Annotation of imach/src/imach.c, revision 1.285
1.285 ! brouard 1: /* $Id: imach.c,v 1.284 2018/04/20 05:22:13 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.285 ! brouard 4: Revision 1.284 2018/04/20 05:22:13 brouard
! 5: Summary: Computing mean and stdeviation of fixed quantitative variables
! 6:
1.284 brouard 7: Revision 1.283 2018/04/19 14:49:16 brouard
8: Summary: Some minor bugs fixed
9:
1.283 brouard 10: Revision 1.282 2018/02/27 22:50:02 brouard
11: *** empty log message ***
12:
1.282 brouard 13: Revision 1.281 2018/02/27 19:25:23 brouard
14: Summary: Adding second argument for quitting
15:
1.281 brouard 16: Revision 1.280 2018/02/21 07:58:13 brouard
17: Summary: 0.99r15
18:
19: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
20:
1.280 brouard 21: Revision 1.279 2017/07/20 13:35:01 brouard
22: Summary: temporary working
23:
1.279 brouard 24: Revision 1.278 2017/07/19 14:09:02 brouard
25: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
26:
1.278 brouard 27: Revision 1.277 2017/07/17 08:53:49 brouard
28: Summary: BOM files can be read now
29:
1.277 brouard 30: Revision 1.276 2017/06/30 15:48:31 brouard
31: Summary: Graphs improvements
32:
1.276 brouard 33: Revision 1.275 2017/06/30 13:39:33 brouard
34: Summary: Saito's color
35:
1.275 brouard 36: Revision 1.274 2017/06/29 09:47:08 brouard
37: Summary: Version 0.99r14
38:
1.274 brouard 39: Revision 1.273 2017/06/27 11:06:02 brouard
40: Summary: More documentation on projections
41:
1.273 brouard 42: Revision 1.272 2017/06/27 10:22:40 brouard
43: Summary: Color of backprojection changed from 6 to 5(yellow)
44:
1.272 brouard 45: Revision 1.271 2017/06/27 10:17:50 brouard
46: Summary: Some bug with rint
47:
1.271 brouard 48: Revision 1.270 2017/05/24 05:45:29 brouard
49: *** empty log message ***
50:
1.270 brouard 51: Revision 1.269 2017/05/23 08:39:25 brouard
52: Summary: Code into subroutine, cleanings
53:
1.269 brouard 54: Revision 1.268 2017/05/18 20:09:32 brouard
55: Summary: backprojection and confidence intervals of backprevalence
56:
1.268 brouard 57: Revision 1.267 2017/05/13 10:25:05 brouard
58: Summary: temporary save for backprojection
59:
1.267 brouard 60: Revision 1.266 2017/05/13 07:26:12 brouard
61: Summary: Version 0.99r13 (improvements and bugs fixed)
62:
1.266 brouard 63: Revision 1.265 2017/04/26 16:22:11 brouard
64: Summary: imach 0.99r13 Some bugs fixed
65:
1.265 brouard 66: Revision 1.264 2017/04/26 06:01:29 brouard
67: Summary: Labels in graphs
68:
1.264 brouard 69: Revision 1.263 2017/04/24 15:23:15 brouard
70: Summary: to save
71:
1.263 brouard 72: Revision 1.262 2017/04/18 16:48:12 brouard
73: *** empty log message ***
74:
1.262 brouard 75: Revision 1.261 2017/04/05 10:14:09 brouard
76: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
77:
1.261 brouard 78: Revision 1.260 2017/04/04 17:46:59 brouard
79: Summary: Gnuplot indexations fixed (humm)
80:
1.260 brouard 81: Revision 1.259 2017/04/04 13:01:16 brouard
82: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
83:
1.259 brouard 84: Revision 1.258 2017/04/03 10:17:47 brouard
85: Summary: Version 0.99r12
86:
87: Some cleanings, conformed with updated documentation.
88:
1.258 brouard 89: Revision 1.257 2017/03/29 16:53:30 brouard
90: Summary: Temp
91:
1.257 brouard 92: Revision 1.256 2017/03/27 05:50:23 brouard
93: Summary: Temporary
94:
1.256 brouard 95: Revision 1.255 2017/03/08 16:02:28 brouard
96: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
97:
1.255 brouard 98: Revision 1.254 2017/03/08 07:13:00 brouard
99: Summary: Fixing data parameter line
100:
1.254 brouard 101: Revision 1.253 2016/12/15 11:59:41 brouard
102: Summary: 0.99 in progress
103:
1.253 brouard 104: Revision 1.252 2016/09/15 21:15:37 brouard
105: *** empty log message ***
106:
1.252 brouard 107: Revision 1.251 2016/09/15 15:01:13 brouard
108: Summary: not working
109:
1.251 brouard 110: Revision 1.250 2016/09/08 16:07:27 brouard
111: Summary: continue
112:
1.250 brouard 113: Revision 1.249 2016/09/07 17:14:18 brouard
114: Summary: Starting values from frequencies
115:
1.249 brouard 116: Revision 1.248 2016/09/07 14:10:18 brouard
117: *** empty log message ***
118:
1.248 brouard 119: Revision 1.247 2016/09/02 11:11:21 brouard
120: *** empty log message ***
121:
1.247 brouard 122: Revision 1.246 2016/09/02 08:49:22 brouard
123: *** empty log message ***
124:
1.246 brouard 125: Revision 1.245 2016/09/02 07:25:01 brouard
126: *** empty log message ***
127:
1.245 brouard 128: Revision 1.244 2016/09/02 07:17:34 brouard
129: *** empty log message ***
130:
1.244 brouard 131: Revision 1.243 2016/09/02 06:45:35 brouard
132: *** empty log message ***
133:
1.243 brouard 134: Revision 1.242 2016/08/30 15:01:20 brouard
135: Summary: Fixing a lots
136:
1.242 brouard 137: Revision 1.241 2016/08/29 17:17:25 brouard
138: Summary: gnuplot problem in Back projection to fix
