dum = fu; */
2023: /* fu = *fc; */
2024: /* *fc =dum; */
2025: /* } */
1.224 brouard 2026: #ifdef DEBUGMNBRAK
2027: double A, fparabu;
2028: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2029: fparabu= *fa - A*(*ax-u)*(*ax-u);
2030: 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);
2031: 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 2032: #endif
1.191 brouard 2033: dum=u; /* Shifting c and u */
2034: u = *cx;
2035: *cx = dum;
2036: dum = fu;
2037: fu = *fc;
2038: *fc =dum;
1.183 brouard 2039: #endif
1.162 brouard 2040: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2041: #ifdef DEBUG
1.224 brouard 2042: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2043: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2044: #endif
1.126 brouard 2045: fu=(*func)(u);
2046: if (fu < *fc) {
1.183 brouard 2047: #ifdef DEBUG
1.224 brouard 2048: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2049: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2050: #endif
2051: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2052: SHFT(*fb,*fc,fu,(*func)(u))
2053: #ifdef DEBUG
2054: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2055: #endif
2056: }
1.162 brouard 2057: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2058: #ifdef DEBUG
1.224 brouard 2059: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2060: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2061: #endif
1.126 brouard 2062: u=ulim;
2063: fu=(*func)(u);
1.183 brouard 2064: } else { /* u could be left to b (if r > q parabola has a maximum) */
2065: #ifdef DEBUG
1.224 brouard 2066: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2067: 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 2068: #endif
1.126 brouard 2069: u=(*cx)+GOLD*(*cx-*bx);
2070: fu=(*func)(u);
1.224 brouard 2071: #ifdef DEBUG
2072: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2073: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2074: #endif
1.183 brouard 2075: } /* end tests */
1.126 brouard 2076: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2077: SHFT(*fa,*fb,*fc,fu)
2078: #ifdef DEBUG
1.224 brouard 2079: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2080: 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 2081: #endif
2082: } /* 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 2083: }
2084:
2085: /*************** linmin ************************/
1.162 brouard 2086: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2087: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2088: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2089: the value of func at the returned location p . This is actually all accomplished by calling the
2090: routines mnbrak and brent .*/
1.126 brouard 2091: int ncom;
2092: double *pcom,*xicom;
2093: double (*nrfunc)(double []);
2094:
1.224 brouard 2095: #ifdef LINMINORIGINAL
1.126 brouard 2096: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2097: #else
2098: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2099: #endif
1.126 brouard 2100: {
2101: double brent(double ax, double bx, double cx,
2102: double (*f)(double), double tol, double *xmin);
2103: double f1dim(double x);
2104: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2105: double *fc, double (*func)(double));
2106: int j;
2107: double xx,xmin,bx,ax;
2108: double fx,fb,fa;
1.187 brouard 2109:
1.203 brouard 2110: #ifdef LINMINORIGINAL
2111: #else
2112: double scale=10., axs, xxs; /* Scale added for infinity */
2113: #endif
2114:
1.126 brouard 2115: ncom=n;
2116: pcom=vector(1,n);
2117: xicom=vector(1,n);
2118: nrfunc=func;
2119: for (j=1;j<=n;j++) {
2120: pcom[j]=p[j];
1.202 brouard 2121: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2122: }
1.187 brouard 2123:
1.203 brouard 2124: #ifdef LINMINORIGINAL
2125: xx=1.;
2126: #else
2127: axs=0.0;
2128: xxs=1.;
2129: do{
2130: xx= xxs;
2131: #endif
1.187 brouard 2132: ax=0.;
2133: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2134: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2135: /* 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)) */
2136: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2137: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2138: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2139: /* 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 2140: #ifdef LINMINORIGINAL
2141: #else
2142: if (fx != fx){
1.224 brouard 2143: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2144: printf("|");
2145: fprintf(ficlog,"|");
1.203 brouard 2146: #ifdef DEBUGLINMIN
1.224 brouard 2147: 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 2148: #endif
2149: }
1.224 brouard 2150: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2151: #endif
2152:
1.191 brouard 2153: #ifdef DEBUGLINMIN
2154: 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 2155: 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 2156: #endif
1.224 brouard 2157: #ifdef LINMINORIGINAL
2158: #else
2159: if(fb == fx){ /* Flat function in the direction */
2160: xmin=xx;
2161: *flat=1;
2162: }else{
2163: *flat=0;
2164: #endif
2165: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2166: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2167: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2168: /* fmin = f(p[j] + xmin * xi[j]) */
2169: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2170: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2171: #ifdef DEBUG
1.224 brouard 2172: 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);
2173: 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);
2174: #endif
2175: #ifdef LINMINORIGINAL
2176: #else
2177: }
1.126 brouard 2178: #endif
1.191 brouard 2179: #ifdef DEBUGLINMIN
2180: printf("linmin end ");
1.202 brouard 2181: fprintf(ficlog,"linmin end ");
1.191 brouard 2182: #endif
1.126 brouard 2183: for (j=1;j<=n;j++) {
1.203 brouard 2184: #ifdef LINMINORIGINAL
2185: xi[j] *= xmin;
2186: #else
2187: #ifdef DEBUGLINMIN
2188: if(xxs <1.0)
2189: printf(" before xi[%d]=%12.8f", j,xi[j]);
2190: #endif
2191: 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) */
2192: #ifdef DEBUGLINMIN
2193: if(xxs <1.0)
2194: 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 );
2195: #endif
2196: #endif
1.187 brouard 2197: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2198: }
1.191 brouard 2199: #ifdef DEBUGLINMIN
1.203 brouard 2200: printf("\n");
1.191 brouard 2201: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2202: 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 2203: for (j=1;j<=n;j++) {
1.202 brouard 2204: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2205: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2206: if(j % ncovmodel == 0){
1.191 brouard 2207: printf("\n");
1.202 brouard 2208: fprintf(ficlog,"\n");
2209: }
1.191 brouard 2210: }
1.203 brouard 2211: #else
1.191 brouard 2212: #endif
1.126 brouard 2213: free_vector(xicom,1,n);
2214: free_vector(pcom,1,n);
2215: }
2216:
2217:
2218: /*************** powell ************************/
1.162 brouard 2219: /*
2220: Minimization of a function func of n variables. Input consists of an initial starting point
2221: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2222: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2223: such that failure to decrease by more than this amount on one iteration signals doneness. On
2224: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2225: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2226: */
1.224 brouard 2227: #ifdef LINMINORIGINAL
2228: #else
2229: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2230: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2231: #endif
1.126 brouard 2232: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2233: double (*func)(double []))
2234: {
1.224 brouard 2235: #ifdef LINMINORIGINAL
2236: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2237: double (*func)(double []));
1.224 brouard 2238: #else
1.241 brouard 2239: void linmin(double p[], double xi[], int n, double *fret,
2240: double (*func)(double []),int *flat);
1.224 brouard 2241: #endif
1.239 brouard 2242: int i,ibig,j,jk,k;
1.126 brouard 2243: double del,t,*pt,*ptt,*xit;
1.181 brouard 2244: double directest;
1.126 brouard 2245: double fp,fptt;
2246: double *xits;
2247: int niterf, itmp;
1.224 brouard 2248: #ifdef LINMINORIGINAL
2249: #else
2250:
2251: flatdir=ivector(1,n);
2252: for (j=1;j<=n;j++) flatdir[j]=0;
2253: #endif
1.126 brouard 2254:
2255: pt=vector(1,n);
2256: ptt=vector(1,n);
2257: xit=vector(1,n);
2258: xits=vector(1,n);
2259: *fret=(*func)(p);
2260: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2261: rcurr_time = time(NULL);
1.126 brouard 2262: for (*iter=1;;++(*iter)) {
1.187 brouard 2263: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2264: ibig=0;
2265: del=0.0;
1.157 brouard 2266: rlast_time=rcurr_time;
2267: /* (void) gettimeofday(&curr_time,&tzp); */
2268: rcurr_time = time(NULL);
2269: curr_time = *localtime(&rcurr_time);
2270: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2271: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2272: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2273: for (i=1;i<=n;i++) {
1.126 brouard 2274: fprintf(ficrespow," %.12lf", p[i]);
2275: }
1.239 brouard 2276: fprintf(ficrespow,"\n");fflush(ficrespow);
2277: printf("\n#model= 1 + age ");
2278: fprintf(ficlog,"\n#model= 1 + age ");
2279: if(nagesqr==1){
1.241 brouard 2280: printf(" + age*age ");
2281: fprintf(ficlog," + age*age ");
1.239 brouard 2282: }
2283: for(j=1;j <=ncovmodel-2;j++){
2284: if(Typevar[j]==0) {
2285: printf(" + V%d ",Tvar[j]);
2286: fprintf(ficlog," + V%d ",Tvar[j]);
2287: }else if(Typevar[j]==1) {
2288: printf(" + V%d*age ",Tvar[j]);
2289: fprintf(ficlog," + V%d*age ",Tvar[j]);
2290: }else if(Typevar[j]==2) {
2291: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2292: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2293: }
2294: }
1.126 brouard 2295: printf("\n");
1.239 brouard 2296: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2297: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2298: fprintf(ficlog,"\n");
1.239 brouard 2299: for(i=1,jk=1; i <=nlstate; i++){
2300: for(k=1; k <=(nlstate+ndeath); k++){
2301: if (k != i) {
2302: printf("%d%d ",i,k);
2303: fprintf(ficlog,"%d%d ",i,k);
2304: for(j=1; j <=ncovmodel; j++){
2305: printf("%12.7f ",p[jk]);
2306: fprintf(ficlog,"%12.7f ",p[jk]);
2307: jk++;
2308: }
2309: printf("\n");
2310: fprintf(ficlog,"\n");
2311: }
2312: }
2313: }
1.241 brouard 2314: if(*iter <=3 && *iter >1){
1.157 brouard 2315: tml = *localtime(&rcurr_time);
2316: strcpy(strcurr,asctime(&tml));
2317: rforecast_time=rcurr_time;
1.126 brouard 2318: itmp = strlen(strcurr);
2319: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2320: strcurr[itmp-1]='\0';
1.162 brouard 2321: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2322: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2323: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2324: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2325: forecast_time = *localtime(&rforecast_time);
2326: strcpy(strfor,asctime(&forecast_time));
2327: itmp = strlen(strfor);
2328: if(strfor[itmp-1]=='\n')
2329: strfor[itmp-1]='\0';
2330: 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);
2331: 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 2332: }
2333: }
1.187 brouard 2334: for (i=1;i<=n;i++) { /* For each direction i */
2335: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2336: fptt=(*fret);
2337: #ifdef DEBUG
1.203 brouard 2338: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2339: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2340: #endif
1.203 brouard 2341: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2342: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2343: #ifdef LINMINORIGINAL
1.188 brouard 2344: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2345: #else
2346: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2347: flatdir[i]=flat; /* Function is vanishing in that direction i */
2348: #endif
2349: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2350: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2351: /* because that direction will be replaced unless the gain del is small */
2352: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2353: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2354: /* with the new direction. */
2355: del=fabs(fptt-(*fret));
2356: ibig=i;
1.126 brouard 2357: }
2358: #ifdef DEBUG
2359: printf("%d %.12e",i,(*fret));
2360: fprintf(ficlog,"%d %.12e",i,(*fret));
2361: for (j=1;j<=n;j++) {
1.224 brouard 2362: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2363: printf(" x(%d)=%.12e",j,xit[j]);
2364: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2365: }
2366: for(j=1;j<=n;j++) {
1.225 brouard 2367: printf(" p(%d)=%.12e",j,p[j]);
2368: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2369: }
2370: printf("\n");
2371: fprintf(ficlog,"\n");
2372: #endif
1.187 brouard 2373: } /* end loop on each direction i */
2374: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2375: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2376: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2377: for(j=1;j<=n;j++) {
1.225 brouard 2378: if(flatdir[j] >0){
2379: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2380: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2381: }
2382: /* printf("\n"); */
2383: /* fprintf(ficlog,"\n"); */
2384: }
1.243 brouard 2385: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2386: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2387: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2388: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2389: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2390: /* decreased of more than 3.84 */
2391: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2392: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2393: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2394:
1.188 brouard 2395: /* Starting the program with initial values given by a former maximization will simply change */
2396: /* the scales of the directions and the directions, because the are reset to canonical directions */
2397: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2398: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2399: #ifdef DEBUG
2400: int k[2],l;
2401: k[0]=1;
2402: k[1]=-1;
2403: printf("Max: %.12e",(*func)(p));
2404: fprintf(ficlog,"Max: %.12e",(*func)(p));
2405: for (j=1;j<=n;j++) {
2406: printf(" %.12e",p[j]);
2407: fprintf(ficlog," %.12e",p[j]);
2408: }
2409: printf("\n");
2410: fprintf(ficlog,"\n");
2411: for(l=0;l<=1;l++) {
2412: for (j=1;j<=n;j++) {
2413: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2414: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2415: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2416: }
2417: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2418: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2419: }
2420: #endif
2421:
1.224 brouard 2422: #ifdef LINMINORIGINAL
2423: #else
2424: free_ivector(flatdir,1,n);
2425: #endif
1.126 brouard 2426: free_vector(xit,1,n);
2427: free_vector(xits,1,n);
2428: free_vector(ptt,1,n);
2429: free_vector(pt,1,n);
2430: return;
1.192 brouard 2431: } /* enough precision */
1.240 brouard 2432: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2433: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2434: ptt[j]=2.0*p[j]-pt[j];
2435: xit[j]=p[j]-pt[j];
2436: pt[j]=p[j];
2437: }
1.181 brouard 2438: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2439: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2440: if (*iter <=4) {
1.225 brouard 2441: #else
2442: #endif
1.224 brouard 2443: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2444: #else
1.161 brouard 2445: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2446: #endif
1.162 brouard 2447: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2448: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2449: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2450: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2451: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2452: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2453: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2454: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2455: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2456: /* Even if f3 <f1, directest can be negative and t >0 */
2457: /* mu² and del² are equal when f3=f1 */
2458: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2459: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2460: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2461: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2462: #ifdef NRCORIGINAL
2463: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2464: #else
2465: 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 2466: t= t- del*SQR(fp-fptt);
1.183 brouard 2467: #endif
1.202 brouard 2468: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2469: #ifdef DEBUG
1.181 brouard 2470: 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);
2471: 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 2472: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2473: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2474: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2475: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2476: 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);
2477: 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);
2478: #endif
1.183 brouard 2479: #ifdef POWELLORIGINAL
2480: if (t < 0.0) { /* Then we use it for new direction */
2481: #else
1.182 brouard 2482: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2483: 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 2484: 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 2485: 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 2486: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2487: }
1.181 brouard 2488: if (directest < 0.0) { /* Then we use it for new direction */
2489: #endif
1.191 brouard 2490: #ifdef DEBUGLINMIN
1.234 brouard 2491: printf("Before linmin in direction P%d-P0\n",n);
2492: for (j=1;j<=n;j++) {
2493: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2494: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2495: if(j % ncovmodel == 0){
2496: printf("\n");
2497: fprintf(ficlog,"\n");
2498: }
2499: }
1.224 brouard 2500: #endif
2501: #ifdef LINMINORIGINAL
1.234 brouard 2502: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2503: #else
1.234 brouard 2504: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2505: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2506: #endif
1.234 brouard 2507:
1.191 brouard 2508: #ifdef DEBUGLINMIN
1.234 brouard 2509: for (j=1;j<=n;j++) {
2510: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2511: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2512: if(j % ncovmodel == 0){
2513: printf("\n");
2514: fprintf(ficlog,"\n");
2515: }
2516: }
1.224 brouard 2517: #endif
1.234 brouard 2518: for (j=1;j<=n;j++) {
2519: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2520: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2521: }
1.224 brouard 2522: #ifdef LINMINORIGINAL
2523: #else
1.234 brouard 2524: for (j=1, flatd=0;j<=n;j++) {
2525: if(flatdir[j]>0)
2526: flatd++;
2527: }
2528: if(flatd >0){
1.255 brouard 2529: printf("%d flat directions: ",flatd);
2530: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2531: for (j=1;j<=n;j++) {
2532: if(flatdir[j]>0){
2533: printf("%d ",j);
2534: fprintf(ficlog,"%d ",j);
2535: }
2536: }
2537: printf("\n");
2538: fprintf(ficlog,"\n");
2539: }
1.191 brouard 2540: #endif
1.234 brouard 2541: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2542: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2543:
1.126 brouard 2544: #ifdef DEBUG
1.234 brouard 2545: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2546: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2547: for(j=1;j<=n;j++){
2548: printf(" %lf",xit[j]);
2549: fprintf(ficlog," %lf",xit[j]);
2550: }
2551: printf("\n");
2552: fprintf(ficlog,"\n");
1.126 brouard 2553: #endif
1.192 brouard 2554: } /* end of t or directest negative */
1.224 brouard 2555: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2556: #else
1.234 brouard 2557: } /* end if (fptt < fp) */
1.192 brouard 2558: #endif
1.225 brouard 2559: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2560: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2561: #else
1.224 brouard 2562: #endif
1.234 brouard 2563: } /* loop iteration */
1.126 brouard 2564: }
1.234 brouard 2565:
1.126 brouard 2566: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2567:
1.235 brouard 2568: 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 2569: {
1.279 brouard 2570: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2571: * (and selected quantitative values in nres)
2572: * by left multiplying the unit
2573: * matrix by transitions matrix until convergence is reached with precision ftolpl
2574: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2575: * Wx is row vector: population in state 1, population in state 2, population dead
2576: * or prevalence in state 1, prevalence in state 2, 0
2577: * newm is the matrix after multiplications, its rows are identical at a factor.
2578: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2579: * Output is prlim.
2580: * Initial matrix pimij
2581: */
1.206 brouard 2582: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2583: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2584: /* 0, 0 , 1} */
2585: /*
2586: * and after some iteration: */
2587: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2588: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2589: /* 0, 0 , 1} */
2590: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2591: /* {0.51571254859325999, 0.4842874514067399, */
2592: /* 0.51326036147820708, 0.48673963852179264} */
2593: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2594:
1.126 brouard 2595: int i, ii,j,k;
1.209 brouard 2596: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2597: /* double **matprod2(); */ /* test */
1.218 brouard 2598: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2599: double **newm;
1.209 brouard 2600: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2601: int ncvloop=0;
1.288 brouard 2602: int first=0;
1.169 brouard 2603:
1.209 brouard 2604: min=vector(1,nlstate);
2605: max=vector(1,nlstate);
2606: meandiff=vector(1,nlstate);
2607:
1.218 brouard 2608: /* Starting with matrix unity */
1.126 brouard 2609: for (ii=1;ii<=nlstate+ndeath;ii++)
2610: for (j=1;j<=nlstate+ndeath;j++){
2611: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2612: }
1.169 brouard 2613:
2614: cov[1]=1.;
2615:
2616: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2617: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2618: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2619: ncvloop++;
1.126 brouard 2620: newm=savm;
2621: /* Covariates have to be included here again */
1.138 brouard 2622: cov[2]=agefin;
1.187 brouard 2623: if(nagesqr==1)
2624: cov[3]= agefin*agefin;;
1.234 brouard 2625: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2626: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2627: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2628: /* 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 2629: }
2630: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2631: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2632: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2633: /* 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 2634: }
1.237 brouard 2635: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2636: if(Dummy[Tvar[Tage[k]]]){
2637: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2638: } else{
1.235 brouard 2639: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2640: }
1.235 brouard 2641: /* 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 2642: }
1.237 brouard 2643: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2644: /* 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 2645: if(Dummy[Tvard[k][1]==0]){
2646: if(Dummy[Tvard[k][2]==0]){
2647: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2648: }else{
2649: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2650: }
2651: }else{
2652: if(Dummy[Tvard[k][2]==0]){
2653: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2654: }else{
2655: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2656: }
2657: }
1.234 brouard 2658: }
1.138 brouard 2659: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2660: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2661: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2662: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2663: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2664: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2665: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2666:
1.126 brouard 2667: savm=oldm;
2668: oldm=newm;
1.209 brouard 2669:
2670: for(j=1; j<=nlstate; j++){
2671: max[j]=0.;
2672: min[j]=1.;
2673: }
2674: for(i=1;i<=nlstate;i++){
2675: sumnew=0;
2676: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2677: for(j=1; j<=nlstate; j++){
2678: prlim[i][j]= newm[i][j]/(1-sumnew);
2679: max[j]=FMAX(max[j],prlim[i][j]);
2680: min[j]=FMIN(min[j],prlim[i][j]);
2681: }
2682: }
2683:
1.126 brouard 2684: maxmax=0.;
1.209 brouard 2685: for(j=1; j<=nlstate; j++){
2686: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2687: maxmax=FMAX(maxmax,meandiff[j]);
2688: /* 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 2689: } /* j loop */
1.203 brouard 2690: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2691: /* 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 2692: if(maxmax < ftolpl){
1.209 brouard 2693: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2694: free_vector(min,1,nlstate);
2695: free_vector(max,1,nlstate);
2696: free_vector(meandiff,1,nlstate);
1.126 brouard 2697: return prlim;
2698: }
1.288 brouard 2699: } /* agefin loop */
1.208 brouard 2700: /* After some age loop it doesn't converge */
1.288 brouard 2701: if(!first){
2702: first=1;
2703: 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);
2704: }
2705: 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);
2706:
1.209 brouard 2707: /* 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); */
2708: free_vector(min,1,nlstate);
2709: free_vector(max,1,nlstate);
2710: free_vector(meandiff,1,nlstate);
1.208 brouard 2711:
1.169 brouard 2712: return prlim; /* should not reach here */
1.126 brouard 2713: }
2714:
1.217 brouard 2715:
2716: /**** Back Prevalence limit (stable or period prevalence) ****************/
2717:
1.218 brouard 2718: /* 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) */
2719: /* 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 2720: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2721: {
1.264 brouard 2722: /* 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 2723: matrix by transitions matrix until convergence is reached with precision ftolpl */
2724: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2725: /* Wx is row vector: population in state 1, population in state 2, population dead */
2726: /* or prevalence in state 1, prevalence in state 2, 0 */
2727: /* newm is the matrix after multiplications, its rows are identical at a factor */
2728: /* Initial matrix pimij */
2729: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2730: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2731: /* 0, 0 , 1} */
2732: /*
2733: * and after some iteration: */
2734: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2735: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2736: /* 0, 0 , 1} */
2737: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2738: /* {0.51571254859325999, 0.4842874514067399, */
2739: /* 0.51326036147820708, 0.48673963852179264} */
2740: /* If we start from prlim again, prlim tends to a constant matrix */
2741:
2742: int i, ii,j,k;
1.247 brouard 2743: int first=0;
1.217 brouard 2744: double *min, *max, *meandiff, maxmax,sumnew=0.;
2745: /* double **matprod2(); */ /* test */
2746: double **out, cov[NCOVMAX+1], **bmij();
2747: double **newm;
1.218 brouard 2748: double **dnewm, **doldm, **dsavm; /* for use */
2749: double **oldm, **savm; /* for use */
2750:
1.217 brouard 2751: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2752: int ncvloop=0;
2753:
2754: min=vector(1,nlstate);
2755: max=vector(1,nlstate);
2756: meandiff=vector(1,nlstate);
2757:
1.266 brouard 2758: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2759: oldm=oldms; savm=savms;
2760:
2761: /* Starting with matrix unity */
2762: for (ii=1;ii<=nlstate+ndeath;ii++)
2763: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2764: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2765: }
2766:
2767: cov[1]=1.;
2768:
2769: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2770: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2771: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2772: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2773: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2774: ncvloop++;
1.218 brouard 2775: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2776: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2777: /* Covariates have to be included here again */
2778: cov[2]=agefin;
2779: if(nagesqr==1)
2780: cov[3]= agefin*agefin;;
1.242 brouard 2781: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2782: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2783: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2784: /* 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 2785: }
2786: /* for (k=1; k<=cptcovn;k++) { */
2787: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2788: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2789: /* /\* 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])]); *\/ */
2790: /* } */
2791: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2792: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2793: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2794: /* 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]); */
2795: }
2796: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2797: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2798: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2799: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2800: for (k=1; k<=cptcovage;k++){ /* For product with age */
2801: if(Dummy[Tvar[Tage[k]]]){
2802: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2803: } else{
2804: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2805: }
2806: /* 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]); */
2807: }
2808: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2809: /* 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]); */
2810: if(Dummy[Tvard[k][1]==0]){
2811: if(Dummy[Tvard[k][2]==0]){
2812: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2813: }else{
2814: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2815: }
2816: }else{
2817: if(Dummy[Tvard[k][2]==0]){
2818: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2819: }else{
2820: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2821: }
2822: }
1.217 brouard 2823: }
2824:
2825: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2826: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2827: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2828: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2829: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2830: /* ij should be linked to the correct index of cov */
2831: /* age and covariate values ij are in 'cov', but we need to pass
2832: * ij for the observed prevalence at age and status and covariate
2833: * number: prevacurrent[(int)agefin][ii][ij]
2834: */
2835: /* 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 *\/ */
2836: /* 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 *\/ */
2837: 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 2838: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2839: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2840: /* for(i=1; i<=nlstate+ndeath; i++) { */
2841: /* printf("%d newm= ",i); */
2842: /* for(j=1;j<=nlstate+ndeath;j++) { */
2843: /* printf("%f ",newm[i][j]); */
2844: /* } */
2845: /* printf("oldm * "); */
2846: /* for(j=1;j<=nlstate+ndeath;j++) { */
2847: /* printf("%f ",oldm[i][j]); */
2848: /* } */
1.268 brouard 2849: /* printf(" bmmij "); */
1.266 brouard 2850: /* for(j=1;j<=nlstate+ndeath;j++) { */
2851: /* printf("%f ",pmmij[i][j]); */
2852: /* } */
2853: /* printf("\n"); */
2854: /* } */
2855: /* } */
1.217 brouard 2856: savm=oldm;
2857: oldm=newm;
1.266 brouard 2858:
1.217 brouard 2859: for(j=1; j<=nlstate; j++){
2860: max[j]=0.;
2861: min[j]=1.;
2862: }
2863: for(j=1; j<=nlstate; j++){
2864: for(i=1;i<=nlstate;i++){
1.234 brouard 2865: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2866: bprlim[i][j]= newm[i][j];
2867: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2868: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2869: }
2870: }
1.218 brouard 2871:
1.217 brouard 2872: maxmax=0.;
2873: for(i=1; i<=nlstate; i++){
2874: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2875: maxmax=FMAX(maxmax,meandiff[i]);
2876: /* 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 2877: } /* i loop */
1.217 brouard 2878: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2879: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2880: if(maxmax < ftolpl){
1.220 brouard 2881: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2882: free_vector(min,1,nlstate);
2883: free_vector(max,1,nlstate);
2884: free_vector(meandiff,1,nlstate);
2885: return bprlim;
2886: }
1.288 brouard 2887: } /* agefin loop */
1.217 brouard 2888: /* After some age loop it doesn't converge */
1.288 brouard 2889: if(!first){
1.247 brouard 2890: first=1;
2891: 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\
2892: 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);
2893: }
2894: 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 2895: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
2896: /* 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); */
2897: free_vector(min,1,nlstate);
2898: free_vector(max,1,nlstate);
2899: free_vector(meandiff,1,nlstate);
2900:
2901: return bprlim; /* should not reach here */
2902: }
2903:
1.126 brouard 2904: /*************** transition probabilities ***************/
2905:
2906: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2907: {
1.138 brouard 2908: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2909: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2910: model to the ncovmodel covariates (including constant and age).
2911: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2912: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2913: ncth covariate in the global vector x is given by the formula:
2914: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2915: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2916: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2917: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2918: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2919: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2920: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2921: */
2922: double s1, lnpijopii;
1.126 brouard 2923: /*double t34;*/
1.164 brouard 2924: int i,j, nc, ii, jj;
1.126 brouard 2925:
1.223 brouard 2926: for(i=1; i<= nlstate; i++){
2927: for(j=1; j<i;j++){
2928: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2929: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2930: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2931: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2932: }
2933: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2934: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2935: }
2936: for(j=i+1; j<=nlstate+ndeath;j++){
2937: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2938: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2939: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2940: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2941: }
2942: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2943: }
2944: }
1.218 brouard 2945:
1.223 brouard 2946: for(i=1; i<= nlstate; i++){
2947: s1=0;
2948: for(j=1; j<i; j++){
2949: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2950: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2951: }
2952: for(j=i+1; j<=nlstate+ndeath; j++){
2953: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2954: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2955: }
2956: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2957: ps[i][i]=1./(s1+1.);
2958: /* Computing other pijs */
2959: for(j=1; j<i; j++)
2960: ps[i][j]= exp(ps[i][j])*ps[i][i];
2961: for(j=i+1; j<=nlstate+ndeath; j++)
2962: ps[i][j]= exp(ps[i][j])*ps[i][i];
2963: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2964: } /* end i */
1.218 brouard 2965:
1.223 brouard 2966: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2967: for(jj=1; jj<= nlstate+ndeath; jj++){
2968: ps[ii][jj]=0;
2969: ps[ii][ii]=1;
2970: }
2971: }
1.294 ! brouard 2972:
! 2973:
1.223 brouard 2974: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2975: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2976: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2977: /* } */
2978: /* printf("\n "); */
2979: /* } */
2980: /* printf("\n ");printf("%lf ",cov[2]);*/
2981: /*
2982: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2983: goto end;*/
1.266 brouard 2984: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2985: }
2986:
1.218 brouard 2987: /*************** backward transition probabilities ***************/
2988:
2989: /* 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 ) */
2990: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2991: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2992: {
1.266 brouard 2993: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2994: * 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 2995: */
1.218 brouard 2996: int i, ii, j,k;
1.222 brouard 2997:
2998: double **out, **pmij();
2999: double sumnew=0.;
1.218 brouard 3000: double agefin;
1.292 brouard 3001: 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 3002: double **dnewm, **dsavm, **doldm;
3003: double **bbmij;
3004:
1.218 brouard 3005: doldm=ddoldms; /* global pointers */
1.222 brouard 3006: dnewm=ddnewms;
3007: dsavm=ddsavms;
3008:
3009: agefin=cov[2];
1.268 brouard 3010: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3011: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3012: the observed prevalence (with this covariate ij) at beginning of transition */
3013: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3014:
3015: /* P_x */
1.266 brouard 3016: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3017: /* outputs pmmij which is a stochastic matrix in row */
3018:
3019: /* Diag(w_x) */
1.292 brouard 3020: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3021: sumnew=0.;
1.269 brouard 3022: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3023: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 3024: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3025: sumnew+=prevacurrent[(int)agefin][ii][ij];
3026: }
3027: if(sumnew >0.01){ /* At least some value in the prevalence */
3028: for (ii=1;ii<=nlstate+ndeath;ii++){
3029: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3030: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3031: }
3032: }else{
3033: for (ii=1;ii<=nlstate+ndeath;ii++){
3034: for (j=1;j<=nlstate+ndeath;j++)
3035: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3036: }
3037: /* if(sumnew <0.9){ */
3038: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3039: /* } */
3040: }
3041: k3=0.0; /* We put the last diagonal to 0 */
3042: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3043: doldm[ii][ii]= k3;
3044: }
3045: /* End doldm, At the end doldm is diag[(w_i)] */
3046:
1.292 brouard 3047: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3048: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3049:
1.292 brouard 3050: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3051: /* 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 3052: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3053: sumnew=0.;
1.222 brouard 3054: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3055: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3056: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3057: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3058: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3059: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3060: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3061: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3062: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3063: /* }else */
1.268 brouard 3064: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3065: } /*End ii */
3066: } /* 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 */
3067:
1.292 brouard 3068: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3069: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3070: /* end bmij */
1.266 brouard 3071: return ps; /*pointer is unchanged */
1.218 brouard 3072: }
1.217 brouard 3073: /*************** transition probabilities ***************/
3074:
1.218 brouard 3075: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3076: {
3077: /* According to parameters values stored in x and the covariate's values stored in cov,
3078: computes the probability to be observed in state j being in state i by appying the
3079: model to the ncovmodel covariates (including constant and age).
3080: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3081: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3082: ncth covariate in the global vector x is given by the formula:
3083: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3084: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3085: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3086: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3087: Outputs ps[i][j] the probability to be observed in j being in j according to
3088: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3089: */
3090: double s1, lnpijopii;
3091: /*double t34;*/
3092: int i,j, nc, ii, jj;
3093:
1.234 brouard 3094: for(i=1; i<= nlstate; i++){
3095: for(j=1; j<i;j++){
3096: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3097: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3098: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3099: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3100: }
3101: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3102: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3103: }
3104: for(j=i+1; j<=nlstate+ndeath;j++){
3105: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3106: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3107: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3108: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3109: }
3110: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3111: }
3112: }
3113:
3114: for(i=1; i<= nlstate; i++){
3115: s1=0;
3116: for(j=1; j<i; j++){
3117: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3118: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3119: }
3120: for(j=i+1; j<=nlstate+ndeath; j++){
3121: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3122: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3123: }
3124: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3125: ps[i][i]=1./(s1+1.);
3126: /* Computing other pijs */
3127: for(j=1; j<i; j++)
3128: ps[i][j]= exp(ps[i][j])*ps[i][i];
3129: for(j=i+1; j<=nlstate+ndeath; j++)
3130: ps[i][j]= exp(ps[i][j])*ps[i][i];
3131: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3132: } /* end i */
3133:
3134: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3135: for(jj=1; jj<= nlstate+ndeath; jj++){
3136: ps[ii][jj]=0;
3137: ps[ii][ii]=1;
3138: }
3139: }
3140: /* Added for backcast */ /* Transposed matrix too */
3141: for(jj=1; jj<= nlstate+ndeath; jj++){
3142: s1=0.;
3143: for(ii=1; ii<= nlstate+ndeath; ii++){
3144: s1+=ps[ii][jj];
3145: }
3146: for(ii=1; ii<= nlstate; ii++){
3147: ps[ii][jj]=ps[ii][jj]/s1;
3148: }
3149: }
3150: /* Transposition */
3151: for(jj=1; jj<= nlstate+ndeath; jj++){
3152: for(ii=jj; ii<= nlstate+ndeath; ii++){
3153: s1=ps[ii][jj];
3154: ps[ii][jj]=ps[jj][ii];
3155: ps[jj][ii]=s1;
3156: }
3157: }
3158: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3159: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3160: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3161: /* } */
3162: /* printf("\n "); */
3163: /* } */
3164: /* printf("\n ");printf("%lf ",cov[2]);*/
3165: /*
3166: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3167: goto end;*/
3168: return ps;
1.217 brouard 3169: }
3170:
3171:
1.126 brouard 3172: /**************** Product of 2 matrices ******************/
3173:
1.145 brouard 3174: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3175: {
3176: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3177: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3178: /* in, b, out are matrice of pointers which should have been initialized
3179: before: only the contents of out is modified. The function returns
3180: a pointer to pointers identical to out */
1.145 brouard 3181: int i, j, k;
1.126 brouard 3182: for(i=nrl; i<= nrh; i++)
1.145 brouard 3183: for(k=ncolol; k<=ncoloh; k++){
3184: out[i][k]=0.;
3185: for(j=ncl; j<=nch; j++)
3186: out[i][k] +=in[i][j]*b[j][k];
3187: }
1.126 brouard 3188: return out;
3189: }
3190:
3191:
3192: /************* Higher Matrix Product ***************/
3193:
1.235 brouard 3194: 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 3195: {
1.218 brouard 3196: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3197: 'nhstepm*hstepm*stepm' months (i.e. until
3198: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3199: nhstepm*hstepm matrices.
3200: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3201: (typically every 2 years instead of every month which is too big
3202: for the memory).
3203: Model is determined by parameters x and covariates have to be
3204: included manually here.
3205:
3206: */
3207:
3208: int i, j, d, h, k;
1.131 brouard 3209: double **out, cov[NCOVMAX+1];
1.126 brouard 3210: double **newm;
1.187 brouard 3211: double agexact;
1.214 brouard 3212: double agebegin, ageend;
1.126 brouard 3213:
3214: /* Hstepm could be zero and should return the unit matrix */
3215: for (i=1;i<=nlstate+ndeath;i++)
3216: for (j=1;j<=nlstate+ndeath;j++){
3217: oldm[i][j]=(i==j ? 1.0 : 0.0);
3218: po[i][j][0]=(i==j ? 1.0 : 0.0);
3219: }
3220: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3221: for(h=1; h <=nhstepm; h++){
3222: for(d=1; d <=hstepm; d++){
3223: newm=savm;
3224: /* Covariates have to be included here again */
3225: cov[1]=1.;
1.214 brouard 3226: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3227: cov[2]=agexact;
3228: if(nagesqr==1)
1.227 brouard 3229: cov[3]= agexact*agexact;
1.235 brouard 3230: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3231: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3232: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3233: /* 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)); */
3234: }
3235: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3236: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3237: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3238: /* 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]); */
3239: }
3240: for (k=1; k<=cptcovage;k++){
3241: if(Dummy[Tvar[Tage[k]]]){
3242: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3243: } else{
3244: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3245: }
3246: /* 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]); */
3247: }
3248: for (k=1; k<=cptcovprod;k++){ /* */
3249: /* 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]); */
3250: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3251: }
3252: /* for (k=1; k<=cptcovn;k++) */
3253: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3254: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3255: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3256: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3257: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3258:
3259:
1.126 brouard 3260: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3261: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3262: /* right multiplication of oldm by the current matrix */
1.126 brouard 3263: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3264: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3265: /* if((int)age == 70){ */
3266: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3267: /* for(i=1; i<=nlstate+ndeath; i++) { */
3268: /* printf("%d pmmij ",i); */
3269: /* for(j=1;j<=nlstate+ndeath;j++) { */
3270: /* printf("%f ",pmmij[i][j]); */
3271: /* } */
3272: /* printf(" oldm "); */
3273: /* for(j=1;j<=nlstate+ndeath;j++) { */
3274: /* printf("%f ",oldm[i][j]); */
3275: /* } */
3276: /* printf("\n"); */
3277: /* } */
3278: /* } */
1.126 brouard 3279: savm=oldm;
3280: oldm=newm;
3281: }
3282: for(i=1; i<=nlstate+ndeath; i++)
3283: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3284: po[i][j][h]=newm[i][j];
3285: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3286: }
1.128 brouard 3287: /*printf("h=%d ",h);*/
1.126 brouard 3288: } /* end h */
1.267 brouard 3289: /* printf("\n H=%d \n",h); */
1.126 brouard 3290: return po;
3291: }
3292:
1.217 brouard 3293: /************* Higher Back Matrix Product ***************/
1.218 brouard 3294: /* 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 3295: 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 3296: {
1.266 brouard 3297: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3298: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3299: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3300: nhstepm*hstepm matrices.
3301: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3302: (typically every 2 years instead of every month which is too big
1.217 brouard 3303: for the memory).