139:
1.241 brouard 140: Revision 1.240 2016/08/29 07:53:18 brouard
141: Summary: Better
142:
1.240 brouard 143: Revision 1.239 2016/08/26 15:51:03 brouard
144: Summary: Improvement in Powell output in order to copy and paste
145:
146: Author:
147:
1.239 brouard 148: Revision 1.238 2016/08/26 14:23:35 brouard
149: Summary: Starting tests of 0.99
150:
1.238 brouard 151: Revision 1.237 2016/08/26 09:20:19 brouard
152: Summary: to valgrind
153:
1.237 brouard 154: Revision 1.236 2016/08/25 10:50:18 brouard
155: *** empty log message ***
156:
1.236 brouard 157: Revision 1.235 2016/08/25 06:59:23 brouard
158: *** empty log message ***
159:
1.235 brouard 160: Revision 1.234 2016/08/23 16:51:20 brouard
161: *** empty log message ***
162:
1.234 brouard 163: Revision 1.233 2016/08/23 07:40:50 brouard
164: Summary: not working
165:
1.233 brouard 166: Revision 1.232 2016/08/22 14:20:21 brouard
167: Summary: not working
168:
1.232 brouard 169: Revision 1.231 2016/08/22 07:17:15 brouard
170: Summary: not working
171:
1.231 brouard 172: Revision 1.230 2016/08/22 06:55:53 brouard
173: Summary: Not working
174:
1.230 brouard 175: Revision 1.229 2016/07/23 09:45:53 brouard
176: Summary: Completing for func too
177:
1.229 brouard 178: Revision 1.228 2016/07/22 17:45:30 brouard
179: Summary: Fixing some arrays, still debugging
180:
1.227 brouard 181: Revision 1.226 2016/07/12 18:42:34 brouard
182: Summary: temp
183:
1.226 brouard 184: Revision 1.225 2016/07/12 08:40:03 brouard
185: Summary: saving but not running
186:
1.225 brouard 187: Revision 1.224 2016/07/01 13:16:01 brouard
188: Summary: Fixes
189:
1.224 brouard 190: Revision 1.223 2016/02/19 09:23:35 brouard
191: Summary: temporary
192:
1.223 brouard 193: Revision 1.222 2016/02/17 08:14:50 brouard
194: Summary: Probably last 0.98 stable version 0.98r6
195:
1.222 brouard 196: Revision 1.221 2016/02/15 23:35:36 brouard
197: Summary: minor bug
198:
1.220 brouard 199: Revision 1.219 2016/02/15 00:48:12 brouard
200: *** empty log message ***
201:
1.219 brouard 202: Revision 1.218 2016/02/12 11:29:23 brouard
203: Summary: 0.99 Back projections
204:
1.218 brouard 205: Revision 1.217 2015/12/23 17:18:31 brouard
206: Summary: Experimental backcast
207:
1.217 brouard 208: Revision 1.216 2015/12/18 17:32:11 brouard
209: Summary: 0.98r4 Warning and status=-2
210:
211: Version 0.98r4 is now:
212: - displaying an error when status is -1, date of interview unknown and date of death known;
213: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
214: Older changes concerning s=-2, dating from 2005 have been supersed.
215:
1.216 brouard 216: Revision 1.215 2015/12/16 08:52:24 brouard
217: Summary: 0.98r4 working
218:
1.215 brouard 219: Revision 1.214 2015/12/16 06:57:54 brouard
220: Summary: temporary not working
221:
1.214 brouard 222: Revision 1.213 2015/12/11 18:22:17 brouard
223: Summary: 0.98r4
224:
1.213 brouard 225: Revision 1.212 2015/11/21 12:47:24 brouard
226: Summary: minor typo
227:
1.212 brouard 228: Revision 1.211 2015/11/21 12:41:11 brouard
229: Summary: 0.98r3 with some graph of projected cross-sectional
230:
231: Author: Nicolas Brouard
232:
1.211 brouard 233: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 234: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 235: Summary: Adding ftolpl parameter
236: Author: N Brouard
237:
238: We had difficulties to get smoothed confidence intervals. It was due
239: to the period prevalence which wasn't computed accurately. The inner
240: parameter ftolpl is now an outer parameter of the .imach parameter
241: file after estepm. If ftolpl is small 1.e-4 and estepm too,
242: computation are long.
243:
1.209 brouard 244: Revision 1.208 2015/11/17 14:31:57 brouard
245: Summary: temporary
246:
1.208 brouard 247: Revision 1.207 2015/10/27 17:36:57 brouard
248: *** empty log message ***
249:
1.207 brouard 250: Revision 1.206 2015/10/24 07:14:11 brouard
251: *** empty log message ***
252:
1.206 brouard 253: Revision 1.205 2015/10/23 15:50:53 brouard
254: Summary: 0.98r3 some clarification for graphs on likelihood contributions
255:
1.205 brouard 256: Revision 1.204 2015/10/01 16:20:26 brouard
257: Summary: Some new graphs of contribution to likelihood
258:
1.204 brouard 259: Revision 1.203 2015/09/30 17:45:14 brouard
260: Summary: looking at better estimation of the hessian
261:
262: Also a better criteria for convergence to the period prevalence And
263: therefore adding the number of years needed to converge. (The
264: prevalence in any alive state shold sum to one
265:
1.203 brouard 266: Revision 1.202 2015/09/22 19:45:16 brouard
267: Summary: Adding some overall graph on contribution to likelihood. Might change
268:
1.202 brouard 269: Revision 1.201 2015/09/15 17:34:58 brouard
270: Summary: 0.98r0
271:
272: - Some new graphs like suvival functions
273: - Some bugs fixed like model=1+age+V2.
274:
1.201 brouard 275: Revision 1.200 2015/09/09 16:53:55 brouard
276: Summary: Big bug thanks to Flavia
277:
278: Even model=1+age+V2. did not work anymore
279:
1.200 brouard 280: Revision 1.199 2015/09/07 14:09:23 brouard
281: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
282:
1.199 brouard 283: Revision 1.198 2015/09/03 07:14:39 brouard
284: Summary: 0.98q5 Flavia
285:
1.198 brouard 286: Revision 1.197 2015/09/01 18:24:39 brouard
287: *** empty log message ***
288:
1.197 brouard 289: Revision 1.196 2015/08/18 23:17:52 brouard
290: Summary: 0.98q5
291:
1.196 brouard 292: Revision 1.195 2015/08/18 16:28:39 brouard
293: Summary: Adding a hack for testing purpose
294:
295: After reading the title, ftol and model lines, if the comment line has
296: a q, starting with #q, the answer at the end of the run is quit. It
297: permits to run test files in batch with ctest. The former workaround was
298: $ echo q | imach foo.imach
299:
1.195 brouard 300: Revision 1.194 2015/08/18 13:32:00 brouard
301: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
302:
1.194 brouard 303: Revision 1.193 2015/08/04 07:17:42 brouard
304: Summary: 0.98q4
305:
1.193 brouard 306: Revision 1.192 2015/07/16 16:49:02 brouard
307: Summary: Fixing some outputs
308:
1.192 brouard 309: Revision 1.191 2015/07/14 10:00:33 brouard
310: Summary: Some fixes
311:
1.191 brouard 312: Revision 1.190 2015/05/05 08:51:13 brouard
313: Summary: Adding digits in output parameters (7 digits instead of 6)
314:
315: Fix 1+age+.
316:
1.190 brouard 317: Revision 1.189 2015/04/30 14:45:16 brouard
318: Summary: 0.98q2
319:
1.189 brouard 320: Revision 1.188 2015/04/30 08:27:53 brouard
321: *** empty log message ***
322:
1.188 brouard 323: Revision 1.187 2015/04/29 09:11:15 brouard
324: *** empty log message ***
325:
1.187 brouard 326: Revision 1.186 2015/04/23 12:01:52 brouard
327: Summary: V1*age is working now, version 0.98q1
328:
329: Some codes had been disabled in order to simplify and Vn*age was
330: working in the optimization phase, ie, giving correct MLE parameters,
331: but, as usual, outputs were not correct and program core dumped.
332:
1.186 brouard 333: Revision 1.185 2015/03/11 13:26:42 brouard
334: Summary: Inclusion of compile and links command line for Intel Compiler
335:
1.185 brouard 336: Revision 1.184 2015/03/11 11:52:39 brouard
337: Summary: Back from Windows 8. Intel Compiler
338:
1.184 brouard 339: Revision 1.183 2015/03/10 20:34:32 brouard
340: Summary: 0.98q0, trying with directest, mnbrak fixed
341:
342: We use directest instead of original Powell test; probably no
343: incidence on the results, but better justifications;
344: We fixed Numerical Recipes mnbrak routine which was wrong and gave
345: wrong results.
346:
1.183 brouard 347: Revision 1.182 2015/02/12 08:19:57 brouard
348: Summary: Trying to keep directest which seems simpler and more general
349: Author: Nicolas Brouard
350:
1.182 brouard 351: Revision 1.181 2015/02/11 23:22:24 brouard
352: Summary: Comments on Powell added
353:
354: Author:
355:
1.181 brouard 356: Revision 1.180 2015/02/11 17:33:45 brouard
357: Summary: Finishing move from main to function (hpijx and prevalence_limit)
358:
1.180 brouard 359: Revision 1.179 2015/01/04 09:57:06 brouard
360: Summary: back to OS/X
361:
1.179 brouard 362: Revision 1.178 2015/01/04 09:35:48 brouard
363: *** empty log message ***
364:
1.178 brouard 365: Revision 1.177 2015/01/03 18:40:56 brouard
366: Summary: Still testing ilc32 on OSX
367:
1.177 brouard 368: Revision 1.176 2015/01/03 16:45:04 brouard
369: *** empty log message ***
370:
1.176 brouard 371: Revision 1.175 2015/01/03 16:33:42 brouard
372: *** empty log message ***
373:
1.175 brouard 374: Revision 1.174 2015/01/03 16:15:49 brouard
375: Summary: Still in cross-compilation
376:
1.174 brouard 377: Revision 1.173 2015/01/03 12:06:26 brouard
378: Summary: trying to detect cross-compilation
379:
1.173 brouard 380: Revision 1.172 2014/12/27 12:07:47 brouard
381: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
382:
1.172 brouard 383: Revision 1.171 2014/12/23 13:26:59 brouard
384: Summary: Back from Visual C
385:
386: Still problem with utsname.h on Windows
387:
1.171 brouard 388: Revision 1.170 2014/12/23 11:17:12 brouard
389: Summary: Cleaning some \%% back to %%
390:
391: The escape was mandatory for a specific compiler (which one?), but too many warnings.
392:
1.170 brouard 393: Revision 1.169 2014/12/22 23:08:31 brouard
394: Summary: 0.98p
395:
396: Outputs some informations on compiler used, OS etc. Testing on different platforms.