1.218 brouard 3304: Model is determined by parameters x and covariates have to be
1.266 brouard 3305: included manually here. Then we use a call to bmij(x and cov)
3306: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3307: */
1.217 brouard 3308:
3309: int i, j, d, h, k;
1.266 brouard 3310: double **out, cov[NCOVMAX+1], **bmij();
3311: double **newm, ***newmm;
1.217 brouard 3312: double agexact;
3313: double agebegin, ageend;
1.222 brouard 3314: double **oldm, **savm;
1.217 brouard 3315:
1.266 brouard 3316: newmm=po; /* To be saved */
3317: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3318: /* Hstepm could be zero and should return the unit matrix */
3319: for (i=1;i<=nlstate+ndeath;i++)
3320: for (j=1;j<=nlstate+ndeath;j++){
3321: oldm[i][j]=(i==j ? 1.0 : 0.0);
3322: po[i][j][0]=(i==j ? 1.0 : 0.0);
3323: }
3324: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3325: for(h=1; h <=nhstepm; h++){
3326: for(d=1; d <=hstepm; d++){
3327: newm=savm;
3328: /* Covariates have to be included here again */
3329: cov[1]=1.;
1.271 brouard 3330: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3331: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3332: cov[2]=agexact;
3333: if(nagesqr==1)
1.222 brouard 3334: cov[3]= agexact*agexact;
1.266 brouard 3335: for (k=1; k<=cptcovn;k++){
3336: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3337: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3338: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3339: /* 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)); */
3340: }
1.267 brouard 3341: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3342: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3343: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3344: /* 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]); */
3345: }
3346: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3347: if(Dummy[Tvar[Tage[k]]]){
3348: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3349: } else{
3350: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3351: }
3352: /* 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]); */
3353: }
3354: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3355: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3356: }
1.217 brouard 3357: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3358: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3359:
1.218 brouard 3360: /* Careful transposed matrix */
1.266 brouard 3361: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3362: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3363: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3364: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3365: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3366: /* if((int)age == 70){ */
3367: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3368: /* for(i=1; i<=nlstate+ndeath; i++) { */
3369: /* printf("%d pmmij ",i); */
3370: /* for(j=1;j<=nlstate+ndeath;j++) { */
3371: /* printf("%f ",pmmij[i][j]); */
3372: /* } */
3373: /* printf(" oldm "); */
3374: /* for(j=1;j<=nlstate+ndeath;j++) { */
3375: /* printf("%f ",oldm[i][j]); */
3376: /* } */
3377: /* printf("\n"); */
3378: /* } */
3379: /* } */
3380: savm=oldm;
3381: oldm=newm;
3382: }
3383: for(i=1; i<=nlstate+ndeath; i++)
3384: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3385: po[i][j][h]=newm[i][j];
1.268 brouard 3386: /* if(h==nhstepm) */
3387: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3388: }
1.268 brouard 3389: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3390: } /* end h */
1.268 brouard 3391: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3392: return po;
3393: }
3394:
3395:
1.162 brouard 3396: #ifdef NLOPT
3397: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3398: double fret;
3399: double *xt;
3400: int j;
3401: myfunc_data *d2 = (myfunc_data *) pd;
3402: /* xt = (p1-1); */
3403: xt=vector(1,n);
3404: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3405:
3406: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3407: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3408: printf("Function = %.12lf ",fret);
3409: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3410: printf("\n");
3411: free_vector(xt,1,n);
3412: return fret;
3413: }
3414: #endif
1.126 brouard 3415:
3416: /*************** log-likelihood *************/
3417: double func( double *x)
3418: {
1.226 brouard 3419: int i, ii, j, k, mi, d, kk;
3420: int ioffset=0;
3421: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3422: double **out;
3423: double lli; /* Individual log likelihood */
3424: int s1, s2;
1.228 brouard 3425: 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 3426: double bbh, survp;
3427: long ipmx;
3428: double agexact;
3429: /*extern weight */
3430: /* We are differentiating ll according to initial status */
3431: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3432: /*for(i=1;i<imx;i++)
3433: printf(" %d\n",s[4][i]);
3434: */
1.162 brouard 3435:
1.226 brouard 3436: ++countcallfunc;
1.162 brouard 3437:
1.226 brouard 3438: cov[1]=1.;
1.126 brouard 3439:
1.226 brouard 3440: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3441: ioffset=0;
1.226 brouard 3442: if(mle==1){
3443: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3444: /* Computes the values of the ncovmodel covariates of the model
3445: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3446: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3447: to be observed in j being in i according to the model.
3448: */
1.243 brouard 3449: ioffset=2+nagesqr ;
1.233 brouard 3450: /* Fixed */
1.234 brouard 3451: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3452: 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)*/
3453: }
1.226 brouard 3454: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3455: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3456: has been calculated etc */
3457: /* For an individual i, wav[i] gives the number of effective waves */
3458: /* We compute the contribution to Likelihood of each effective transition
3459: mw[mi][i] is real wave of the mi th effectve wave */
3460: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3461: s2=s[mw[mi+1][i]][i];
3462: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3463: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3464: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3465: */
3466: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3467: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3468: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3469: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3470: }
3471: for (ii=1;ii<=nlstate+ndeath;ii++)
3472: for (j=1;j<=nlstate+ndeath;j++){
3473: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3474: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3475: }
3476: for(d=0; d<dh[mi][i]; d++){
3477: newm=savm;
3478: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3479: cov[2]=agexact;
3480: if(nagesqr==1)
3481: cov[3]= agexact*agexact; /* Should be changed here */
3482: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3483: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3484: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3485: else
3486: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3487: }
3488: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3489: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3490: savm=oldm;
3491: oldm=newm;
3492: } /* end mult */
3493:
3494: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3495: /* But now since version 0.9 we anticipate for bias at large stepm.
3496: * If stepm is larger than one month (smallest stepm) and if the exact delay
3497: * (in months) between two waves is not a multiple of stepm, we rounded to
3498: * the nearest (and in case of equal distance, to the lowest) interval but now
3499: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3500: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3501: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3502: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3503: * -stepm/2 to stepm/2 .
3504: * For stepm=1 the results are the same as for previous versions of Imach.
3505: * For stepm > 1 the results are less biased than in previous versions.
3506: */
1.234 brouard 3507: s1=s[mw[mi][i]][i];
3508: s2=s[mw[mi+1][i]][i];
3509: bbh=(double)bh[mi][i]/(double)stepm;
3510: /* bias bh is positive if real duration
3511: * is higher than the multiple of stepm and negative otherwise.
3512: */
3513: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3514: if( s2 > nlstate){
3515: /* i.e. if s2 is a death state and if the date of death is known
3516: then the contribution to the likelihood is the probability to
3517: die between last step unit time and current step unit time,
3518: which is also equal to probability to die before dh
3519: minus probability to die before dh-stepm .
3520: In version up to 0.92 likelihood was computed
3521: as if date of death was unknown. Death was treated as any other
3522: health state: the date of the interview describes the actual state
3523: and not the date of a change in health state. The former idea was
3524: to consider that at each interview the state was recorded
3525: (healthy, disable or death) and IMaCh was corrected; but when we
3526: introduced the exact date of death then we should have modified
3527: the contribution of an exact death to the likelihood. This new
3528: contribution is smaller and very dependent of the step unit
3529: stepm. It is no more the probability to die between last interview
3530: and month of death but the probability to survive from last
3531: interview up to one month before death multiplied by the
3532: probability to die within a month. Thanks to Chris
3533: Jackson for correcting this bug. Former versions increased
3534: mortality artificially. The bad side is that we add another loop
3535: which slows down the processing. The difference can be up to 10%
3536: lower mortality.
3537: */
3538: /* If, at the beginning of the maximization mostly, the
3539: cumulative probability or probability to be dead is
3540: constant (ie = 1) over time d, the difference is equal to
3541: 0. out[s1][3] = savm[s1][3]: probability, being at state
3542: s1 at precedent wave, to be dead a month before current
3543: wave is equal to probability, being at state s1 at
3544: precedent wave, to be dead at mont of the current
3545: wave. Then the observed probability (that this person died)
3546: is null according to current estimated parameter. In fact,
3547: it should be very low but not zero otherwise the log go to
3548: infinity.
3549: */
1.183 brouard 3550: /* #ifdef INFINITYORIGINAL */
3551: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3552: /* #else */
3553: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3554: /* lli=log(mytinydouble); */
3555: /* else */
3556: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3557: /* #endif */
1.226 brouard 3558: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3559:
1.226 brouard 3560: } else if ( s2==-1 ) { /* alive */
3561: for (j=1,survp=0. ; j<=nlstate; j++)
3562: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3563: /*survp += out[s1][j]; */
3564: lli= log(survp);
3565: }
3566: else if (s2==-4) {
3567: for (j=3,survp=0. ; j<=nlstate; j++)
3568: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3569: lli= log(survp);
3570: }
3571: else if (s2==-5) {
3572: for (j=1,survp=0. ; j<=2; j++)
3573: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3574: lli= log(survp);
3575: }
3576: else{
3577: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3578: /* 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 */
3579: }
3580: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3581: /*if(lli ==000.0)*/
3582: /*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); */
3583: ipmx +=1;
3584: sw += weight[i];
3585: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3586: /* if (lli < log(mytinydouble)){ */
3587: /* 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); */
3588: /* 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]); */
3589: /* } */
3590: } /* end of wave */
3591: } /* end of individual */
3592: } else if(mle==2){
3593: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3594: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3595: for(mi=1; mi<= wav[i]-1; mi++){
3596: for (ii=1;ii<=nlstate+ndeath;ii++)
3597: for (j=1;j<=nlstate+ndeath;j++){
3598: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3599: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3600: }
3601: for(d=0; d<=dh[mi][i]; d++){
3602: newm=savm;
3603: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3604: cov[2]=agexact;
3605: if(nagesqr==1)
3606: cov[3]= agexact*agexact;
3607: for (kk=1; kk<=cptcovage;kk++) {
3608: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3609: }
3610: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3611: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3612: savm=oldm;
3613: oldm=newm;
3614: } /* end mult */
3615:
3616: s1=s[mw[mi][i]][i];
3617: s2=s[mw[mi+1][i]][i];
3618: bbh=(double)bh[mi][i]/(double)stepm;
3619: 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 */
3620: ipmx +=1;
3621: sw += weight[i];
3622: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3623: } /* end of wave */
3624: } /* end of individual */
3625: } else if(mle==3){ /* exponential inter-extrapolation */
3626: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3627: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3628: for(mi=1; mi<= wav[i]-1; mi++){
3629: for (ii=1;ii<=nlstate+ndeath;ii++)
3630: for (j=1;j<=nlstate+ndeath;j++){
3631: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3632: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3633: }
3634: for(d=0; d<dh[mi][i]; d++){
3635: newm=savm;
3636: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3637: cov[2]=agexact;
3638: if(nagesqr==1)
3639: cov[3]= agexact*agexact;
3640: for (kk=1; kk<=cptcovage;kk++) {
3641: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3642: }
3643: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3644: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3645: savm=oldm;
3646: oldm=newm;
3647: } /* end mult */
3648:
3649: s1=s[mw[mi][i]][i];
3650: s2=s[mw[mi+1][i]][i];
3651: bbh=(double)bh[mi][i]/(double)stepm;
3652: 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 */
3653: ipmx +=1;
3654: sw += weight[i];
3655: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3656: } /* end of wave */
3657: } /* end of individual */
3658: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3659: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3660: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3661: for(mi=1; mi<= wav[i]-1; mi++){
3662: for (ii=1;ii<=nlstate+ndeath;ii++)
3663: for (j=1;j<=nlstate+ndeath;j++){
3664: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3665: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3666: }
3667: for(d=0; d<dh[mi][i]; d++){
3668: newm=savm;
3669: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3670: cov[2]=agexact;
3671: if(nagesqr==1)
3672: cov[3]= agexact*agexact;
3673: for (kk=1; kk<=cptcovage;kk++) {
3674: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3675: }
1.126 brouard 3676:
1.226 brouard 3677: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3678: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3679: savm=oldm;
3680: oldm=newm;
3681: } /* end mult */
3682:
3683: s1=s[mw[mi][i]][i];
3684: s2=s[mw[mi+1][i]][i];
3685: if( s2 > nlstate){
3686: lli=log(out[s1][s2] - savm[s1][s2]);
3687: } else if ( s2==-1 ) { /* alive */
3688: for (j=1,survp=0. ; j<=nlstate; j++)
3689: survp += out[s1][j];
3690: lli= log(survp);
3691: }else{
3692: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3693: }
3694: ipmx +=1;
3695: sw += weight[i];
3696: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3697: /* 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 3698: } /* end of wave */
3699: } /* end of individual */
3700: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3701: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3702: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3703: for(mi=1; mi<= wav[i]-1; mi++){
3704: for (ii=1;ii<=nlstate+ndeath;ii++)
3705: for (j=1;j<=nlstate+ndeath;j++){
3706: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3707: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3708: }
3709: for(d=0; d<dh[mi][i]; d++){
3710: newm=savm;
3711: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3712: cov[2]=agexact;
3713: if(nagesqr==1)
3714: cov[3]= agexact*agexact;
3715: for (kk=1; kk<=cptcovage;kk++) {
3716: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3717: }
1.126 brouard 3718:
1.226 brouard 3719: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3720: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3721: savm=oldm;
3722: oldm=newm;
3723: } /* end mult */
3724:
3725: s1=s[mw[mi][i]][i];
3726: s2=s[mw[mi+1][i]][i];
3727: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3728: ipmx +=1;
3729: sw += weight[i];
3730: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3731: /*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]);*/
3732: } /* end of wave */
3733: } /* end of individual */
3734: } /* End of if */
3735: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3736: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3737: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3738: return -l;
1.126 brouard 3739: }
3740:
3741: /*************** log-likelihood *************/
3742: double funcone( double *x)
3743: {
1.228 brouard 3744: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3745: int i, ii, j, k, mi, d, kk;
1.228 brouard 3746: int ioffset=0;
1.131 brouard 3747: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3748: double **out;
3749: double lli; /* Individual log likelihood */
3750: double llt;
3751: int s1, s2;
1.228 brouard 3752: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3753:
1.126 brouard 3754: double bbh, survp;
1.187 brouard 3755: double agexact;
1.214 brouard 3756: double agebegin, ageend;
1.126 brouard 3757: /*extern weight */
3758: /* We are differentiating ll according to initial status */
3759: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3760: /*for(i=1;i<imx;i++)
3761: printf(" %d\n",s[4][i]);
3762: */
3763: cov[1]=1.;
3764:
3765: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3766: ioffset=0;
3767: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3768: /* ioffset=2+nagesqr+cptcovage; */
3769: ioffset=2+nagesqr;
1.232 brouard 3770: /* Fixed */
1.224 brouard 3771: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3772: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3773: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3774: 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)*/
3775: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3776: /* cov[2+6]=covar[Tvar[6]][i]; */
3777: /* cov[2+6]=covar[2][i]; V2 */
3778: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3779: /* cov[2+7]=covar[Tvar[7]][i]; */
3780: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3781: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3782: /* cov[2+9]=covar[Tvar[9]][i]; */
3783: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3784: }
1.232 brouard 3785: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3786: /* 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?)*\/ */
3787: /* } */
1.231 brouard 3788: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3789: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3790: /* } */
1.225 brouard 3791:
1.233 brouard 3792:
3793: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3794: /* Wave varying (but not age varying) */
3795: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3796: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3797: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3798: }
1.232 brouard 3799: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3800: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3801: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3802: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3803: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3804: /* 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 3805: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3806: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3807: /* /\* 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]); *\/ */
3808: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3809: /* } */
1.126 brouard 3810: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3811: for (j=1;j<=nlstate+ndeath;j++){
3812: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3813: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3814: }
1.214 brouard 3815:
3816: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3817: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3818: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3819: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3820: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3821: and mw[mi+1][i]. dh depends on stepm.*/
3822: newm=savm;
1.247 brouard 3823: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3824: cov[2]=agexact;
3825: if(nagesqr==1)
3826: cov[3]= agexact*agexact;
3827: for (kk=1; kk<=cptcovage;kk++) {
3828: if(!FixedV[Tvar[Tage[kk]]])
3829: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3830: else
3831: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3832: }
3833: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3834: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3835: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3836: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3837: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3838: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3839: savm=oldm;
3840: oldm=newm;
1.126 brouard 3841: } /* end mult */
3842:
3843: s1=s[mw[mi][i]][i];
3844: s2=s[mw[mi+1][i]][i];
1.217 brouard 3845: /* if(s2==-1){ */
1.268 brouard 3846: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3847: /* /\* exit(1); *\/ */
3848: /* } */
1.126 brouard 3849: bbh=(double)bh[mi][i]/(double)stepm;
3850: /* bias is positive if real duration
3851: * is higher than the multiple of stepm and negative otherwise.
3852: */
3853: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3854: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3855: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3856: for (j=1,survp=0. ; j<=nlstate; j++)
3857: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3858: lli= log(survp);
1.126 brouard 3859: }else if (mle==1){
1.242 brouard 3860: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3861: } else if(mle==2){
1.242 brouard 3862: 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 3863: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3864: 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 3865: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3866: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3867: } else{ /* mle=0 back to 1 */
1.242 brouard 3868: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3869: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3870: } /* End of if */
3871: ipmx +=1;
3872: sw += weight[i];
3873: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3874: /*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 3875: if(globpr){
1.246 brouard 3876: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3877: %11.6f %11.6f %11.6f ", \
1.242 brouard 3878: 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 3879: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3880: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3881: llt +=ll[k]*gipmx/gsw;
3882: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3883: }
3884: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3885: }
1.232 brouard 3886: } /* end of wave */
3887: } /* end of individual */
3888: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3889: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3890: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3891: if(globpr==0){ /* First time we count the contributions and weights */
3892: gipmx=ipmx;
3893: gsw=sw;
3894: }
3895: return -l;
1.126 brouard 3896: }
3897:
3898:
3899: /*************** function likelione ***********/
1.292 brouard 3900: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 3901: {
3902: /* This routine should help understanding what is done with
3903: the selection of individuals/waves and
3904: to check the exact contribution to the likelihood.
3905: Plotting could be done.
3906: */
3907: int k;
3908:
3909: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3910: strcpy(fileresilk,"ILK_");
1.202 brouard 3911: strcat(fileresilk,fileresu);
1.126 brouard 3912: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3913: printf("Problem with resultfile: %s\n", fileresilk);
3914: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3915: }
1.214 brouard 3916: 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");
3917: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3918: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3919: for(k=1; k<=nlstate; k++)
3920: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3921: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3922: }
3923:
1.292 brouard 3924: *fretone=(*func)(p);
1.126 brouard 3925: if(*globpri !=0){
3926: fclose(ficresilk);
1.205 brouard 3927: if (mle ==0)
3928: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3929: else if(mle >=1)
3930: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3931: 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 3932: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3933:
3934: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3935: 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 3936: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3937: }
1.207 brouard 3938: 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 3939: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3940: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3941: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3942: fflush(fichtm);
1.205 brouard 3943: }
1.126 brouard 3944: return;
3945: }
3946:
3947:
3948: /*********** Maximum Likelihood Estimation ***************/
3949:
3950: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3951: {
1.165 brouard 3952: int i,j, iter=0;
1.126 brouard 3953: double **xi;
3954: double fret;
3955: double fretone; /* Only one call to likelihood */
3956: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3957:
3958: #ifdef NLOPT
3959: int creturn;
3960: nlopt_opt opt;
3961: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3962: double *lb;
3963: double minf; /* the minimum objective value, upon return */
3964: double * p1; /* Shifted parameters from 0 instead of 1 */
3965: myfunc_data dinst, *d = &dinst;
3966: #endif
3967:
3968:
1.126 brouard 3969: xi=matrix(1,npar,1,npar);
3970: for (i=1;i<=npar;i++)
3971: for (j=1;j<=npar;j++)
3972: xi[i][j]=(i==j ? 1.0 : 0.0);
3973: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3974: strcpy(filerespow,"POW_");
1.126 brouard 3975: strcat(filerespow,fileres);
3976: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3977: printf("Problem with resultfile: %s\n", filerespow);
3978: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3979: }
3980: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3981: for (i=1;i<=nlstate;i++)
3982: for(j=1;j<=nlstate+ndeath;j++)
3983: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3984: fprintf(ficrespow,"\n");
1.162 brouard 3985: #ifdef POWELL
1.126 brouard 3986: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3987: #endif
1.126 brouard 3988:
1.162 brouard 3989: #ifdef NLOPT
3990: #ifdef NEWUOA
3991: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3992: #else
3993: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3994: #endif
3995: lb=vector(0,npar-1);
3996: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3997: nlopt_set_lower_bounds(opt, lb);
3998: nlopt_set_initial_step1(opt, 0.1);
3999:
4000: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4001: d->function = func;
4002: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4003: nlopt_set_min_objective(opt, myfunc, d);
4004: nlopt_set_xtol_rel(opt, ftol);
4005: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4006: printf("nlopt failed! %d\n",creturn);
4007: }
4008: else {
4009: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4010: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4011: iter=1; /* not equal */
4012: }
4013: nlopt_destroy(opt);
4014: #endif
1.126 brouard 4015: free_matrix(xi,1,npar,1,npar);
4016: fclose(ficrespow);
1.203 brouard 4017: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4018: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4019: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4020:
4021: }
4022:
4023: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4024: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4025: {
4026: double **a,**y,*x,pd;
1.203 brouard 4027: /* double **hess; */
1.164 brouard 4028: int i, j;
1.126 brouard 4029: int *indx;
4030:
4031: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4032: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4033: void lubksb(double **a, int npar, int *indx, double b[]) ;
4034: void ludcmp(double **a, int npar, int *indx, double *d) ;
4035: double gompertz(double p[]);
1.203 brouard 4036: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4037:
4038: printf("\nCalculation of the hessian matrix. Wait...\n");
4039: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4040: for (i=1;i<=npar;i++){
1.203 brouard 4041: printf("%d-",i);fflush(stdout);
4042: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4043:
4044: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4045:
4046: /* printf(" %f ",p[i]);
4047: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4048: }
4049:
4050: for (i=1;i<=npar;i++) {
4051: for (j=1;j<=npar;j++) {
4052: if (j>i) {
1.203 brouard 4053: printf(".%d-%d",i,j);fflush(stdout);
4054: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4055: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4056:
4057: hess[j][i]=hess[i][j];
4058: /*printf(" %lf ",hess[i][j]);*/
4059: }
4060: }
4061: }
4062: printf("\n");
4063: fprintf(ficlog,"\n");
4064:
4065: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4066: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4067:
4068: a=matrix(1,npar,1,npar);
4069: y=matrix(1,npar,1,npar);
4070: x=vector(1,npar);
4071: indx=ivector(1,npar);
4072: for (i=1;i<=npar;i++)
4073: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4074: ludcmp(a,npar,indx,&pd);
4075:
4076: for (j=1;j<=npar;j++) {
4077: for (i=1;i<=npar;i++) x[i]=0;
4078: x[j]=1;
4079: lubksb(a,npar,indx,x);
4080: for (i=1;i<=npar;i++){
4081: matcov[i][j]=x[i];
4082: }
4083: }
4084:
4085: printf("\n#Hessian matrix#\n");
4086: fprintf(ficlog,"\n#Hessian matrix#\n");
4087: for (i=1;i<=npar;i++) {
4088: for (j=1;j<=npar;j++) {
1.203 brouard 4089: printf("%.6e ",hess[i][j]);
4090: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4091: }
4092: printf("\n");
4093: fprintf(ficlog,"\n");
4094: }
4095:
1.203 brouard 4096: /* printf("\n#Covariance matrix#\n"); */
4097: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4098: /* for (i=1;i<=npar;i++) { */
4099: /* for (j=1;j<=npar;j++) { */
4100: /* printf("%.6e ",matcov[i][j]); */
4101: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4102: /* } */
4103: /* printf("\n"); */
4104: /* fprintf(ficlog,"\n"); */
4105: /* } */
4106:
1.126 brouard 4107: /* Recompute Inverse */
1.203 brouard 4108: /* for (i=1;i<=npar;i++) */
4109: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4110: /* ludcmp(a,npar,indx,&pd); */
4111:
4112: /* printf("\n#Hessian matrix recomputed#\n"); */
4113:
4114: /* for (j=1;j<=npar;j++) { */
4115: /* for (i=1;i<=npar;i++) x[i]=0; */
4116: /* x[j]=1; */
4117: /* lubksb(a,npar,indx,x); */
4118: /* for (i=1;i<=npar;i++){ */
4119: /* y[i][j]=x[i]; */
4120: /* printf("%.3e ",y[i][j]); */
4121: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4122: /* } */
4123: /* printf("\n"); */
4124: /* fprintf(ficlog,"\n"); */
4125: /* } */
4126:
4127: /* Verifying the inverse matrix */
4128: #ifdef DEBUGHESS
4129: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4130:
1.203 brouard 4131: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4132: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4133:
4134: for (j=1;j<=npar;j++) {
4135: for (i=1;i<=npar;i++){
1.203 brouard 4136: printf("%.2f ",y[i][j]);
4137: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4138: }
4139: printf("\n");
4140: fprintf(ficlog,"\n");
4141: }
1.203 brouard 4142: #endif
1.126 brouard 4143:
4144: free_matrix(a,1,npar,1,npar);
4145: free_matrix(y,1,npar,1,npar);
4146: free_vector(x,1,npar);
4147: free_ivector(indx,1,npar);
1.203 brouard 4148: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4149:
4150:
4151: }
4152:
4153: /*************** hessian matrix ****************/
4154: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4155: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4156: int i;
4157: int l=1, lmax=20;
1.203 brouard 4158: double k1,k2, res, fx;
1.132 brouard 4159: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4160: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4161: int k=0,kmax=10;
4162: double l1;
4163:
4164: fx=func(x);
4165: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4166: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4167: l1=pow(10,l);
4168: delts=delt;
4169: for(k=1 ; k <kmax; k=k+1){
4170: delt = delta*(l1*k);
4171: p2[theta]=x[theta] +delt;
1.145 brouard 4172: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4173: p2[theta]=x[theta]-delt;
4174: k2=func(p2)-fx;
4175: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4176: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4177:
1.203 brouard 4178: #ifdef DEBUGHESSII
1.126 brouard 4179: 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);
4180: 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);
4181: #endif
4182: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4183: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4184: k=kmax;
4185: }
4186: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4187: k=kmax; l=lmax*10;
1.126 brouard 4188: }
4189: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4190: delts=delt;
4191: }
1.203 brouard 4192: } /* End loop k */
1.126 brouard 4193: }
4194: delti[theta]=delts;
4195: return res;
4196:
4197: }
4198:
1.203 brouard 4199: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4200: {
4201: int i;
1.164 brouard 4202: int l=1, lmax=20;
1.126 brouard 4203: double k1,k2,k3,k4,res,fx;
1.132 brouard 4204: double p2[MAXPARM+1];
1.203 brouard 4205: int k, kmax=1;
4206: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4207:
4208: int firstime=0;
1.203 brouard 4209:
1.126 brouard 4210: fx=func(x);
1.203 brouard 4211: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4212: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4213: p2[thetai]=x[thetai]+delti[thetai]*k;
4214: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4215: k1=func(p2)-fx;
4216:
1.203 brouard 4217: p2[thetai]=x[thetai]+delti[thetai]*k;
4218: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4219: k2=func(p2)-fx;
4220:
1.203 brouard 4221: p2[thetai]=x[thetai]-delti[thetai]*k;
4222: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4223: k3=func(p2)-fx;
4224:
1.203 brouard 4225: p2[thetai]=x[thetai]-delti[thetai]*k;
4226: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4227: k4=func(p2)-fx;
1.203 brouard 4228: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4229: if(k1*k2*k3*k4 <0.){
1.208 brouard 4230: firstime=1;
1.203 brouard 4231: kmax=kmax+10;
1.208 brouard 4232: }
4233: if(kmax >=10 || firstime ==1){
1.246 brouard 4234: 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);
4235: 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 4236: 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);
4237: 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);
4238: }
4239: #ifdef DEBUGHESSIJ
4240: v1=hess[thetai][thetai];
4241: v2=hess[thetaj][thetaj];
4242: cv12=res;
4243: /* Computing eigen value of Hessian matrix */
4244: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4245: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4246: if ((lc2 <0) || (lc1 <0) ){
4247: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4248: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4249: 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);
4250: 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);
4251: }
1.126 brouard 4252: #endif
4253: }
4254: return res;
4255: }
4256:
1.203 brouard 4257: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4258: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4259: /* { */
4260: /* int i; */
4261: /* int l=1, lmax=20; */
4262: /* double k1,k2,k3,k4,res,fx; */
4263: /* double p2[MAXPARM+1]; */
4264: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4265: /* int k=0,kmax=10; */
4266: /* double l1; */
4267:
4268: /* fx=func(x); */
4269: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4270: /* l1=pow(10,l); */
4271: /* delts=delt; */
4272: /* for(k=1 ; k <kmax; k=k+1){ */
4273: /* delt = delti*(l1*k); */
4274: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4275: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4276: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4277: /* k1=func(p2)-fx; */
4278:
4279: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4280: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4281: /* k2=func(p2)-fx; */
4282:
4283: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4284: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4285: /* k3=func(p2)-fx; */
4286:
4287: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4288: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4289: /* k4=func(p2)-fx; */
4290: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4291: /* #ifdef DEBUGHESSIJ */
4292: /* 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); */
4293: /* 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); */
4294: /* #endif */
4295: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4296: /* k=kmax; */
4297: /* } */
4298: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4299: /* k=kmax; l=lmax*10; */
4300: /* } */
4301: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4302: /* delts=delt; */
4303: /* } */
4304: /* } /\* End loop k *\/ */
4305: /* } */
4306: /* delti[theta]=delts; */
4307: /* return res; */
4308: /* } */
4309:
4310:
1.126 brouard 4311: /************** Inverse of matrix **************/
4312: void ludcmp(double **a, int n, int *indx, double *d)
4313: {
4314: int i,imax,j,k;
4315: double big,dum,sum,temp;
4316: double *vv;
4317:
4318: vv=vector(1,n);
4319: *d=1.0;
4320: for (i=1;i<=n;i++) {
4321: big=0.0;
4322: for (j=1;j<=n;j++)
4323: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4324: if (big == 0.0){
4325: printf(" Singular Hessian matrix at row %d:\n",i);
4326: for (j=1;j<=n;j++) {
4327: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4328: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4329: }
4330: fflush(ficlog);
4331: fclose(ficlog);
4332: nrerror("Singular matrix in routine ludcmp");
4333: }
1.126 brouard 4334: vv[i]=1.0/big;
4335: }
4336: for (j=1;j<=n;j++) {
4337: for (i=1;i<j;i++) {
4338: sum=a[i][j];
4339: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4340: a[i][j]=sum;
4341: }
4342: big=0.0;
4343: for (i=j;i<=n;i++) {
4344: sum=a[i][j];
4345: for (k=1;k<j;k++)
4346: sum -= a[i][k]*a[k][j];
4347: a[i][j]=sum;
4348: if ( (dum=vv[i]*fabs(sum)) >= big) {
4349: big=dum;
4350: imax=i;
4351: }
4352: }
4353: if (j != imax) {
4354: for (k=1;k<=n;k++) {
4355: dum=a[imax][k];
4356: a[imax][k]=a[j][k];
4357: a[j][k]=dum;
4358: }
4359: *d = -(*d);
4360: vv[imax]=vv[j];
4361: }
4362: indx[j]=imax;
4363: if (a[j][j] == 0.0) a[j][j]=TINY;
4364: if (j != n) {
4365: dum=1.0/(a[j][j]);
4366: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4367: }
4368: }
4369: free_vector(vv,1,n); /* Doesn't work */
4370: ;
4371: }
4372:
4373: void lubksb(double **a, int n, int *indx, double b[])
4374: {
4375: int i,ii=0,ip,j;
4376: double sum;
4377:
4378: for (i=1;i<=n;i++) {
4379: ip=indx[i];
4380: sum=b[ip];
4381: b[ip]=b[i];
4382: if (ii)
4383: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4384: else if (sum) ii=i;
4385: b[i]=sum;
4386: }
4387: for (i=n;i>=1;i--) {
4388: sum=b[i];
4389: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4390: b[i]=sum/a[i][i];
4391: }
4392: }
4393:
4394: void pstamp(FILE *fichier)
4395: {
1.196 brouard 4396: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4397: }
4398:
1.253 brouard 4399:
4400:
1.126 brouard 4401: /************ Frequencies ********************/
1.251 brouard 4402: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4403: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4404: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4405: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4406:
1.265 brouard 4407: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4408: int iind=0, iage=0;
4409: int mi; /* Effective wave */
4410: int first;
4411: double ***freq; /* Frequencies */
1.268 brouard 4412: 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 */
4413: 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 4414: double *meanq, *stdq, *idq;
1.226 brouard 4415: double **meanqt;
4416: double *pp, **prop, *posprop, *pospropt;
4417: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4418: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4419: double agebegin, ageend;
4420:
4421: pp=vector(1,nlstate);
1.251 brouard 4422: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4423: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4424: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4425: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4426: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4427: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4428: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4429: meanqt=matrix(1,lastpass,1,nqtveff);
4430: strcpy(fileresp,"P_");
4431: strcat(fileresp,fileresu);
4432: /*strcat(fileresphtm,fileresu);*/
4433: if((ficresp=fopen(fileresp,"w"))==NULL) {
4434: printf("Problem with prevalence resultfile: %s\n", fileresp);
4435: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4436: exit(0);
4437: }
1.240 brouard 4438:
1.226 brouard 4439: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4440: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4441: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4442: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4443: fflush(ficlog);
4444: exit(70);
4445: }
4446: else{
4447: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4448: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4449: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4450: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4451: }
1.237 brouard 4452: 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 4453:
1.226 brouard 4454: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4455: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4456: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4457: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4458: fflush(ficlog);
4459: exit(70);
1.240 brouard 4460: } else{
1.226 brouard 4461: 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 4462: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4463: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4464: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4465: }
1.240 brouard 4466: 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);
4467:
1.253 brouard 4468: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4469: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4470: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4471: j1=0;
1.126 brouard 4472:
1.227 brouard 4473: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4474: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4475: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4476:
4477:
1.226 brouard 4478: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4479: reference=low_education V1=0,V2=0
4480: med_educ V1=1 V2=0,
4481: high_educ V1=0 V2=1
4482: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4483: */
1.249 brouard 4484: dateintsum=0;
4485: k2cpt=0;
4486:
1.253 brouard 4487: if(cptcoveff == 0 )
1.265 brouard 4488: nl=1; /* Constant and age model only */
1.253 brouard 4489: else
4490: nl=2;
1.265 brouard 4491:
4492: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4493: /* Loop on nj=1 or 2 if dummy covariates j!=0
4494: * Loop on j1(1 to 2**cptcoveff) covariate combination
4495: * freq[s1][s2][iage] =0.