397:
1.169 brouard 398: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 399: Summary: update
1.169 brouard 400:
1.168 brouard 401: Revision 1.167 2014/12/22 13:50:56 brouard
402: Summary: Testing uname and compiler version and if compiled 32 or 64
403:
404: Testing on Linux 64
405:
1.167 brouard 406: Revision 1.166 2014/12/22 11:40:47 brouard
407: *** empty log message ***
408:
1.166 brouard 409: Revision 1.165 2014/12/16 11:20:36 brouard
410: Summary: After compiling on Visual C
411:
412: * imach.c (Module): Merging 1.61 to 1.162
413:
1.165 brouard 414: Revision 1.164 2014/12/16 10:52:11 brouard
415: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
416:
417: * imach.c (Module): Merging 1.61 to 1.162
418:
1.164 brouard 419: Revision 1.163 2014/12/16 10:30:11 brouard
420: * imach.c (Module): Merging 1.61 to 1.162
421:
1.163 brouard 422: Revision 1.162 2014/09/25 11:43:39 brouard
423: Summary: temporary backup 0.99!
424:
1.162 brouard 425: Revision 1.1 2014/09/16 11:06:58 brouard
426: Summary: With some code (wrong) for nlopt
427:
428: Author:
429:
430: Revision 1.161 2014/09/15 20:41:41 brouard
431: Summary: Problem with macro SQR on Intel compiler
432:
1.161 brouard 433: Revision 1.160 2014/09/02 09:24:05 brouard
434: *** empty log message ***
435:
1.160 brouard 436: Revision 1.159 2014/09/01 10:34:10 brouard
437: Summary: WIN32
438: Author: Brouard
439:
1.159 brouard 440: Revision 1.158 2014/08/27 17:11:51 brouard
441: *** empty log message ***
442:
1.158 brouard 443: Revision 1.157 2014/08/27 16:26:55 brouard
444: Summary: Preparing windows Visual studio version
445: Author: Brouard
446:
447: In order to compile on Visual studio, time.h is now correct and time_t
448: and tm struct should be used. difftime should be used but sometimes I
449: just make the differences in raw time format (time(&now).
450: Trying to suppress #ifdef LINUX
451: Add xdg-open for __linux in order to open default browser.
452:
1.157 brouard 453: Revision 1.156 2014/08/25 20:10:10 brouard
454: *** empty log message ***
455:
1.156 brouard 456: Revision 1.155 2014/08/25 18:32:34 brouard
457: Summary: New compile, minor changes
458: Author: Brouard
459:
1.155 brouard 460: Revision 1.154 2014/06/20 17:32:08 brouard
461: Summary: Outputs now all graphs of convergence to period prevalence
462:
1.154 brouard 463: Revision 1.153 2014/06/20 16:45:46 brouard
464: Summary: If 3 live state, convergence to period prevalence on same graph
465: Author: Brouard
466:
1.153 brouard 467: Revision 1.152 2014/06/18 17:54:09 brouard
468: Summary: open browser, use gnuplot on same dir than imach if not found in the path
469:
1.152 brouard 470: Revision 1.151 2014/06/18 16:43:30 brouard
471: *** empty log message ***
472:
1.151 brouard 473: Revision 1.150 2014/06/18 16:42:35 brouard
474: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
475: Author: brouard
476:
1.150 brouard 477: Revision 1.149 2014/06/18 15:51:14 brouard
478: Summary: Some fixes in parameter files errors
479: Author: Nicolas Brouard
480:
1.149 brouard 481: Revision 1.148 2014/06/17 17:38:48 brouard
482: Summary: Nothing new
483: Author: Brouard
484:
485: Just a new packaging for OS/X version 0.98nS
486:
1.148 brouard 487: Revision 1.147 2014/06/16 10:33:11 brouard
488: *** empty log message ***
489:
1.147 brouard 490: Revision 1.146 2014/06/16 10:20:28 brouard
491: Summary: Merge
492: Author: Brouard
493:
494: Merge, before building revised version.
495:
1.146 brouard 496: Revision 1.145 2014/06/10 21:23:15 brouard
497: Summary: Debugging with valgrind
498: Author: Nicolas Brouard
499:
500: Lot of changes in order to output the results with some covariates
501: After the Edimburgh REVES conference 2014, it seems mandatory to
502: improve the code.
503: No more memory valgrind error but a lot has to be done in order to
504: continue the work of splitting the code into subroutines.
505: Also, decodemodel has been improved. Tricode is still not
506: optimal. nbcode should be improved. Documentation has been added in
507: the source code.
508:
1.144 brouard 509: Revision 1.143 2014/01/26 09:45:38 brouard
510: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
511:
512: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
513: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
514:
1.143 brouard 515: Revision 1.142 2014/01/26 03:57:36 brouard
516: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
517:
518: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
519:
1.142 brouard 520: Revision 1.141 2014/01/26 02:42:01 brouard
521: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
522:
1.141 brouard 523: Revision 1.140 2011/09/02 10:37:54 brouard
524: Summary: times.h is ok with mingw32 now.
525:
1.140 brouard 526: Revision 1.139 2010/06/14 07:50:17 brouard
527: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
528: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
529:
1.139 brouard 530: Revision 1.138 2010/04/30 18:19:40 brouard
531: *** empty log message ***
532:
1.138 brouard 533: Revision 1.137 2010/04/29 18:11:38 brouard
534: (Module): Checking covariates for more complex models
535: than V1+V2. A lot of change to be done. Unstable.
536:
1.137 brouard 537: Revision 1.136 2010/04/26 20:30:53 brouard
538: (Module): merging some libgsl code. Fixing computation
539: of likelione (using inter/intrapolation if mle = 0) in order to
540: get same likelihood as if mle=1.
541: Some cleaning of code and comments added.
542:
1.136 brouard 543: Revision 1.135 2009/10/29 15:33:14 brouard
544: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
545:
1.135 brouard 546: Revision 1.134 2009/10/29 13:18:53 brouard
547: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
548:
1.134 brouard 549: Revision 1.133 2009/07/06 10:21:25 brouard
550: just nforces
551:
1.133 brouard 552: Revision 1.132 2009/07/06 08:22:05 brouard
553: Many tings
554:
1.132 brouard 555: Revision 1.131 2009/06/20 16:22:47 brouard
556: Some dimensions resccaled
557:
1.131 brouard 558: Revision 1.130 2009/05/26 06:44:34 brouard
559: (Module): Max Covariate is now set to 20 instead of 8. A
560: lot of cleaning with variables initialized to 0. Trying to make
561: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
562:
1.130 brouard 563: Revision 1.129 2007/08/31 13:49:27 lievre
564: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
565:
1.129 lievre 566: Revision 1.128 2006/06/30 13:02:05 brouard
567: (Module): Clarifications on computing e.j
568:
1.128 brouard 569: Revision 1.127 2006/04/28 18:11:50 brouard
570: (Module): Yes the sum of survivors was wrong since
571: imach-114 because nhstepm was no more computed in the age
572: loop. Now we define nhstepma in the age loop.
573: (Module): In order to speed up (in case of numerous covariates) we
574: compute health expectancies (without variances) in a first step
575: and then all the health expectancies with variances or standard
576: deviation (needs data from the Hessian matrices) which slows the
577: computation.
578: In the future we should be able to stop the program is only health
579: expectancies and graph are needed without standard deviations.
580:
1.127 brouard 581: Revision 1.126 2006/04/28 17:23:28 brouard
582: (Module): Yes the sum of survivors was wrong since
583: imach-114 because nhstepm was no more computed in the age
584: loop. Now we define nhstepma in the age loop.
585: Version 0.98h
586:
1.126 brouard 587: Revision 1.125 2006/04/04 15:20:31 lievre
588: Errors in calculation of health expectancies. Age was not initialized.
589: Forecasting file added.
590:
591: Revision 1.124 2006/03/22 17:13:53 lievre
592: Parameters are printed with %lf instead of %f (more numbers after the comma).
593: The log-likelihood is printed in the log file
594:
595: Revision 1.123 2006/03/20 10:52:43 brouard
596: * imach.c (Module): <title> changed, corresponds to .htm file
597: name. <head> headers where missing.
598:
599: * imach.c (Module): Weights can have a decimal point as for
600: English (a comma might work with a correct LC_NUMERIC environment,
601: otherwise the weight is truncated).
602: Modification of warning when the covariates values are not 0 or
603: 1.
604: Version 0.98g
605:
606: Revision 1.122 2006/03/20 09:45:41 brouard
607: (Module): Weights can have a decimal point as for
608: English (a comma might work with a correct LC_NUMERIC environment,
609: otherwise the weight is truncated).
610: Modification of warning when the covariates values are not 0 or
611: 1.
612: Version 0.98g
613:
614: Revision 1.121 2006/03/16 17:45:01 lievre
615: * imach.c (Module): Comments concerning covariates added
616:
617: * imach.c (Module): refinements in the computation of lli if
618: status=-2 in order to have more reliable computation if stepm is
619: not 1 month. Version 0.98f
620:
621: Revision 1.120 2006/03/16 15:10:38 lievre
622: (Module): refinements in the computation of lli if
623: status=-2 in order to have more reliable computation if stepm is
624: not 1 month. Version 0.98f
625:
626: Revision 1.119 2006/03/15 17:42:26 brouard
627: (Module): Bug if status = -2, the loglikelihood was
628: computed as likelihood omitting the logarithm. Version O.98e
629:
630: Revision 1.118 2006/03/14 18:20:07 brouard
631: (Module): varevsij Comments added explaining the second
632: table of variances if popbased=1 .
633: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
634: (Module): Function pstamp added
635: (Module): Version 0.98d
636:
637: Revision 1.117 2006/03/14 17:16:22 brouard
638: (Module): varevsij Comments added explaining the second
639: table of variances if popbased=1 .
640: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
641: (Module): Function pstamp added
642: (Module): Version 0.98d
643:
644: Revision 1.116 2006/03/06 10:29:27 brouard
645: (Module): Variance-covariance wrong links and
646: varian-covariance of ej. is needed (Saito).
647:
648: Revision 1.115 2006/02/27 12:17:45 brouard
649: (Module): One freematrix added in mlikeli! 0.98c
650:
651: Revision 1.114 2006/02/26 12:57:58 brouard
652: (Module): Some improvements in processing parameter
653: filename with strsep.
654:
655: Revision 1.113 2006/02/24 14:20:24 brouard
656: (Module): Memory leaks checks with valgrind and:
657: datafile was not closed, some imatrix were not freed and on matrix
658: allocation too.
659:
660: Revision 1.112 2006/01/30 09:55:26 brouard
661: (Module): Back to gnuplot.exe instead of wgnuplot.exe
662:
663: Revision 1.111 2006/01/25 20:38:18 brouard
664: (Module): Lots of cleaning and bugs added (Gompertz)
665: (Module): Comments can be added in data file. Missing date values
666: can be a simple dot '.'.
667:
668: Revision 1.110 2006/01/25 00:51:50 brouard
669: (Module): Lots of cleaning and bugs added (Gompertz)
670:
671: Revision 1.109 2006/01/24 19:37:15 brouard
672: (Module): Comments (lines starting with a #) are allowed in data.
673:
674: Revision 1.108 2006/01/19 18:05:42 lievre
675: Gnuplot problem appeared...