4496: * Loop on iind
4497: * ++freq[s1][s2][iage] weighted
4498: * end iind
4499: * if covariate and j!0
4500: * headers Variable on one line
4501: * endif cov j!=0
4502: * header of frequency table by age
4503: * Loop on age
4504: * pp[s1]+=freq[s1][s2][iage] weighted
4505: * pos+=freq[s1][s2][iage] weighted
4506: * Loop on s1 initial state
4507: * fprintf(ficresp
4508: * end s1
4509: * end age
4510: * if j!=0 computes starting values
4511: * end compute starting values
4512: * end j1
4513: * end nl
4514: */
1.253 brouard 4515: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4516: if(nj==1)
4517: j=0; /* First pass for the constant */
1.265 brouard 4518: else{
1.253 brouard 4519: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4520: }
1.251 brouard 4521: first=1;
1.265 brouard 4522: 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 4523: posproptt=0.;
4524: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4525: scanf("%d", i);*/
4526: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4527: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4528: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4529: freq[i][s2][m]=0;
1.251 brouard 4530:
4531: for (i=1; i<=nlstate; i++) {
1.240 brouard 4532: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4533: prop[i][m]=0;
4534: posprop[i]=0;
4535: pospropt[i]=0;
4536: }
1.283 brouard 4537: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4538: idq[z1]=0.;
4539: meanq[z1]=0.;
4540: stdq[z1]=0.;
1.283 brouard 4541: }
4542: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4543: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4544: /* meanqt[m][z1]=0.; */
4545: /* } */
4546: /* } */
1.251 brouard 4547: /* dateintsum=0; */
4548: /* k2cpt=0; */
4549:
1.265 brouard 4550: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4551: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4552: bool=1;
4553: if(j !=0){
4554: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4555: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4556: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4557: /* if(Tvaraff[z1] ==-20){ */
4558: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4559: /* }else if(Tvaraff[z1] ==-10){ */
4560: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4561: /* }else */
4562: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4563: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4564: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4565: /* 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",
4566: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4567: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4568: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4569: } /* Onlyf fixed */
4570: } /* end z1 */
4571: } /* cptcovn > 0 */
4572: } /* end any */
4573: }/* end j==0 */
1.265 brouard 4574: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4575: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4576: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4577: m=mw[mi][iind];
4578: if(j!=0){
4579: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4580: for (z1=1; z1<=cptcoveff; z1++) {
4581: if( Fixed[Tmodelind[z1]]==1){
4582: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4583: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4584: value is -1, we don't select. It differs from the
4585: constant and age model which counts them. */
4586: bool=0; /* not selected */
4587: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4588: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4589: bool=0;
4590: }
4591: }
4592: }
4593: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4594: } /* end j==0 */
4595: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4596: if(bool==1){ /*Selected */
1.251 brouard 4597: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4598: and mw[mi+1][iind]. dh depends on stepm. */
4599: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4600: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4601: if(m >=firstpass && m <=lastpass){
4602: k2=anint[m][iind]+(mint[m][iind]/12.);
4603: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4604: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4605: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4606: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4607: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4608: if (m<lastpass) {
4609: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4610: /* 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]); */
4611: if(s[m][iind]==-1)
4612: 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.));
4613: 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 4614: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4615: idq[z1]=idq[z1]+weight[iind];
4616: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4617: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4618: }
1.251 brouard 4619: /* if((int)agev[m][iind] == 55) */
4620: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4621: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4622: 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 4623: }
1.251 brouard 4624: } /* end if between passes */
4625: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4626: dateintsum=dateintsum+k2; /* on all covariates ?*/
4627: k2cpt++;
4628: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4629: }
1.251 brouard 4630: }else{
4631: bool=1;
4632: }/* end bool 2 */
4633: } /* end m */
1.284 brouard 4634: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4635: /* idq[z1]=idq[z1]+weight[iind]; */
4636: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4637: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4638: /* } */
1.251 brouard 4639: } /* end bool */
4640: } /* end iind = 1 to imx */
4641: /* prop[s][age] is feeded for any initial and valid live state as well as
4642: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4643:
4644:
4645: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4646: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4647: pstamp(ficresp);
1.251 brouard 4648: if (cptcoveff>0 && j!=0){
1.265 brouard 4649: pstamp(ficresp);
1.251 brouard 4650: printf( "\n#********** Variable ");
4651: fprintf(ficresp, "\n#********** Variable ");
4652: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4653: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4654: fprintf(ficlog, "\n#********** Variable ");
4655: for (z1=1; z1<=cptcoveff; z1++){
4656: if(!FixedV[Tvaraff[z1]]){
4657: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4658: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4659: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4660: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4661: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4662: }else{
1.251 brouard 4663: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4664: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4665: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4666: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4667: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4668: }
4669: }
4670: printf( "**********\n#");
4671: fprintf(ficresp, "**********\n#");
4672: fprintf(ficresphtm, "**********</h3>\n");
4673: fprintf(ficresphtmfr, "**********</h3>\n");
4674: fprintf(ficlog, "**********\n");
4675: }
1.284 brouard 4676: /*
4677: Printing means of quantitative variables if any
4678: */
4679: for (z1=1; z1<= nqfveff; z1++) {
1.285 brouard 4680: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4681: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4682: if(weightopt==1){
4683: printf(" Weighted mean and standard deviation of");
4684: fprintf(ficlog," Weighted mean and standard deviation of");
4685: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4686: }
1.285 brouard 4687: 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]));
4688: 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]));
4689: 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 4690: }
4691: /* for (z1=1; z1<= nqtveff; z1++) { */
4692: /* for(m=1;m<=lastpass;m++){ */
4693: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4694: /* } */
4695: /* } */
1.283 brouard 4696:
1.251 brouard 4697: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4698: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4699: fprintf(ficresp, " Age");
4700: 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 4701: for(i=1; i<=nlstate;i++) {
1.265 brouard 4702: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4703: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4704: }
1.265 brouard 4705: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4706: fprintf(ficresphtm, "\n");
4707:
4708: /* Header of frequency table by age */
4709: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4710: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4711: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4712: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4713: if(s2!=0 && m!=0)
4714: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4715: }
1.226 brouard 4716: }
1.251 brouard 4717: fprintf(ficresphtmfr, "\n");
4718:
4719: /* For each age */
4720: for(iage=iagemin; iage <= iagemax+3; iage++){
4721: fprintf(ficresphtm,"<tr>");
4722: if(iage==iagemax+1){
4723: fprintf(ficlog,"1");
4724: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4725: }else if(iage==iagemax+2){
4726: fprintf(ficlog,"0");
4727: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4728: }else if(iage==iagemax+3){
4729: fprintf(ficlog,"Total");
4730: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4731: }else{
1.240 brouard 4732: if(first==1){
1.251 brouard 4733: first=0;
4734: printf("See log file for details...\n");
4735: }
4736: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4737: fprintf(ficlog,"Age %d", iage);
4738: }
1.265 brouard 4739: for(s1=1; s1 <=nlstate ; s1++){
4740: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4741: pp[s1] += freq[s1][m][iage];
1.251 brouard 4742: }
1.265 brouard 4743: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4744: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4745: pos += freq[s1][m][iage];
4746: if(pp[s1]>=1.e-10){
1.251 brouard 4747: if(first==1){
1.265 brouard 4748: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4749: }
1.265 brouard 4750: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4751: }else{
4752: if(first==1)
1.265 brouard 4753: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4754: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4755: }
4756: }
4757:
1.265 brouard 4758: for(s1=1; s1 <=nlstate ; s1++){
4759: /* posprop[s1]=0; */
4760: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4761: pp[s1] += freq[s1][m][iage];
4762: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4763:
4764: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4765: pos += pp[s1]; /* pos is the total number of transitions until this age */
4766: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4767: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4768: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4769: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4770: }
4771:
4772: /* Writing ficresp */
4773: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4774: if( iage <= iagemax){
4775: fprintf(ficresp," %d",iage);
4776: }
4777: }else if( nj==2){
4778: if( iage <= iagemax){
4779: fprintf(ficresp," %d",iage);
4780: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4781: }
1.240 brouard 4782: }
1.265 brouard 4783: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4784: if(pos>=1.e-5){
1.251 brouard 4785: if(first==1)
1.265 brouard 4786: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4787: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4788: }else{
4789: if(first==1)
1.265 brouard 4790: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4791: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4792: }
4793: if( iage <= iagemax){
4794: if(pos>=1.e-5){
1.265 brouard 4795: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4796: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4797: }else if( nj==2){
4798: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4799: }
4800: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4801: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4802: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4803: } else{
4804: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4805: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4806: }
1.240 brouard 4807: }
1.265 brouard 4808: pospropt[s1] +=posprop[s1];
4809: } /* end loop s1 */
1.251 brouard 4810: /* pospropt=0.; */
1.265 brouard 4811: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4812: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4813: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4814: if(first==1){
1.265 brouard 4815: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4816: }
1.265 brouard 4817: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4818: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4819: }
1.265 brouard 4820: if(s1!=0 && m!=0)
4821: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4822: }
1.265 brouard 4823: } /* end loop s1 */
1.251 brouard 4824: posproptt=0.;
1.265 brouard 4825: for(s1=1; s1 <=nlstate; s1++){
4826: posproptt += pospropt[s1];
1.251 brouard 4827: }
4828: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4829: fprintf(ficresphtm,"</tr>\n");
4830: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4831: if(iage <= iagemax)
4832: fprintf(ficresp,"\n");
1.240 brouard 4833: }
1.251 brouard 4834: if(first==1)
4835: printf("Others in log...\n");
4836: fprintf(ficlog,"\n");
4837: } /* end loop age iage */
1.265 brouard 4838:
1.251 brouard 4839: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4840: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4841: if(posproptt < 1.e-5){
1.265 brouard 4842: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4843: }else{
1.265 brouard 4844: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4845: }
1.226 brouard 4846: }
1.251 brouard 4847: fprintf(ficresphtm,"</tr>\n");
4848: fprintf(ficresphtm,"</table>\n");
4849: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4850: if(posproptt < 1.e-5){
1.251 brouard 4851: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4852: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4853: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4854: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4855: invalidvarcomb[j1]=1;
1.226 brouard 4856: }else{
1.251 brouard 4857: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4858: invalidvarcomb[j1]=0;
1.226 brouard 4859: }
1.251 brouard 4860: fprintf(ficresphtmfr,"</table>\n");
4861: fprintf(ficlog,"\n");
4862: if(j!=0){
4863: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4864: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4865: for(k=1; k <=(nlstate+ndeath); k++){
4866: if (k != i) {
1.265 brouard 4867: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4868: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4869: if(j1==1){ /* All dummy covariates to zero */
4870: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4871: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4872: printf("%d%d ",i,k);
4873: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4874: 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]));
4875: 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]));
4876: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4877: }
1.253 brouard 4878: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4879: for(iage=iagemin; iage <= iagemax+3; iage++){
4880: x[iage]= (double)iage;
4881: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4882: /* 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 4883: }
1.268 brouard 4884: /* Some are not finite, but linreg will ignore these ages */
4885: no=0;
1.253 brouard 4886: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4887: pstart[s1]=b;
4888: pstart[s1-1]=a;
1.252 brouard 4889: }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 */
4890: 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]);
4891: 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 4892: 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 4893: printf("%d%d ",i,k);
4894: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4895: 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 4896: }else{ /* Other cases, like quantitative fixed or varying covariates */
4897: ;
4898: }
4899: /* printf("%12.7f )", param[i][jj][k]); */
4900: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4901: s1++;
1.251 brouard 4902: } /* end jj */
4903: } /* end k!= i */
4904: } /* end k */
1.265 brouard 4905: } /* end i, s1 */
1.251 brouard 4906: } /* end j !=0 */
4907: } /* end selected combination of covariate j1 */
4908: if(j==0){ /* We can estimate starting values from the occurences in each case */
4909: printf("#Freqsummary: Starting values for the constants:\n");
4910: fprintf(ficlog,"\n");
1.265 brouard 4911: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4912: for(k=1; k <=(nlstate+ndeath); k++){
4913: if (k != i) {
4914: printf("%d%d ",i,k);
4915: fprintf(ficlog,"%d%d ",i,k);
4916: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4917: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4918: if(jj==1){ /* Age has to be done */
1.265 brouard 4919: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4920: 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]));
4921: 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 4922: }
4923: /* printf("%12.7f )", param[i][jj][k]); */
4924: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4925: s1++;
1.250 brouard 4926: }
1.251 brouard 4927: printf("\n");
4928: fprintf(ficlog,"\n");
1.250 brouard 4929: }
4930: }
1.284 brouard 4931: } /* end of state i */
1.251 brouard 4932: printf("#Freqsummary\n");
4933: fprintf(ficlog,"\n");
1.265 brouard 4934: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4935: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4936: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4937: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4938: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4939: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4940: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4941: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4942: /* } */
4943: }
1.265 brouard 4944: } /* end loop s1 */
1.251 brouard 4945:
4946: printf("\n");
4947: fprintf(ficlog,"\n");
4948: } /* end j=0 */
1.249 brouard 4949: } /* end j */
1.252 brouard 4950:
1.253 brouard 4951: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4952: for(i=1, jk=1; i <=nlstate; i++){
4953: for(j=1; j <=nlstate+ndeath; j++){
4954: if(j!=i){
4955: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4956: printf("%1d%1d",i,j);
4957: fprintf(ficparo,"%1d%1d",i,j);
4958: for(k=1; k<=ncovmodel;k++){
4959: /* printf(" %lf",param[i][j][k]); */
4960: /* fprintf(ficparo," %lf",param[i][j][k]); */
4961: p[jk]=pstart[jk];
4962: printf(" %f ",pstart[jk]);
4963: fprintf(ficparo," %f ",pstart[jk]);
4964: jk++;
4965: }
4966: printf("\n");
4967: fprintf(ficparo,"\n");
4968: }
4969: }
4970: }
4971: } /* end mle=-2 */
1.226 brouard 4972: dateintmean=dateintsum/k2cpt;
1.240 brouard 4973:
1.226 brouard 4974: fclose(ficresp);
4975: fclose(ficresphtm);
4976: fclose(ficresphtmfr);
1.283 brouard 4977: free_vector(idq,1,nqfveff);
1.226 brouard 4978: free_vector(meanq,1,nqfveff);
1.284 brouard 4979: free_vector(stdq,1,nqfveff);
1.226 brouard 4980: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4981: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4982: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4983: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4984: free_vector(pospropt,1,nlstate);
4985: free_vector(posprop,1,nlstate);
1.251 brouard 4986: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4987: free_vector(pp,1,nlstate);
4988: /* End of freqsummary */
4989: }
1.126 brouard 4990:
1.268 brouard 4991: /* Simple linear regression */
4992: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4993:
4994: /* y=a+bx regression */
4995: double sumx = 0.0; /* sum of x */
4996: double sumx2 = 0.0; /* sum of x**2 */
4997: double sumxy = 0.0; /* sum of x * y */
4998: double sumy = 0.0; /* sum of y */
4999: double sumy2 = 0.0; /* sum of y**2 */
5000: double sume2 = 0.0; /* sum of square or residuals */
5001: double yhat;
5002:
5003: double denom=0;
5004: int i;
5005: int ne=*no;
5006:
5007: for ( i=ifi, ne=0;i<=ila;i++) {
5008: if(!isfinite(x[i]) || !isfinite(y[i])){
5009: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5010: continue;
5011: }
5012: ne=ne+1;
5013: sumx += x[i];
5014: sumx2 += x[i]*x[i];
5015: sumxy += x[i] * y[i];
5016: sumy += y[i];
5017: sumy2 += y[i]*y[i];
5018: denom = (ne * sumx2 - sumx*sumx);
5019: /* 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); */
5020: }
5021:
5022: denom = (ne * sumx2 - sumx*sumx);
5023: if (denom == 0) {
5024: // vertical, slope m is infinity
5025: *b = INFINITY;
5026: *a = 0;
5027: if (r) *r = 0;
5028: return 1;
5029: }
5030:
5031: *b = (ne * sumxy - sumx * sumy) / denom;
5032: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5033: if (r!=NULL) {
5034: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5035: sqrt((sumx2 - sumx*sumx/ne) *
5036: (sumy2 - sumy*sumy/ne));
5037: }
5038: *no=ne;
5039: for ( i=ifi, ne=0;i<=ila;i++) {
5040: if(!isfinite(x[i]) || !isfinite(y[i])){
5041: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5042: continue;
5043: }
5044: ne=ne+1;
5045: yhat = y[i] - *a -*b* x[i];
5046: sume2 += yhat * yhat ;
5047:
5048: denom = (ne * sumx2 - sumx*sumx);
5049: /* 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); */
5050: }
5051: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5052: *sa= *sb * sqrt(sumx2/ne);
5053:
5054: return 0;
5055: }
5056:
1.126 brouard 5057: /************ Prevalence ********************/
1.227 brouard 5058: 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)
5059: {
5060: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5061: in each health status at the date of interview (if between dateprev1 and dateprev2).
5062: We still use firstpass and lastpass as another selection.
5063: */
1.126 brouard 5064:
1.227 brouard 5065: int i, m, jk, j1, bool, z1,j, iv;
5066: int mi; /* Effective wave */
5067: int iage;
5068: double agebegin, ageend;
5069:
5070: double **prop;
5071: double posprop;
5072: double y2; /* in fractional years */
5073: int iagemin, iagemax;
5074: int first; /** to stop verbosity which is redirected to log file */
5075:
5076: iagemin= (int) agemin;
5077: iagemax= (int) agemax;
5078: /*pp=vector(1,nlstate);*/
1.251 brouard 5079: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5080: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5081: j1=0;
1.222 brouard 5082:
1.227 brouard 5083: /*j=cptcoveff;*/
5084: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5085:
1.288 brouard 5086: first=0;
1.227 brouard 5087: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5088: for (i=1; i<=nlstate; i++)
1.251 brouard 5089: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5090: prop[i][iage]=0.0;
5091: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5092: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5093: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5094:
5095: for (i=1; i<=imx; i++) { /* Each individual */
5096: bool=1;
5097: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5098: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5099: m=mw[mi][i];
5100: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5101: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5102: for (z1=1; z1<=cptcoveff; z1++){
5103: if( Fixed[Tmodelind[z1]]==1){
5104: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5105: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5106: bool=0;
5107: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5108: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5109: bool=0;
5110: }
5111: }
5112: if(bool==1){ /* Otherwise we skip that wave/person */
5113: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5114: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5115: if(m >=firstpass && m <=lastpass){
5116: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5117: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5118: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5119: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5120: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5121: 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);
5122: exit(1);
5123: }
5124: if (s[m][i]>0 && s[m][i]<=nlstate) {
5125: /*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]]);*/
5126: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5127: prop[s[m][i]][iagemax+3] += weight[i];
5128: } /* end valid statuses */
5129: } /* end selection of dates */
5130: } /* end selection of waves */
5131: } /* end bool */
5132: } /* end wave */
5133: } /* end individual */
5134: for(i=iagemin; i <= iagemax+3; i++){
5135: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5136: posprop += prop[jk][i];
5137: }
5138:
5139: for(jk=1; jk <=nlstate ; jk++){
5140: if( i <= iagemax){
5141: if(posprop>=1.e-5){
5142: probs[i][jk][j1]= prop[jk][i]/posprop;
5143: } else{
1.288 brouard 5144: if(!first){
5145: first=1;
1.266 brouard 5146: 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]);
5147: }else{
1.288 brouard 5148: 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 5149: }
5150: }
5151: }
5152: }/* end jk */
5153: }/* end i */
1.222 brouard 5154: /*} *//* end i1 */
1.227 brouard 5155: } /* end j1 */
1.222 brouard 5156:
1.227 brouard 5157: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5158: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5159: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5160: } /* End of prevalence */
1.126 brouard 5161:
5162: /************* Waves Concatenation ***************/
5163:
5164: 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)
5165: {
5166: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5167: Death is a valid wave (if date is known).
5168: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5169: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5170: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5171: */
1.126 brouard 5172:
1.224 brouard 5173: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5174: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5175: double sum=0., jmean=0.;*/
1.224 brouard 5176: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5177: int j, k=0,jk, ju, jl;
5178: double sum=0.;
5179: first=0;
1.214 brouard 5180: firstwo=0;
1.217 brouard 5181: firsthree=0;
1.218 brouard 5182: firstfour=0;
1.164 brouard 5183: jmin=100000;
1.126 brouard 5184: jmax=-1;
5185: jmean=0.;
1.224 brouard 5186:
5187: /* Treating live states */
1.214 brouard 5188: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5189: mi=0; /* First valid wave */
1.227 brouard 5190: mli=0; /* Last valid wave */
1.126 brouard 5191: m=firstpass;
1.214 brouard 5192: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5193: 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 */
5194: mli=m-1;/* mw[++mi][i]=m-1; */
5195: }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 */
5196: mw[++mi][i]=m;
5197: mli=m;
1.224 brouard 5198: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5199: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5200: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5201: }
1.227 brouard 5202: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5203: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5204: break;
1.224 brouard 5205: #else
1.227 brouard 5206: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5207: if(firsthree == 0){
1.262 brouard 5208: 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 5209: firsthree=1;
5210: }
1.262 brouard 5211: 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 5212: mw[++mi][i]=m;
5213: mli=m;
5214: }
5215: if(s[m][i]==-2){ /* Vital status is really unknown */
5216: nbwarn++;
5217: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5218: 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);
5219: 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);
5220: }
5221: break;
5222: }
5223: break;
1.224 brouard 5224: #endif
1.227 brouard 5225: }/* End m >= lastpass */
1.126 brouard 5226: }/* end while */
1.224 brouard 5227:
1.227 brouard 5228: /* 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 5229: /* After last pass */
1.224 brouard 5230: /* Treating death states */
1.214 brouard 5231: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5232: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5233: /* } */
1.126 brouard 5234: mi++; /* Death is another wave */
5235: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5236: /* Only death is a correct wave */
1.126 brouard 5237: mw[mi][i]=m;
1.257 brouard 5238: } /* else not in a death state */
1.224 brouard 5239: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5240: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5241: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5242: 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 */
5243: nbwarn++;
5244: if(firstfiv==0){
5245: 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 );
5246: firstfiv=1;
5247: }else{
5248: 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 );
5249: }
5250: }else{ /* Death occured afer last wave potential bias */
5251: nberr++;
5252: if(firstwo==0){
1.257 brouard 5253: 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 5254: firstwo=1;
5255: }
1.257 brouard 5256: 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 5257: }
1.257 brouard 5258: }else{ /* if date of interview is unknown */
1.227 brouard 5259: /* death is known but not confirmed by death status at any wave */
5260: if(firstfour==0){
5261: 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 );
5262: firstfour=1;
5263: }
5264: 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 5265: }
1.224 brouard 5266: } /* end if date of death is known */
5267: #endif
5268: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5269: /* wav[i]=mw[mi][i]; */
1.126 brouard 5270: if(mi==0){
5271: nbwarn++;
5272: if(first==0){
1.227 brouard 5273: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5274: first=1;
1.126 brouard 5275: }
5276: if(first==1){
1.227 brouard 5277: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5278: }
5279: } /* end mi==0 */
5280: } /* End individuals */
1.214 brouard 5281: /* wav and mw are no more changed */
1.223 brouard 5282:
1.214 brouard 5283:
1.126 brouard 5284: for(i=1; i<=imx; i++){
5285: for(mi=1; mi<wav[i];mi++){
5286: if (stepm <=0)
1.227 brouard 5287: dh[mi][i]=1;
1.126 brouard 5288: else{
1.260 brouard 5289: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5290: if (agedc[i] < 2*AGESUP) {
5291: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5292: if(j==0) j=1; /* Survives at least one month after exam */
5293: else if(j<0){
5294: nberr++;
5295: 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]);
5296: j=1; /* Temporary Dangerous patch */
5297: 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);
5298: 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]);
5299: 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);
5300: }
5301: k=k+1;
5302: if (j >= jmax){
5303: jmax=j;
5304: ijmax=i;
5305: }
5306: if (j <= jmin){
5307: jmin=j;
5308: ijmin=i;
5309: }
5310: sum=sum+j;
5311: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5312: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5313: }
5314: }
5315: else{
5316: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5317: /* 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 5318:
1.227 brouard 5319: k=k+1;
5320: if (j >= jmax) {
5321: jmax=j;
5322: ijmax=i;
5323: }
5324: else if (j <= jmin){
5325: jmin=j;
5326: ijmin=i;
5327: }
5328: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5329: /*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]);*/
5330: if(j<0){
5331: nberr++;
5332: 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]);
5333: 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]);
5334: }
5335: sum=sum+j;
5336: }
5337: jk= j/stepm;
5338: jl= j -jk*stepm;
5339: ju= j -(jk+1)*stepm;
5340: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5341: if(jl==0){
5342: dh[mi][i]=jk;
5343: bh[mi][i]=0;
5344: }else{ /* We want a negative bias in order to only have interpolation ie
5345: * to avoid the price of an extra matrix product in likelihood */
5346: dh[mi][i]=jk+1;
5347: bh[mi][i]=ju;
5348: }
5349: }else{
5350: if(jl <= -ju){
5351: dh[mi][i]=jk;
5352: bh[mi][i]=jl; /* bias is positive if real duration
5353: * is higher than the multiple of stepm and negative otherwise.
5354: */
5355: }
5356: else{
5357: dh[mi][i]=jk+1;
5358: bh[mi][i]=ju;
5359: }
5360: if(dh[mi][i]==0){
5361: dh[mi][i]=1; /* At least one step */
5362: bh[mi][i]=ju; /* At least one step */
5363: /* 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);*/
5364: }
5365: } /* end if mle */
1.126 brouard 5366: }
5367: } /* end wave */
5368: }
5369: jmean=sum/k;
5370: 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 5371: 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 5372: }
1.126 brouard 5373:
5374: /*********** Tricode ****************************/
1.220 brouard 5375: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5376: {
5377: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5378: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5379: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5380: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5381: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5382: */
1.130 brouard 5383:
1.242 brouard 5384: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5385: int modmaxcovj=0; /* Modality max of covariates j */
5386: int cptcode=0; /* Modality max of covariates j */
5387: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5388:
5389:
1.242 brouard 5390: /* cptcoveff=0; */
5391: /* *cptcov=0; */
1.126 brouard 5392:
1.242 brouard 5393: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5394: for (k=1; k <= maxncov; k++)
5395: for(j=1; j<=2; j++)
5396: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5397:
1.242 brouard 5398: /* Loop on covariates without age and products and no quantitative variable */
5399: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5400: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5401: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5402: switch(Fixed[k]) {
5403: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5404: 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*/
5405: ij=(int)(covar[Tvar[k]][i]);
5406: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5407: * If product of Vn*Vm, still boolean *:
5408: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5409: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5410: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5411: modality of the nth covariate of individual i. */
5412: if (ij > modmaxcovj)
5413: modmaxcovj=ij;
5414: else if (ij < modmincovj)
5415: modmincovj=ij;
1.287 brouard 5416: if (ij <0 || ij >1 ){
5417: printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5418: fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5419: }
5420: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5421: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5422: exit(1);
5423: }else
5424: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5425: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5426: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5427: /* getting the maximum value of the modality of the covariate
5428: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5429: female ies 1, then modmaxcovj=1.
5430: */
5431: } /* end for loop on individuals i */
5432: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5433: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5434: cptcode=modmaxcovj;
5435: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5436: /*for (i=0; i<=cptcode; i++) {*/
5437: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5438: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5439: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5440: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5441: if( j != -1){
5442: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5443: covariate for which somebody answered excluding
5444: undefined. Usually 2: 0 and 1. */
5445: }
5446: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5447: covariate for which somebody answered including
5448: undefined. Usually 3: -1, 0 and 1. */
5449: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5450: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5451: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5452:
1.242 brouard 5453: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5454: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5455: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5456: /* modmincovj=3; modmaxcovj = 7; */
5457: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5458: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5459: /* defining two dummy variables: variables V1_1 and V1_2.*/
5460: /* nbcode[Tvar[j]][ij]=k; */
5461: /* nbcode[Tvar[j]][1]=0; */
5462: /* nbcode[Tvar[j]][2]=1; */
5463: /* nbcode[Tvar[j]][3]=2; */
5464: /* To be continued (not working yet). */
5465: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5466:
5467: /* 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*/
5468: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5469: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5470: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5471: /*, could be restored in the future */
5472: 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 5473: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5474: break;
5475: }
5476: ij++;
1.287 brouard 5477: 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 5478: cptcode = ij; /* New max modality for covar j */
5479: } /* end of loop on modality i=-1 to 1 or more */
5480: break;
5481: case 1: /* Testing on varying covariate, could be simple and
5482: * should look at waves or product of fixed *
5483: * varying. No time to test -1, assuming 0 and 1 only */
5484: ij=0;
5485: for(i=0; i<=1;i++){
5486: nbcode[Tvar[k]][++ij]=i;
5487: }
5488: break;
5489: default:
5490: break;
5491: } /* end switch */
5492: } /* end dummy test */
1.287 brouard 5493: } /* 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 5494:
5495: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5496: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5497: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5498: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5499: 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 */
5500: 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 */
5501: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5502: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5503:
5504: ij=0;
5505: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5506: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5507: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5508: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5509: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5510: /* If product not in single variable we don't print results */
5511: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5512: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5513: 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*/
5514: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5515: 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 */
5516: if(Fixed[k]!=0)
5517: anyvaryingduminmodel=1;
5518: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5519: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5520: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5521: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5522: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5523: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5524: }
5525: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5526: /* ij--; */
5527: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5528: *cptcov=ij; /*Number of total real effective covariates: effective
5529: * because they can be excluded from the model and real
5530: * if in the model but excluded because missing values, but how to get k from ij?*/
5531: for(j=ij+1; j<= cptcovt; j++){
5532: Tvaraff[j]=0;
5533: Tmodelind[j]=0;
5534: }
5535: for(j=ntveff+1; j<= cptcovt; j++){
5536: TmodelInvind[j]=0;
5537: }
5538: /* To be sorted */
5539: ;
5540: }
1.126 brouard 5541:
1.145 brouard 5542:
1.126 brouard 5543: /*********** Health Expectancies ****************/
5544:
1.235 brouard 5545: 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 5546:
5547: {
5548: /* Health expectancies, no variances */
1.164 brouard 5549: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5550: int nhstepma, nstepma; /* Decreasing with age */
5551: double age, agelim, hf;
5552: double ***p3mat;
5553: double eip;
5554:
1.238 brouard 5555: /* pstamp(ficreseij); */
1.126 brouard 5556: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5557: fprintf(ficreseij,"# Age");
5558: for(i=1; i<=nlstate;i++){
5559: for(j=1; j<=nlstate;j++){
5560: fprintf(ficreseij," e%1d%1d ",i,j);
5561: }
5562: fprintf(ficreseij," e%1d. ",i);
5563: }
5564: fprintf(ficreseij,"\n");
5565:
5566:
5567: if(estepm < stepm){
5568: printf ("Problem %d lower than %d\n",estepm, stepm);
5569: }
5570: else hstepm=estepm;
5571: /* We compute the life expectancy from trapezoids spaced every estepm months
5572: * This is mainly to measure the difference between two models: for example
5573: * if stepm=24 months pijx are given only every 2 years and by summing them
5574: * we are calculating an estimate of the Life Expectancy assuming a linear
5575: * progression in between and thus overestimating or underestimating according
5576: * to the curvature of the survival function. If, for the same date, we
5577: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5578: * to compare the new estimate of Life expectancy with the same linear
5579: * hypothesis. A more precise result, taking into account a more precise
5580: * curvature will be obtained if estepm is as small as stepm. */
5581:
5582: /* For example we decided to compute the life expectancy with the smallest unit */
5583: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5584: nhstepm is the number of hstepm from age to agelim
5585: nstepm is the number of stepm from age to agelin.
1.270 brouard 5586: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5587: and note for a fixed period like estepm months */
5588: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5589: survival function given by stepm (the optimization length). Unfortunately it
5590: means that if the survival funtion is printed only each two years of age and if
5591: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5592: results. So we changed our mind and took the option of the best precision.
5593: */
5594: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5595:
5596: agelim=AGESUP;
5597: /* If stepm=6 months */
5598: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5599: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5600:
5601: /* nhstepm age range expressed in number of stepm */
5602: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5603: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5604: /* if (stepm >= YEARM) hstepm=1;*/
5605: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5606: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5607:
5608: for (age=bage; age<=fage; age ++){
5609: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5610: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5611: /* if (stepm >= YEARM) hstepm=1;*/
5612: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5613:
5614: /* If stepm=6 months */
5615: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5616: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5617:
1.235 brouard 5618: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5619:
5620: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5621:
5622: printf("%d|",(int)age);fflush(stdout);
5623: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5624:
5625: /* Computing expectancies */
5626: for(i=1; i<=nlstate;i++)
5627: for(j=1; j<=nlstate;j++)
5628: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5629: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5630:
5631: /* 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]);*/
5632:
5633: }
5634:
5635: fprintf(ficreseij,"%3.0f",age );
5636: for(i=1; i<=nlstate;i++){
5637: eip=0;
5638: for(j=1; j<=nlstate;j++){
5639: eip +=eij[i][j][(int)age];
5640: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5641: }
5642: fprintf(ficreseij,"%9.4f", eip );
5643: }
5644: fprintf(ficreseij,"\n");
5645:
5646: }
5647: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5648: printf("\n");
5649: fprintf(ficlog,"\n");
5650:
5651: }
5652:
1.235 brouard 5653: 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 5654:
5655: {
5656: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5657: to initial status i, ei. .
1.126 brouard 5658: */
5659: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5660: int nhstepma, nstepma; /* Decreasing with age */
5661: double age, agelim, hf;
5662: double ***p3matp, ***p3matm, ***varhe;
5663: double **dnewm,**doldm;
5664: double *xp, *xm;
5665: double **gp, **gm;
5666: double ***gradg, ***trgradg;
5667: int theta;
5668:
5669: double eip, vip;
5670:
5671: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5672: xp=vector(1,npar);
5673: xm=vector(1,npar);
5674: dnewm=matrix(1,nlstate*nlstate,1,npar);
5675: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5676:
5677: pstamp(ficresstdeij);
5678: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5679: fprintf(ficresstdeij,"# Age");
5680: for(i=1; i<=nlstate;i++){
5681: for(j=1; j<=nlstate;j++)
5682: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5683: fprintf(ficresstdeij," e%1d. ",i);
5684: }
5685: fprintf(ficresstdeij,"\n");
5686:
5687: pstamp(ficrescveij);
5688: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5689: fprintf(ficrescveij,"# Age");
5690: for(i=1; i<=nlstate;i++)
5691: for(j=1; j<=nlstate;j++){
5692: cptj= (j-1)*nlstate+i;
5693: for(i2=1; i2<=nlstate;i2++)
5694: for(j2=1; j2<=nlstate;j2++){
5695: cptj2= (j2-1)*nlstate+i2;
5696: if(cptj2 <= cptj)
5697: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5698: }
5699: }
5700: fprintf(ficrescveij,"\n");
5701:
5702: if(estepm < stepm){
5703: printf ("Problem %d lower than %d\n",estepm, stepm);
5704: }
5705: else hstepm=estepm;
5706: /* We compute the life expectancy from trapezoids spaced every estepm months
5707: * This is mainly to measure the difference between two models: for example
5708: * if stepm=24 months pijx are given only every 2 years and by summing them
5709: * we are calculating an estimate of the Life Expectancy assuming a linear
5710: * progression in between and thus overestimating or underestimating according
5711: * to the curvature of the survival function. If, for the same date, we
5712: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5713: * to compare the new estimate of Life expectancy with the same linear
5714: * hypothesis. A more precise result, taking into account a more precise
5715: * curvature will be obtained if estepm is as small as stepm. */
5716:
5717: /* For example we decided to compute the life expectancy with the smallest unit */
5718: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5719: nhstepm is the number of hstepm from age to agelim
5720: nstepm is the number of stepm from age to agelin.
5721: Look at hpijx to understand the reason of that which relies in memory size
5722: and note for a fixed period like estepm months */
5723: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5724: survival function given by stepm (the optimization length). Unfortunately it
5725: means that if the survival funtion is printed only each two years of age and if
5726: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5727: results. So we changed our mind and took the option of the best precision.
5728: */
5729: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5730:
5731: /* If stepm=6 months */
5732: /* nhstepm age range expressed in number of stepm */
5733: agelim=AGESUP;
5734: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5735: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5736: /* if (stepm >= YEARM) hstepm=1;*/
5737: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5738:
5739: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5740: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5741: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5742: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5743: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5744: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5745:
5746: for (age=bage; age<=fage; age ++){
5747: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5748: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5749: /* if (stepm >= YEARM) hstepm=1;*/
5750: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5751:
1.126 brouard 5752: /* If stepm=6 months */
5753: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5754: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5755:
5756: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5757:
1.126 brouard 5758: /* Computing Variances of health expectancies */
5759: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5760: decrease memory allocation */
5761: for(theta=1; theta <=npar; theta++){
5762: for(i=1; i<=npar; i++){
1.222 brouard 5763: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5764: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5765: }
1.235 brouard 5766: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5767: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5768:
1.126 brouard 5769: for(j=1; j<= nlstate; j++){
1.222 brouard 5770: for(i=1; i<=nlstate; i++){
5771: for(h=0; h<=nhstepm-1; h++){
5772: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5773: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5774: }
5775: }
1.126 brouard 5776: }
1.218 brouard 5777:
1.126 brouard 5778: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5779: for(h=0; h<=nhstepm-1; h++){
5780: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5781: }
1.126 brouard 5782: }/* End theta */
5783:
5784:
5785: for(h=0; h<=nhstepm-1; h++)
5786: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5787: for(theta=1; theta <=npar; theta++)
5788: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5789:
1.218 brouard 5790:
1.222 brouard 5791: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5792: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5793: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5794:
1.222 brouard 5795: printf("%d|",(int)age);fflush(stdout);
5796: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5797: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5798: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5799: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5800: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5801: for(ij=1;ij<=nlstate*nlstate;ij++)
5802: for(ji=1;ji<=nlstate*nlstate;ji++)
5803: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5804: }
5805: }
1.218 brouard 5806:
1.126 brouard 5807: /* Computing expectancies */
1.235 brouard 5808: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5809: for(i=1; i<=nlstate;i++)
5810: for(j=1; j<=nlstate;j++)
1.222 brouard 5811: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5812: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5813:
1.222 brouard 5814: /* 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 5815:
1.222 brouard 5816: }
1.269 brouard 5817:
5818: /* Standard deviation of expectancies ij */
1.126 brouard 5819: fprintf(ficresstdeij,"%3.0f",age );
5820: for(i=1; i<=nlstate;i++){
5821: eip=0.;
5822: vip=0.;
5823: for(j=1; j<=nlstate;j++){
1.222 brouard 5824: eip += eij[i][j][(int)age];
5825: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5826: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5827: 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 5828: }
5829: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5830: }
5831: fprintf(ficresstdeij,"\n");
1.218 brouard 5832:
1.269 brouard 5833: /* Variance of expectancies ij */
1.126 brouard 5834: fprintf(ficrescveij,"%3.0f",age );
5835: for(i=1; i<=nlstate;i++)
5836: for(j=1; j<=nlstate;j++){
1.222 brouard 5837: cptj= (j-1)*nlstate+i;
5838: for(i2=1; i2<=nlstate;i2++)
5839: for(j2=1; j2<=nlstate;j2++){
5840: cptj2= (j2-1)*nlstate+i2;
5841: if(cptj2 <= cptj)
5842: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5843: }
1.126 brouard 5844: }
5845: fprintf(ficrescveij,"\n");
1.218 brouard 5846:
1.126 brouard 5847: }
5848: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5849: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5850: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5851: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5852: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5853: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5854: printf("\n");
5855: fprintf(ficlog,"\n");
1.218 brouard 5856:
1.126 brouard 5857: free_vector(xm,1,npar);
5858: free_vector(xp,1,npar);
5859: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5860: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5861: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5862: }
1.218 brouard 5863:
1.126 brouard 5864: /************ Variance ******************/
1.235 brouard 5865: 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 5866: {
1.279 brouard 5867: /** Variance of health expectancies
5868: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5869: * double **newm;
5870: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5871: */
1.218 brouard 5872:
5873: /* int movingaverage(); */
5874: double **dnewm,**doldm;
5875: double **dnewmp,**doldmp;
5876: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 5877: int first=0;
1.218 brouard 5878: int k;
5879: double *xp;
1.279 brouard 5880: double **gp, **gm; /**< for var eij */
5881: double ***gradg, ***trgradg; /**< for var eij */
5882: double **gradgp, **trgradgp; /**< for var p point j */
5883: double *gpp, *gmp; /**< for var p point j */
5884: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5885: double ***p3mat;
5886: double age,agelim, hf;
5887: /* double ***mobaverage; */
5888: int theta;
5889: char digit[4];
5890: char digitp[25];
5891:
5892: char fileresprobmorprev[FILENAMELENGTH];
5893:
5894: if(popbased==1){
5895: if(mobilav!=0)
5896: strcpy(digitp,"-POPULBASED-MOBILAV_");
5897: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5898: }
5899: else
5900: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5901:
1.218 brouard 5902: /* if (mobilav!=0) { */
5903: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5904: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5905: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5906: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5907: /* } */
5908: /* } */
5909:
5910: strcpy(fileresprobmorprev,"PRMORPREV-");
5911: sprintf(digit,"%-d",ij);
5912: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5913: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5914: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5915: strcat(fileresprobmorprev,fileresu);
5916: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5917: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5918: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5919: }
5920: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5921: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5922: pstamp(ficresprobmorprev);
5923: 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 5924: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5925: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5926: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5927: }
5928: for(j=1;j<=cptcoveff;j++)
5929: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5930: fprintf(ficresprobmorprev,"\n");
5931:
1.218 brouard 5932: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5933: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5934: fprintf(ficresprobmorprev," p.%-d SE",j);
5935: for(i=1; i<=nlstate;i++)
5936: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5937: }
5938: fprintf(ficresprobmorprev,"\n");
5939:
5940: fprintf(ficgp,"\n# Routine varevsij");
5941: fprintf(ficgp,"\nunset title \n");
5942: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5943: 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");
5944: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5945:
1.218 brouard 5946: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5947: pstamp(ficresvij);
5948: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5949: if(popbased==1)
5950: 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);
5951: else
5952: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5953: fprintf(ficresvij,"# Age");
5954: for(i=1; i<=nlstate;i++)
5955: for(j=1; j<=nlstate;j++)
5956: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5957: fprintf(ficresvij,"\n");
5958:
5959: xp=vector(1,npar);
5960: dnewm=matrix(1,nlstate,1,npar);
5961: doldm=matrix(1,nlstate,1,nlstate);
5962: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5963: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5964:
5965: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5966: gpp=vector(nlstate+1,nlstate+ndeath);
5967: gmp=vector(nlstate+1,nlstate+ndeath);
5968: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5969:
1.218 brouard 5970: if(estepm < stepm){
5971: printf ("Problem %d lower than %d\n",estepm, stepm);
5972: }
5973: else hstepm=estepm;
5974: /* For example we decided to compute the life expectancy with the smallest unit */
5975: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5976: nhstepm is the number of hstepm from age to agelim
5977: nstepm is the number of stepm from age to agelim.
5978: Look at function hpijx to understand why because of memory size limitations,
5979: we decided (b) to get a life expectancy respecting the most precise curvature of the
5980: survival function given by stepm (the optimization length). Unfortunately it
5981: means that if the survival funtion is printed every two years of age and if
5982: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5983: results. So we changed our mind and took the option of the best precision.