676: To be fixed
677:
678: Revision 1.107 2006/01/19 16:20:37 brouard
679: Test existence of gnuplot in imach path
680:
681: Revision 1.106 2006/01/19 13:24:36 brouard
682: Some cleaning and links added in html output
683:
684: Revision 1.105 2006/01/05 20:23:19 lievre
685: *** empty log message ***
686:
687: Revision 1.104 2005/09/30 16:11:43 lievre
688: (Module): sump fixed, loop imx fixed, and simplifications.
689: (Module): If the status is missing at the last wave but we know
690: that the person is alive, then we can code his/her status as -2
691: (instead of missing=-1 in earlier versions) and his/her
692: contributions to the likelihood is 1 - Prob of dying from last
693: health status (= 1-p13= p11+p12 in the easiest case of somebody in
694: the healthy state at last known wave). Version is 0.98
695:
696: Revision 1.103 2005/09/30 15:54:49 lievre
697: (Module): sump fixed, loop imx fixed, and simplifications.
698:
699: Revision 1.102 2004/09/15 17:31:30 brouard
700: Add the possibility to read data file including tab characters.
701:
702: Revision 1.101 2004/09/15 10:38:38 brouard
703: Fix on curr_time
704:
705: Revision 1.100 2004/07/12 18:29:06 brouard
706: Add version for Mac OS X. Just define UNIX in Makefile
707:
708: Revision 1.99 2004/06/05 08:57:40 brouard
709: *** empty log message ***
710:
711: Revision 1.98 2004/05/16 15:05:56 brouard
712: New version 0.97 . First attempt to estimate force of mortality
713: directly from the data i.e. without the need of knowing the health
714: state at each age, but using a Gompertz model: log u =a + b*age .
715: This is the basic analysis of mortality and should be done before any
716: other analysis, in order to test if the mortality estimated from the
717: cross-longitudinal survey is different from the mortality estimated
718: from other sources like vital statistic data.
719:
720: The same imach parameter file can be used but the option for mle should be -3.
721:
1.133 brouard 722: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 723: former routines in order to include the new code within the former code.
724:
725: The output is very simple: only an estimate of the intercept and of
726: the slope with 95% confident intervals.
727:
728: Current limitations:
729: A) Even if you enter covariates, i.e. with the
730: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
731: B) There is no computation of Life Expectancy nor Life Table.
732:
733: Revision 1.97 2004/02/20 13:25:42 lievre
734: Version 0.96d. Population forecasting command line is (temporarily)
735: suppressed.
736:
737: Revision 1.96 2003/07/15 15:38:55 brouard
738: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
739: rewritten within the same printf. Workaround: many printfs.
740:
741: Revision 1.95 2003/07/08 07:54:34 brouard
742: * imach.c (Repository):
743: (Repository): Using imachwizard code to output a more meaningful covariance
744: matrix (cov(a12,c31) instead of numbers.
745:
746: Revision 1.94 2003/06/27 13:00:02 brouard
747: Just cleaning
748:
749: Revision 1.93 2003/06/25 16:33:55 brouard
750: (Module): On windows (cygwin) function asctime_r doesn't
751: exist so I changed back to asctime which exists.
752: (Module): Version 0.96b
753:
754: Revision 1.92 2003/06/25 16:30:45 brouard
755: (Module): On windows (cygwin) function asctime_r doesn't
756: exist so I changed back to asctime which exists.
757:
758: Revision 1.91 2003/06/25 15:30:29 brouard
759: * imach.c (Repository): Duplicated warning errors corrected.
760: (Repository): Elapsed time after each iteration is now output. It
761: helps to forecast when convergence will be reached. Elapsed time
762: is stamped in powell. We created a new html file for the graphs
763: concerning matrix of covariance. It has extension -cov.htm.
764:
765: Revision 1.90 2003/06/24 12:34:15 brouard
766: (Module): Some bugs corrected for windows. Also, when
767: mle=-1 a template is output in file "or"mypar.txt with the design
768: of the covariance matrix to be input.
769:
770: Revision 1.89 2003/06/24 12:30:52 brouard
771: (Module): Some bugs corrected for windows. Also, when
772: mle=-1 a template is output in file "or"mypar.txt with the design
773: of the covariance matrix to be input.
774:
775: Revision 1.88 2003/06/23 17:54:56 brouard
776: * 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.
777:
778: Revision 1.87 2003/06/18 12:26:01 brouard
779: Version 0.96
780:
781: Revision 1.86 2003/06/17 20:04:08 brouard
782: (Module): Change position of html and gnuplot routines and added
783: routine fileappend.
784:
785: Revision 1.85 2003/06/17 13:12:43 brouard
786: * imach.c (Repository): Check when date of death was earlier that
787: current date of interview. It may happen when the death was just
788: prior to the death. In this case, dh was negative and likelihood
789: was wrong (infinity). We still send an "Error" but patch by
790: assuming that the date of death was just one stepm after the
791: interview.
792: (Repository): Because some people have very long ID (first column)
793: we changed int to long in num[] and we added a new lvector for
794: memory allocation. But we also truncated to 8 characters (left
795: truncation)
796: (Repository): No more line truncation errors.
797:
798: Revision 1.84 2003/06/13 21:44:43 brouard
799: * imach.c (Repository): Replace "freqsummary" at a correct
800: place. It differs from routine "prevalence" which may be called
801: many times. Probs is memory consuming and must be used with
802: parcimony.
803: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
804:
805: Revision 1.83 2003/06/10 13:39:11 lievre
806: *** empty log message ***
807:
808: Revision 1.82 2003/06/05 15:57:20 brouard
809: Add log in imach.c and fullversion number is now printed.
810:
811: */
812: /*
813: Interpolated Markov Chain
814:
815: Short summary of the programme:
816:
1.227 brouard 817: This program computes Healthy Life Expectancies or State-specific
818: (if states aren't health statuses) Expectancies from
819: cross-longitudinal data. Cross-longitudinal data consist in:
820:
821: -1- a first survey ("cross") where individuals from different ages
822: are interviewed on their health status or degree of disability (in
823: the case of a health survey which is our main interest)
824:
825: -2- at least a second wave of interviews ("longitudinal") which
826: measure each change (if any) in individual health status. Health
827: expectancies are computed from the time spent in each health state
828: according to a model. More health states you consider, more time is
829: necessary to reach the Maximum Likelihood of the parameters involved
830: in the model. The simplest model is the multinomial logistic model
831: where pij is the probability to be observed in state j at the second
832: wave conditional to be observed in state i at the first
833: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
834: etc , where 'age' is age and 'sex' is a covariate. If you want to
835: have a more complex model than "constant and age", you should modify
836: the program where the markup *Covariates have to be included here
837: again* invites you to do it. More covariates you add, slower the
1.126 brouard 838: convergence.
839:
840: The advantage of this computer programme, compared to a simple
841: multinomial logistic model, is clear when the delay between waves is not
842: identical for each individual. Also, if a individual missed an
843: intermediate interview, the information is lost, but taken into
844: account using an interpolation or extrapolation.
845:
846: hPijx is the probability to be observed in state i at age x+h
847: conditional to the observed state i at age x. The delay 'h' can be
848: split into an exact number (nh*stepm) of unobserved intermediate
849: states. This elementary transition (by month, quarter,
850: semester or year) is modelled as a multinomial logistic. The hPx
851: matrix is simply the matrix product of nh*stepm elementary matrices
852: and the contribution of each individual to the likelihood is simply
853: hPijx.
854:
855: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 856: of the life expectancies. It also computes the period (stable) prevalence.
857:
858: Back prevalence and projections:
1.227 brouard 859:
860: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
861: double agemaxpar, double ftolpl, int *ncvyearp, double
862: dateprev1,double dateprev2, int firstpass, int lastpass, int
863: mobilavproj)
864:
865: Computes the back prevalence limit for any combination of
866: covariate values k at any age between ageminpar and agemaxpar and
867: returns it in **bprlim. In the loops,
868:
869: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
870: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
871:
872: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 873: Computes for any combination of covariates k and any age between bage and fage
874: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
875: oldm=oldms;savm=savms;
1.227 brouard 876:
1.267 brouard 877: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 878: Computes the transition matrix starting at age 'age' over
879: 'nhstepm*hstepm*stepm' months (i.e. until
880: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 881: nhstepm*hstepm matrices.
882:
883: Returns p3mat[i][j][h] after calling
884: p3mat[i][j][h]=matprod2(newm,
885: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
886: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
887: oldm);
1.226 brouard 888:
889: Important routines
890:
891: - func (or funcone), computes logit (pij) distinguishing
892: o fixed variables (single or product dummies or quantitative);
893: o varying variables by:
894: (1) wave (single, product dummies, quantitative),
895: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
896: % fixed dummy (treated) or quantitative (not done because time-consuming);
897: % varying dummy (not done) or quantitative (not done);
898: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
899: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
900: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
901: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
902: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 903:
1.226 brouard 904:
905:
1.133 brouard 906: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
907: Institut national d'études démographiques, Paris.
1.126 brouard 908: This software have been partly granted by Euro-REVES, a concerted action
909: from the European Union.
910: It is copyrighted identically to a GNU software product, ie programme and
911: software can be distributed freely for non commercial use. Latest version
912: can be accessed at http://euroreves.ined.fr/imach .
913:
914: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
915: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
916:
917: **********************************************************************/
918: /*
919: main
920: read parameterfile
921: read datafile
922: concatwav
923: freqsummary
924: if (mle >= 1)
925: mlikeli
926: print results files
927: if mle==1
928: computes hessian
929: read end of parameter file: agemin, agemax, bage, fage, estepm
930: begin-prev-date,...
931: open gnuplot file
932: open html file
1.145 brouard 933: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
934: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
935: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
936: freexexit2 possible for memory heap.
937:
938: h Pij x | pij_nom ficrestpij
939: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
940: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
941: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
942:
943: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
944: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
945: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
946: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
947: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
948:
1.126 brouard 949: forecasting if prevfcast==1 prevforecast call prevalence()
950: health expectancies
951: Variance-covariance of DFLE
952: prevalence()
953: movingaverage()
954: varevsij()
955: if popbased==1 varevsij(,popbased)
956: total life expectancies
957: Variance of period (stable) prevalence
958: end
959: */
960:
1.187 brouard 961: /* #define DEBUG */
962: /* #define DEBUGBRENT */
1.203 brouard 963: /* #define DEBUGLINMIN */
964: /* #define DEBUGHESS */
965: #define DEBUGHESSIJ
1.224 brouard 966: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 967: #define POWELL /* Instead of NLOPT */
1.224 brouard 968: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 969: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
970: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 971:
972: #include <math.h>
973: #include <stdio.h>
974: #include <stdlib.h>
975: #include <string.h>
1.226 brouard 976: #include <ctype.h>
1.159 brouard 977:
978: #ifdef _WIN32
979: #include <io.h>
1.172 brouard 980: #include <windows.h>
981: #include <tchar.h>
1.159 brouard 982: #else
1.126 brouard 983: #include <unistd.h>
1.159 brouard 984: #endif
1.126 brouard 985:
986: #include <limits.h>
987: #include <sys/types.h>
1.171 brouard 988:
989: #if defined(__GNUC__)
990: #include <sys/utsname.h> /* Doesn't work on Windows */
991: #endif
992:
1.126 brouard 993: #include <sys/stat.h>