5984: */
5985: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5986: agelim = AGESUP;
5987: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5988: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5989: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5990: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5991: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5992: gp=matrix(0,nhstepm,1,nlstate);
5993: gm=matrix(0,nhstepm,1,nlstate);
5994:
5995:
5996: for(theta=1; theta <=npar; theta++){
5997: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5998: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5999: }
1.279 brouard 6000: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6001: * returns into prlim .
1.288 brouard 6002: */
1.242 brouard 6003: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6004:
6005: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6006: if (popbased==1) {
6007: if(mobilav ==0){
6008: for(i=1; i<=nlstate;i++)
6009: prlim[i][i]=probs[(int)age][i][ij];
6010: }else{ /* mobilav */
6011: for(i=1; i<=nlstate;i++)
6012: prlim[i][i]=mobaverage[(int)age][i][ij];
6013: }
6014: }
1.279 brouard 6015: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}_x\f$ at horizon h.
6016: */
6017: 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 6018: /**< 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 6019: * at horizon h in state j including mortality.
6020: */
1.218 brouard 6021: for(j=1; j<= nlstate; j++){
6022: for(h=0; h<=nhstepm; h++){
6023: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6024: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6025: }
6026: }
1.279 brouard 6027: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6028: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6029: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6030: */
6031: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6032: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6033: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6034: }
6035:
6036: /* Again with minus shift */
1.218 brouard 6037:
6038: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6039: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6040:
1.242 brouard 6041: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6042:
6043: if (popbased==1) {
6044: if(mobilav ==0){
6045: for(i=1; i<=nlstate;i++)
6046: prlim[i][i]=probs[(int)age][i][ij];
6047: }else{ /* mobilav */
6048: for(i=1; i<=nlstate;i++)
6049: prlim[i][i]=mobaverage[(int)age][i][ij];
6050: }
6051: }
6052:
1.235 brouard 6053: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6054:
6055: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6056: for(h=0; h<=nhstepm; h++){
6057: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6058: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6059: }
6060: }
6061: /* This for computing probability of death (h=1 means
6062: computed over hstepm matrices product = hstepm*stepm months)
6063: as a weighted average of prlim.
6064: */
6065: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6066: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6067: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6068: }
1.279 brouard 6069: /* end shifting computations */
6070:
6071: /**< Computing gradient matrix at horizon h
6072: */
1.218 brouard 6073: for(j=1; j<= nlstate; j++) /* vareij */
6074: for(h=0; h<=nhstepm; h++){
6075: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6076: }
1.279 brouard 6077: /**< Gradient of overall mortality p.3 (or p.j)
6078: */
6079: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6080: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6081: }
6082:
6083: } /* End theta */
1.279 brouard 6084:
6085: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6086: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6087:
6088: for(h=0; h<=nhstepm; h++) /* veij */
6089: for(j=1; j<=nlstate;j++)
6090: for(theta=1; theta <=npar; theta++)
6091: trgradg[h][j][theta]=gradg[h][theta][j];
6092:
6093: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6094: for(theta=1; theta <=npar; theta++)
6095: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6096: /**< as well as its transposed matrix
6097: */
1.218 brouard 6098:
6099: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6100: for(i=1;i<=nlstate;i++)
6101: for(j=1;j<=nlstate;j++)
6102: vareij[i][j][(int)age] =0.;
1.279 brouard 6103:
6104: /* Computing trgradg by matcov by gradg at age and summing over h
6105: * and k (nhstepm) formula 15 of article
6106: * Lievre-Brouard-Heathcote
6107: */
6108:
1.218 brouard 6109: for(h=0;h<=nhstepm;h++){
6110: for(k=0;k<=nhstepm;k++){
6111: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6112: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6113: for(i=1;i<=nlstate;i++)
6114: for(j=1;j<=nlstate;j++)
6115: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6116: }
6117: }
6118:
1.279 brouard 6119: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6120: * p.j overall mortality formula 49 but computed directly because
6121: * we compute the grad (wix pijx) instead of grad (pijx),even if
6122: * wix is independent of theta.
6123: */
1.218 brouard 6124: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6125: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6126: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6127: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6128: varppt[j][i]=doldmp[j][i];
6129: /* end ppptj */
6130: /* x centered again */
6131:
1.242 brouard 6132: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6133:
6134: if (popbased==1) {
6135: if(mobilav ==0){
6136: for(i=1; i<=nlstate;i++)
6137: prlim[i][i]=probs[(int)age][i][ij];
6138: }else{ /* mobilav */
6139: for(i=1; i<=nlstate;i++)
6140: prlim[i][i]=mobaverage[(int)age][i][ij];
6141: }
6142: }
6143:
6144: /* This for computing probability of death (h=1 means
6145: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6146: as a weighted average of prlim.
6147: */
1.235 brouard 6148: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6149: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6150: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6151: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6152: }
6153: /* end probability of death */
6154:
6155: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6156: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6157: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6158: for(i=1; i<=nlstate;i++){
6159: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6160: }
6161: }
6162: fprintf(ficresprobmorprev,"\n");
6163:
6164: fprintf(ficresvij,"%.0f ",age );
6165: for(i=1; i<=nlstate;i++)
6166: for(j=1; j<=nlstate;j++){
6167: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6168: }
6169: fprintf(ficresvij,"\n");
6170: free_matrix(gp,0,nhstepm,1,nlstate);
6171: free_matrix(gm,0,nhstepm,1,nlstate);
6172: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6173: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6174: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6175: } /* End age */
6176: free_vector(gpp,nlstate+1,nlstate+ndeath);
6177: free_vector(gmp,nlstate+1,nlstate+ndeath);
6178: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6179: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6180: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6181: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6182: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6183: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6184: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6185: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6186: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6187: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6188: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6189: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6190: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6191: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6192: 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);
6193: /* 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 6194: */
1.218 brouard 6195: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6196: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6197:
1.218 brouard 6198: free_vector(xp,1,npar);
6199: free_matrix(doldm,1,nlstate,1,nlstate);
6200: free_matrix(dnewm,1,nlstate,1,npar);
6201: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6202: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6203: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6204: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6205: fclose(ficresprobmorprev);
6206: fflush(ficgp);
6207: fflush(fichtm);
6208: } /* end varevsij */
1.126 brouard 6209:
6210: /************ Variance of prevlim ******************/
1.269 brouard 6211: 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 6212: {
1.205 brouard 6213: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6214: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6215:
1.268 brouard 6216: double **dnewmpar,**doldm;
1.126 brouard 6217: int i, j, nhstepm, hstepm;
6218: double *xp;
6219: double *gp, *gm;
6220: double **gradg, **trgradg;
1.208 brouard 6221: double **mgm, **mgp;
1.126 brouard 6222: double age,agelim;
6223: int theta;
6224:
6225: pstamp(ficresvpl);
1.288 brouard 6226: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6227: fprintf(ficresvpl,"# Age ");
6228: if(nresult >=1)
6229: fprintf(ficresvpl," Result# ");
1.126 brouard 6230: for(i=1; i<=nlstate;i++)
6231: fprintf(ficresvpl," %1d-%1d",i,i);
6232: fprintf(ficresvpl,"\n");
6233:
6234: xp=vector(1,npar);
1.268 brouard 6235: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6236: doldm=matrix(1,nlstate,1,nlstate);
6237:
6238: hstepm=1*YEARM; /* Every year of age */
6239: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6240: agelim = AGESUP;
6241: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6242: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6243: if (stepm >= YEARM) hstepm=1;
6244: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6245: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6246: mgp=matrix(1,npar,1,nlstate);
6247: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6248: gp=vector(1,nlstate);
6249: gm=vector(1,nlstate);
6250:
6251: for(theta=1; theta <=npar; theta++){
6252: for(i=1; i<=npar; i++){ /* Computes gradient */
6253: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6254: }
1.288 brouard 6255: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6256: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6257: /* else */
6258: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6259: for(i=1;i<=nlstate;i++){
1.126 brouard 6260: gp[i] = prlim[i][i];
1.208 brouard 6261: mgp[theta][i] = prlim[i][i];
6262: }
1.126 brouard 6263: for(i=1; i<=npar; i++) /* Computes gradient */
6264: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6265: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6266: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6267: /* else */
6268: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6269: for(i=1;i<=nlstate;i++){
1.126 brouard 6270: gm[i] = prlim[i][i];
1.208 brouard 6271: mgm[theta][i] = prlim[i][i];
6272: }
1.126 brouard 6273: for(i=1;i<=nlstate;i++)
6274: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6275: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6276: } /* End theta */
6277:
6278: trgradg =matrix(1,nlstate,1,npar);
6279:
6280: for(j=1; j<=nlstate;j++)
6281: for(theta=1; theta <=npar; theta++)
6282: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6283: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6284: /* printf("\nmgm mgp %d ",(int)age); */
6285: /* for(j=1; j<=nlstate;j++){ */
6286: /* printf(" %d ",j); */
6287: /* for(theta=1; theta <=npar; theta++) */
6288: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6289: /* printf("\n "); */
6290: /* } */
6291: /* } */
6292: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6293: /* printf("\n gradg %d ",(int)age); */
6294: /* for(j=1; j<=nlstate;j++){ */
6295: /* printf("%d ",j); */
6296: /* for(theta=1; theta <=npar; theta++) */
6297: /* printf("%d %lf ",theta,gradg[theta][j]); */
6298: /* printf("\n "); */
6299: /* } */
6300: /* } */
1.126 brouard 6301:
6302: for(i=1;i<=nlstate;i++)
6303: varpl[i][(int)age] =0.;
1.209 brouard 6304: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6305: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6306: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6307: }else{
1.268 brouard 6308: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6309: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6310: }
1.126 brouard 6311: for(i=1;i<=nlstate;i++)
6312: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6313:
6314: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6315: if(nresult >=1)
6316: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6317: for(i=1; i<=nlstate;i++){
1.126 brouard 6318: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6319: /* for(j=1;j<=nlstate;j++) */
6320: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6321: }
1.126 brouard 6322: fprintf(ficresvpl,"\n");
6323: free_vector(gp,1,nlstate);
6324: free_vector(gm,1,nlstate);
1.208 brouard 6325: free_matrix(mgm,1,npar,1,nlstate);
6326: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6327: free_matrix(gradg,1,npar,1,nlstate);
6328: free_matrix(trgradg,1,nlstate,1,npar);
6329: } /* End age */
6330:
6331: free_vector(xp,1,npar);
6332: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6333: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6334:
6335: }
6336:
6337:
6338: /************ Variance of backprevalence limit ******************/
1.269 brouard 6339: 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 6340: {
6341: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6342: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6343:
6344: double **dnewmpar,**doldm;
6345: int i, j, nhstepm, hstepm;
6346: double *xp;
6347: double *gp, *gm;
6348: double **gradg, **trgradg;
6349: double **mgm, **mgp;
6350: double age,agelim;
6351: int theta;
6352:
6353: pstamp(ficresvbl);
6354: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6355: fprintf(ficresvbl,"# Age ");
6356: if(nresult >=1)
6357: fprintf(ficresvbl," Result# ");
6358: for(i=1; i<=nlstate;i++)
6359: fprintf(ficresvbl," %1d-%1d",i,i);
6360: fprintf(ficresvbl,"\n");
6361:
6362: xp=vector(1,npar);
6363: dnewmpar=matrix(1,nlstate,1,npar);
6364: doldm=matrix(1,nlstate,1,nlstate);
6365:
6366: hstepm=1*YEARM; /* Every year of age */
6367: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6368: agelim = AGEINF;
6369: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6370: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6371: if (stepm >= YEARM) hstepm=1;
6372: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6373: gradg=matrix(1,npar,1,nlstate);
6374: mgp=matrix(1,npar,1,nlstate);
6375: mgm=matrix(1,npar,1,nlstate);
6376: gp=vector(1,nlstate);
6377: gm=vector(1,nlstate);
6378:
6379: for(theta=1; theta <=npar; theta++){
6380: for(i=1; i<=npar; i++){ /* Computes gradient */
6381: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6382: }
6383: if(mobilavproj > 0 )
6384: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6385: else
6386: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6387: for(i=1;i<=nlstate;i++){
6388: gp[i] = bprlim[i][i];
6389: mgp[theta][i] = bprlim[i][i];
6390: }
6391: for(i=1; i<=npar; i++) /* Computes gradient */
6392: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6393: if(mobilavproj > 0 )
6394: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6395: else
6396: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6397: for(i=1;i<=nlstate;i++){
6398: gm[i] = bprlim[i][i];
6399: mgm[theta][i] = bprlim[i][i];
6400: }
6401: for(i=1;i<=nlstate;i++)
6402: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6403: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6404: } /* End theta */
6405:
6406: trgradg =matrix(1,nlstate,1,npar);
6407:
6408: for(j=1; j<=nlstate;j++)
6409: for(theta=1; theta <=npar; theta++)
6410: trgradg[j][theta]=gradg[theta][j];
6411: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6412: /* printf("\nmgm mgp %d ",(int)age); */
6413: /* for(j=1; j<=nlstate;j++){ */
6414: /* printf(" %d ",j); */
6415: /* for(theta=1; theta <=npar; theta++) */
6416: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6417: /* printf("\n "); */
6418: /* } */
6419: /* } */
6420: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6421: /* printf("\n gradg %d ",(int)age); */
6422: /* for(j=1; j<=nlstate;j++){ */
6423: /* printf("%d ",j); */
6424: /* for(theta=1; theta <=npar; theta++) */
6425: /* printf("%d %lf ",theta,gradg[theta][j]); */
6426: /* printf("\n "); */
6427: /* } */
6428: /* } */
6429:
6430: for(i=1;i<=nlstate;i++)
6431: varbpl[i][(int)age] =0.;
6432: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6433: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6434: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6435: }else{
6436: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6437: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6438: }
6439: for(i=1;i<=nlstate;i++)
6440: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6441:
6442: fprintf(ficresvbl,"%.0f ",age );
6443: if(nresult >=1)
6444: fprintf(ficresvbl,"%d ",nres );
6445: for(i=1; i<=nlstate;i++)
6446: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6447: fprintf(ficresvbl,"\n");
6448: free_vector(gp,1,nlstate);
6449: free_vector(gm,1,nlstate);
6450: free_matrix(mgm,1,npar,1,nlstate);
6451: free_matrix(mgp,1,npar,1,nlstate);
6452: free_matrix(gradg,1,npar,1,nlstate);
6453: free_matrix(trgradg,1,nlstate,1,npar);
6454: } /* End age */
6455:
6456: free_vector(xp,1,npar);
6457: free_matrix(doldm,1,nlstate,1,npar);
6458: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6459:
6460: }
6461:
6462: /************ Variance of one-step probabilities ******************/
6463: 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 6464: {
6465: int i, j=0, k1, l1, tj;
6466: int k2, l2, j1, z1;
6467: int k=0, l;
6468: int first=1, first1, first2;
6469: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6470: double **dnewm,**doldm;
6471: double *xp;
6472: double *gp, *gm;
6473: double **gradg, **trgradg;
6474: double **mu;
6475: double age, cov[NCOVMAX+1];
6476: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6477: int theta;
6478: char fileresprob[FILENAMELENGTH];
6479: char fileresprobcov[FILENAMELENGTH];
6480: char fileresprobcor[FILENAMELENGTH];
6481: double ***varpij;
6482:
6483: strcpy(fileresprob,"PROB_");
6484: strcat(fileresprob,fileres);
6485: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6486: printf("Problem with resultfile: %s\n", fileresprob);
6487: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6488: }
6489: strcpy(fileresprobcov,"PROBCOV_");
6490: strcat(fileresprobcov,fileresu);
6491: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6492: printf("Problem with resultfile: %s\n", fileresprobcov);
6493: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6494: }
6495: strcpy(fileresprobcor,"PROBCOR_");
6496: strcat(fileresprobcor,fileresu);
6497: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6498: printf("Problem with resultfile: %s\n", fileresprobcor);
6499: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6500: }
6501: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6502: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6503: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6504: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6505: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6506: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6507: pstamp(ficresprob);
6508: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6509: fprintf(ficresprob,"# Age");
6510: pstamp(ficresprobcov);
6511: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6512: fprintf(ficresprobcov,"# Age");
6513: pstamp(ficresprobcor);
6514: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6515: fprintf(ficresprobcor,"# Age");
1.126 brouard 6516:
6517:
1.222 brouard 6518: for(i=1; i<=nlstate;i++)
6519: for(j=1; j<=(nlstate+ndeath);j++){
6520: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6521: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6522: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6523: }
6524: /* fprintf(ficresprob,"\n");
6525: fprintf(ficresprobcov,"\n");
6526: fprintf(ficresprobcor,"\n");
6527: */
6528: xp=vector(1,npar);
6529: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6530: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6531: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6532: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6533: first=1;
6534: fprintf(ficgp,"\n# Routine varprob");
6535: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6536: fprintf(fichtm,"\n");
6537:
1.288 brouard 6538: 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 6539: 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);
6540: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6541: and drawn. It helps understanding how is the covariance between two incidences.\
6542: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6543: 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 6544: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6545: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6546: standard deviations wide on each axis. <br>\
6547: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6548: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6549: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6550:
1.222 brouard 6551: cov[1]=1;
6552: /* tj=cptcoveff; */
1.225 brouard 6553: tj = (int) pow(2,cptcoveff);
1.222 brouard 6554: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6555: j1=0;
1.224 brouard 6556: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6557: if (cptcovn>0) {
6558: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6559: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6560: fprintf(ficresprob, "**********\n#\n");
6561: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6562: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6563: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6564:
1.222 brouard 6565: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6566: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6567: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6568:
6569:
1.222 brouard 6570: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6571: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6572: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6573:
1.222 brouard 6574: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6575: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6576: fprintf(ficresprobcor, "**********\n#");
6577: if(invalidvarcomb[j1]){
6578: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6579: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6580: continue;
6581: }
6582: }
6583: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6584: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6585: gp=vector(1,(nlstate)*(nlstate+ndeath));
6586: gm=vector(1,(nlstate)*(nlstate+ndeath));
6587: for (age=bage; age<=fage; age ++){
6588: cov[2]=age;
6589: if(nagesqr==1)
6590: cov[3]= age*age;
6591: for (k=1; k<=cptcovn;k++) {
6592: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6593: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6594: * 1 1 1 1 1
6595: * 2 2 1 1 1
6596: * 3 1 2 1 1
6597: */
6598: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6599: }
6600: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6601: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6602: for (k=1; k<=cptcovprod;k++)
6603: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6604:
6605:
1.222 brouard 6606: for(theta=1; theta <=npar; theta++){
6607: for(i=1; i<=npar; i++)
6608: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6609:
1.222 brouard 6610: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6611:
1.222 brouard 6612: k=0;
6613: for(i=1; i<= (nlstate); i++){
6614: for(j=1; j<=(nlstate+ndeath);j++){
6615: k=k+1;
6616: gp[k]=pmmij[i][j];
6617: }
6618: }
1.220 brouard 6619:
1.222 brouard 6620: for(i=1; i<=npar; i++)
6621: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6622:
1.222 brouard 6623: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6624: k=0;
6625: for(i=1; i<=(nlstate); i++){
6626: for(j=1; j<=(nlstate+ndeath);j++){
6627: k=k+1;
6628: gm[k]=pmmij[i][j];
6629: }
6630: }
1.220 brouard 6631:
1.222 brouard 6632: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6633: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6634: }
1.126 brouard 6635:
1.222 brouard 6636: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6637: for(theta=1; theta <=npar; theta++)
6638: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6639:
1.222 brouard 6640: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6641: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6642:
1.222 brouard 6643: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6644:
1.222 brouard 6645: k=0;
6646: for(i=1; i<=(nlstate); i++){
6647: for(j=1; j<=(nlstate+ndeath);j++){
6648: k=k+1;
6649: mu[k][(int) age]=pmmij[i][j];
6650: }
6651: }
6652: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6653: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6654: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6655:
1.222 brouard 6656: /*printf("\n%d ",(int)age);
6657: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6658: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6659: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6660: }*/
1.220 brouard 6661:
1.222 brouard 6662: fprintf(ficresprob,"\n%d ",(int)age);
6663: fprintf(ficresprobcov,"\n%d ",(int)age);
6664: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6665:
1.222 brouard 6666: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6667: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6668: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6669: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6670: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6671: }
6672: i=0;
6673: for (k=1; k<=(nlstate);k++){
6674: for (l=1; l<=(nlstate+ndeath);l++){
6675: i++;
6676: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6677: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6678: for (j=1; j<=i;j++){
6679: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6680: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6681: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6682: }
6683: }
6684: }/* end of loop for state */
6685: } /* end of loop for age */
6686: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6687: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6688: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6689: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6690:
6691: /* Confidence intervalle of pij */
6692: /*
6693: fprintf(ficgp,"\nunset parametric;unset label");
6694: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6695: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6696: 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);
6697: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6698: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6699: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6700: */
6701:
6702: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6703: first1=1;first2=2;
6704: for (k2=1; k2<=(nlstate);k2++){
6705: for (l2=1; l2<=(nlstate+ndeath);l2++){
6706: if(l2==k2) continue;
6707: j=(k2-1)*(nlstate+ndeath)+l2;
6708: for (k1=1; k1<=(nlstate);k1++){
6709: for (l1=1; l1<=(nlstate+ndeath);l1++){
6710: if(l1==k1) continue;
6711: i=(k1-1)*(nlstate+ndeath)+l1;
6712: if(i<=j) continue;
6713: for (age=bage; age<=fage; age ++){
6714: if ((int)age %5==0){
6715: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6716: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6717: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6718: mu1=mu[i][(int) age]/stepm*YEARM ;
6719: mu2=mu[j][(int) age]/stepm*YEARM;
6720: c12=cv12/sqrt(v1*v2);
6721: /* Computing eigen value of matrix of covariance */
6722: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6723: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6724: if ((lc2 <0) || (lc1 <0) ){
6725: if(first2==1){
6726: first1=0;
6727: 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);
6728: }
6729: 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);
6730: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6731: /* lc2=fabs(lc2); */
6732: }
1.220 brouard 6733:
1.222 brouard 6734: /* Eigen vectors */
1.280 brouard 6735: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6736: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6737: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6738: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6739: }else
6740: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6741: /*v21=sqrt(1.-v11*v11); *//* error */
6742: v21=(lc1-v1)/cv12*v11;
6743: v12=-v21;
6744: v22=v11;
6745: tnalp=v21/v11;
6746: if(first1==1){
6747: first1=0;
6748: 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);
6749: }
6750: 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);
6751: /*printf(fignu*/
6752: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6753: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6754: if(first==1){
6755: first=0;
6756: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6757: fprintf(ficgp,"\nset parametric;unset label");
6758: 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);
6759: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6760: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6761: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6762: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6763: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6764: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6765: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6766: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6767: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6768: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6769: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6770: 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 6771: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6772: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6773: }else{
6774: first=0;
6775: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6776: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6777: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6778: 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 6779: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6780: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6781: }/* if first */
6782: } /* age mod 5 */
6783: } /* end loop age */
6784: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6785: first=1;
6786: } /*l12 */
6787: } /* k12 */
6788: } /*l1 */
6789: }/* k1 */
6790: } /* loop on combination of covariates j1 */
6791: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6792: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6793: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6794: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6795: free_vector(xp,1,npar);
6796: fclose(ficresprob);
6797: fclose(ficresprobcov);
6798: fclose(ficresprobcor);
6799: fflush(ficgp);
6800: fflush(fichtmcov);
6801: }
1.126 brouard 6802:
6803:
6804: /******************* Printing html file ***********/
1.201 brouard 6805: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6806: int lastpass, int stepm, int weightopt, char model[],\
6807: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6808: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.273 brouard 6809: double jprev1, double mprev1,double anprev1, double dateprev1, double dateproj1, double dateback1, \
6810: double jprev2, double mprev2,double anprev2, double dateprev2, double dateproj2, double dateback2){
1.237 brouard 6811: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6812:
6813: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6814: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6815: </ul>");
1.237 brouard 6816: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6817: </ul>", model);
1.214 brouard 6818: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6819: 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",
6820: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6821: 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 6822: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6823: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6824: fprintf(fichtm,"\
6825: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6826: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6827: fprintf(fichtm,"\
1.217 brouard 6828: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6829: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6830: fprintf(fichtm,"\
1.288 brouard 6831: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6832: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6833: fprintf(fichtm,"\
1.288 brouard 6834: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6835: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6836: fprintf(fichtm,"\
1.211 brouard 6837: - (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 6838: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6839: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6840: if(prevfcast==1){
6841: fprintf(fichtm,"\
6842: - Prevalence projections by age and states: \
1.201 brouard 6843: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6844: }
1.126 brouard 6845:
6846:
1.225 brouard 6847: m=pow(2,cptcoveff);
1.222 brouard 6848: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6849:
1.264 brouard 6850: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6851:
6852: jj1=0;
6853:
6854: fprintf(fichtm," \n<ul>");
6855: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6856: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6857: if(m != 1 && TKresult[nres]!= k1)
6858: continue;
6859: jj1++;
6860: if (cptcovn > 0) {
6861: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6862: for (cpt=1; cpt<=cptcoveff;cpt++){
6863: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6864: }
6865: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6866: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6867: }
6868: fprintf(fichtm,"\">");
6869:
6870: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6871: fprintf(fichtm,"************ Results for covariates");
6872: for (cpt=1; cpt<=cptcoveff;cpt++){
6873: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6874: }
6875: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6876: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6877: }
6878: if(invalidvarcomb[k1]){
6879: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6880: continue;
6881: }
6882: fprintf(fichtm,"</a></li>");
6883: } /* cptcovn >0 */
6884: }
6885: fprintf(fichtm," \n</ul>");
6886:
1.222 brouard 6887: jj1=0;
1.237 brouard 6888:
6889: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6890: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6891: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6892: continue;
1.220 brouard 6893:
1.222 brouard 6894: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6895: jj1++;
6896: if (cptcovn > 0) {
1.264 brouard 6897: fprintf(fichtm,"\n<p><a name=\"rescov");
6898: for (cpt=1; cpt<=cptcoveff;cpt++){
6899: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6900: }
6901: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6902: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6903: }
6904: fprintf(fichtm,"\"</a>");
6905:
1.222 brouard 6906: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6907: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6908: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6909: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6910: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6911: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6912: }
1.237 brouard 6913: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6914: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6915: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6916: }
6917:
1.230 brouard 6918: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6919: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6920: if(invalidvarcomb[k1]){
6921: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6922: printf("\nCombination (%d) ignored because no cases \n",k1);
6923: continue;
6924: }
6925: }
6926: /* aij, bij */
1.259 brouard 6927: 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 6928: <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 6929: /* Pij */
1.241 brouard 6930: 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> \
6931: <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 6932: /* Quasi-incidences */
6933: 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 6934: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6935: 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 6936: 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> \
6937: <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 6938: /* Survival functions (period) in state j */
6939: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 6940: 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 6941: <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 6942: }
6943: /* State specific survival functions (period) */
6944: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 6945: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
6946: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 6947: <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 6948: }
1.288 brouard 6949: /* Period (forward stable) 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 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> \
6952: <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 6953: }
6954: if(backcast==1){
1.288 brouard 6955: /* Backward prevalence in each health state */
1.222 brouard 6956: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6957: 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 6958: <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 6959: }
1.217 brouard 6960: }
1.222 brouard 6961: if(prevfcast==1){
1.288 brouard 6962: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 6963: for(cpt=1; cpt<=nlstate;cpt++){
1.288 brouard 6964: 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 6965: <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 6966: }
6967: }
1.268 brouard 6968: if(backcast==1){
6969: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6970: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6971: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6972: 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 \
6973: 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) \
6974: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6975: <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 6976: }
6977: }
1.220 brouard 6978:
1.222 brouard 6979: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6980: 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> \
6981: <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 6982: }
6983: /* } /\* end i1 *\/ */
6984: }/* End k1 */
6985: fprintf(fichtm,"</ul>");
1.126 brouard 6986:
1.222 brouard 6987: fprintf(fichtm,"\
1.126 brouard 6988: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6989: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6990: - 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 6991: But because parameters are usually highly correlated (a higher incidence of disability \
6992: and a higher incidence of recovery can give very close observed transition) it might \
6993: be very useful to look not only at linear confidence intervals estimated from the \
6994: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6995: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6996: covariance matrix of the one-step probabilities. \
6997: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6998:
1.222 brouard 6999: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7000: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7001: fprintf(fichtm,"\
1.126 brouard 7002: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7003: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7004:
1.222 brouard 7005: fprintf(fichtm,"\
1.126 brouard 7006: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7007: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7008: fprintf(fichtm,"\
1.126 brouard 7009: - 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): \
7010: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7011: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7012: fprintf(fichtm,"\
1.126 brouard 7013: - (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): \
7014: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7015: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7016: fprintf(fichtm,"\
1.288 brouard 7017: - 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 7018: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7019: fprintf(fichtm,"\
1.128 brouard 7020: - 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 7021: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7022: fprintf(fichtm,"\
1.288 brouard 7023: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7024: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7025:
7026: /* if(popforecast==1) fprintf(fichtm,"\n */
7027: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7028: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7029: /* <br>",fileres,fileres,fileres,fileres); */
7030: /* else */
7031: /* 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 7032: fflush(fichtm);
7033: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7034:
1.225 brouard 7035: m=pow(2,cptcoveff);
1.222 brouard 7036: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7037:
1.222 brouard 7038: jj1=0;
1.237 brouard 7039:
1.241 brouard 7040: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7041: for(k1=1; k1<=m;k1++){
1.253 brouard 7042: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7043: continue;
1.222 brouard 7044: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7045: jj1++;
1.126 brouard 7046: if (cptcovn > 0) {
7047: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7048: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7049: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7050: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7051: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7052: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7053: }
7054:
1.126 brouard 7055: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7056:
1.222 brouard 7057: if(invalidvarcomb[k1]){
7058: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7059: continue;
7060: }
1.126 brouard 7061: }
7062: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7063: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7064: 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 7065: <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 7066: }
7067: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7068: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7069: true period expectancies (those weighted with period prevalences are also\
7070: drawn in addition to the population based expectancies computed using\
1.241 brouard 7071: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7072: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7073: /* } /\* end i1 *\/ */
7074: }/* End k1 */
1.241 brouard 7075: }/* End nres */
1.222 brouard 7076: fprintf(fichtm,"</ul>");
7077: fflush(fichtm);
1.126 brouard 7078: }
7079:
7080: /******************* Gnuplot file **************/
1.270 brouard 7081: 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 7082:
7083: char dirfileres[132],optfileres[132];
1.264 brouard 7084: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7085: 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 7086: int lv=0, vlv=0, kl=0;
1.130 brouard 7087: int ng=0;
1.201 brouard 7088: int vpopbased;
1.223 brouard 7089: int ioffset; /* variable offset for columns */
1.270 brouard 7090: int iyearc=1; /* variable column for year of projection */
7091: int iagec=1; /* variable column for age of projection */
1.235 brouard 7092: int nres=0; /* Index of resultline */
1.266 brouard 7093: int istart=1; /* For starting graphs in projections */
1.219 brouard 7094:
1.126 brouard 7095: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7096: /* printf("Problem with file %s",optionfilegnuplot); */
7097: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7098: /* } */
7099:
7100: /*#ifdef windows */
7101: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7102: /*#endif */
1.225 brouard 7103: m=pow(2,cptcoveff);
1.126 brouard 7104:
1.274 brouard 7105: /* diagram of the model */
7106: fprintf(ficgp,"\n#Diagram of the model \n");
7107: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7108: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7109: 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);
7110:
7111: 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);
7112: fprintf(ficgp,"\n#show arrow\nunset label\n");
7113: 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);
7114: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7115: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7116: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7117: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7118:
1.202 brouard 7119: /* Contribution to likelihood */
7120: /* Plot the probability implied in the likelihood */
1.223 brouard 7121: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7122: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7123: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7124: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7125: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7126: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7127: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7128: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7129: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7130: 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));
7131: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7132: 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));
7133: for (i=1; i<= nlstate ; i ++) {
7134: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7135: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7136: 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);
7137: for (j=2; j<= nlstate+ndeath ; j ++) {
7138: 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);
7139: }
7140: fprintf(ficgp,";\nset out; unset ylabel;\n");
7141: }
7142: /* 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 */
7143: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7144: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7145: fprintf(ficgp,"\nset out;unset log\n");
7146: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7147:
1.126 brouard 7148: strcpy(dirfileres,optionfilefiname);
7149: strcpy(optfileres,"vpl");
1.223 brouard 7150: /* 1eme*/
1.238 brouard 7151: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7152: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7153: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7154: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7155: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7156: continue;
7157: /* We are interested in selected combination by the resultline */
1.246 brouard 7158: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7159: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7160: strcpy(gplotlabel,"(");
1.238 brouard 7161: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7162: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7163: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7164: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7165: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7166: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7167: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7168: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7169: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7170: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7171: }
7172: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7173: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7174: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7175: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7176: }
7177: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7178: /* printf("\n#\n"); */
1.238 brouard 7179: fprintf(ficgp,"\n#\n");
7180: if(invalidvarcomb[k1]){
1.260 brouard 7181: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7182: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7183: continue;
7184: }
1.235 brouard 7185:
1.241 brouard 7186: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7187: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7188: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7189: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7190: 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);
7191: /* 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); */
7192: /* k1-1 error should be nres-1*/
1.238 brouard 7193: for (i=1; i<= nlstate ; i ++) {
7194: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7195: else fprintf(ficgp," %%*lf (%%*lf)");
7196: }
1.288 brouard 7197: 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 7198: for (i=1; i<= nlstate ; i ++) {
7199: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7200: else fprintf(ficgp," %%*lf (%%*lf)");
7201: }
1.260 brouard 7202: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7203: for (i=1; i<= nlstate ; i ++) {
7204: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7205: else fprintf(ficgp," %%*lf (%%*lf)");
7206: }
1.265 brouard 7207: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7208:
7209: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7210: if(cptcoveff ==0){
1.271 brouard 7211: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7212: }else{
7213: kl=0;
7214: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7215: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7216: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7217: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7218: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7219: vlv= nbcode[Tvaraff[k]][lv];
7220: kl++;
7221: /* 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 *\/ */
7222: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7223: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7224: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7225: if(k==cptcoveff){
7226: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7227: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7228: }else{
7229: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7230: kl++;
7231: }
7232: } /* end covariate */
7233: } /* end if no covariate */
7234:
1.238 brouard 7235: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7236: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7237: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7238: if(cptcoveff ==0){
1.245 brouard 7239: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7240: }else{
7241: kl=0;
7242: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7243: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7244: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7245: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7246: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7247: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7248: kl++;
1.238 brouard 7249: /* 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 *\/ */
7250: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7251: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7252: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7253: if(k==cptcoveff){
1.245 brouard 7254: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7255: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7256: }else{
7257: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7258: kl++;
7259: }
7260: } /* end covariate */
7261: } /* end if no covariate */
1.268 brouard 7262: if(backcast == 1){
7263: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7264: /* k1-1 error should be nres-1*/
7265: for (i=1; i<= nlstate ; i ++) {
7266: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7267: else fprintf(ficgp," %%*lf (%%*lf)");
7268: }
1.271 brouard 7269: 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 7270: for (i=1; i<= nlstate ; i ++) {
7271: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7272: else fprintf(ficgp," %%*lf (%%*lf)");
7273: }
1.276 brouard 7274: 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 7275: for (i=1; i<= nlstate ; i ++) {
7276: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7277: else fprintf(ficgp," %%*lf (%%*lf)");
7278: }
1.274 brouard 7279: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7280: } /* end if backprojcast */
1.238 brouard 7281: } /* end if backcast */
1.276 brouard 7282: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7283: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7284: } /* nres */
1.201 brouard 7285: } /* k1 */
7286: } /* cpt */
1.235 brouard 7287:
7288:
1.126 brouard 7289: /*2 eme*/
1.238 brouard 7290: for (k1=1; k1<= m ; k1 ++){
7291: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7292: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7293: continue;
7294: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7295: strcpy(gplotlabel,"(");
1.238 brouard 7296: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7297: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7298: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7299: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7300: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7301: vlv= nbcode[Tvaraff[k]][lv];
7302: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7303: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7304: }
1.237 brouard 7305: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7306: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7307: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7308: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7309: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7310: }
1.264 brouard 7311: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7312: fprintf(ficgp,"\n#\n");
1.223 brouard 7313: if(invalidvarcomb[k1]){
7314: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7315: continue;
7316: }
1.219 brouard 7317:
1.241 brouard 7318: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7319: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7320: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7321: if(vpopbased==0){
1.238 brouard 7322: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7323: }else
1.238 brouard 7324: fprintf(ficgp,"\nreplot ");
7325: for (i=1; i<= nlstate+1 ; i ++) {
7326: k=2*i;
1.261 brouard 7327: 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 7328: for (j=1; j<= nlstate+1 ; j ++) {
7329: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7330: else fprintf(ficgp," %%*lf (%%*lf)");
7331: }
7332: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7333: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
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: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7340: 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 7341: for (j=1; j<= nlstate+1 ; j ++) {
7342: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7343: else fprintf(ficgp," %%*lf (%%*lf)");
7344: }
7345: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7346: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7347: } /* state */
7348: } /* vpopbased */
1.264 brouard 7349: 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 7350: } /* end nres */
7351: } /* k1 end 2 eme*/
7352:
7353:
7354: /*3eme*/
7355: for (k1=1; k1<= m ; k1 ++){
7356: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7357: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7358: continue;
7359:
7360: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7361: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7362: strcpy(gplotlabel,"(");
1.238 brouard 7363: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7364: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7365: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7366: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7367: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7368: vlv= nbcode[Tvaraff[k]][lv];
7369: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7370: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7371: }
7372: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7373: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7374: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7375: }
1.264 brouard 7376: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7377: fprintf(ficgp,"\n#\n");
7378: if(invalidvarcomb[k1]){
7379: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7380: continue;
7381: }
7382:
7383: /* k=2+nlstate*(2*cpt-2); */
7384: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7385: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7386: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7387: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7388: 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 7389: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7390: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7391: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7392: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7393: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7394: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7395:
1.238 brouard 7396: */
7397: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7398: 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 7399: /* 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 7400:
1.238 brouard 7401: }
1.261 brouard 7402: 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 7403: }
1.264 brouard 7404: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7405: } /* end nres */
7406: } /* end kl 3eme */
1.126 brouard 7407:
1.223 brouard 7408: /* 4eme */
1.201 brouard 7409: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7410: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7411: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7412: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7413: continue;
1.238 brouard 7414: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7415: strcpy(gplotlabel,"(");
1.238 brouard 7416: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7417: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7418: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7419: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7420: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7421: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7422: vlv= nbcode[Tvaraff[k]][lv];
7423: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7424: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7425: }
7426: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7427: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7428: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7429: }
1.264 brouard 7430: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7431: fprintf(ficgp,"\n#\n");
7432: if(invalidvarcomb[k1]){
7433: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7434: continue;
1.223 brouard 7435: }
1.238 brouard 7436:
1.241 brouard 7437: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7438: 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 7439: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7440: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7441: k=3;
7442: for (i=1; i<= nlstate ; i ++){
7443: if(i==1){
7444: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7445: }else{
7446: fprintf(ficgp,", '' ");
7447: }
7448: l=(nlstate+ndeath)*(i-1)+1;
7449: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7450: for (j=2; j<= nlstate+ndeath ; j ++)
7451: fprintf(ficgp,"+$%d",k+l+j-1);
7452: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7453: } /* nlstate */
1.264 brouard 7454: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7455: } /* end cpt state*/
7456: } /* end nres */
7457: } /* end covariate k1 */
7458:
1.220 brouard 7459: /* 5eme */
1.201 brouard 7460: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7461: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7462: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7463: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7464: continue;
1.238 brouard 7465: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7466: strcpy(gplotlabel,"(");
1.238 brouard 7467: 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);
7468: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7469: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7470: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7471: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7472: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7473: vlv= nbcode[Tvaraff[k]][lv];
7474: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7475: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7476: }
7477: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7478: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7479: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7480: }
1.264 brouard 7481: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7482: fprintf(ficgp,"\n#\n");
7483: if(invalidvarcomb[k1]){
7484: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7485: continue;
7486: }
1.227 brouard 7487:
1.241 brouard 7488: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7489: 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 7490: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7491: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7492: k=3;
7493: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7494: if(j==1)
7495: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7496: else
7497: fprintf(ficgp,", '' ");
7498: l=(nlstate+ndeath)*(cpt-1) +j;
7499: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7500: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7501: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7502: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7503: } /* nlstate */
7504: fprintf(ficgp,", '' ");
7505: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7506: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7507: l=(nlstate+ndeath)*(cpt-1) +j;
7508: if(j < nlstate)
7509: fprintf(ficgp,"$%d +",k+l);
7510: else
7511: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7512: }
1.264 brouard 7513: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7514: } /* end cpt state*/
7515: } /* end covariate */
7516: } /* end nres */
1.227 brouard 7517:
1.220 brouard 7518: /* 6eme */
1.202 brouard 7519: /* CV preval stable (period) for each covariate */
1.237 brouard 7520: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7521: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7522: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7523: continue;
1.255 brouard 7524: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7525: strcpy(gplotlabel,"(");
1.288 brouard 7526: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7527: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7528: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7529: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7530: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7531: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7532: vlv= nbcode[Tvaraff[k]][lv];
7533: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7534: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7535: }
1.237 brouard 7536: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7537: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7538: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7539: }
1.264 brouard 7540: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7541: fprintf(ficgp,"\n#\n");
1.223 brouard 7542: if(invalidvarcomb[k1]){
1.227 brouard 7543: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7544: continue;
1.223 brouard 7545: }
1.227 brouard 7546:
1.241 brouard 7547: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7548: 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 7549: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7550: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7551: k=3; /* Offset */
1.255 brouard 7552: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7553: if(i==1)
7554: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7555: else
7556: fprintf(ficgp,", '' ");
1.255 brouard 7557: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7558: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7559: for (j=2; j<= nlstate ; j ++)
7560: fprintf(ficgp,"+$%d",k+l+j-1);
7561: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7562: } /* nlstate */
1.264 brouard 7563: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7564: } /* end cpt state*/
7565: } /* end covariate */
1.227 brouard 7566:
7567:
1.220 brouard 7568: /* 7eme */
1.218 brouard 7569: if(backcast == 1){
1.288 brouard 7570: /* CV backward prevalence for each covariate */
1.237 brouard 7571: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7572: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7573: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7574: continue;
1.268 brouard 7575: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7576: strcpy(gplotlabel,"(");
1.288 brouard 7577: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7578: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7579: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7580: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7581: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7582: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7583: vlv= nbcode[Tvaraff[k]][lv];
7584: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7585: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7586: }
1.237 brouard 7587: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7588: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7589: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7590: }
1.264 brouard 7591: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7592: fprintf(ficgp,"\n#\n");
7593: if(invalidvarcomb[k1]){
7594: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7595: continue;
7596: }
7597:
1.241 brouard 7598: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7599: 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 7600: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7601: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7602: k=3; /* Offset */
1.268 brouard 7603: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7604: if(i==1)
7605: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7606: else
7607: fprintf(ficgp,", '' ");
7608: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7609: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7610: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7611: /* 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 7612: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7613: /* for (j=2; j<= nlstate ; j ++) */
7614: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7615: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7616: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7617: } /* nlstate */
1.264 brouard 7618: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7619: } /* end cpt state*/
7620: } /* end covariate */
7621: } /* End if backcast */
7622:
1.223 brouard 7623: /* 8eme */
1.218 brouard 7624: if(prevfcast==1){
1.288 brouard 7625: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7626:
1.237 brouard 7627: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7628: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7629: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7630: continue;
1.211 brouard 7631: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7632: strcpy(gplotlabel,"(");
1.288 brouard 7633: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7634: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7635: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7636: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7637: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7638: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7639: vlv= nbcode[Tvaraff[k]][lv];
7640: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7641: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7642: }
1.237 brouard 7643: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7644: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7645: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7646: }
1.264 brouard 7647: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7648: fprintf(ficgp,"\n#\n");
7649: if(invalidvarcomb[k1]){
7650: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7651: continue;
7652: }
7653:
7654: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7655: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7656: 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 7657: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7658: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7659:
7660: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7661: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7662: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7663: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7664: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7665: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7666: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7667: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7668: if(i==istart){
1.227 brouard 7669: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7670: }else{
7671: fprintf(ficgp,",\\\n '' ");
7672: }
7673: if(cptcoveff ==0){ /* No covariate */
7674: ioffset=2; /* Age is in 2 */
7675: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7676: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7677: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7678: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7679: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7680: if(i==nlstate+1){
1.270 brouard 7681: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7682: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7683: fprintf(ficgp,",\\\n '' ");
7684: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7685: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7686: offyear, \
1.268 brouard 7687: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7688: }else
1.227 brouard 7689: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7690: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7691: }else{ /* more than 2 covariates */
1.270 brouard 7692: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7693: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7694: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7695: iyearc=ioffset-1;
7696: iagec=ioffset;
1.227 brouard 7697: fprintf(ficgp," u %d:(",ioffset);
7698: kl=0;
7699: strcpy(gplotcondition,"(");
7700: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7701: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7702: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7703: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7704: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7705: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7706: kl++;
7707: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7708: kl++;
7709: if(k <cptcoveff && cptcoveff>1)
7710: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7711: }
7712: strcpy(gplotcondition+strlen(gplotcondition),")");
7713: /* 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 *\/ */
7714: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7715: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7716: /* '' 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*/
7717: if(i==nlstate+1){
1.270 brouard 7718: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7719: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7720: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7721: fprintf(ficgp," u %d:(",iagec);
7722: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7723: iyearc, iagec, offyear, \
7724: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7725: /* '' 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 7726: }else{
7727: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7728: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7729: }
7730: } /* end if covariate */
7731: } /* nlstate */
1.264 brouard 7732: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7733: } /* end cpt state*/
7734: } /* end covariate */
7735: } /* End if prevfcast */
1.227 brouard 7736:
1.268 brouard 7737: if(backcast==1){
7738: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7739:
7740: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7741: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7742: if(m != 1 && TKresult[nres]!= k1)
7743: continue;
7744: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7745: strcpy(gplotlabel,"(");
7746: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7747: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7748: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7749: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7750: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7751: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7752: vlv= nbcode[Tvaraff[k]][lv];
7753: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7754: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7755: }
7756: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7757: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7758: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7759: }
7760: strcpy(gplotlabel+strlen(gplotlabel),")");
7761: fprintf(ficgp,"\n#\n");
7762: if(invalidvarcomb[k1]){
7763: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7764: continue;
7765: }
7766:
7767: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7768: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7769: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7770: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7771: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7772:
7773: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7774: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7775: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7776: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7777: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7778: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7779: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7780: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7781: if(i==istart){
7782: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7783: }else{
7784: fprintf(ficgp,",\\\n '' ");
7785: }
7786: if(cptcoveff ==0){ /* No covariate */
7787: ioffset=2; /* Age is in 2 */
7788: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7789: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7790: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7791: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7792: fprintf(ficgp," u %d:(", ioffset);
7793: if(i==nlstate+1){
1.270 brouard 7794: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7795: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7796: fprintf(ficgp,",\\\n '' ");
7797: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7798: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7799: offbyear, \
7800: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7801: }else
7802: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7803: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7804: }else{ /* more than 2 covariates */
1.270 brouard 7805: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7806: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7807: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7808: iyearc=ioffset-1;
7809: iagec=ioffset;
1.268 brouard 7810: fprintf(ficgp," u %d:(",ioffset);
7811: kl=0;
7812: strcpy(gplotcondition,"(");
7813: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7814: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7815: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7816: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7817: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7818: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7819: kl++;
7820: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7821: kl++;
7822: if(k <cptcoveff && cptcoveff>1)
7823: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7824: }
7825: strcpy(gplotcondition+strlen(gplotcondition),")");
7826: /* 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 *\/ */
7827: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7828: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7829: /* '' 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*/
7830: if(i==nlstate+1){
1.270 brouard 7831: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7832: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7833: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7834: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7835: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7836: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7837: iyearc,iagec,offbyear, \
7838: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7839: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7840: }else{
7841: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7842: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7843: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7844: }
7845: } /* end if covariate */
7846: } /* nlstate */
7847: fprintf(ficgp,"\nset out; unset label;\n");
7848: } /* end cpt state*/
7849: } /* end covariate */
7850: } /* End if backcast */
7851:
1.227 brouard 7852:
1.238 brouard 7853: /* 9eme writing MLE parameters */
7854: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7855: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7856: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7857: for(k=1; k <=(nlstate+ndeath); k++){
7858: if (k != i) {
1.227 brouard 7859: fprintf(ficgp,"# current state %d\n",k);
7860: for(j=1; j <=ncovmodel; j++){
7861: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7862: jk++;
7863: }
7864: fprintf(ficgp,"\n");
1.126 brouard 7865: }
7866: }
1.223 brouard 7867: }
1.187 brouard 7868: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7869:
1.145 brouard 7870: /*goto avoid;*/
1.238 brouard 7871: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7872: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7873: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7874: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7875: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7876: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7877: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7878: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7879: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7880: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7881: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7882: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7883: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7884: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7885: fprintf(ficgp,"#\n");
1.223 brouard 7886: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7887: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7888: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7889: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7890: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7891: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7892: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7893: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7894: continue;
1.264 brouard 7895: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7896: strcpy(gplotlabel,"(");
1.276 brouard 7897: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7898: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7899: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7900: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7901: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7902: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7903: vlv= nbcode[Tvaraff[k]][lv];
7904: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7905: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7906: }
1.237 brouard 7907: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7908: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7909: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7910: }
1.264 brouard 7911: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7912: fprintf(ficgp,"\n#\n");
1.264 brouard 7913: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7914: fprintf(ficgp,"\nset key outside ");
7915: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7916: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7917: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7918: if (ng==1){
7919: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7920: fprintf(ficgp,"\nunset log y");
7921: }else if (ng==2){
7922: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7923: fprintf(ficgp,"\nset log y");
7924: }else if (ng==3){
7925: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7926: fprintf(ficgp,"\nset log y");
7927: }else
7928: fprintf(ficgp,"\nunset title ");
7929: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7930: i=1;
7931: for(k2=1; k2<=nlstate; k2++) {
7932: k3=i;
7933: for(k=1; k<=(nlstate+ndeath); k++) {
7934: if (k != k2){
7935: switch( ng) {
7936: case 1:
7937: if(nagesqr==0)
7938: fprintf(ficgp," p%d+p%d*x",i,i+1);
7939: else /* nagesqr =1 */
7940: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7941: break;
7942: case 2: /* ng=2 */
7943: if(nagesqr==0)
7944: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7945: else /* nagesqr =1 */
7946: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7947: break;
7948: case 3:
7949: if(nagesqr==0)
7950: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7951: else /* nagesqr =1 */
7952: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7953: break;
7954: }
7955: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7956: ijp=1; /* product no age */
7957: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7958: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7959: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7960: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7961: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7962: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7963: if(DummyV[j]==0){
7964: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7965: }else{ /* quantitative */
7966: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7967: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7968: }
7969: ij++;
1.237 brouard 7970: }
1.268 brouard 7971: }
7972: }else if(cptcovprod >0){
7973: if(j==Tprod[ijp]) { /* */
7974: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7975: if(ijp <=cptcovprod) { /* Product */
7976: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7977: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7978: /* 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)]); */
7979: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7980: }else{ /* Vn is dummy and Vm is quanti */
7981: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7982: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7983: }
7984: }else{ /* Vn*Vm Vn is quanti */
7985: if(DummyV[Tvard[ijp][2]]==0){
7986: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7987: }else{ /* Both quanti */
7988: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7989: }
1.237 brouard 7990: }
1.268 brouard 7991: ijp++;
1.237 brouard 7992: }
1.268 brouard 7993: } /* end Tprod */
1.237 brouard 7994: } else{ /* simple covariate */
1.264 brouard 7995: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7996: if(Dummy[j]==0){
7997: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7998: }else{ /* quantitative */
7999: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8000: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8001: }
1.237 brouard 8002: } /* end simple */
8003: } /* end j */
1.223 brouard 8004: }else{
8005: i=i-ncovmodel;
8006: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8007: fprintf(ficgp," (1.");
8008: }
1.227 brouard 8009:
1.223 brouard 8010: if(ng != 1){
8011: fprintf(ficgp,")/(1");
1.227 brouard 8012:
1.264 brouard 8013: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8014: if(nagesqr==0)
1.264 brouard 8015: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8016: else /* nagesqr =1 */
1.264 brouard 8017: 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 8018:
1.223 brouard 8019: ij=1;
8020: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8021: if(cptcovage >0){
8022: if((j-2)==Tage[ij]) { /* Bug valgrind */
8023: if(ij <=cptcovage) { /* Bug valgrind */
8024: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8025: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8026: ij++;
8027: }
8028: }
8029: }else
8030: 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 8031: }
8032: fprintf(ficgp,")");
8033: }
8034: fprintf(ficgp,")");
8035: if(ng ==2)
1.276 brouard 8036: 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 8037: else /* ng= 3 */
1.276 brouard 8038: 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 8039: }else{ /* end ng <> 1 */
8040: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8041: 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 8042: }
8043: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8044: fprintf(ficgp,",");
8045: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8046: fprintf(ficgp,",");
8047: i=i+ncovmodel;
8048: } /* end k */
8049: } /* end k2 */
1.276 brouard 8050: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8051: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8052: } /* end k1 */
1.223 brouard 8053: } /* end ng */
8054: /* avoid: */
8055: fflush(ficgp);
1.126 brouard 8056: } /* end gnuplot */
8057:
8058:
8059: /*************** Moving average **************/
1.219 brouard 8060: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8061: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8062:
1.222 brouard 8063: int i, cpt, cptcod;
8064: int modcovmax =1;
8065: int mobilavrange, mob;
8066: int iage=0;
1.288 brouard 8067: int firstA1=0, firstA2=0;
1.222 brouard 8068:
1.266 brouard 8069: double sum=0., sumr=0.;
1.222 brouard 8070: double age;
1.266 brouard 8071: double *sumnewp, *sumnewm, *sumnewmr;
8072: double *agemingood, *agemaxgood;
8073: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8074:
8075:
1.278 brouard 8076: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8077: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8078:
8079: sumnewp = vector(1,ncovcombmax);
8080: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8081: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8082: agemingood = vector(1,ncovcombmax);
1.266 brouard 8083: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8084: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8085: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8086:
8087: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8088: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8089: sumnewp[cptcod]=0.;
1.266 brouard 8090: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8091: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8092: }
8093: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8094:
1.266 brouard 8095: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8096: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8097: else mobilavrange=mobilav;
8098: for (age=bage; age<=fage; age++)
8099: for (i=1; i<=nlstate;i++)
8100: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8101: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8102: /* We keep the original values on the extreme ages bage, fage and for
8103: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8104: we use a 5 terms etc. until the borders are no more concerned.
8105: */
8106: for (mob=3;mob <=mobilavrange;mob=mob+2){
8107: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8108: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8109: sumnewm[cptcod]=0.;
8110: for (i=1; i<=nlstate;i++){
1.222 brouard 8111: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8112: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8113: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8114: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8115: }
8116: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8117: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8118: } /* end i */
8119: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8120: } /* end cptcod */
1.222 brouard 8121: }/* end age */
8122: }/* end mob */
1.266 brouard 8123: }else{
8124: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8125: return -1;
1.266 brouard 8126: }
8127:
8128: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8129: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8130: if(invalidvarcomb[cptcod]){
8131: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8132: continue;
8133: }
1.219 brouard 8134:
1.266 brouard 8135: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8136: sumnewm[cptcod]=0.;
8137: sumnewmr[cptcod]=0.;
8138: for (i=1; i<=nlstate;i++){
8139: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8140: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8141: }
8142: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8143: agemingoodr[cptcod]=age;
8144: }
8145: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8146: agemingood[cptcod]=age;
8147: }
8148: } /* age */
8149: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8150: sumnewm[cptcod]=0.;
1.266 brouard 8151: sumnewmr[cptcod]=0.;
1.222 brouard 8152: for (i=1; i<=nlstate;i++){
8153: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8154: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8155: }
8156: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8157: agemaxgoodr[cptcod]=age;
1.222 brouard 8158: }
8159: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8160: agemaxgood[cptcod]=age;
8161: }
8162: } /* age */
8163: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8164: /* but they will change */
1.288 brouard 8165: firstA1=0;firstA2=0;
1.266 brouard 8166: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8167: sumnewm[cptcod]=0.;
8168: sumnewmr[cptcod]=0.;
8169: for (i=1; i<=nlstate;i++){
8170: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8171: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8172: }
8173: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8174: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8175: agemaxgoodr[cptcod]=age; /* age min */
8176: for (i=1; i<=nlstate;i++)
8177: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8178: }else{ /* bad we change the value with the values of good ages */
8179: for (i=1; i<=nlstate;i++){
8180: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8181: } /* i */
8182: } /* end bad */
8183: }else{
8184: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8185: agemaxgood[cptcod]=age;
8186: }else{ /* bad we change the value with the values of good ages */
8187: for (i=1; i<=nlstate;i++){
8188: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8189: } /* i */
8190: } /* end bad */
8191: }/* end else */
8192: sum=0.;sumr=0.;
8193: for (i=1; i<=nlstate;i++){
8194: sum+=mobaverage[(int)age][i][cptcod];
8195: sumr+=probs[(int)age][i][cptcod];
8196: }
8197: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8198: if(!firstA1){
8199: firstA1=1;
8200: 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);
8201: }
8202: 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 8203: } /* end bad */
8204: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8205: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8206: if(!firstA2){
8207: firstA2=1;
8208: 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);
8209: }
8210: 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 8211: } /* end bad */
8212: }/* age */
1.266 brouard 8213:
8214: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8215: sumnewm[cptcod]=0.;
1.266 brouard 8216: sumnewmr[cptcod]=0.;
1.222 brouard 8217: for (i=1; i<=nlstate;i++){
8218: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8219: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8220: }
8221: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8222: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8223: agemingoodr[cptcod]=age;
8224: for (i=1; i<=nlstate;i++)
8225: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8226: }else{ /* bad we change the value with the values of good ages */
8227: for (i=1; i<=nlstate;i++){
8228: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8229: } /* i */
8230: } /* end bad */
8231: }else{
8232: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8233: agemingood[cptcod]=age;
8234: }else{ /* bad */
8235: for (i=1; i<=nlstate;i++){
8236: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8237: } /* i */
8238: } /* end bad */
8239: }/* end else */
8240: sum=0.;sumr=0.;
8241: for (i=1; i<=nlstate;i++){
8242: sum+=mobaverage[(int)age][i][cptcod];
8243: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8244: }
1.266 brouard 8245: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8246: 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 8247: } /* end bad */
8248: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8249: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8250: 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 8251: } /* end bad */
8252: }/* age */
1.266 brouard 8253:
1.222 brouard 8254:
8255: for (age=bage; age<=fage; age++){
1.235 brouard 8256: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8257: sumnewp[cptcod]=0.;
8258: sumnewm[cptcod]=0.;
8259: for (i=1; i<=nlstate;i++){
8260: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8261: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8262: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8263: }
8264: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8265: }
8266: /* printf("\n"); */
8267: /* } */
1.266 brouard 8268:
1.222 brouard 8269: /* brutal averaging */
1.266 brouard 8270: /* for (i=1; i<=nlstate;i++){ */
8271: /* for (age=1; age<=bage; age++){ */
8272: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8273: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8274: /* } */
8275: /* for (age=fage; age<=AGESUP; age++){ */
8276: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8277: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8278: /* } */
8279: /* } /\* end i status *\/ */
8280: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8281: /* for (age=1; age<=AGESUP; age++){ */
8282: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8283: /* mobaverage[(int)age][i][cptcod]=0.; */
8284: /* } */
8285: /* } */
1.222 brouard 8286: }/* end cptcod */
1.266 brouard 8287: free_vector(agemaxgoodr,1, ncovcombmax);
8288: free_vector(agemaxgood,1, ncovcombmax);
8289: free_vector(agemingood,1, ncovcombmax);
8290: free_vector(agemingoodr,1, ncovcombmax);
8291: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8292: free_vector(sumnewm,1, ncovcombmax);
8293: free_vector(sumnewp,1, ncovcombmax);
8294: return 0;
8295: }/* End movingaverage */
1.218 brouard 8296:
1.126 brouard 8297:
8298: /************** Forecasting ******************/
1.269 brouard 8299: 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 8300: /* proj1, year, month, day of starting projection
8301: agemin, agemax range of age
8302: dateprev1 dateprev2 range of dates during which prevalence is computed
8303: anproj2 year of en of projection (same day and month as proj1).
8304: */
1.267 brouard 8305: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8306: double agec; /* generic age */
8307: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8308: double *popeffectif,*popcount;
8309: double ***p3mat;
1.218 brouard 8310: /* double ***mobaverage; */
1.126 brouard 8311: char fileresf[FILENAMELENGTH];
8312:
8313: agelim=AGESUP;
1.211 brouard 8314: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8315: in each health status at the date of interview (if between dateprev1 and dateprev2).
8316: We still use firstpass and lastpass as another selection.
8317: */
1.214 brouard 8318: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8319: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8320:
1.201 brouard 8321: strcpy(fileresf,"F_");
8322: strcat(fileresf,fileresu);
1.126 brouard 8323: if((ficresf=fopen(fileresf,"w"))==NULL) {
8324: printf("Problem with forecast resultfile: %s\n", fileresf);
8325: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8326: }
1.235 brouard 8327: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8328: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8329:
1.225 brouard 8330: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8331:
8332:
8333: stepsize=(int) (stepm+YEARM-1)/YEARM;
8334: if (stepm<=12) stepsize=1;
8335: if(estepm < stepm){
8336: printf ("Problem %d lower than %d\n",estepm, stepm);
8337: }
1.270 brouard 8338: else{
8339: hstepm=estepm;
8340: }
8341: if(estepm > stepm){ /* Yes every two year */
8342: stepsize=2;
8343: }
1.126 brouard 8344:
8345: hstepm=hstepm/stepm;
8346: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8347: fractional in yp1 */
8348: anprojmean=yp;
8349: yp2=modf((yp1*12),&yp);
8350: mprojmean=yp;
8351: yp1=modf((yp2*30.5),&yp);
8352: jprojmean=yp;
8353: if(jprojmean==0) jprojmean=1;
8354: if(mprojmean==0) jprojmean=1;
8355:
1.227 brouard 8356: i1=pow(2,cptcoveff);
1.126 brouard 8357: if (cptcovn < 1){i1=1;}
8358:
8359: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8360:
8361: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8362:
1.126 brouard 8363: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8364: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8365: for(k=1; k<=i1;k++){
1.253 brouard 8366: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8367: continue;
1.227 brouard 8368: if(invalidvarcomb[k]){
8369: printf("\nCombination (%d) projection ignored because no cases \n",k);
8370: continue;
8371: }
8372: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8373: for(j=1;j<=cptcoveff;j++) {
8374: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8375: }
1.235 brouard 8376: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8377: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8378: }
1.227 brouard 8379: fprintf(ficresf," yearproj age");
8380: for(j=1; j<=nlstate+ndeath;j++){
8381: for(i=1; i<=nlstate;i++)
8382: fprintf(ficresf," p%d%d",i,j);
8383: fprintf(ficresf," wp.%d",j);
8384: }
8385: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8386: fprintf(ficresf,"\n");
8387: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8388: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8389: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8390: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8391: nhstepm = nhstepm/hstepm;
8392: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8393: oldm=oldms;savm=savms;
1.268 brouard 8394: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8395: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8396: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8397: for (h=0; h<=nhstepm; h++){
8398: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8399: break;
8400: }
8401: }
8402: fprintf(ficresf,"\n");
8403: for(j=1;j<=cptcoveff;j++)
8404: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8405: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8406:
8407: for(j=1; j<=nlstate+ndeath;j++) {
8408: ppij=0.;
8409: for(i=1; i<=nlstate;i++) {
1.278 brouard 8410: if (mobilav>=1)
8411: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8412: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8413: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8414: }
1.268 brouard 8415: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8416: } /* end i */
8417: fprintf(ficresf," %.3f", ppij);
8418: }/* end j */
1.227 brouard 8419: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8420: } /* end agec */
1.266 brouard 8421: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8422: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8423: } /* end yearp */
8424: } /* end k */
1.219 brouard 8425:
1.126 brouard 8426: fclose(ficresf);
1.215 brouard 8427: printf("End of Computing forecasting \n");
8428: fprintf(ficlog,"End of Computing forecasting\n");
8429:
1.126 brouard 8430: }
8431:
1.269 brouard 8432: /************** Back Forecasting ******************/
8433: 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 8434: /* back1, year, month, day of starting backection
8435: agemin, agemax range of age
8436: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8437: anback2 year of end of backprojection (same day and month as back1).
8438: prevacurrent and prev are prevalences.
1.267 brouard 8439: */
8440: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8441: double agec; /* generic age */
1.268 brouard 8442: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8443: double *popeffectif,*popcount;
8444: double ***p3mat;
8445: /* double ***mobaverage; */
8446: char fileresfb[FILENAMELENGTH];
8447:
1.268 brouard 8448: agelim=AGEINF;
1.267 brouard 8449: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8450: in each health status at the date of interview (if between dateprev1 and dateprev2).
8451: We still use firstpass and lastpass as another selection.
8452: */
8453: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8454: /* firstpass, lastpass, stepm, weightopt, model); */
8455:
8456: /*Do we need to compute prevalence again?*/
8457:
8458: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8459:
8460: strcpy(fileresfb,"FB_");
8461: strcat(fileresfb,fileresu);
8462: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8463: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8464: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8465: }
8466: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8467: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8468:
8469: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8470:
8471:
8472: stepsize=(int) (stepm+YEARM-1)/YEARM;
8473: if (stepm<=12) stepsize=1;
8474: if(estepm < stepm){
8475: printf ("Problem %d lower than %d\n",estepm, stepm);
8476: }
1.270 brouard 8477: else{
8478: hstepm=estepm;
8479: }
8480: if(estepm >= stepm){ /* Yes every two year */
8481: stepsize=2;
8482: }
1.267 brouard 8483:
8484: hstepm=hstepm/stepm;
8485: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8486: fractional in yp1 */
8487: anprojmean=yp;
8488: yp2=modf((yp1*12),&yp);
8489: mprojmean=yp;
8490: yp1=modf((yp2*30.5),&yp);
8491: jprojmean=yp;
8492: if(jprojmean==0) jprojmean=1;
8493: if(mprojmean==0) jprojmean=1;
8494:
8495: i1=pow(2,cptcoveff);
8496: if (cptcovn < 1){i1=1;}
8497:
8498: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8499: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8500:
8501: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8502:
8503: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8504: for(k=1; k<=i1;k++){
8505: if(i1 != 1 && TKresult[nres]!= k)
8506: continue;
8507: if(invalidvarcomb[k]){
8508: printf("\nCombination (%d) projection ignored because no cases \n",k);
8509: continue;
8510: }
1.268 brouard 8511: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8512: for(j=1;j<=cptcoveff;j++) {
8513: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8514: }
8515: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8516: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8517: }
8518: fprintf(ficresfb," yearbproj age");
8519: for(j=1; j<=nlstate+ndeath;j++){
8520: for(i=1; i<=nlstate;i++)
1.268 brouard 8521: fprintf(ficresfb," b%d%d",i,j);
8522: fprintf(ficresfb," b.%d",j);
1.267 brouard 8523: }
8524: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8525: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8526: fprintf(ficresfb,"\n");
8527: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.273 brouard 8528: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8529: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8530: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8531: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8532: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8533: nhstepm = nhstepm/hstepm;
8534: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8535: oldm=oldms;savm=savms;
1.268 brouard 8536: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8537: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8538: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8539: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8540: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8541: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8542: for (h=0; h<=nhstepm; h++){
1.268 brouard 8543: if (h*hstepm/YEARM*stepm ==-yearp) {
8544: break;
8545: }
8546: }
8547: fprintf(ficresfb,"\n");
8548: for(j=1;j<=cptcoveff;j++)
8549: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8550: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8551: for(i=1; i<=nlstate+ndeath;i++) {
8552: ppij=0.;ppi=0.;
8553: for(j=1; j<=nlstate;j++) {
8554: /* if (mobilav==1) */
1.269 brouard 8555: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8556: ppi=ppi+prevacurrent[(int)agec][j][k];
8557: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8558: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8559: /* else { */
8560: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8561: /* } */
1.268 brouard 8562: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8563: } /* end j */
8564: if(ppi <0.99){
8565: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8566: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8567: }
8568: fprintf(ficresfb," %.3f", ppij);
8569: }/* end j */
1.267 brouard 8570: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8571: } /* end agec */
8572: } /* end yearp */
8573: } /* end k */
1.217 brouard 8574:
1.267 brouard 8575: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8576:
1.267 brouard 8577: fclose(ficresfb);
8578: printf("End of Computing Back forecasting \n");
8579: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8580:
1.267 brouard 8581: }
1.217 brouard 8582:
1.269 brouard 8583: /* Variance of prevalence limit: varprlim */
8584: 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 8585: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8586:
8587: char fileresvpl[FILENAMELENGTH];
8588: FILE *ficresvpl;
8589: double **oldm, **savm;
8590: double **varpl; /* Variances of prevalence limits by age */
8591: int i1, k, nres, j ;
8592:
8593: strcpy(fileresvpl,"VPL_");
8594: strcat(fileresvpl,fileresu);
8595: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8596: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8597: exit(0);
8598: }
1.288 brouard 8599: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8600: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8601:
8602: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8603: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8604:
8605: i1=pow(2,cptcoveff);
8606: if (cptcovn < 1){i1=1;}
8607:
8608: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8609: for(k=1; k<=i1;k++){
8610: if(i1 != 1 && TKresult[nres]!= k)
8611: continue;
8612: fprintf(ficresvpl,"\n#****** ");
8613: printf("\n#****** ");
8614: fprintf(ficlog,"\n#****** ");
8615: for(j=1;j<=cptcoveff;j++) {
8616: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8617: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8618: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8619: }
8620: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8621: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8622: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8623: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8624: }
8625: fprintf(ficresvpl,"******\n");
8626: printf("******\n");
8627: fprintf(ficlog,"******\n");
8628:
8629: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8630: oldm=oldms;savm=savms;
8631: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8632: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8633: /*}*/
8634: }
8635:
8636: fclose(ficresvpl);
1.288 brouard 8637: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8638: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8639:
8640: }
8641: /* Variance of back prevalence: varbprlim */
8642: 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){
8643: /*------- Variance of back (stable) prevalence------*/
8644:
8645: char fileresvbl[FILENAMELENGTH];
8646: FILE *ficresvbl;
8647:
8648: double **oldm, **savm;
8649: double **varbpl; /* Variances of back prevalence limits by age */
8650: int i1, k, nres, j ;
8651:
8652: strcpy(fileresvbl,"VBL_");
8653: strcat(fileresvbl,fileresu);
8654: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8655: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8656: exit(0);
8657: }
8658: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8659: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8660:
8661:
8662: i1=pow(2,cptcoveff);
8663: if (cptcovn < 1){i1=1;}
8664:
8665: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8666: for(k=1; k<=i1;k++){
8667: if(i1 != 1 && TKresult[nres]!= k)
8668: continue;
8669: fprintf(ficresvbl,"\n#****** ");
8670: printf("\n#****** ");
8671: fprintf(ficlog,"\n#****** ");
8672: for(j=1;j<=cptcoveff;j++) {
8673: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8674: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8675: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8676: }
8677: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8678: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8679: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8680: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8681: }
8682: fprintf(ficresvbl,"******\n");
8683: printf("******\n");
8684: fprintf(ficlog,"******\n");
8685:
8686: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8687: oldm=oldms;savm=savms;
8688:
8689: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8690: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8691: /*}*/
8692: }
8693:
8694: fclose(ficresvbl);
8695: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8696: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8697:
8698: } /* End of varbprlim */
8699:
1.126 brouard 8700: /************** Forecasting *****not tested NB*************/
1.227 brouard 8701: /* 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 8702:
1.227 brouard 8703: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8704: /* int *popage; */
8705: /* double calagedatem, agelim, kk1, kk2; */
8706: /* double *popeffectif,*popcount; */
8707: /* double ***p3mat,***tabpop,***tabpopprev; */
8708: /* /\* double ***mobaverage; *\/ */
8709: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8710:
1.227 brouard 8711: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8712: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8713: /* agelim=AGESUP; */
8714: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8715:
1.227 brouard 8716: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8717:
8718:
1.227 brouard 8719: /* strcpy(filerespop,"POP_"); */
8720: /* strcat(filerespop,fileresu); */
8721: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8722: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8723: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8724: /* } */
8725: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8726: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8727:
1.227 brouard 8728: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8729:
1.227 brouard 8730: /* /\* if (mobilav!=0) { *\/ */
8731: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8732: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8733: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8734: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8735: /* /\* } *\/ */
8736: /* /\* } *\/ */
1.126 brouard 8737:
1.227 brouard 8738: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8739: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8740:
1.227 brouard 8741: /* agelim=AGESUP; */
1.126 brouard 8742:
1.227 brouard 8743: /* hstepm=1; */
8744: /* hstepm=hstepm/stepm; */
1.218 brouard 8745:
1.227 brouard 8746: /* if (popforecast==1) { */
8747: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8748: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8749: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8750: /* } */
8751: /* popage=ivector(0,AGESUP); */
8752: /* popeffectif=vector(0,AGESUP); */
8753: /* popcount=vector(0,AGESUP); */
1.126 brouard 8754:
1.227 brouard 8755: /* i=1; */
8756: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8757:
1.227 brouard 8758: /* imx=i; */
8759: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8760: /* } */
1.218 brouard 8761:
1.227 brouard 8762: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8763: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8764: /* k=k+1; */
8765: /* fprintf(ficrespop,"\n#******"); */
8766: /* for(j=1;j<=cptcoveff;j++) { */
8767: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8768: /* } */
8769: /* fprintf(ficrespop,"******\n"); */
8770: /* fprintf(ficrespop,"# Age"); */
8771: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8772: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8773:
1.227 brouard 8774: /* for (cpt=0; cpt<=0;cpt++) { */
8775: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8776:
1.227 brouard 8777: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8778: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8779: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8780:
1.227 brouard 8781: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8782: /* oldm=oldms;savm=savms; */
8783: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8784:
1.227 brouard 8785: /* for (h=0; h<=nhstepm; h++){ */
8786: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8787: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8788: /* } */
8789: /* for(j=1; j<=nlstate+ndeath;j++) { */
8790: /* kk1=0.;kk2=0; */
8791: /* for(i=1; i<=nlstate;i++) { */
8792: /* if (mobilav==1) */
8793: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8794: /* else { */
8795: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8796: /* } */
8797: /* } */
8798: /* if (h==(int)(calagedatem+12*cpt)){ */
8799: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8800: /* /\*fprintf(ficrespop," %.3f", kk1); */
8801: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8802: /* } */
8803: /* } */
8804: /* for(i=1; i<=nlstate;i++){ */
8805: /* kk1=0.; */
8806: /* for(j=1; j<=nlstate;j++){ */
8807: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8808: /* } */
8809: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8810: /* } */
1.218 brouard 8811:
1.227 brouard 8812: /* if (h==(int)(calagedatem+12*cpt)) */
8813: /* for(j=1; j<=nlstate;j++) */
8814: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8815: /* } */
8816: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8817: /* } */
8818: /* } */
1.218 brouard 8819:
1.227 brouard 8820: /* /\******\/ */
1.218 brouard 8821:
1.227 brouard 8822: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8823: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8824: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8825: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8826: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8827:
1.227 brouard 8828: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8829: /* oldm=oldms;savm=savms; */
8830: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8831: /* for (h=0; h<=nhstepm; h++){ */
8832: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8833: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8834: /* } */
8835: /* for(j=1; j<=nlstate+ndeath;j++) { */
8836: /* kk1=0.;kk2=0; */
8837: /* for(i=1; i<=nlstate;i++) { */
8838: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8839: /* } */
8840: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8841: /* } */
8842: /* } */
8843: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8844: /* } */
8845: /* } */
8846: /* } */
8847: /* } */
1.218 brouard 8848:
1.227 brouard 8849: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8850:
1.227 brouard 8851: /* if (popforecast==1) { */
8852: /* free_ivector(popage,0,AGESUP); */
8853: /* free_vector(popeffectif,0,AGESUP); */
8854: /* free_vector(popcount,0,AGESUP); */
8855: /* } */
8856: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8857: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8858: /* fclose(ficrespop); */
8859: /* } /\* End of popforecast *\/ */
1.218 brouard 8860:
1.126 brouard 8861: int fileappend(FILE *fichier, char *optionfich)
8862: {
8863: if((fichier=fopen(optionfich,"a"))==NULL) {
8864: printf("Problem with file: %s\n", optionfich);
8865: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8866: return (0);
8867: }
8868: fflush(fichier);
8869: return (1);
8870: }
8871:
8872:
8873: /**************** function prwizard **********************/
8874: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8875: {
8876:
8877: /* Wizard to print covariance matrix template */
8878:
1.164 brouard 8879: char ca[32], cb[32];
8880: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8881: int numlinepar;
8882:
8883: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8884: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8885: for(i=1; i <=nlstate; i++){
8886: jj=0;
8887: for(j=1; j <=nlstate+ndeath; j++){
8888: if(j==i) continue;
8889: jj++;
8890: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8891: printf("%1d%1d",i,j);
8892: fprintf(ficparo,"%1d%1d",i,j);
8893: for(k=1; k<=ncovmodel;k++){
8894: /* printf(" %lf",param[i][j][k]); */
8895: /* fprintf(ficparo," %lf",param[i][j][k]); */
8896: printf(" 0.");
8897: fprintf(ficparo," 0.");
8898: }
8899: printf("\n");
8900: fprintf(ficparo,"\n");
8901: }
8902: }
8903: printf("# Scales (for hessian or gradient estimation)\n");
8904: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8905: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8906: for(i=1; i <=nlstate; i++){
8907: jj=0;
8908: for(j=1; j <=nlstate+ndeath; j++){
8909: if(j==i) continue;
8910: jj++;
8911: fprintf(ficparo,"%1d%1d",i,j);
8912: printf("%1d%1d",i,j);
8913: fflush(stdout);
8914: for(k=1; k<=ncovmodel;k++){
8915: /* printf(" %le",delti3[i][j][k]); */
8916: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8917: printf(" 0.");
8918: fprintf(ficparo," 0.");
8919: }
8920: numlinepar++;
8921: printf("\n");
8922: fprintf(ficparo,"\n");
8923: }
8924: }
8925: printf("# Covariance matrix\n");
8926: /* # 121 Var(a12)\n\ */
8927: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8928: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8929: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8930: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8931: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8932: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8933: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8934: fflush(stdout);
8935: fprintf(ficparo,"# Covariance matrix\n");
8936: /* # 121 Var(a12)\n\ */
8937: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8938: /* # ...\n\ */
8939: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8940:
8941: for(itimes=1;itimes<=2;itimes++){
8942: jj=0;
8943: for(i=1; i <=nlstate; i++){
8944: for(j=1; j <=nlstate+ndeath; j++){
8945: if(j==i) continue;
8946: for(k=1; k<=ncovmodel;k++){
8947: jj++;
8948: ca[0]= k+'a'-1;ca[1]='\0';
8949: if(itimes==1){
8950: printf("#%1d%1d%d",i,j,k);
8951: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8952: }else{
8953: printf("%1d%1d%d",i,j,k);
8954: fprintf(ficparo,"%1d%1d%d",i,j,k);
8955: /* printf(" %.5le",matcov[i][j]); */
8956: }
8957: ll=0;
8958: for(li=1;li <=nlstate; li++){
8959: for(lj=1;lj <=nlstate+ndeath; lj++){
8960: if(lj==li) continue;
8961: for(lk=1;lk<=ncovmodel;lk++){
8962: ll++;
8963: if(ll<=jj){
8964: cb[0]= lk +'a'-1;cb[1]='\0';
8965: if(ll<jj){
8966: if(itimes==1){
8967: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8968: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8969: }else{
8970: printf(" 0.");
8971: fprintf(ficparo," 0.");
8972: }
8973: }else{
8974: if(itimes==1){
8975: printf(" Var(%s%1d%1d)",ca,i,j);
8976: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8977: }else{
8978: printf(" 0.");
8979: fprintf(ficparo," 0.");
8980: }
8981: }
8982: }
8983: } /* end lk */
8984: } /* end lj */
8985: } /* end li */
8986: printf("\n");
8987: fprintf(ficparo,"\n");
8988: numlinepar++;
8989: } /* end k*/
8990: } /*end j */
8991: } /* end i */
8992: } /* end itimes */
8993:
8994: } /* end of prwizard */
8995: /******************* Gompertz Likelihood ******************************/
8996: double gompertz(double x[])
8997: {
8998: double A,B,L=0.0,sump=0.,num=0.;
8999: int i,n=0; /* n is the size of the sample */
9000:
1.220 brouard 9001: for (i=1;i<=imx ; i++) {
1.126 brouard 9002: sump=sump+weight[i];
9003: /* sump=sump+1;*/
9004: num=num+1;
9005: }
9006:
9007:
9008: /* for (i=0; i<=imx; i++)
9009: 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]);*/
9010:
9011: for (i=1;i<=imx ; i++)
9012: {
9013: if (cens[i] == 1 && wav[i]>1)
9014: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9015:
9016: if (cens[i] == 0 && wav[i]>1)
9017: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
9018: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
9019:
9020: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9021: if (wav[i] > 1 ) { /* ??? */
9022: L=L+A*weight[i];
9023: /* 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]);*/
9024: }
9025: }
9026:
9027: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9028:
9029: return -2*L*num/sump;
9030: }
9031:
1.136 brouard 9032: #ifdef GSL
9033: /******************* Gompertz_f Likelihood ******************************/
9034: double gompertz_f(const gsl_vector *v, void *params)
9035: {
9036: double A,B,LL=0.0,sump=0.,num=0.;
9037: double *x= (double *) v->data;
9038: int i,n=0; /* n is the size of the sample */
9039:
9040: for (i=0;i<=imx-1 ; i++) {
9041: sump=sump+weight[i];
9042: /* sump=sump+1;*/
9043: num=num+1;
9044: }
9045:
9046:
9047: /* for (i=0; i<=imx; i++)
9048: 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]);*/
9049: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9050: for (i=1;i<=imx ; i++)
9051: {
9052: if (cens[i] == 1 && wav[i]>1)
9053: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9054:
9055: if (cens[i] == 0 && wav[i]>1)
9056: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9057: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9058:
9059: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9060: if (wav[i] > 1 ) { /* ??? */
9061: LL=LL+A*weight[i];
9062: /* 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]);*/
9063: }
9064: }
9065:
9066: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9067: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9068:
9069: return -2*LL*num/sump;
9070: }
9071: #endif
9072:
1.126 brouard 9073: /******************* Printing html file ***********/
1.201 brouard 9074: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9075: int lastpass, int stepm, int weightopt, char model[],\
9076: int imx, double p[],double **matcov,double agemortsup){
9077: int i,k;
9078:
9079: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9080: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9081: for (i=1;i<=2;i++)
9082: 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 9083: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9084: fprintf(fichtm,"</ul>");
9085:
9086: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9087:
9088: 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>");
9089:
9090: for (k=agegomp;k<(agemortsup-2);k++)
9091: 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]);
9092:
9093:
9094: fflush(fichtm);
9095: }
9096:
9097: /******************* Gnuplot file **************/
1.201 brouard 9098: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9099:
9100: char dirfileres[132],optfileres[132];
1.164 brouard 9101:
1.126 brouard 9102: int ng;
9103:
9104:
9105: /*#ifdef windows */
9106: fprintf(ficgp,"cd \"%s\" \n",pathc);
9107: /*#endif */
9108:
9109:
9110: strcpy(dirfileres,optionfilefiname);
9111: strcpy(optfileres,"vpl");
1.199 brouard 9112: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9113: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9114: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9115: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9116: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9117:
9118: }
9119:
1.136 brouard 9120: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9121: {
1.126 brouard 9122:
1.136 brouard 9123: /*-------- data file ----------*/
9124: FILE *fic;
9125: char dummy[]=" ";
1.240 brouard 9126: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9127: int lstra;
1.136 brouard 9128: int linei, month, year,iout;
9129: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9130: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9131: char *stratrunc;
1.223 brouard 9132:
1.240 brouard 9133: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9134: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9135:
1.240 brouard 9136: for(v=1; v <=ncovcol;v++){
9137: DummyV[v]=0;
9138: FixedV[v]=0;
9139: }
9140: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9141: DummyV[v]=1;
9142: FixedV[v]=0;
9143: }
9144: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9145: DummyV[v]=0;
9146: FixedV[v]=1;
9147: }
9148: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9149: DummyV[v]=1;
9150: FixedV[v]=1;
9151: }
9152: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9153: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9154: 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]);
9155: }
1.126 brouard 9156:
1.136 brouard 9157: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9158: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9159: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9160: }
1.126 brouard 9161:
1.136 brouard 9162: i=1;
9163: linei=0;
9164: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9165: linei=linei+1;
9166: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9167: if(line[j] == '\t')
9168: line[j] = ' ';
9169: }
9170: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9171: ;
9172: };
9173: line[j+1]=0; /* Trims blanks at end of line */
9174: if(line[0]=='#'){
9175: fprintf(ficlog,"Comment line\n%s\n",line);
9176: printf("Comment line\n%s\n",line);
9177: continue;
9178: }
9179: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9180: strcpy(line, linetmp);
1.223 brouard 9181:
9182: /* Loops on waves */
9183: for (j=maxwav;j>=1;j--){
9184: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9185: cutv(stra, strb, line, ' ');
9186: if(strb[0]=='.') { /* Missing value */
9187: lval=-1;
9188: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9189: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9190: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9191: 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);
9192: 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);
9193: return 1;
9194: }
9195: }else{
9196: errno=0;
9197: /* what_kind_of_number(strb); */
9198: dval=strtod(strb,&endptr);
9199: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9200: /* if(strb != endptr && *endptr == '\0') */
9201: /* dval=dlval; */
9202: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9203: if( strb[0]=='\0' || (*endptr != '\0')){
9204: 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);
9205: 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);
9206: return 1;
9207: }
9208: cotqvar[j][iv][i]=dval;
9209: cotvar[j][ntv+iv][i]=dval;
9210: }
9211: strcpy(line,stra);
1.223 brouard 9212: }/* end loop ntqv */
1.225 brouard 9213:
1.223 brouard 9214: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9215: cutv(stra, strb, line, ' ');
9216: if(strb[0]=='.') { /* Missing value */
9217: lval=-1;
9218: }else{
9219: errno=0;
9220: lval=strtol(strb,&endptr,10);
9221: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9222: if( strb[0]=='\0' || (*endptr != '\0')){
9223: 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);
9224: 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);
9225: return 1;
9226: }
9227: }
9228: if(lval <-1 || lval >1){
9229: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9230: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9231: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9232: For example, for multinomial values like 1, 2 and 3,\n \
9233: build V1=0 V2=0 for the reference value (1),\n \
9234: V1=1 V2=0 for (2) \n \
1.223 brouard 9235: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9236: output of IMaCh is often meaningless.\n \
1.223 brouard 9237: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9238: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9239: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9240: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9241: For example, for multinomial values like 1, 2 and 3,\n \
9242: build V1=0 V2=0 for the reference value (1),\n \
9243: V1=1 V2=0 for (2) \n \
1.223 brouard 9244: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9245: output of IMaCh is often meaningless.\n \
1.223 brouard 9246: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9247: return 1;
9248: }
9249: cotvar[j][iv][i]=(double)(lval);
9250: strcpy(line,stra);
1.223 brouard 9251: }/* end loop ntv */
1.225 brouard 9252:
1.223 brouard 9253: /* Statuses at wave */
1.137 brouard 9254: cutv(stra, strb, line, ' ');
1.223 brouard 9255: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9256: lval=-1;
1.136 brouard 9257: }else{
1.238 brouard 9258: errno=0;
9259: lval=strtol(strb,&endptr,10);
9260: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9261: if( strb[0]=='\0' || (*endptr != '\0')){
9262: 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);
9263: 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);
9264: return 1;
9265: }
1.136 brouard 9266: }
1.225 brouard 9267:
1.136 brouard 9268: s[j][i]=lval;
1.225 brouard 9269:
1.223 brouard 9270: /* Date of Interview */
1.136 brouard 9271: strcpy(line,stra);
9272: cutv(stra, strb,line,' ');
1.169 brouard 9273: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9274: }
1.169 brouard 9275: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9276: month=99;
9277: year=9999;
1.136 brouard 9278: }else{
1.225 brouard 9279: 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);
9280: 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);
9281: return 1;
1.136 brouard 9282: }
9283: anint[j][i]= (double) year;
9284: mint[j][i]= (double)month;
9285: strcpy(line,stra);
1.223 brouard 9286: } /* End loop on waves */
1.225 brouard 9287:
1.223 brouard 9288: /* Date of death */
1.136 brouard 9289: cutv(stra, strb,line,' ');
1.169 brouard 9290: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9291: }
1.169 brouard 9292: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9293: month=99;
9294: year=9999;
9295: }else{
1.141 brouard 9296: 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 9297: 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);
9298: return 1;
1.136 brouard 9299: }
9300: andc[i]=(double) year;
9301: moisdc[i]=(double) month;
9302: strcpy(line,stra);
9303:
1.223 brouard 9304: /* Date of birth */
1.136 brouard 9305: cutv(stra, strb,line,' ');
1.169 brouard 9306: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9307: }
1.169 brouard 9308: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9309: month=99;
9310: year=9999;
9311: }else{
1.141 brouard 9312: 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);
9313: 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 9314: return 1;
1.136 brouard 9315: }
9316: if (year==9999) {
1.141 brouard 9317: 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);
9318: 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 9319: return 1;
9320:
1.136 brouard 9321: }
9322: annais[i]=(double)(year);
9323: moisnais[i]=(double)(month);
9324: strcpy(line,stra);
1.225 brouard 9325:
1.223 brouard 9326: /* Sample weight */
1.136 brouard 9327: cutv(stra, strb,line,' ');
9328: errno=0;
9329: dval=strtod(strb,&endptr);
9330: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9331: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9332: 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 9333: fflush(ficlog);
9334: return 1;
9335: }
9336: weight[i]=dval;
9337: strcpy(line,stra);
1.225 brouard 9338:
1.223 brouard 9339: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9340: cutv(stra, strb, line, ' ');
9341: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9342: lval=-1;
1.223 brouard 9343: }else{
1.225 brouard 9344: errno=0;
9345: /* what_kind_of_number(strb); */
9346: dval=strtod(strb,&endptr);
9347: /* if(strb != endptr && *endptr == '\0') */
9348: /* dval=dlval; */
9349: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9350: if( strb[0]=='\0' || (*endptr != '\0')){
9351: 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);
9352: 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);
9353: return 1;
9354: }
9355: coqvar[iv][i]=dval;
1.226 brouard 9356: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9357: }
9358: strcpy(line,stra);
9359: }/* end loop nqv */
1.136 brouard 9360:
1.223 brouard 9361: /* Covariate values */
1.136 brouard 9362: for (j=ncovcol;j>=1;j--){
9363: cutv(stra, strb,line,' ');
1.223 brouard 9364: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9365: lval=-1;
1.136 brouard 9366: }else{
1.225 brouard 9367: errno=0;
9368: lval=strtol(strb,&endptr,10);
9369: if( strb[0]=='\0' || (*endptr != '\0')){
9370: 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);
9371: 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);
9372: return 1;
9373: }
1.136 brouard 9374: }
9375: if(lval <-1 || lval >1){
1.225 brouard 9376: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9377: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9378: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9379: For example, for multinomial values like 1, 2 and 3,\n \
9380: build V1=0 V2=0 for the reference value (1),\n \
9381: V1=1 V2=0 for (2) \n \
1.136 brouard 9382: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9383: output of IMaCh is often meaningless.\n \
1.136 brouard 9384: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9385: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9386: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9387: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9388: For example, for multinomial values like 1, 2 and 3,\n \
9389: build V1=0 V2=0 for the reference value (1),\n \
9390: V1=1 V2=0 for (2) \n \
1.136 brouard 9391: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9392: output of IMaCh is often meaningless.\n \
1.136 brouard 9393: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9394: return 1;
1.136 brouard 9395: }
9396: covar[j][i]=(double)(lval);
9397: strcpy(line,stra);
9398: }
9399: lstra=strlen(stra);
1.225 brouard 9400:
1.136 brouard 9401: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9402: stratrunc = &(stra[lstra-9]);
9403: num[i]=atol(stratrunc);
9404: }
9405: else
9406: num[i]=atol(stra);
9407: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9408: 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;}*/
9409:
9410: i=i+1;
9411: } /* End loop reading data */
1.225 brouard 9412:
1.136 brouard 9413: *imax=i-1; /* Number of individuals */
9414: fclose(fic);
1.225 brouard 9415:
1.136 brouard 9416: return (0);
1.164 brouard 9417: /* endread: */
1.225 brouard 9418: printf("Exiting readdata: ");
9419: fclose(fic);
9420: return (1);
1.223 brouard 9421: }
1.126 brouard 9422:
1.234 brouard 9423: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9424: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9425: while (*p2 == ' ')
1.234 brouard 9426: p2++;
9427: /* while ((*p1++ = *p2++) !=0) */
9428: /* ; */
9429: /* do */
9430: /* while (*p2 == ' ') */
9431: /* p2++; */
9432: /* while (*p1++ == *p2++); */
9433: *stri=p2;
1.145 brouard 9434: }
9435:
1.235 brouard 9436: int decoderesult ( char resultline[], int nres)
1.230 brouard 9437: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9438: {
1.235 brouard 9439: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9440: char resultsav[MAXLINE];
1.234 brouard 9441: int resultmodel[MAXLINE];
9442: int modelresult[MAXLINE];
1.230 brouard 9443: char stra[80], strb[80], strc[80], strd[80],stre[80];
9444:
1.234 brouard 9445: removefirstspace(&resultline);
1.233 brouard 9446: printf("decoderesult:%s\n",resultline);
1.230 brouard 9447:
9448: if (strstr(resultline,"v") !=0){
9449: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9450: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9451: return 1;
9452: }
9453: trimbb(resultsav, resultline);
9454: if (strlen(resultsav) >1){
9455: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9456: }
1.253 brouard 9457: if(j == 0){ /* Resultline but no = */
9458: TKresult[nres]=0; /* Combination for the nresult and the model */
9459: return (0);
9460: }
9461:
1.234 brouard 9462: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9463: 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);
9464: 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);
9465: }
9466: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9467: if(nbocc(resultsav,'=') >1){
9468: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9469: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9470: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9471: }else
9472: cutl(strc,strd,resultsav,'=');
1.230 brouard 9473: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9474:
1.230 brouard 9475: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9476: Tvarsel[k]=atoi(strc);
9477: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9478: /* cptcovsel++; */
9479: if (nbocc(stra,'=') >0)
9480: strcpy(resultsav,stra); /* and analyzes it */
9481: }
1.235 brouard 9482: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9483: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9484: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9485: match=0;
1.236 brouard 9486: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9487: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9488: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9489: match=1;
9490: break;
9491: }
9492: }
9493: if(match == 0){
9494: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9495: }
9496: }
9497: }
1.235 brouard 9498: /* Checking for missing or useless values in comparison of current model needs */
9499: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9500: match=0;
1.235 brouard 9501: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9502: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9503: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9504: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9505: ++match;
9506: }
9507: }
9508: }
9509: if(match == 0){
9510: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9511: }else if(match > 1){
9512: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9513: }
9514: }
1.235 brouard 9515:
1.234 brouard 9516: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9517: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9518: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9519: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9520: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9521: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9522: /* 1 0 0 0 */
9523: /* 2 1 0 0 */
9524: /* 3 0 1 0 */
9525: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9526: /* 5 0 0 1 */
9527: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9528: /* 7 0 1 1 */
9529: /* 8 1 1 1 */
1.237 brouard 9530: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9531: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9532: /* V5*age V5 known which value for nres? */
9533: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9534: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9535: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9536: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9537: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9538: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9539: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9540: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9541: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9542: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9543: k4++;;
9544: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9545: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9546: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9547: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9548: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9549: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9550: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9551: k4q++;;
9552: }
9553: }
1.234 brouard 9554:
1.235 brouard 9555: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9556: return (0);
9557: }
1.235 brouard 9558:
1.230 brouard 9559: int decodemodel( char model[], int lastobs)
9560: /**< This routine decodes the model and returns:
1.224 brouard 9561: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9562: * - nagesqr = 1 if age*age in the model, otherwise 0.
9563: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9564: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9565: * - cptcovage number of covariates with age*products =2
9566: * - cptcovs number of simple covariates
9567: * - 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
9568: * which is a new column after the 9 (ncovcol) variables.
9569: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9570: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9571: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9572: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9573: */
1.136 brouard 9574: {
1.238 brouard 9575: int i, j, k, ks, v;
1.227 brouard 9576: int j1, k1, k2, k3, k4;
1.136 brouard 9577: char modelsav[80];
1.145 brouard 9578: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9579: char *strpt;
1.136 brouard 9580:
1.145 brouard 9581: /*removespace(model);*/
1.136 brouard 9582: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9583: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9584: if (strstr(model,"AGE") !=0){
1.192 brouard 9585: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9586: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9587: return 1;
9588: }
1.141 brouard 9589: if (strstr(model,"v") !=0){
9590: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9591: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9592: return 1;
9593: }
1.187 brouard 9594: strcpy(modelsav,model);
9595: if ((strpt=strstr(model,"age*age")) !=0){
9596: printf(" strpt=%s, model=%s\n",strpt, model);
9597: if(strpt != model){
1.234 brouard 9598: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9599: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9600: corresponding column of parameters.\n",model);
1.234 brouard 9601: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9602: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9603: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9604: return 1;
1.225 brouard 9605: }
1.187 brouard 9606: nagesqr=1;
9607: if (strstr(model,"+age*age") !=0)
1.234 brouard 9608: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9609: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9610: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9611: else
1.234 brouard 9612: substrchaine(modelsav, model, "age*age");
1.187 brouard 9613: }else
9614: nagesqr=0;
9615: if (strlen(modelsav) >1){
9616: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9617: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9618: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9619: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9620: * cst, age and age*age
9621: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9622: /* including age products which are counted in cptcovage.
9623: * but the covariates which are products must be treated
9624: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9625: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9626: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9627:
9628:
1.187 brouard 9629: /* Design
9630: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9631: * < ncovcol=8 >
9632: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9633: * k= 1 2 3 4 5 6 7 8
9634: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9635: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9636: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9637: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9638: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9639: * Tage[++cptcovage]=k
9640: * if products, new covar are created after ncovcol with k1
9641: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9642: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9643: * 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
9644: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9645: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9646: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9647: * < ncovcol=8 >
9648: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9649: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9650: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9651: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9652: * p Tprod[1]@2={ 6, 5}
9653: *p Tvard[1][1]@4= {7, 8, 5, 6}
9654: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9655: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9656: *How to reorganize?
9657: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9658: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9659: * {2, 1, 4, 8, 5, 6, 3, 7}
9660: * Struct []
9661: */
1.225 brouard 9662:
1.187 brouard 9663: /* This loop fills the array Tvar from the string 'model'.*/
9664: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9665: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9666: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9667: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9668: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9669: /* k=1 Tvar[1]=2 (from V2) */
9670: /* k=5 Tvar[5] */
9671: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9672: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9673: /* } */
1.198 brouard 9674: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9675: /*
9676: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9677: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9678: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9679: }
1.187 brouard 9680: cptcovage=0;
9681: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9682: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9683: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9684: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9685: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9686: /*scanf("%d",i);*/
9687: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9688: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9689: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9690: /* covar is not filled and then is empty */
9691: cptcovprod--;
9692: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9693: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9694: Typevar[k]=1; /* 1 for age product */
9695: cptcovage++; /* Sums the number of covariates which include age as a product */
9696: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9697: /*printf("stre=%s ", stre);*/
9698: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9699: cptcovprod--;
9700: cutl(stre,strb,strc,'V');
9701: Tvar[k]=atoi(stre);
9702: Typevar[k]=1; /* 1 for age product */
9703: cptcovage++;
9704: Tage[cptcovage]=k;
9705: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9706: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9707: cptcovn++;
9708: cptcovprodnoage++;k1++;
9709: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9710: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9711: because this model-covariate is a construction we invent a new column
9712: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9713: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9714: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9715: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9716: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9717: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9718: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9719: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9720: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9721: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9722: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9723: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9724: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9725: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9726: for (i=1; i<=lastobs;i++){
9727: /* Computes the new covariate which is a product of
9728: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9729: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9730: }
9731: } /* End age is not in the model */
9732: } /* End if model includes a product */
9733: else { /* no more sum */
9734: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9735: /* scanf("%d",i);*/
9736: cutl(strd,strc,strb,'V');
9737: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9738: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9739: Tvar[k]=atoi(strd);
9740: Typevar[k]=0; /* 0 for simple covariates */
9741: }
9742: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9743: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9744: scanf("%d",i);*/
1.187 brouard 9745: } /* end of loop + on total covariates */
9746: } /* end if strlen(modelsave == 0) age*age might exist */
9747: } /* end if strlen(model == 0) */
1.136 brouard 9748:
9749: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9750: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9751:
1.136 brouard 9752: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9753: printf("cptcovprod=%d ", cptcovprod);
9754: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9755: scanf("%d ",i);*/
9756:
9757:
1.230 brouard 9758: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9759: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9760: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9761: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9762: k = 1 2 3 4 5 6 7 8 9
9763: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9764: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9765: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9766: Dummy[k] 1 0 0 0 3 1 1 2 3
9767: Tmodelind[combination of covar]=k;
1.225 brouard 9768: */
9769: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9770: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9771: /* 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 9772: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9773: printf("Model=%s\n\
9774: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9775: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9776: 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);
9777: fprintf(ficlog,"Model=%s\n\
9778: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9779: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9780: 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 9781: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9782: 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 */
9783: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9784: Fixed[k]= 0;
9785: Dummy[k]= 0;
1.225 brouard 9786: ncoveff++;
1.232 brouard 9787: ncovf++;
1.234 brouard 9788: nsd++;
9789: modell[k].maintype= FTYPE;
9790: TvarsD[nsd]=Tvar[k];
9791: TvarsDind[nsd]=k;
9792: TvarF[ncovf]=Tvar[k];
9793: TvarFind[ncovf]=k;
9794: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9795: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9796: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9797: Fixed[k]= 0;
9798: Dummy[k]= 0;
9799: ncoveff++;
9800: ncovf++;
9801: modell[k].maintype= FTYPE;
9802: TvarF[ncovf]=Tvar[k];
9803: TvarFind[ncovf]=k;
1.230 brouard 9804: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9805: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9806: }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 9807: Fixed[k]= 0;
9808: Dummy[k]= 1;
1.230 brouard 9809: nqfveff++;
1.234 brouard 9810: modell[k].maintype= FTYPE;
9811: modell[k].subtype= FQ;
9812: nsq++;
9813: TvarsQ[nsq]=Tvar[k];
9814: TvarsQind[nsq]=k;
1.232 brouard 9815: ncovf++;
1.234 brouard 9816: TvarF[ncovf]=Tvar[k];
9817: TvarFind[ncovf]=k;
1.231 brouard 9818: 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 9819: 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 9820: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9821: Fixed[k]= 1;
9822: Dummy[k]= 0;
1.225 brouard 9823: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9824: modell[k].maintype= VTYPE;
9825: modell[k].subtype= VD;
9826: nsd++;
9827: TvarsD[nsd]=Tvar[k];
9828: TvarsDind[nsd]=k;
9829: ncovv++; /* Only simple time varying variables */
9830: TvarV[ncovv]=Tvar[k];
1.242 brouard 9831: 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 9832: 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 */
9833: 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 9834: 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);
9835: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9836: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9837: Fixed[k]= 1;
9838: Dummy[k]= 1;
9839: nqtveff++;
9840: modell[k].maintype= VTYPE;
9841: modell[k].subtype= VQ;
9842: ncovv++; /* Only simple time varying variables */
9843: nsq++;
9844: TvarsQ[nsq]=Tvar[k];
9845: TvarsQind[nsq]=k;
9846: TvarV[ncovv]=Tvar[k];
1.242 brouard 9847: 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 9848: 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 */
9849: 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 9850: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9851: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9852: 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 9853: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9854: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9855: ncova++;
9856: TvarA[ncova]=Tvar[k];
9857: TvarAind[ncova]=k;
1.231 brouard 9858: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9859: Fixed[k]= 2;
9860: Dummy[k]= 2;
9861: modell[k].maintype= ATYPE;
9862: modell[k].subtype= APFD;
9863: /* ncoveff++; */
1.227 brouard 9864: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9865: Fixed[k]= 2;
9866: Dummy[k]= 3;
9867: modell[k].maintype= ATYPE;
9868: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9869: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9870: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9871: Fixed[k]= 3;
9872: Dummy[k]= 2;
9873: modell[k].maintype= ATYPE;
9874: modell[k].subtype= APVD; /* Product age * varying dummy */
9875: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9876: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9877: Fixed[k]= 3;
9878: Dummy[k]= 3;
9879: modell[k].maintype= ATYPE;
9880: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9881: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9882: }
9883: }else if (Typevar[k] == 2) { /* product without age */
9884: k1=Tposprod[k];
9885: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9886: if(Tvard[k1][2] <=ncovcol){
9887: Fixed[k]= 1;
9888: Dummy[k]= 0;
9889: modell[k].maintype= FTYPE;
9890: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9891: ncovf++; /* Fixed variables without age */
9892: TvarF[ncovf]=Tvar[k];
9893: TvarFind[ncovf]=k;
9894: }else if(Tvard[k1][2] <=ncovcol+nqv){
9895: Fixed[k]= 0; /* or 2 ?*/
9896: Dummy[k]= 1;
9897: modell[k].maintype= FTYPE;
9898: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9899: ncovf++; /* Varying variables without age */
9900: TvarF[ncovf]=Tvar[k];
9901: TvarFind[ncovf]=k;
9902: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9903: Fixed[k]= 1;
9904: Dummy[k]= 0;
9905: modell[k].maintype= VTYPE;
9906: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9907: ncovv++; /* Varying variables without age */
9908: TvarV[ncovv]=Tvar[k];
9909: TvarVind[ncovv]=k;
9910: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9911: Fixed[k]= 1;
9912: Dummy[k]= 1;
9913: modell[k].maintype= VTYPE;
9914: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9915: ncovv++; /* Varying variables without age */
9916: TvarV[ncovv]=Tvar[k];
9917: TvarVind[ncovv]=k;
9918: }
1.227 brouard 9919: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9920: if(Tvard[k1][2] <=ncovcol){
9921: Fixed[k]= 0; /* or 2 ?*/
9922: Dummy[k]= 1;
9923: modell[k].maintype= FTYPE;
9924: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9925: ncovf++; /* Fixed variables without age */
9926: TvarF[ncovf]=Tvar[k];
9927: TvarFind[ncovf]=k;
9928: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9929: Fixed[k]= 1;
9930: Dummy[k]= 1;
9931: modell[k].maintype= VTYPE;
9932: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9933: ncovv++; /* Varying variables without age */
9934: TvarV[ncovv]=Tvar[k];
9935: TvarVind[ncovv]=k;
9936: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9937: Fixed[k]= 1;
9938: Dummy[k]= 1;
9939: modell[k].maintype= VTYPE;
9940: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9941: ncovv++; /* Varying variables without age */
9942: TvarV[ncovv]=Tvar[k];
9943: TvarVind[ncovv]=k;
9944: ncovv++; /* Varying variables without age */
9945: TvarV[ncovv]=Tvar[k];
9946: TvarVind[ncovv]=k;
9947: }
1.227 brouard 9948: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9949: if(Tvard[k1][2] <=ncovcol){
9950: Fixed[k]= 1;
9951: Dummy[k]= 1;
9952: modell[k].maintype= VTYPE;
9953: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9954: ncovv++; /* Varying variables without age */
9955: TvarV[ncovv]=Tvar[k];
9956: TvarVind[ncovv]=k;
9957: }else if(Tvard[k1][2] <=ncovcol+nqv){
9958: Fixed[k]= 1;
9959: Dummy[k]= 1;
9960: modell[k].maintype= VTYPE;
9961: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9962: ncovv++; /* Varying variables without age */
9963: TvarV[ncovv]=Tvar[k];
9964: TvarVind[ncovv]=k;
9965: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9966: Fixed[k]= 1;
9967: Dummy[k]= 0;
9968: modell[k].maintype= VTYPE;
9969: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9970: ncovv++; /* Varying variables without age */
9971: TvarV[ncovv]=Tvar[k];
9972: TvarVind[ncovv]=k;
9973: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9974: Fixed[k]= 1;
9975: Dummy[k]= 1;
9976: modell[k].maintype= VTYPE;
9977: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9978: ncovv++; /* Varying variables without age */
9979: TvarV[ncovv]=Tvar[k];
9980: TvarVind[ncovv]=k;
9981: }
1.227 brouard 9982: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9983: if(Tvard[k1][2] <=ncovcol){
9984: Fixed[k]= 1;
9985: Dummy[k]= 1;
9986: modell[k].maintype= VTYPE;
9987: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9988: ncovv++; /* Varying variables without age */
9989: TvarV[ncovv]=Tvar[k];
9990: TvarVind[ncovv]=k;
9991: }else if(Tvard[k1][2] <=ncovcol+nqv){
9992: Fixed[k]= 1;
9993: Dummy[k]= 1;
9994: modell[k].maintype= VTYPE;
9995: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9996: ncovv++; /* Varying variables without age */
9997: TvarV[ncovv]=Tvar[k];
9998: TvarVind[ncovv]=k;
9999: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10000: Fixed[k]= 1;
10001: Dummy[k]= 1;
10002: modell[k].maintype= VTYPE;
10003: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10004: ncovv++; /* Varying variables without age */
10005: TvarV[ncovv]=Tvar[k];
10006: TvarVind[ncovv]=k;
10007: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10008: Fixed[k]= 1;
10009: Dummy[k]= 1;
10010: modell[k].maintype= VTYPE;
10011: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10012: ncovv++; /* Varying variables without age */
10013: TvarV[ncovv]=Tvar[k];
10014: TvarVind[ncovv]=k;
10015: }
1.227 brouard 10016: }else{
1.240 brouard 10017: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10018: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10019: } /*end k1*/
1.225 brouard 10020: }else{
1.226 brouard 10021: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10022: 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 10023: }
1.227 brouard 10024: 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 10025: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10026: 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]);
10027: }
10028: /* Searching for doublons in the model */
10029: for(k1=1; k1<= cptcovt;k1++){
10030: for(k2=1; k2 <k1;k2++){
1.285 brouard 10031: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10032: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10033: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10034: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10035: 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]);
10036: 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 10037: return(1);
10038: }
10039: }else if (Typevar[k1] ==2){
10040: k3=Tposprod[k1];
10041: k4=Tposprod[k2];
10042: 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])) ){
10043: 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]]);
10044: 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);
10045: return(1);
10046: }
10047: }
1.227 brouard 10048: }
10049: }
1.225 brouard 10050: }
10051: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10052: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10053: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10054: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10055: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10056: /*endread:*/
1.225 brouard 10057: printf("Exiting decodemodel: ");
10058: return (1);
1.136 brouard 10059: }
10060:
1.169 brouard 10061: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10062: {/* Check ages at death */
1.136 brouard 10063: int i, m;
1.218 brouard 10064: int firstone=0;
10065:
1.136 brouard 10066: for (i=1; i<=imx; i++) {
10067: for(m=2; (m<= maxwav); m++) {
10068: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10069: anint[m][i]=9999;
1.216 brouard 10070: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10071: s[m][i]=-1;
1.136 brouard 10072: }
10073: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10074: *nberr = *nberr + 1;
1.218 brouard 10075: if(firstone == 0){
10076: firstone=1;
1.260 brouard 10077: 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 10078: }
1.262 brouard 10079: 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 10080: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10081: }
10082: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10083: (*nberr)++;
1.259 brouard 10084: 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 10085: 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 10086: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10087: }
10088: }
10089: }
10090:
10091: for (i=1; i<=imx; i++) {
10092: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10093: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10094: 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 10095: if (s[m][i] >= nlstate+1) {
1.169 brouard 10096: if(agedc[i]>0){
10097: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10098: agev[m][i]=agedc[i];
1.214 brouard 10099: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10100: }else {
1.136 brouard 10101: if ((int)andc[i]!=9999){
10102: nbwarn++;
10103: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10104: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10105: agev[m][i]=-1;
10106: }
10107: }
1.169 brouard 10108: } /* agedc > 0 */
1.214 brouard 10109: } /* end if */
1.136 brouard 10110: else if(s[m][i] !=9){ /* Standard case, age in fractional
10111: years but with the precision of a month */
10112: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10113: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10114: agev[m][i]=1;
10115: else if(agev[m][i] < *agemin){
10116: *agemin=agev[m][i];
10117: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10118: }
10119: else if(agev[m][i] >*agemax){
10120: *agemax=agev[m][i];
1.156 brouard 10121: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10122: }
10123: /*agev[m][i]=anint[m][i]-annais[i];*/
10124: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10125: } /* en if 9*/
1.136 brouard 10126: else { /* =9 */
1.214 brouard 10127: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10128: agev[m][i]=1;
10129: s[m][i]=-1;
10130: }
10131: }
1.214 brouard 10132: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10133: agev[m][i]=1;
1.214 brouard 10134: else{
10135: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10136: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10137: agev[m][i]=0;
10138: }
10139: } /* End for lastpass */
10140: }
1.136 brouard 10141:
10142: for (i=1; i<=imx; i++) {
10143: for(m=firstpass; (m<=lastpass); m++){
10144: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10145: (*nberr)++;
1.136 brouard 10146: 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);
10147: 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);
10148: return 1;
10149: }
10150: }
10151: }
10152:
10153: /*for (i=1; i<=imx; i++){
10154: for (m=firstpass; (m<lastpass); m++){
10155: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10156: }
10157:
10158: }*/
10159:
10160:
1.139 brouard 10161: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10162: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10163:
10164: return (0);
1.164 brouard 10165: /* endread:*/
1.136 brouard 10166: printf("Exiting calandcheckages: ");
10167: return (1);
10168: }
10169:
1.172 brouard 10170: #if defined(_MSC_VER)
10171: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10172: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10173: //#include "stdafx.h"
10174: //#include <stdio.h>
10175: //#include <tchar.h>
10176: //#include <windows.h>
10177: //#include <iostream>
10178: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10179:
10180: LPFN_ISWOW64PROCESS fnIsWow64Process;
10181:
10182: BOOL IsWow64()
10183: {
10184: BOOL bIsWow64 = FALSE;
10185:
10186: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10187: // (HANDLE, PBOOL);
10188:
10189: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10190:
10191: HMODULE module = GetModuleHandle(_T("kernel32"));
10192: const char funcName[] = "IsWow64Process";
10193: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10194: GetProcAddress(module, funcName);
10195:
10196: if (NULL != fnIsWow64Process)
10197: {
10198: if (!fnIsWow64Process(GetCurrentProcess(),
10199: &bIsWow64))
10200: //throw std::exception("Unknown error");
10201: printf("Unknown error\n");
10202: }
10203: return bIsWow64 != FALSE;
10204: }
10205: #endif
1.177 brouard 10206:
1.191 brouard 10207: void syscompilerinfo(int logged)
1.292 brouard 10208: {
10209: #include <stdint.h>
10210:
10211: /* #include "syscompilerinfo.h"*/
1.185 brouard 10212: /* command line Intel compiler 32bit windows, XP compatible:*/
10213: /* /GS /W3 /Gy
10214: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10215: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10216: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10217: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10218: */
10219: /* 64 bits */
1.185 brouard 10220: /*
10221: /GS /W3 /Gy
10222: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10223: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10224: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10225: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10226: /* Optimization are useless and O3 is slower than O2 */
10227: /*
10228: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10229: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10230: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10231: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10232: */
1.186 brouard 10233: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10234: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10235: /PDB:"visual studio
10236: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10237: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10238: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10239: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10240: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10241: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10242: uiAccess='false'"
10243: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10244: /NOLOGO /TLBID:1
10245: */
1.292 brouard 10246:
10247:
1.177 brouard 10248: #if defined __INTEL_COMPILER
1.178 brouard 10249: #if defined(__GNUC__)
10250: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10251: #endif
1.177 brouard 10252: #elif defined(__GNUC__)
1.179 brouard 10253: #ifndef __APPLE__
1.174 brouard 10254: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10255: #endif
1.177 brouard 10256: struct utsname sysInfo;
1.178 brouard 10257: int cross = CROSS;
10258: if (cross){
10259: printf("Cross-");
1.191 brouard 10260: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10261: }
1.174 brouard 10262: #endif
10263:
1.191 brouard 10264: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10265: #if defined(__clang__)
1.191 brouard 10266: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10267: #endif
10268: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10269: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10270: #endif
10271: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10272: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10273: #endif
10274: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10275: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10276: #endif
10277: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10278: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10279: #endif
10280: #if defined(_MSC_VER)
1.191 brouard 10281: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10282: #endif
10283: #if defined(__PGI)
1.191 brouard 10284: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10285: #endif
10286: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10287: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10288: #endif
1.191 brouard 10289: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10290:
1.167 brouard 10291: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10292: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10293: // Windows (x64 and x86)
1.191 brouard 10294: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10295: #elif __unix__ // all unices, not all compilers
10296: // Unix
1.191 brouard 10297: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10298: #elif __linux__
10299: // linux
1.191 brouard 10300: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10301: #elif __APPLE__
1.174 brouard 10302: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10303: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10304: #endif
10305:
10306: /* __MINGW32__ */
10307: /* __CYGWIN__ */
10308: /* __MINGW64__ */
10309: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10310: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10311: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10312: /* _WIN64 // Defined for applications for Win64. */
10313: /* _M_X64 // Defined for compilations that target x64 processors. */
10314: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10315:
1.167 brouard 10316: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10317: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10318: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10319: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10320: #else
1.191 brouard 10321: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10322: #endif
10323:
1.169 brouard 10324: #if defined(__GNUC__)
10325: # if defined(__GNUC_PATCHLEVEL__)
10326: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10327: + __GNUC_MINOR__ * 100 \
10328: + __GNUC_PATCHLEVEL__)
10329: # else
10330: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10331: + __GNUC_MINOR__ * 100)
10332: # endif
1.174 brouard 10333: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10334: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10335:
10336: if (uname(&sysInfo) != -1) {
10337: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10338: 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 10339: }
10340: else
10341: perror("uname() error");
1.179 brouard 10342: //#ifndef __INTEL_COMPILER
10343: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10344: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10345: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10346: #endif
1.169 brouard 10347: #endif
1.172 brouard 10348:
1.286 brouard 10349: // void main ()
1.172 brouard 10350: // {
1.169 brouard 10351: #if defined(_MSC_VER)
1.174 brouard 10352: if (IsWow64()){
1.191 brouard 10353: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10354: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10355: }
10356: else{
1.191 brouard 10357: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10358: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10359: }
1.172 brouard 10360: // printf("\nPress Enter to continue...");
10361: // getchar();
10362: // }
10363:
1.169 brouard 10364: #endif
10365:
1.167 brouard 10366:
1.219 brouard 10367: }
1.136 brouard 10368:
1.219 brouard 10369: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10370: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10371: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10372: /* double ftolpl = 1.e-10; */
1.180 brouard 10373: double age, agebase, agelim;
1.203 brouard 10374: double tot;
1.180 brouard 10375:
1.202 brouard 10376: strcpy(filerespl,"PL_");
10377: strcat(filerespl,fileresu);
10378: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10379: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10380: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10381: }
1.288 brouard 10382: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10383: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10384: pstamp(ficrespl);
1.288 brouard 10385: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10386: fprintf(ficrespl,"#Age ");
10387: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10388: fprintf(ficrespl,"\n");
1.180 brouard 10389:
1.219 brouard 10390: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10391:
1.219 brouard 10392: agebase=ageminpar;
10393: agelim=agemaxpar;
1.180 brouard 10394:
1.227 brouard 10395: /* i1=pow(2,ncoveff); */
1.234 brouard 10396: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10397: if (cptcovn < 1){i1=1;}
1.180 brouard 10398:
1.238 brouard 10399: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10400: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10401: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10402: continue;
1.235 brouard 10403:
1.238 brouard 10404: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10405: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10406: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10407: /* k=k+1; */
10408: /* to clean */
10409: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10410: fprintf(ficrespl,"#******");
10411: printf("#******");
10412: fprintf(ficlog,"#******");
10413: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10414: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10415: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10416: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10417: }
10418: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10419: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10420: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10421: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10422: }
10423: fprintf(ficrespl,"******\n");
10424: printf("******\n");
10425: fprintf(ficlog,"******\n");
10426: if(invalidvarcomb[k]){
10427: printf("\nCombination (%d) ignored because no case \n",k);
10428: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10429: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10430: continue;
10431: }
1.219 brouard 10432:
1.238 brouard 10433: fprintf(ficrespl,"#Age ");
10434: for(j=1;j<=cptcoveff;j++) {
10435: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10436: }
10437: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10438: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10439:
1.238 brouard 10440: for (age=agebase; age<=agelim; age++){
10441: /* for (age=agebase; age<=agebase; age++){ */
10442: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10443: fprintf(ficrespl,"%.0f ",age );
10444: for(j=1;j<=cptcoveff;j++)
10445: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10446: tot=0.;
10447: for(i=1; i<=nlstate;i++){
10448: tot += prlim[i][i];
10449: fprintf(ficrespl," %.5f", prlim[i][i]);
10450: }
10451: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10452: } /* Age */
10453: /* was end of cptcod */
10454: } /* cptcov */
10455: } /* nres */
1.219 brouard 10456: return 0;
1.180 brouard 10457: }
10458:
1.218 brouard 10459: 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 10460: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10461:
10462: /* Computes the back prevalence limit for any combination of covariate values
10463: * at any age between ageminpar and agemaxpar
10464: */
1.235 brouard 10465: int i, j, k, i1, nres=0 ;
1.217 brouard 10466: /* double ftolpl = 1.e-10; */
10467: double age, agebase, agelim;
10468: double tot;
1.218 brouard 10469: /* double ***mobaverage; */
10470: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10471:
10472: strcpy(fileresplb,"PLB_");
10473: strcat(fileresplb,fileresu);
10474: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10475: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10476: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10477: }
1.288 brouard 10478: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10479: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10480: pstamp(ficresplb);
1.288 brouard 10481: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10482: fprintf(ficresplb,"#Age ");
10483: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10484: fprintf(ficresplb,"\n");
10485:
1.218 brouard 10486:
10487: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10488:
10489: agebase=ageminpar;
10490: agelim=agemaxpar;
10491:
10492:
1.227 brouard 10493: i1=pow(2,cptcoveff);
1.218 brouard 10494: if (cptcovn < 1){i1=1;}
1.227 brouard 10495:
1.238 brouard 10496: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10497: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10498: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10499: continue;
10500: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10501: fprintf(ficresplb,"#******");
10502: printf("#******");
10503: fprintf(ficlog,"#******");
10504: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10505: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10506: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10507: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10508: }
10509: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10510: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10511: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10512: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10513: }
10514: fprintf(ficresplb,"******\n");
10515: printf("******\n");
10516: fprintf(ficlog,"******\n");
10517: if(invalidvarcomb[k]){
10518: printf("\nCombination (%d) ignored because no cases \n",k);
10519: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10520: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10521: continue;
10522: }
1.218 brouard 10523:
1.238 brouard 10524: fprintf(ficresplb,"#Age ");
10525: for(j=1;j<=cptcoveff;j++) {
10526: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10527: }
10528: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10529: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10530:
10531:
1.238 brouard 10532: for (age=agebase; age<=agelim; age++){
10533: /* for (age=agebase; age<=agebase; age++){ */
10534: if(mobilavproj > 0){
10535: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10536: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10537: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10538: }else if (mobilavproj == 0){
10539: 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);
10540: 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);
10541: exit(1);
10542: }else{
10543: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10544: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10545: /* printf("TOTOT\n"); */
10546: /* exit(1); */
1.238 brouard 10547: }
10548: fprintf(ficresplb,"%.0f ",age );
10549: for(j=1;j<=cptcoveff;j++)
10550: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10551: tot=0.;
10552: for(i=1; i<=nlstate;i++){
10553: tot += bprlim[i][i];
10554: fprintf(ficresplb," %.5f", bprlim[i][i]);
10555: }
10556: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10557: } /* Age */
10558: /* was end of cptcod */
1.255 brouard 10559: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10560: } /* end of any combination */
10561: } /* end of nres */
1.218 brouard 10562: /* hBijx(p, bage, fage); */
10563: /* fclose(ficrespijb); */
10564:
10565: return 0;
1.217 brouard 10566: }
1.218 brouard 10567:
1.180 brouard 10568: int hPijx(double *p, int bage, int fage){
10569: /*------------- h Pij x at various ages ------------*/
10570:
10571: int stepsize;
10572: int agelim;
10573: int hstepm;
10574: int nhstepm;
1.235 brouard 10575: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10576:
10577: double agedeb;
10578: double ***p3mat;
10579:
1.201 brouard 10580: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10581: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10582: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10583: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10584: }
10585: printf("Computing pij: result on file '%s' \n", filerespij);
10586: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10587:
10588: stepsize=(int) (stepm+YEARM-1)/YEARM;
10589: /*if (stepm<=24) stepsize=2;*/
10590:
10591: agelim=AGESUP;
10592: hstepm=stepsize*YEARM; /* Every year of age */
10593: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10594:
1.180 brouard 10595: /* hstepm=1; aff par mois*/
10596: pstamp(ficrespij);
10597: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10598: i1= pow(2,cptcoveff);
1.218 brouard 10599: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10600: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10601: /* k=k+1; */
1.235 brouard 10602: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10603: for(k=1; k<=i1;k++){
1.253 brouard 10604: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10605: continue;
1.183 brouard 10606: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10607: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10608: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10609: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10610: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10611: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10612: }
1.183 brouard 10613: fprintf(ficrespij,"******\n");
10614:
10615: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10616: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10617: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10618:
10619: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10620:
1.183 brouard 10621: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10622: oldm=oldms;savm=savms;
1.235 brouard 10623: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10624: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10625: for(i=1; i<=nlstate;i++)
10626: for(j=1; j<=nlstate+ndeath;j++)
10627: fprintf(ficrespij," %1d-%1d",i,j);
10628: fprintf(ficrespij,"\n");
10629: for (h=0; h<=nhstepm; h++){
10630: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10631: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10632: for(i=1; i<=nlstate;i++)
10633: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10634: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10635: fprintf(ficrespij,"\n");
10636: }
1.183 brouard 10637: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10638: fprintf(ficrespij,"\n");
10639: }
1.180 brouard 10640: /*}*/
10641: }
1.218 brouard 10642: return 0;
1.180 brouard 10643: }
1.218 brouard 10644:
10645: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10646: /*------------- h Bij x at various ages ------------*/
10647:
10648: int stepsize;
1.218 brouard 10649: /* int agelim; */
10650: int ageminl;
1.217 brouard 10651: int hstepm;
10652: int nhstepm;
1.238 brouard 10653: int h, i, i1, j, k, nres;
1.218 brouard 10654:
1.217 brouard 10655: double agedeb;
10656: double ***p3mat;
1.218 brouard 10657:
10658: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10659: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10660: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10661: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10662: }
10663: printf("Computing pij back: result on file '%s' \n", filerespijb);
10664: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10665:
10666: stepsize=(int) (stepm+YEARM-1)/YEARM;
10667: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10668:
1.218 brouard 10669: /* agelim=AGESUP; */
1.289 brouard 10670: ageminl=AGEINF; /* was 30 */
1.218 brouard 10671: hstepm=stepsize*YEARM; /* Every year of age */
10672: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10673:
10674: /* hstepm=1; aff par mois*/
10675: pstamp(ficrespijb);
1.255 brouard 10676: 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 10677: i1= pow(2,cptcoveff);
1.218 brouard 10678: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10679: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10680: /* k=k+1; */
1.238 brouard 10681: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10682: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10683: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10684: continue;
10685: fprintf(ficrespijb,"\n#****** ");
10686: for(j=1;j<=cptcoveff;j++)
10687: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10688: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10689: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10690: }
10691: fprintf(ficrespijb,"******\n");
1.264 brouard 10692: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10693: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10694: continue;
10695: }
10696:
10697: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10698: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10699: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10700: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10701: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10702:
10703: /* nhstepm=nhstepm*YEARM; aff par mois*/
10704:
1.266 brouard 10705: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10706: /* and memory limitations if stepm is small */
10707:
1.238 brouard 10708: /* oldm=oldms;savm=savms; */
10709: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10710: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10711: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10712: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10713: for(i=1; i<=nlstate;i++)
10714: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10715: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10716: fprintf(ficrespijb,"\n");
1.238 brouard 10717: for (h=0; h<=nhstepm; h++){
10718: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10719: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10720: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10721: for(i=1; i<=nlstate;i++)
10722: for(j=1; j<=nlstate+ndeath;j++)
10723: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10724: fprintf(ficrespijb,"\n");
10725: }
10726: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10727: fprintf(ficrespijb,"\n");
10728: } /* end age deb */
10729: } /* end combination */
10730: } /* end nres */
1.218 brouard 10731: return 0;
10732: } /* hBijx */
1.217 brouard 10733:
1.180 brouard 10734:
1.136 brouard 10735: /***********************************************/
10736: /**************** Main Program *****************/
10737: /***********************************************/
10738:
10739: int main(int argc, char *argv[])
10740: {
10741: #ifdef GSL
10742: const gsl_multimin_fminimizer_type *T;
10743: size_t iteri = 0, it;
10744: int rval = GSL_CONTINUE;
10745: int status = GSL_SUCCESS;
10746: double ssval;
10747: #endif
10748: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 10749: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
10750: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 10751: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10752: int jj, ll, li, lj, lk;
1.136 brouard 10753: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10754: int num_filled;
1.136 brouard 10755: int itimes;
10756: int NDIM=2;
10757: int vpopbased=0;
1.235 brouard 10758: int nres=0;
1.258 brouard 10759: int endishere=0;
1.277 brouard 10760: int noffset=0;
1.274 brouard 10761: int ncurrv=0; /* Temporary variable */
10762:
1.164 brouard 10763: char ca[32], cb[32];
1.136 brouard 10764: /* FILE *fichtm; *//* Html File */
10765: /* FILE *ficgp;*/ /*Gnuplot File */
10766: struct stat info;
1.191 brouard 10767: double agedeb=0.;
1.194 brouard 10768:
10769: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10770: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10771:
1.165 brouard 10772: double fret;
1.191 brouard 10773: double dum=0.; /* Dummy variable */
1.136 brouard 10774: double ***p3mat;
1.218 brouard 10775: /* double ***mobaverage; */
1.164 brouard 10776:
10777: char line[MAXLINE];
1.197 brouard 10778: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10779:
1.234 brouard 10780: char modeltemp[MAXLINE];
1.230 brouard 10781: char resultline[MAXLINE];
10782:
1.136 brouard 10783: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10784: char *tok, *val; /* pathtot */
1.290 brouard 10785: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 10786: int c, h , cpt, c2;
1.191 brouard 10787: int jl=0;
10788: int i1, j1, jk, stepsize=0;
1.194 brouard 10789: int count=0;
10790:
1.164 brouard 10791: int *tab;
1.136 brouard 10792: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.293 brouard 10793: int backcast=0; /* defined as global for mlikeli and mle*/
1.136 brouard 10794: int mobilav=0,popforecast=0;
1.191 brouard 10795: int hstepm=0, nhstepm=0;
1.136 brouard 10796: int agemortsup;
10797: float sumlpop=0.;
10798: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10799: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10800:
1.191 brouard 10801: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10802: double ftolpl=FTOL;
10803: double **prlim;
1.217 brouard 10804: double **bprlim;
1.136 brouard 10805: double ***param; /* Matrix of parameters */
1.251 brouard 10806: double ***paramstart; /* Matrix of starting parameter values */
10807: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10808: double **matcov; /* Matrix of covariance */
1.203 brouard 10809: double **hess; /* Hessian matrix */
1.136 brouard 10810: double ***delti3; /* Scale */
10811: double *delti; /* Scale */
10812: double ***eij, ***vareij;
10813: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10814:
1.136 brouard 10815: double *epj, vepp;
1.164 brouard 10816:
1.273 brouard 10817: double dateprev1, dateprev2;
10818: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0;
10819: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0;
1.217 brouard 10820:
1.136 brouard 10821: double **ximort;
1.145 brouard 10822: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10823: int *dcwave;
10824:
1.164 brouard 10825: char z[1]="c";
1.136 brouard 10826:
10827: /*char *strt;*/
10828: char strtend[80];
1.126 brouard 10829:
1.164 brouard 10830:
1.126 brouard 10831: /* setlocale (LC_ALL, ""); */
10832: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10833: /* textdomain (PACKAGE); */
10834: /* setlocale (LC_CTYPE, ""); */
10835: /* setlocale (LC_MESSAGES, ""); */
10836:
10837: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10838: rstart_time = time(NULL);
10839: /* (void) gettimeofday(&start_time,&tzp);*/
10840: start_time = *localtime(&rstart_time);
1.126 brouard 10841: curr_time=start_time;
1.157 brouard 10842: /*tml = *localtime(&start_time.tm_sec);*/
10843: /* strcpy(strstart,asctime(&tml)); */
10844: strcpy(strstart,asctime(&start_time));
1.126 brouard 10845:
10846: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10847: /* tp.tm_sec = tp.tm_sec +86400; */
10848: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10849: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10850: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10851: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10852: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10853: /* strt=asctime(&tmg); */
10854: /* printf("Time(after) =%s",strstart); */
10855: /* (void) time (&time_value);
10856: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10857: * tm = *localtime(&time_value);
10858: * strstart=asctime(&tm);
10859: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10860: */
10861:
10862: nberr=0; /* Number of errors and warnings */
10863: nbwarn=0;
1.184 brouard 10864: #ifdef WIN32
10865: _getcwd(pathcd, size);
10866: #else
1.126 brouard 10867: getcwd(pathcd, size);
1.184 brouard 10868: #endif
1.191 brouard 10869: syscompilerinfo(0);
1.196 brouard 10870: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10871: if(argc <=1){
10872: printf("\nEnter the parameter file name: ");
1.205 brouard 10873: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10874: printf("ERROR Empty parameter file name\n");
10875: goto end;
10876: }
1.126 brouard 10877: i=strlen(pathr);
10878: if(pathr[i-1]=='\n')
10879: pathr[i-1]='\0';
1.156 brouard 10880: i=strlen(pathr);
1.205 brouard 10881: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10882: pathr[i-1]='\0';
1.205 brouard 10883: }
10884: i=strlen(pathr);
10885: if( i==0 ){
10886: printf("ERROR Empty parameter file name\n");
10887: goto end;
10888: }
10889: for (tok = pathr; tok != NULL; ){
1.126 brouard 10890: printf("Pathr |%s|\n",pathr);
10891: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10892: printf("val= |%s| pathr=%s\n",val,pathr);
10893: strcpy (pathtot, val);
10894: if(pathr[0] == '\0') break; /* Dirty */
10895: }
10896: }
1.281 brouard 10897: else if (argc<=2){
10898: strcpy(pathtot,argv[1]);
10899: }
1.126 brouard 10900: else{
10901: strcpy(pathtot,argv[1]);
1.281 brouard 10902: strcpy(z,argv[2]);
10903: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10904: }
10905: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10906: /*cygwin_split_path(pathtot,path,optionfile);
10907: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10908: /* cutv(path,optionfile,pathtot,'\\');*/
10909:
10910: /* Split argv[0], imach program to get pathimach */
10911: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10912: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10913: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10914: /* strcpy(pathimach,argv[0]); */
10915: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10916: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10917: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10918: #ifdef WIN32
10919: _chdir(path); /* Can be a relative path */
10920: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10921: #else
1.126 brouard 10922: chdir(path); /* Can be a relative path */
1.184 brouard 10923: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10924: #endif
10925: printf("Current directory %s!\n",pathcd);
1.126 brouard 10926: strcpy(command,"mkdir ");
10927: strcat(command,optionfilefiname);
10928: if((outcmd=system(command)) != 0){
1.169 brouard 10929: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10930: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10931: /* fclose(ficlog); */
10932: /* exit(1); */
10933: }
10934: /* if((imk=mkdir(optionfilefiname))<0){ */
10935: /* perror("mkdir"); */
10936: /* } */
10937:
10938: /*-------- arguments in the command line --------*/
10939:
1.186 brouard 10940: /* Main Log file */
1.126 brouard 10941: strcat(filelog, optionfilefiname);
10942: strcat(filelog,".log"); /* */
10943: if((ficlog=fopen(filelog,"w"))==NULL) {
10944: printf("Problem with logfile %s\n",filelog);
10945: goto end;
10946: }
10947: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10948: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10949: fprintf(ficlog,"\nEnter the parameter file name: \n");
10950: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10951: path=%s \n\
10952: optionfile=%s\n\
10953: optionfilext=%s\n\
1.156 brouard 10954: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10955:
1.197 brouard 10956: syscompilerinfo(1);
1.167 brouard 10957:
1.126 brouard 10958: printf("Local time (at start):%s",strstart);
10959: fprintf(ficlog,"Local time (at start): %s",strstart);
10960: fflush(ficlog);
10961: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10962: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10963:
10964: /* */
10965: strcpy(fileres,"r");
10966: strcat(fileres, optionfilefiname);
1.201 brouard 10967: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10968: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10969: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10970:
1.186 brouard 10971: /* Main ---------arguments file --------*/
1.126 brouard 10972:
10973: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10974: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10975: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10976: fflush(ficlog);
1.149 brouard 10977: /* goto end; */
10978: exit(70);
1.126 brouard 10979: }
10980:
10981: strcpy(filereso,"o");
1.201 brouard 10982: strcat(filereso,fileresu);
1.126 brouard 10983: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10984: printf("Problem with Output resultfile: %s\n", filereso);
10985: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10986: fflush(ficlog);
10987: goto end;
10988: }
1.278 brouard 10989: /*-------- Rewriting parameter file ----------*/
10990: strcpy(rfileres,"r"); /* "Rparameterfile */
10991: strcat(rfileres,optionfilefiname); /* Parameter file first name */
10992: strcat(rfileres,"."); /* */
10993: strcat(rfileres,optionfilext); /* Other files have txt extension */
10994: if((ficres =fopen(rfileres,"w"))==NULL) {
10995: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10996: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
10997: fflush(ficlog);
10998: goto end;
10999: }
11000: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11001:
1.278 brouard 11002:
1.126 brouard 11003: /* Reads comments: lines beginning with '#' */
11004: numlinepar=0;
1.277 brouard 11005: /* Is it a BOM UTF-8 Windows file? */
11006: /* First parameter line */
1.197 brouard 11007: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11008: noffset=0;
11009: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11010: {
11011: noffset=noffset+3;
11012: printf("# File is an UTF8 Bom.\n"); // 0xBF
11013: }
11014: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
11015: {
11016: noffset=noffset+2;
11017: printf("# File is an UTF16BE BOM file\n");
11018: }
11019: else if( line[0] == 0 && line[1] == 0)
11020: {
11021: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11022: noffset=noffset+4;
11023: printf("# File is an UTF16BE BOM file\n");
11024: }
11025: } else{
11026: ;/*printf(" Not a BOM file\n");*/
11027: }
11028:
1.197 brouard 11029: /* If line starts with a # it is a comment */
1.277 brouard 11030: if (line[noffset] == '#') {
1.197 brouard 11031: numlinepar++;
11032: fputs(line,stdout);
11033: fputs(line,ficparo);
1.278 brouard 11034: fputs(line,ficres);
1.197 brouard 11035: fputs(line,ficlog);
11036: continue;
11037: }else
11038: break;
11039: }
11040: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11041: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11042: if (num_filled != 5) {
11043: printf("Should be 5 parameters\n");
1.283 brouard 11044: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11045: }
1.126 brouard 11046: numlinepar++;
1.197 brouard 11047: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11048: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11049: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11050: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11051: }
11052: /* Second parameter line */
11053: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11054: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11055: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11056: if (line[0] == '#') {
11057: numlinepar++;
1.283 brouard 11058: printf("%s",line);
11059: fprintf(ficres,"%s",line);
11060: fprintf(ficparo,"%s",line);
11061: fprintf(ficlog,"%s",line);
1.197 brouard 11062: continue;
11063: }else
11064: break;
11065: }
1.223 brouard 11066: 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", \
11067: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11068: if (num_filled != 11) {
11069: 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 11070: printf("but line=%s\n",line);
1.283 brouard 11071: 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");
11072: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11073: }
1.286 brouard 11074: if( lastpass > maxwav){
11075: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11076: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11077: fflush(ficlog);
11078: goto end;
11079: }
11080: 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 11081: 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 11082: 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 11083: 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 11084: }
1.203 brouard 11085: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11086: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11087: /* Third parameter line */
11088: while(fgets(line, MAXLINE, ficpar)) {
11089: /* If line starts with a # it is a comment */
11090: if (line[0] == '#') {
11091: numlinepar++;
1.283 brouard 11092: printf("%s",line);
11093: fprintf(ficres,"%s",line);
11094: fprintf(ficparo,"%s",line);
11095: fprintf(ficlog,"%s",line);
1.197 brouard 11096: continue;
11097: }else
11098: break;
11099: }
1.201 brouard 11100: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11101: if (num_filled != 1){
11102: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11103: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11104: model[0]='\0';
11105: goto end;
11106: }
11107: else{
11108: if (model[0]=='+'){
11109: for(i=1; i<=strlen(model);i++)
11110: modeltemp[i-1]=model[i];
1.201 brouard 11111: strcpy(model,modeltemp);
1.197 brouard 11112: }
11113: }
1.199 brouard 11114: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11115: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11116: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11117: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11118: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11119: }
11120: /* 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); */
11121: /* numlinepar=numlinepar+3; /\* In general *\/ */
11122: /* 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 11123: /* 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); */
11124: /* 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 11125: fflush(ficlog);
1.190 brouard 11126: /* if(model[0]=='#'|| model[0]== '\0'){ */
11127: if(model[0]=='#'){
1.279 brouard 11128: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11129: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11130: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11131: if(mle != -1){
1.279 brouard 11132: 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 11133: exit(1);
11134: }
11135: }
1.126 brouard 11136: while((c=getc(ficpar))=='#' && c!= EOF){
11137: ungetc(c,ficpar);
11138: fgets(line, MAXLINE, ficpar);
11139: numlinepar++;
1.195 brouard 11140: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11141: z[0]=line[1];
11142: }
11143: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11144: fputs(line, stdout);
11145: //puts(line);
1.126 brouard 11146: fputs(line,ficparo);
11147: fputs(line,ficlog);
11148: }
11149: ungetc(c,ficpar);
11150:
11151:
1.290 brouard 11152: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11153: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11154: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11155: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11156: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11157: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11158: v1+v2*age+v2*v3 makes cptcovn = 3
11159: */
11160: if (strlen(model)>1)
1.187 brouard 11161: 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 11162: else
1.187 brouard 11163: ncovmodel=2; /* Constant and age */
1.133 brouard 11164: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11165: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11166: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11167: 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);
11168: 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);
11169: fflush(stdout);
11170: fclose (ficlog);
11171: goto end;
11172: }
1.126 brouard 11173: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11174: delti=delti3[1][1];
11175: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11176: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11177: /* We could also provide initial parameters values giving by simple logistic regression
11178: * only one way, that is without matrix product. We will have nlstate maximizations */
11179: /* for(i=1;i<nlstate;i++){ */
11180: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11181: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11182: /* } */
1.126 brouard 11183: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11184: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11185: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11186: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11187: fclose (ficparo);
11188: fclose (ficlog);
11189: goto end;
11190: exit(0);
1.220 brouard 11191: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11192: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11193: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11194: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11195: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11196: matcov=matrix(1,npar,1,npar);
1.203 brouard 11197: hess=matrix(1,npar,1,npar);
1.220 brouard 11198: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11199: /* Read guessed parameters */
1.126 brouard 11200: /* Reads comments: lines beginning with '#' */
11201: while((c=getc(ficpar))=='#' && c!= EOF){
11202: ungetc(c,ficpar);
11203: fgets(line, MAXLINE, ficpar);
11204: numlinepar++;
1.141 brouard 11205: fputs(line,stdout);
1.126 brouard 11206: fputs(line,ficparo);
11207: fputs(line,ficlog);
11208: }
11209: ungetc(c,ficpar);
11210:
11211: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11212: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11213: for(i=1; i <=nlstate; i++){
1.234 brouard 11214: j=0;
1.126 brouard 11215: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11216: if(jj==i) continue;
11217: j++;
1.292 brouard 11218: while((c=getc(ficpar))=='#' && c!= EOF){
11219: ungetc(c,ficpar);
11220: fgets(line, MAXLINE, ficpar);
11221: numlinepar++;
11222: fputs(line,stdout);
11223: fputs(line,ficparo);
11224: fputs(line,ficlog);
11225: }
11226: ungetc(c,ficpar);
1.234 brouard 11227: fscanf(ficpar,"%1d%1d",&i1,&j1);
11228: if ((i1 != i) || (j1 != jj)){
11229: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11230: It might be a problem of design; if ncovcol and the model are correct\n \
11231: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11232: exit(1);
11233: }
11234: fprintf(ficparo,"%1d%1d",i1,j1);
11235: if(mle==1)
11236: printf("%1d%1d",i,jj);
11237: fprintf(ficlog,"%1d%1d",i,jj);
11238: for(k=1; k<=ncovmodel;k++){
11239: fscanf(ficpar," %lf",¶m[i][j][k]);
11240: if(mle==1){
11241: printf(" %lf",param[i][j][k]);
11242: fprintf(ficlog," %lf",param[i][j][k]);
11243: }
11244: else
11245: fprintf(ficlog," %lf",param[i][j][k]);
11246: fprintf(ficparo," %lf",param[i][j][k]);
11247: }
11248: fscanf(ficpar,"\n");
11249: numlinepar++;
11250: if(mle==1)
11251: printf("\n");
11252: fprintf(ficlog,"\n");
11253: fprintf(ficparo,"\n");
1.126 brouard 11254: }
11255: }
11256: fflush(ficlog);
1.234 brouard 11257:
1.251 brouard 11258: /* Reads parameters values */
1.126 brouard 11259: p=param[1][1];
1.251 brouard 11260: pstart=paramstart[1][1];
1.126 brouard 11261:
11262: /* Reads comments: lines beginning with '#' */
11263: while((c=getc(ficpar))=='#' && c!= EOF){
11264: ungetc(c,ficpar);
11265: fgets(line, MAXLINE, ficpar);
11266: numlinepar++;
1.141 brouard 11267: fputs(line,stdout);
1.126 brouard 11268: fputs(line,ficparo);
11269: fputs(line,ficlog);
11270: }
11271: ungetc(c,ficpar);
11272:
11273: for(i=1; i <=nlstate; i++){
11274: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11275: fscanf(ficpar,"%1d%1d",&i1,&j1);
11276: if ( (i1-i) * (j1-j) != 0){
11277: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11278: exit(1);
11279: }
11280: printf("%1d%1d",i,j);
11281: fprintf(ficparo,"%1d%1d",i1,j1);
11282: fprintf(ficlog,"%1d%1d",i1,j1);
11283: for(k=1; k<=ncovmodel;k++){
11284: fscanf(ficpar,"%le",&delti3[i][j][k]);
11285: printf(" %le",delti3[i][j][k]);
11286: fprintf(ficparo," %le",delti3[i][j][k]);
11287: fprintf(ficlog," %le",delti3[i][j][k]);
11288: }
11289: fscanf(ficpar,"\n");
11290: numlinepar++;
11291: printf("\n");
11292: fprintf(ficparo,"\n");
11293: fprintf(ficlog,"\n");
1.126 brouard 11294: }
11295: }
11296: fflush(ficlog);
1.234 brouard 11297:
1.145 brouard 11298: /* Reads covariance matrix */
1.126 brouard 11299: delti=delti3[1][1];
1.220 brouard 11300:
11301:
1.126 brouard 11302: /* 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 11303:
1.126 brouard 11304: /* Reads comments: lines beginning with '#' */
11305: while((c=getc(ficpar))=='#' && c!= EOF){
11306: ungetc(c,ficpar);
11307: fgets(line, MAXLINE, ficpar);
11308: numlinepar++;
1.141 brouard 11309: fputs(line,stdout);
1.126 brouard 11310: fputs(line,ficparo);
11311: fputs(line,ficlog);
11312: }
11313: ungetc(c,ficpar);
1.220 brouard 11314:
1.126 brouard 11315: matcov=matrix(1,npar,1,npar);
1.203 brouard 11316: hess=matrix(1,npar,1,npar);
1.131 brouard 11317: for(i=1; i <=npar; i++)
11318: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11319:
1.194 brouard 11320: /* Scans npar lines */
1.126 brouard 11321: for(i=1; i <=npar; i++){
1.226 brouard 11322: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11323: if(count != 3){
1.226 brouard 11324: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11325: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11326: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11327: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11328: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11329: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11330: exit(1);
1.220 brouard 11331: }else{
1.226 brouard 11332: if(mle==1)
11333: printf("%1d%1d%d",i1,j1,jk);
11334: }
11335: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11336: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11337: for(j=1; j <=i; j++){
1.226 brouard 11338: fscanf(ficpar," %le",&matcov[i][j]);
11339: if(mle==1){
11340: printf(" %.5le",matcov[i][j]);
11341: }
11342: fprintf(ficlog," %.5le",matcov[i][j]);
11343: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11344: }
11345: fscanf(ficpar,"\n");
11346: numlinepar++;
11347: if(mle==1)
1.220 brouard 11348: printf("\n");
1.126 brouard 11349: fprintf(ficlog,"\n");
11350: fprintf(ficparo,"\n");
11351: }
1.194 brouard 11352: /* End of read covariance matrix npar lines */
1.126 brouard 11353: for(i=1; i <=npar; i++)
11354: for(j=i+1;j<=npar;j++)
1.226 brouard 11355: matcov[i][j]=matcov[j][i];
1.126 brouard 11356:
11357: if(mle==1)
11358: printf("\n");
11359: fprintf(ficlog,"\n");
11360:
11361: fflush(ficlog);
11362:
11363: } /* End of mle != -3 */
1.218 brouard 11364:
1.186 brouard 11365: /* Main data
11366: */
1.290 brouard 11367: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11368: /* num=lvector(1,n); */
11369: /* moisnais=vector(1,n); */
11370: /* annais=vector(1,n); */
11371: /* moisdc=vector(1,n); */
11372: /* andc=vector(1,n); */
11373: /* weight=vector(1,n); */
11374: /* agedc=vector(1,n); */
11375: /* cod=ivector(1,n); */
11376: /* for(i=1;i<=n;i++){ */
11377: num=lvector(firstobs,lastobs);
11378: moisnais=vector(firstobs,lastobs);
11379: annais=vector(firstobs,lastobs);
11380: moisdc=vector(firstobs,lastobs);
11381: andc=vector(firstobs,lastobs);
11382: weight=vector(firstobs,lastobs);
11383: agedc=vector(firstobs,lastobs);
11384: cod=ivector(firstobs,lastobs);
11385: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11386: num[i]=0;
11387: moisnais[i]=0;
11388: annais[i]=0;
11389: moisdc[i]=0;
11390: andc[i]=0;
11391: agedc[i]=0;
11392: cod[i]=0;
11393: weight[i]=1.0; /* Equal weights, 1 by default */
11394: }
1.290 brouard 11395: mint=matrix(1,maxwav,firstobs,lastobs);
11396: anint=matrix(1,maxwav,firstobs,lastobs);
11397: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11398: tab=ivector(1,NCOVMAX);
1.144 brouard 11399: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11400: 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 11401:
1.136 brouard 11402: /* Reads data from file datafile */
11403: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11404: goto end;
11405:
11406: /* Calculation of the number of parameters from char model */
1.234 brouard 11407: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11408: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11409: k=3 V4 Tvar[k=3]= 4 (from V4)
11410: k=2 V1 Tvar[k=2]= 1 (from V1)
11411: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11412: */
11413:
11414: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11415: TvarsDind=ivector(1,NCOVMAX); /* */
11416: TvarsD=ivector(1,NCOVMAX); /* */
11417: TvarsQind=ivector(1,NCOVMAX); /* */
11418: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11419: TvarF=ivector(1,NCOVMAX); /* */
11420: TvarFind=ivector(1,NCOVMAX); /* */
11421: TvarV=ivector(1,NCOVMAX); /* */
11422: TvarVind=ivector(1,NCOVMAX); /* */
11423: TvarA=ivector(1,NCOVMAX); /* */
11424: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11425: TvarFD=ivector(1,NCOVMAX); /* */
11426: TvarFDind=ivector(1,NCOVMAX); /* */
11427: TvarFQ=ivector(1,NCOVMAX); /* */
11428: TvarFQind=ivector(1,NCOVMAX); /* */
11429: TvarVD=ivector(1,NCOVMAX); /* */
11430: TvarVDind=ivector(1,NCOVMAX); /* */
11431: TvarVQ=ivector(1,NCOVMAX); /* */
11432: TvarVQind=ivector(1,NCOVMAX); /* */
11433:
1.230 brouard 11434: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11435: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11436: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11437: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11438: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11439: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11440: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11441: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11442: */
11443: /* For model-covariate k tells which data-covariate to use but
11444: because this model-covariate is a construction we invent a new column
11445: ncovcol + k1
11446: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11447: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11448: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11449: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11450: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11451: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11452: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11453: */
1.145 brouard 11454: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11455: 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 11456: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11457: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11458: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11459: 4 covariates (3 plus signs)
11460: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11461: */
1.230 brouard 11462: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11463: * individual dummy, fixed or varying:
11464: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11465: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11466: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11467: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11468: * Tmodelind[1]@9={9,0,3,2,}*/
11469: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11470: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11471: * individual quantitative, fixed or varying:
11472: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11473: * 3, 1, 0, 0, 0, 0, 0, 0},
11474: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11475: /* Main decodemodel */
11476:
1.187 brouard 11477:
1.223 brouard 11478: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11479: goto end;
11480:
1.137 brouard 11481: if((double)(lastobs-imx)/(double)imx > 1.10){
11482: nbwarn++;
11483: 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);
11484: 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);
11485: }
1.136 brouard 11486: /* if(mle==1){*/
1.137 brouard 11487: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11488: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11489: }
11490:
11491: /*-calculation of age at interview from date of interview and age at death -*/
11492: agev=matrix(1,maxwav,1,imx);
11493:
11494: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11495: goto end;
11496:
1.126 brouard 11497:
1.136 brouard 11498: agegomp=(int)agemin;
1.290 brouard 11499: free_vector(moisnais,firstobs,lastobs);
11500: free_vector(annais,firstobs,lastobs);
1.126 brouard 11501: /* free_matrix(mint,1,maxwav,1,n);
11502: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11503: /* free_vector(moisdc,1,n); */
11504: /* free_vector(andc,1,n); */
1.145 brouard 11505: /* */
11506:
1.126 brouard 11507: wav=ivector(1,imx);
1.214 brouard 11508: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11509: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11510: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11511: 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.*/
11512: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11513: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11514:
11515: /* Concatenates waves */
1.214 brouard 11516: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11517: Death is a valid wave (if date is known).
11518: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11519: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11520: and mw[mi+1][i]. dh depends on stepm.
11521: */
11522:
1.126 brouard 11523: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11524: /* Concatenates waves */
1.145 brouard 11525:
1.290 brouard 11526: free_vector(moisdc,firstobs,lastobs);
11527: free_vector(andc,firstobs,lastobs);
1.215 brouard 11528:
1.126 brouard 11529: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11530: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11531: ncodemax[1]=1;
1.145 brouard 11532: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11533: cptcoveff=0;
1.220 brouard 11534: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11535: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11536: }
11537:
11538: ncovcombmax=pow(2,cptcoveff);
11539: invalidvarcomb=ivector(1, ncovcombmax);
11540: for(i=1;i<ncovcombmax;i++)
11541: invalidvarcomb[i]=0;
11542:
1.211 brouard 11543: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11544: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11545: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11546:
1.200 brouard 11547: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11548: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11549: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11550: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11551: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11552: * (currently 0 or 1) in the data.
11553: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11554: * corresponding modality (h,j).
11555: */
11556:
1.145 brouard 11557: h=0;
11558: /*if (cptcovn > 0) */
1.126 brouard 11559: m=pow(2,cptcoveff);
11560:
1.144 brouard 11561: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11562: * For k=4 covariates, h goes from 1 to m=2**k
11563: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11564: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11565: * h\k 1 2 3 4
1.143 brouard 11566: *______________________________
11567: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11568: * 2 2 1 1 1
11569: * 3 i=2 1 2 1 1
11570: * 4 2 2 1 1
11571: * 5 i=3 1 i=2 1 2 1
11572: * 6 2 1 2 1
11573: * 7 i=4 1 2 2 1
11574: * 8 2 2 2 1
1.197 brouard 11575: * 9 i=5 1 i=3 1 i=2 1 2
11576: * 10 2 1 1 2
11577: * 11 i=6 1 2 1 2
11578: * 12 2 2 1 2
11579: * 13 i=7 1 i=4 1 2 2
11580: * 14 2 1 2 2
11581: * 15 i=8 1 2 2 2
11582: * 16 2 2 2 2
1.143 brouard 11583: */
1.212 brouard 11584: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11585: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11586: * and the value of each covariate?
11587: * V1=1, V2=1, V3=2, V4=1 ?
11588: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11589: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11590: * In order to get the real value in the data, we use nbcode
11591: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11592: * We are keeping this crazy system in order to be able (in the future?)
11593: * to have more than 2 values (0 or 1) for a covariate.
11594: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11595: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11596: * bbbbbbbb
11597: * 76543210
11598: * h-1 00000101 (6-1=5)
1.219 brouard 11599: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11600: * &
11601: * 1 00000001 (1)
1.219 brouard 11602: * 00000000 = 1 & ((h-1) >> (k-1))
11603: * +1= 00000001 =1
1.211 brouard 11604: *
11605: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11606: * h' 1101 =2^3+2^2+0x2^1+2^0
11607: * >>k' 11
11608: * & 00000001
11609: * = 00000001
11610: * +1 = 00000010=2 = codtabm(14,3)
11611: * Reverse h=6 and m=16?
11612: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11613: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11614: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11615: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11616: * V3=decodtabm(14,3,2**4)=2
11617: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11618: *(h-1) >> (j-1) 0011 =13 >> 2
11619: * &1 000000001
11620: * = 000000001
11621: * +1= 000000010 =2
11622: * 2211
11623: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11624: * V3=2
1.220 brouard 11625: * codtabm and decodtabm are identical
1.211 brouard 11626: */
11627:
1.145 brouard 11628:
11629: free_ivector(Ndum,-1,NCOVMAX);
11630:
11631:
1.126 brouard 11632:
1.186 brouard 11633: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11634: strcpy(optionfilegnuplot,optionfilefiname);
11635: if(mle==-3)
1.201 brouard 11636: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11637: strcat(optionfilegnuplot,".gp");
11638:
11639: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11640: printf("Problem with file %s",optionfilegnuplot);
11641: }
11642: else{
1.204 brouard 11643: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11644: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11645: //fprintf(ficgp,"set missing 'NaNq'\n");
11646: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11647: }
11648: /* fclose(ficgp);*/
1.186 brouard 11649:
11650:
11651: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11652:
11653: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11654: if(mle==-3)
1.201 brouard 11655: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11656: strcat(optionfilehtm,".htm");
11657: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11658: printf("Problem with %s \n",optionfilehtm);
11659: exit(0);
1.126 brouard 11660: }
11661:
11662: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11663: strcat(optionfilehtmcov,"-cov.htm");
11664: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11665: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11666: }
11667: else{
11668: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11669: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11670: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11671: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11672: }
11673:
1.213 brouard 11674: 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 11675: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11676: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11677: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11678: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11679: \n\
11680: <hr size=\"2\" color=\"#EC5E5E\">\
11681: <ul><li><h4>Parameter files</h4>\n\
11682: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11683: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11684: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11685: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11686: - Date and time at start: %s</ul>\n",\
11687: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11688: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11689: fileres,fileres,\
11690: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11691: fflush(fichtm);
11692:
11693: strcpy(pathr,path);
11694: strcat(pathr,optionfilefiname);
1.184 brouard 11695: #ifdef WIN32
11696: _chdir(optionfilefiname); /* Move to directory named optionfile */
11697: #else
1.126 brouard 11698: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11699: #endif
11700:
1.126 brouard 11701:
1.220 brouard 11702: /* Calculates basic frequencies. Computes observed prevalence at single age
11703: and for any valid combination of covariates
1.126 brouard 11704: and prints on file fileres'p'. */
1.251 brouard 11705: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11706: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11707:
11708: fprintf(fichtm,"\n");
1.286 brouard 11709: 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 11710: ftol, stepm);
11711: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11712: ncurrv=1;
11713: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11714: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11715: ncurrv=i;
11716: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11717: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 11718: ncurrv=i;
11719: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11720: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 11721: ncurrv=i;
11722: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11723: 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", \
11724: nlstate, ndeath, maxwav, mle, weightopt);
11725:
11726: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11727: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11728:
11729:
11730: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11731: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11732: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11733: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11734: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11735: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11736: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11737: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11738: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11739:
1.126 brouard 11740: /* For Powell, parameters are in a vector p[] starting at p[1]
11741: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11742: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11743:
11744: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11745: /* For mortality only */
1.126 brouard 11746: if (mle==-3){
1.136 brouard 11747: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11748: for(i=1;i<=NDIM;i++)
11749: for(j=1;j<=NDIM;j++)
11750: ximort[i][j]=0.;
1.186 brouard 11751: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 11752: cens=ivector(firstobs,lastobs);
11753: ageexmed=vector(firstobs,lastobs);
11754: agecens=vector(firstobs,lastobs);
11755: dcwave=ivector(firstobs,lastobs);
1.223 brouard 11756:
1.126 brouard 11757: for (i=1; i<=imx; i++){
11758: dcwave[i]=-1;
11759: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11760: if (s[m][i]>nlstate) {
11761: dcwave[i]=m;
11762: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11763: break;
11764: }
1.126 brouard 11765: }
1.226 brouard 11766:
1.126 brouard 11767: for (i=1; i<=imx; i++) {
11768: if (wav[i]>0){
1.226 brouard 11769: ageexmed[i]=agev[mw[1][i]][i];
11770: j=wav[i];
11771: agecens[i]=1.;
11772:
11773: if (ageexmed[i]> 1 && wav[i] > 0){
11774: agecens[i]=agev[mw[j][i]][i];
11775: cens[i]= 1;
11776: }else if (ageexmed[i]< 1)
11777: cens[i]= -1;
11778: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11779: cens[i]=0 ;
1.126 brouard 11780: }
11781: else cens[i]=-1;
11782: }
11783:
11784: for (i=1;i<=NDIM;i++) {
11785: for (j=1;j<=NDIM;j++)
1.226 brouard 11786: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11787: }
11788:
1.145 brouard 11789: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11790: /*printf("%lf %lf", p[1], p[2]);*/
11791:
11792:
1.136 brouard 11793: #ifdef GSL
11794: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11795: #else
1.126 brouard 11796: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11797: #endif
1.201 brouard 11798: strcpy(filerespow,"POW-MORT_");
11799: strcat(filerespow,fileresu);
1.126 brouard 11800: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11801: printf("Problem with resultfile: %s\n", filerespow);
11802: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11803: }
1.136 brouard 11804: #ifdef GSL
11805: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11806: #else
1.126 brouard 11807: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11808: #endif
1.126 brouard 11809: /* for (i=1;i<=nlstate;i++)
11810: for(j=1;j<=nlstate+ndeath;j++)
11811: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11812: */
11813: fprintf(ficrespow,"\n");
1.136 brouard 11814: #ifdef GSL
11815: /* gsl starts here */
11816: T = gsl_multimin_fminimizer_nmsimplex;
11817: gsl_multimin_fminimizer *sfm = NULL;
11818: gsl_vector *ss, *x;
11819: gsl_multimin_function minex_func;
11820:
11821: /* Initial vertex size vector */
11822: ss = gsl_vector_alloc (NDIM);
11823:
11824: if (ss == NULL){
11825: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11826: }
11827: /* Set all step sizes to 1 */
11828: gsl_vector_set_all (ss, 0.001);
11829:
11830: /* Starting point */
1.126 brouard 11831:
1.136 brouard 11832: x = gsl_vector_alloc (NDIM);
11833:
11834: if (x == NULL){
11835: gsl_vector_free(ss);
11836: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11837: }
11838:
11839: /* Initialize method and iterate */
11840: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11841: /* gsl_vector_set(x, 0, 0.0268); */
11842: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11843: gsl_vector_set(x, 0, p[1]);
11844: gsl_vector_set(x, 1, p[2]);
11845:
11846: minex_func.f = &gompertz_f;
11847: minex_func.n = NDIM;
11848: minex_func.params = (void *)&p; /* ??? */
11849:
11850: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11851: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11852:
11853: printf("Iterations beginning .....\n\n");
11854: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11855:
11856: iteri=0;
11857: while (rval == GSL_CONTINUE){
11858: iteri++;
11859: status = gsl_multimin_fminimizer_iterate(sfm);
11860:
11861: if (status) printf("error: %s\n", gsl_strerror (status));
11862: fflush(0);
11863:
11864: if (status)
11865: break;
11866:
11867: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11868: ssval = gsl_multimin_fminimizer_size (sfm);
11869:
11870: if (rval == GSL_SUCCESS)
11871: printf ("converged to a local maximum at\n");
11872:
11873: printf("%5d ", iteri);
11874: for (it = 0; it < NDIM; it++){
11875: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11876: }
11877: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11878: }
11879:
11880: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11881:
11882: gsl_vector_free(x); /* initial values */
11883: gsl_vector_free(ss); /* inital step size */
11884: for (it=0; it<NDIM; it++){
11885: p[it+1]=gsl_vector_get(sfm->x,it);
11886: fprintf(ficrespow," %.12lf", p[it]);
11887: }
11888: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11889: #endif
11890: #ifdef POWELL
11891: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11892: #endif
1.126 brouard 11893: fclose(ficrespow);
11894:
1.203 brouard 11895: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11896:
11897: for(i=1; i <=NDIM; i++)
11898: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11899: matcov[i][j]=matcov[j][i];
1.126 brouard 11900:
11901: printf("\nCovariance matrix\n ");
1.203 brouard 11902: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11903: for(i=1; i <=NDIM; i++) {
11904: for(j=1;j<=NDIM;j++){
1.220 brouard 11905: printf("%f ",matcov[i][j]);
11906: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11907: }
1.203 brouard 11908: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11909: }
11910:
11911: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11912: for (i=1;i<=NDIM;i++) {
1.126 brouard 11913: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11914: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11915: }
1.126 brouard 11916: lsurv=vector(1,AGESUP);
11917: lpop=vector(1,AGESUP);
11918: tpop=vector(1,AGESUP);
11919: lsurv[agegomp]=100000;
11920:
11921: for (k=agegomp;k<=AGESUP;k++) {
11922: agemortsup=k;
11923: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11924: }
11925:
11926: for (k=agegomp;k<agemortsup;k++)
11927: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11928:
11929: for (k=agegomp;k<agemortsup;k++){
11930: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11931: sumlpop=sumlpop+lpop[k];
11932: }
11933:
11934: tpop[agegomp]=sumlpop;
11935: for (k=agegomp;k<(agemortsup-3);k++){
11936: /* tpop[k+1]=2;*/
11937: tpop[k+1]=tpop[k]-lpop[k];
11938: }
11939:
11940:
11941: printf("\nAge lx qx dx Lx Tx e(x)\n");
11942: for (k=agegomp;k<(agemortsup-2);k++)
11943: 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]);
11944:
11945:
11946: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11947: ageminpar=50;
11948: agemaxpar=100;
1.194 brouard 11949: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11950: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11951: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11952: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11953: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11954: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11955: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11956: }else{
11957: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11958: 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 11959: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11960: }
1.201 brouard 11961: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11962: stepm, weightopt,\
11963: model,imx,p,matcov,agemortsup);
11964:
11965: free_vector(lsurv,1,AGESUP);
11966: free_vector(lpop,1,AGESUP);
11967: free_vector(tpop,1,AGESUP);
1.220 brouard 11968: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 11969: free_ivector(dcwave,firstobs,lastobs);
11970: free_vector(agecens,firstobs,lastobs);
11971: free_vector(ageexmed,firstobs,lastobs);
11972: free_ivector(cens,firstobs,lastobs);
1.220 brouard 11973: #ifdef GSL
1.136 brouard 11974: #endif
1.186 brouard 11975: } /* Endof if mle==-3 mortality only */
1.205 brouard 11976: /* Standard */
11977: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11978: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11979: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11980: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11981: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11982: for (k=1; k<=npar;k++)
11983: printf(" %d %8.5f",k,p[k]);
11984: printf("\n");
1.205 brouard 11985: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11986: /* mlikeli uses func not funcone */
1.247 brouard 11987: /* for(i=1;i<nlstate;i++){ */
11988: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11989: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11990: /* } */
1.205 brouard 11991: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11992: }
11993: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11994: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11995: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11996: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11997: }
11998: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11999: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12000: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12001: for (k=1; k<=npar;k++)
12002: printf(" %d %8.5f",k,p[k]);
12003: printf("\n");
12004:
12005: /*--------- results files --------------*/
1.283 brouard 12006: /* 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 12007:
12008:
12009: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12010: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12011: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12012: for(i=1,jk=1; i <=nlstate; i++){
12013: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12014: if (k != i) {
12015: printf("%d%d ",i,k);
12016: fprintf(ficlog,"%d%d ",i,k);
12017: fprintf(ficres,"%1d%1d ",i,k);
12018: for(j=1; j <=ncovmodel; j++){
12019: printf("%12.7f ",p[jk]);
12020: fprintf(ficlog,"%12.7f ",p[jk]);
12021: fprintf(ficres,"%12.7f ",p[jk]);
12022: jk++;
12023: }
12024: printf("\n");
12025: fprintf(ficlog,"\n");
12026: fprintf(ficres,"\n");
12027: }
1.126 brouard 12028: }
12029: }
1.203 brouard 12030: if(mle != 0){
12031: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12032: ftolhess=ftol; /* Usually correct */
1.203 brouard 12033: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12034: 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");
12035: 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");
12036: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12037: for(k=1; k <=(nlstate+ndeath); k++){
12038: if (k != i) {
12039: printf("%d%d ",i,k);
12040: fprintf(ficlog,"%d%d ",i,k);
12041: for(j=1; j <=ncovmodel; j++){
12042: 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]));
12043: 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]));
12044: jk++;
12045: }
12046: printf("\n");
12047: fprintf(ficlog,"\n");
12048: }
12049: }
1.193 brouard 12050: }
1.203 brouard 12051: } /* end of hesscov and Wald tests */
1.225 brouard 12052:
1.203 brouard 12053: /* */
1.126 brouard 12054: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12055: printf("# Scales (for hessian or gradient estimation)\n");
12056: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12057: for(i=1,jk=1; i <=nlstate; i++){
12058: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12059: if (j!=i) {
12060: fprintf(ficres,"%1d%1d",i,j);
12061: printf("%1d%1d",i,j);
12062: fprintf(ficlog,"%1d%1d",i,j);
12063: for(k=1; k<=ncovmodel;k++){
12064: printf(" %.5e",delti[jk]);
12065: fprintf(ficlog," %.5e",delti[jk]);
12066: fprintf(ficres," %.5e",delti[jk]);
12067: jk++;
12068: }
12069: printf("\n");
12070: fprintf(ficlog,"\n");
12071: fprintf(ficres,"\n");
12072: }
1.126 brouard 12073: }
12074: }
12075:
12076: 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 12077: if(mle >= 1) /* To big for the screen */
1.126 brouard 12078: 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");
12079: 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");
12080: /* # 121 Var(a12)\n\ */
12081: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12082: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12083: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12084: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12085: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12086: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12087: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12088:
12089:
12090: /* Just to have a covariance matrix which will be more understandable
12091: even is we still don't want to manage dictionary of variables
12092: */
12093: for(itimes=1;itimes<=2;itimes++){
12094: jj=0;
12095: for(i=1; i <=nlstate; i++){
1.225 brouard 12096: for(j=1; j <=nlstate+ndeath; j++){
12097: if(j==i) continue;
12098: for(k=1; k<=ncovmodel;k++){
12099: jj++;
12100: ca[0]= k+'a'-1;ca[1]='\0';
12101: if(itimes==1){
12102: if(mle>=1)
12103: printf("#%1d%1d%d",i,j,k);
12104: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12105: fprintf(ficres,"#%1d%1d%d",i,j,k);
12106: }else{
12107: if(mle>=1)
12108: printf("%1d%1d%d",i,j,k);
12109: fprintf(ficlog,"%1d%1d%d",i,j,k);
12110: fprintf(ficres,"%1d%1d%d",i,j,k);
12111: }
12112: ll=0;
12113: for(li=1;li <=nlstate; li++){
12114: for(lj=1;lj <=nlstate+ndeath; lj++){
12115: if(lj==li) continue;
12116: for(lk=1;lk<=ncovmodel;lk++){
12117: ll++;
12118: if(ll<=jj){
12119: cb[0]= lk +'a'-1;cb[1]='\0';
12120: if(ll<jj){
12121: if(itimes==1){
12122: if(mle>=1)
12123: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12124: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12125: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12126: }else{
12127: if(mle>=1)
12128: printf(" %.5e",matcov[jj][ll]);
12129: fprintf(ficlog," %.5e",matcov[jj][ll]);
12130: fprintf(ficres," %.5e",matcov[jj][ll]);
12131: }
12132: }else{
12133: if(itimes==1){
12134: if(mle>=1)
12135: printf(" Var(%s%1d%1d)",ca,i,j);
12136: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12137: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12138: }else{
12139: if(mle>=1)
12140: printf(" %.7e",matcov[jj][ll]);
12141: fprintf(ficlog," %.7e",matcov[jj][ll]);
12142: fprintf(ficres," %.7e",matcov[jj][ll]);
12143: }
12144: }
12145: }
12146: } /* end lk */
12147: } /* end lj */
12148: } /* end li */
12149: if(mle>=1)
12150: printf("\n");
12151: fprintf(ficlog,"\n");
12152: fprintf(ficres,"\n");
12153: numlinepar++;
12154: } /* end k*/
12155: } /*end j */
1.126 brouard 12156: } /* end i */
12157: } /* end itimes */
12158:
12159: fflush(ficlog);
12160: fflush(ficres);
1.225 brouard 12161: while(fgets(line, MAXLINE, ficpar)) {
12162: /* If line starts with a # it is a comment */
12163: if (line[0] == '#') {
12164: numlinepar++;
12165: fputs(line,stdout);
12166: fputs(line,ficparo);
12167: fputs(line,ficlog);
12168: continue;
12169: }else
12170: break;
12171: }
12172:
1.209 brouard 12173: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12174: /* ungetc(c,ficpar); */
12175: /* fgets(line, MAXLINE, ficpar); */
12176: /* fputs(line,stdout); */
12177: /* fputs(line,ficparo); */
12178: /* } */
12179: /* ungetc(c,ficpar); */
1.126 brouard 12180:
12181: estepm=0;
1.209 brouard 12182: 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 12183:
12184: if (num_filled != 6) {
12185: 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);
12186: 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);
12187: goto end;
12188: }
12189: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12190: }
12191: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12192: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12193:
1.209 brouard 12194: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12195: if (estepm==0 || estepm < stepm) estepm=stepm;
12196: if (fage <= 2) {
12197: bage = ageminpar;
12198: fage = agemaxpar;
12199: }
12200:
12201: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12202: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12203: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12204:
1.186 brouard 12205: /* Other stuffs, more or less useful */
1.254 brouard 12206: while(fgets(line, MAXLINE, ficpar)) {
12207: /* If line starts with a # it is a comment */
12208: if (line[0] == '#') {
12209: numlinepar++;
12210: fputs(line,stdout);
12211: fputs(line,ficparo);
12212: fputs(line,ficlog);
12213: continue;
12214: }else
12215: break;
12216: }
12217:
12218: 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){
12219:
12220: if (num_filled != 7) {
12221: 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);
12222: 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);
12223: goto end;
12224: }
12225: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12226: 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);
12227: 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);
12228: 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 12229: }
1.254 brouard 12230:
12231: while(fgets(line, MAXLINE, ficpar)) {
12232: /* If line starts with a # it is a comment */
12233: if (line[0] == '#') {
12234: numlinepar++;
12235: fputs(line,stdout);
12236: fputs(line,ficparo);
12237: fputs(line,ficlog);
12238: continue;
12239: }else
12240: break;
1.126 brouard 12241: }
12242:
12243:
12244: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12245: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12246:
1.254 brouard 12247: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12248: if (num_filled != 1) {
12249: 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);
12250: 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);
12251: goto end;
12252: }
12253: printf("pop_based=%d\n",popbased);
12254: fprintf(ficlog,"pop_based=%d\n",popbased);
12255: fprintf(ficparo,"pop_based=%d\n",popbased);
12256: fprintf(ficres,"pop_based=%d\n",popbased);
12257: }
12258:
1.258 brouard 12259: /* Results */
12260: nresult=0;
12261: do{
12262: if(!fgets(line, MAXLINE, ficpar)){
12263: endishere=1;
12264: parameterline=14;
12265: }else if (line[0] == '#') {
12266: /* If line starts with a # it is a comment */
1.254 brouard 12267: numlinepar++;
12268: fputs(line,stdout);
12269: fputs(line,ficparo);
12270: fputs(line,ficlog);
12271: continue;
1.258 brouard 12272: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12273: parameterline=11;
12274: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12275: parameterline=12;
12276: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12277: parameterline=13;
12278: else{
12279: parameterline=14;
1.254 brouard 12280: }
1.258 brouard 12281: switch (parameterline){
12282: case 11:
12283: 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){
12284: if (num_filled != 8) {
12285: 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);
12286: 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);
12287: goto end;
12288: }
12289: 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);
12290: 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);
12291: 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);
12292: 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);
12293: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12294: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12295: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
12296:
1.258 brouard 12297: }
1.254 brouard 12298: break;
1.258 brouard 12299: case 12:
12300: /*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);*/
12301: 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){
12302: if (num_filled != 8) {
1.262 brouard 12303: 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);
12304: 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 12305: goto end;
12306: }
12307: 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);
12308: 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);
12309: 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);
12310: 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);
12311: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12312: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12313: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.258 brouard 12314: }
1.230 brouard 12315: break;
1.258 brouard 12316: case 13:
12317: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12318: if (num_filled == 0){
12319: resultline[0]='\0';
12320: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12321: 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);
12322: break;
12323: } else if (num_filled != 1){
12324: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12325: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12326: }
12327: nresult++; /* Sum of resultlines */
12328: printf("Result %d: result=%s\n",nresult, resultline);
12329: if(nresult > MAXRESULTLINES){
12330: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12331: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12332: goto end;
12333: }
12334: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12335: fprintf(ficparo,"result: %s\n",resultline);
12336: fprintf(ficres,"result: %s\n",resultline);
12337: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12338: break;
1.258 brouard 12339: case 14:
1.259 brouard 12340: if(ncovmodel >2 && nresult==0 ){
12341: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12342: goto end;
12343: }
1.259 brouard 12344: break;
1.258 brouard 12345: default:
12346: nresult=1;
12347: decoderesult(".",nresult ); /* No covariate */
12348: }
12349: } /* End switch parameterline */
12350: }while(endishere==0); /* End do */
1.126 brouard 12351:
1.230 brouard 12352: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12353: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12354:
12355: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12356: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12357: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12358: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12359: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12360: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12361: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12362: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12363: }else{
1.270 brouard 12364: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12365: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12366: }
12367: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12368: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.273 brouard 12369: jprev1,mprev1,anprev1,dateprev1, dateproj1, dateback1,jprev2,mprev2,anprev2,dateprev2,dateproj2, dateback2);
1.220 brouard 12370:
1.225 brouard 12371: /*------------ free_vector -------------*/
12372: /* chdir(path); */
1.220 brouard 12373:
1.215 brouard 12374: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12375: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12376: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12377: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12378: free_lvector(num,firstobs,lastobs);
12379: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12380: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12381: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12382: fclose(ficparo);
12383: fclose(ficres);
1.220 brouard 12384:
12385:
1.186 brouard 12386: /* Other results (useful)*/
1.220 brouard 12387:
12388:
1.126 brouard 12389: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12390: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12391: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12392: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12393: fclose(ficrespl);
12394:
12395: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12396: /*#include "hpijx.h"*/
12397: hPijx(p, bage, fage);
1.145 brouard 12398: fclose(ficrespij);
1.227 brouard 12399:
1.220 brouard 12400: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12401: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12402: k=1;
1.126 brouard 12403: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12404:
1.269 brouard 12405: /* Prevalence for each covariate combination in probs[age][status][cov] */
12406: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12407: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12408: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12409: for(k=1;k<=ncovcombmax;k++)
12410: probs[i][j][k]=0.;
1.269 brouard 12411: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12412: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12413: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12414: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12415: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12416: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12417: for(k=1;k<=ncovcombmax;k++)
12418: mobaverages[i][j][k]=0.;
1.219 brouard 12419: mobaverage=mobaverages;
12420: if (mobilav!=0) {
1.235 brouard 12421: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12422: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12423: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12424: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12425: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12426: }
1.269 brouard 12427: } else if (mobilavproj !=0) {
1.235 brouard 12428: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12429: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12430: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12431: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12432: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12433: }
1.269 brouard 12434: }else{
12435: printf("Internal error moving average\n");
12436: fflush(stdout);
12437: exit(1);
1.219 brouard 12438: }
12439: }/* end if moving average */
1.227 brouard 12440:
1.126 brouard 12441: /*---------- Forecasting ------------------*/
12442: if(prevfcast==1){
12443: /* if(stepm ==1){*/
1.269 brouard 12444: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12445: }
1.269 brouard 12446:
12447: /* Backcasting */
1.217 brouard 12448: if(backcast==1){
1.219 brouard 12449: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12450: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12451: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12452:
12453: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12454:
12455: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12456:
1.219 brouard 12457: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12458: fclose(ficresplb);
12459:
1.222 brouard 12460: hBijx(p, bage, fage, mobaverage);
12461: fclose(ficrespijb);
1.219 brouard 12462:
1.269 brouard 12463: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12464: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12465: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12466:
12467:
1.269 brouard 12468: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12469: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12470: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12471: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12472: } /* end Backcasting */
1.268 brouard 12473:
1.186 brouard 12474:
12475: /* ------ Other prevalence ratios------------ */
1.126 brouard 12476:
1.215 brouard 12477: free_ivector(wav,1,imx);
12478: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12479: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12480: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12481:
12482:
1.127 brouard 12483: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12484:
1.201 brouard 12485: strcpy(filerese,"E_");
12486: strcat(filerese,fileresu);
1.126 brouard 12487: if((ficreseij=fopen(filerese,"w"))==NULL) {
12488: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12489: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12490: }
1.208 brouard 12491: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12492: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12493:
12494: pstamp(ficreseij);
1.219 brouard 12495:
1.235 brouard 12496: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12497: if (cptcovn < 1){i1=1;}
12498:
12499: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12500: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12501: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12502: continue;
1.219 brouard 12503: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12504: printf("\n#****** ");
1.225 brouard 12505: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12506: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12507: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12508: }
12509: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12510: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12511: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12512: }
12513: fprintf(ficreseij,"******\n");
1.235 brouard 12514: printf("******\n");
1.219 brouard 12515:
12516: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12517: oldm=oldms;savm=savms;
1.235 brouard 12518: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12519:
1.219 brouard 12520: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12521: }
12522: fclose(ficreseij);
1.208 brouard 12523: printf("done evsij\n");fflush(stdout);
12524: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12525:
1.218 brouard 12526:
1.227 brouard 12527: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12528:
1.201 brouard 12529: strcpy(filerest,"T_");
12530: strcat(filerest,fileresu);
1.127 brouard 12531: if((ficrest=fopen(filerest,"w"))==NULL) {
12532: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12533: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12534: }
1.208 brouard 12535: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12536: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12537: strcpy(fileresstde,"STDE_");
12538: strcat(fileresstde,fileresu);
1.126 brouard 12539: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12540: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12541: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12542: }
1.227 brouard 12543: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12544: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12545:
1.201 brouard 12546: strcpy(filerescve,"CVE_");
12547: strcat(filerescve,fileresu);
1.126 brouard 12548: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12549: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12550: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12551: }
1.227 brouard 12552: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12553: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12554:
1.201 brouard 12555: strcpy(fileresv,"V_");
12556: strcat(fileresv,fileresu);
1.126 brouard 12557: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12558: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12559: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12560: }
1.227 brouard 12561: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12562: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12563:
1.235 brouard 12564: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12565: if (cptcovn < 1){i1=1;}
12566:
12567: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12568: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12569: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12570: continue;
1.242 brouard 12571: printf("\n#****** Result for:");
12572: fprintf(ficrest,"\n#****** Result for:");
12573: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12574: for(j=1;j<=cptcoveff;j++){
12575: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12576: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12577: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12578: }
1.235 brouard 12579: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12580: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12581: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12582: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12583: }
1.208 brouard 12584: fprintf(ficrest,"******\n");
1.227 brouard 12585: fprintf(ficlog,"******\n");
12586: printf("******\n");
1.208 brouard 12587:
12588: fprintf(ficresstdeij,"\n#****** ");
12589: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12590: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12591: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12592: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12593: }
1.235 brouard 12594: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12595: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12596: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12597: }
1.208 brouard 12598: fprintf(ficresstdeij,"******\n");
12599: fprintf(ficrescveij,"******\n");
12600:
12601: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12602: /* pstamp(ficresvij); */
1.225 brouard 12603: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12604: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12605: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12606: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12607: }
1.208 brouard 12608: fprintf(ficresvij,"******\n");
12609:
12610: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12611: oldm=oldms;savm=savms;
1.235 brouard 12612: printf(" cvevsij ");
12613: fprintf(ficlog, " cvevsij ");
12614: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12615: printf(" end cvevsij \n ");
12616: fprintf(ficlog, " end cvevsij \n ");
12617:
12618: /*
12619: */
12620: /* goto endfree; */
12621:
12622: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12623: pstamp(ficrest);
12624:
1.269 brouard 12625: epj=vector(1,nlstate+1);
1.208 brouard 12626: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12627: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12628: cptcod= 0; /* To be deleted */
12629: printf("varevsij vpopbased=%d \n",vpopbased);
12630: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12631: 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 12632: 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 ");
12633: if(vpopbased==1)
12634: 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);
12635: else
1.288 brouard 12636: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12637: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12638: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12639: fprintf(ficrest,"\n");
12640: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 12641: printf("Computing age specific forward period (stable) prevalences in each health state \n");
12642: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12643: for(age=bage; age <=fage ;age++){
1.235 brouard 12644: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12645: if (vpopbased==1) {
12646: if(mobilav ==0){
12647: for(i=1; i<=nlstate;i++)
12648: prlim[i][i]=probs[(int)age][i][k];
12649: }else{ /* mobilav */
12650: for(i=1; i<=nlstate;i++)
12651: prlim[i][i]=mobaverage[(int)age][i][k];
12652: }
12653: }
1.219 brouard 12654:
1.227 brouard 12655: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12656: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12657: /* printf(" age %4.0f ",age); */
12658: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12659: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12660: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12661: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12662: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12663: }
12664: epj[nlstate+1] +=epj[j];
12665: }
12666: /* printf(" age %4.0f \n",age); */
1.219 brouard 12667:
1.227 brouard 12668: for(i=1, vepp=0.;i <=nlstate;i++)
12669: for(j=1;j <=nlstate;j++)
12670: vepp += vareij[i][j][(int)age];
12671: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12672: for(j=1;j <=nlstate;j++){
12673: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12674: }
12675: fprintf(ficrest,"\n");
12676: }
1.208 brouard 12677: } /* End vpopbased */
1.269 brouard 12678: free_vector(epj,1,nlstate+1);
1.208 brouard 12679: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12680: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12681: printf("done selection\n");fflush(stdout);
12682: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12683:
1.235 brouard 12684: } /* End k selection */
1.227 brouard 12685:
12686: printf("done State-specific expectancies\n");fflush(stdout);
12687: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12688:
1.288 brouard 12689: /* variance-covariance of forward period prevalence*/
1.269 brouard 12690: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12691:
1.227 brouard 12692:
1.290 brouard 12693: free_vector(weight,firstobs,lastobs);
1.227 brouard 12694: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 12695: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
12696: free_matrix(anint,1,maxwav,firstobs,lastobs);
12697: free_matrix(mint,1,maxwav,firstobs,lastobs);
12698: free_ivector(cod,firstobs,lastobs);
1.227 brouard 12699: free_ivector(tab,1,NCOVMAX);
12700: fclose(ficresstdeij);
12701: fclose(ficrescveij);
12702: fclose(ficresvij);
12703: fclose(ficrest);
12704: fclose(ficpar);
12705:
12706:
1.126 brouard 12707: /*---------- End : free ----------------*/
1.219 brouard 12708: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12709: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12710: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12711: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12712: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12713: } /* mle==-3 arrives here for freeing */
1.227 brouard 12714: /* endfree:*/
12715: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12716: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12717: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 12718: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
12719: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
12720: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
12721: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 12722: free_matrix(matcov,1,npar,1,npar);
12723: free_matrix(hess,1,npar,1,npar);
12724: /*free_vector(delti,1,npar);*/
12725: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12726: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12727: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12728: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12729:
12730: free_ivector(ncodemax,1,NCOVMAX);
12731: free_ivector(ncodemaxwundef,1,NCOVMAX);
12732: free_ivector(Dummy,-1,NCOVMAX);
12733: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12734: free_ivector(DummyV,1,NCOVMAX);
12735: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12736: free_ivector(Typevar,-1,NCOVMAX);
12737: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12738: free_ivector(TvarsQ,1,NCOVMAX);
12739: free_ivector(TvarsQind,1,NCOVMAX);
12740: free_ivector(TvarsD,1,NCOVMAX);
12741: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12742: free_ivector(TvarFD,1,NCOVMAX);
12743: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12744: free_ivector(TvarF,1,NCOVMAX);
12745: free_ivector(TvarFind,1,NCOVMAX);
12746: free_ivector(TvarV,1,NCOVMAX);
12747: free_ivector(TvarVind,1,NCOVMAX);
12748: free_ivector(TvarA,1,NCOVMAX);
12749: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12750: free_ivector(TvarFQ,1,NCOVMAX);
12751: free_ivector(TvarFQind,1,NCOVMAX);
12752: free_ivector(TvarVD,1,NCOVMAX);
12753: free_ivector(TvarVDind,1,NCOVMAX);
12754: free_ivector(TvarVQ,1,NCOVMAX);
12755: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12756: free_ivector(Tvarsel,1,NCOVMAX);
12757: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12758: free_ivector(Tposprod,1,NCOVMAX);
12759: free_ivector(Tprod,1,NCOVMAX);
12760: free_ivector(Tvaraff,1,NCOVMAX);
12761: free_ivector(invalidvarcomb,1,ncovcombmax);
12762: free_ivector(Tage,1,NCOVMAX);
12763: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12764: free_ivector(TmodelInvind,1,NCOVMAX);
12765: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12766:
12767: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12768: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12769: fflush(fichtm);
12770: fflush(ficgp);
12771:
1.227 brouard 12772:
1.126 brouard 12773: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12774: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12775: 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 12776: }else{
12777: printf("End of Imach\n");
12778: fprintf(ficlog,"End of Imach\n");
12779: }
12780: printf("See log file on %s\n",filelog);
12781: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12782: /*(void) gettimeofday(&end_time,&tzp);*/
12783: rend_time = time(NULL);
12784: end_time = *localtime(&rend_time);
12785: /* tml = *localtime(&end_time.tm_sec); */
12786: strcpy(strtend,asctime(&end_time));
1.126 brouard 12787: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12788: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12789: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12790:
1.157 brouard 12791: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12792: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12793: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12794: /* printf("Total time was %d uSec.\n", total_usecs);*/
12795: /* if(fileappend(fichtm,optionfilehtm)){ */
12796: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12797: fclose(fichtm);
12798: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12799: fclose(fichtmcov);
12800: fclose(ficgp);
12801: fclose(ficlog);
12802: /*------ End -----------*/
1.227 brouard 12803:
1.281 brouard 12804:
12805: /* Executes gnuplot */
1.227 brouard 12806:
12807: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12808: #ifdef WIN32
1.227 brouard 12809: if (_chdir(pathcd) != 0)
12810: printf("Can't move to directory %s!\n",path);
12811: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12812: #else
1.227 brouard 12813: if(chdir(pathcd) != 0)
12814: printf("Can't move to directory %s!\n", path);
12815: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12816: #endif
1.126 brouard 12817: printf("Current directory %s!\n",pathcd);
12818: /*strcat(plotcmd,CHARSEPARATOR);*/
12819: sprintf(plotcmd,"gnuplot");
1.157 brouard 12820: #ifdef _WIN32
1.126 brouard 12821: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12822: #endif
12823: if(!stat(plotcmd,&info)){
1.158 brouard 12824: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12825: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12826: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12827: }else
12828: strcpy(pplotcmd,plotcmd);
1.157 brouard 12829: #ifdef __unix
1.126 brouard 12830: strcpy(plotcmd,GNUPLOTPROGRAM);
12831: if(!stat(plotcmd,&info)){
1.158 brouard 12832: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12833: }else
12834: strcpy(pplotcmd,plotcmd);
12835: #endif
12836: }else
12837: strcpy(pplotcmd,plotcmd);
12838:
12839: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12840: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 12841: strcpy(pplotcmd,plotcmd);
1.227 brouard 12842:
1.126 brouard 12843: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 12844: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12845: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12846: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 12847: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 12848: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 12849: strcpy(plotcmd,pplotcmd);
12850: }
1.126 brouard 12851: }
1.158 brouard 12852: printf(" Successful, please wait...");
1.126 brouard 12853: while (z[0] != 'q') {
12854: /* chdir(path); */
1.154 brouard 12855: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12856: scanf("%s",z);
12857: /* if (z[0] == 'c') system("./imach"); */
12858: if (z[0] == 'e') {
1.158 brouard 12859: #ifdef __APPLE__
1.152 brouard 12860: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12861: #elif __linux
12862: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12863: #else
1.152 brouard 12864: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12865: #endif
12866: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12867: system(pplotcmd);
1.126 brouard 12868: }
12869: else if (z[0] == 'g') system(plotcmd);
12870: else if (z[0] == 'q') exit(0);
12871: }
1.227 brouard 12872: end:
1.126 brouard 12873: while (z[0] != 'q') {
1.195 brouard 12874: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12875: scanf("%s",z);
12876: }
1.283 brouard 12877: printf("End\n");
1.282 brouard 12878: exit(0);
1.126 brouard 12879: }
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