994: #include <errno.h>
1.159 brouard 995: /* extern int errno; */
1.126 brouard 996:
1.157 brouard 997: /* #ifdef LINUX */
998: /* #include <time.h> */
999: /* #include "timeval.h" */
1000: /* #else */
1001: /* #include <sys/time.h> */
1002: /* #endif */
1003:
1.126 brouard 1004: #include <time.h>
1005:
1.136 brouard 1006: #ifdef GSL
1007: #include <gsl/gsl_errno.h>
1008: #include <gsl/gsl_multimin.h>
1009: #endif
1010:
1.167 brouard 1011:
1.162 brouard 1012: #ifdef NLOPT
1013: #include <nlopt.h>
1014: typedef struct {
1015: double (* function)(double [] );
1016: } myfunc_data ;
1017: #endif
1018:
1.126 brouard 1019: /* #include <libintl.h> */
1020: /* #define _(String) gettext (String) */
1021:
1.251 brouard 1022: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1023:
1024: #define GNUPLOTPROGRAM "gnuplot"
1025: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1026: #define FILENAMELENGTH 132
1027:
1028: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1029: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1030:
1.144 brouard 1031: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1032: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1033:
1034: #define NINTERVMAX 8
1.144 brouard 1035: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1036: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1037: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1038: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1039: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1040: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 1041: #define MAXN 20000
1.144 brouard 1042: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1043: /* #define AGESUP 130 */
1044: #define AGESUP 150
1.268 brouard 1045: #define AGEINF 0
1.218 brouard 1046: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1047: #define AGEBASE 40
1.194 brouard 1048: #define AGEOVERFLOW 1.e20
1.164 brouard 1049: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1050: #ifdef _WIN32
1051: #define DIRSEPARATOR '\\'
1052: #define CHARSEPARATOR "\\"
1053: #define ODIRSEPARATOR '/'
1054: #else
1.126 brouard 1055: #define DIRSEPARATOR '/'
1056: #define CHARSEPARATOR "/"
1057: #define ODIRSEPARATOR '\\'
1058: #endif
1059:
1.285 ! brouard 1060: /* $Id: imach.c,v 1.284 2018/04/20 05:22:13 brouard Exp $ */
1.126 brouard 1061: /* $State: Exp $ */
1.196 brouard 1062: #include "version.h"
1063: char version[]=__IMACH_VERSION__;
1.283 brouard 1064: 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";
1.285 ! brouard 1065: char fullversion[]="$Revision: 1.284 $ $Date: 2018/04/20 05:22:13 $";
1.126 brouard 1066: char strstart[80];
1067: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1068: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1069: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1070: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1071: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1072: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1073: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1074: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1075: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1076: int cptcovprodnoage=0; /**< Number of covariate products without age */
1077: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1078: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1079: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1080: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1081: int nsd=0; /**< Total number of single dummy variables (output) */
1082: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1083: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1084: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1085: int ntveff=0; /**< ntveff number of effective time varying variables */
1086: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1087: int cptcov=0; /* Working variable */
1.218 brouard 1088: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1089: int npar=NPARMAX;
1090: int nlstate=2; /* Number of live states */
1091: int ndeath=1; /* Number of dead states */
1.130 brouard 1092: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1093: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1094: int popbased=0;
1095:
1096: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1097: int maxwav=0; /* Maxim number of waves */
1098: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1099: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1100: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1101: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1102: int mle=1, weightopt=0;
1.126 brouard 1103: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1104: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1105: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1106: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1107: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1108: int selected(int kvar); /* Is covariate kvar selected for printing results */
1109:
1.130 brouard 1110: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1111: double **matprod2(); /* test */
1.126 brouard 1112: double **oldm, **newm, **savm; /* Working pointers to matrices */
1113: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1114: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1115:
1.136 brouard 1116: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1117: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1118: FILE *ficlog, *ficrespow;
1.130 brouard 1119: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1120: double fretone; /* Only one call to likelihood */
1.130 brouard 1121: long ipmx=0; /* Number of contributions */
1.126 brouard 1122: double sw; /* Sum of weights */
1123: char filerespow[FILENAMELENGTH];
1124: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1125: FILE *ficresilk;
1126: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1127: FILE *ficresprobmorprev;
1128: FILE *fichtm, *fichtmcov; /* Html File */
1129: FILE *ficreseij;
1130: char filerese[FILENAMELENGTH];
1131: FILE *ficresstdeij;
1132: char fileresstde[FILENAMELENGTH];
1133: FILE *ficrescveij;
1134: char filerescve[FILENAMELENGTH];
1135: FILE *ficresvij;
1136: char fileresv[FILENAMELENGTH];
1.269 brouard 1137:
1.126 brouard 1138: char title[MAXLINE];
1.234 brouard 1139: char model[MAXLINE]; /**< The model line */
1.217 brouard 1140: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1141: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1142: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1143: char command[FILENAMELENGTH];
1144: int outcmd=0;
1145:
1.217 brouard 1146: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1147: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1148: char filelog[FILENAMELENGTH]; /* Log file */
1149: char filerest[FILENAMELENGTH];
1150: char fileregp[FILENAMELENGTH];
1151: char popfile[FILENAMELENGTH];
1152:
1153: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1154:
1.157 brouard 1155: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1156: /* struct timezone tzp; */
1157: /* extern int gettimeofday(); */
1158: struct tm tml, *gmtime(), *localtime();
1159:
1160: extern time_t time();
1161:
1162: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1163: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1164: struct tm tm;
1165:
1.126 brouard 1166: char strcurr[80], strfor[80];
1167:
1168: char *endptr;
1169: long lval;
1170: double dval;
1171:
1172: #define NR_END 1
1173: #define FREE_ARG char*
1174: #define FTOL 1.0e-10
1175:
1176: #define NRANSI
1.240 brouard 1177: #define ITMAX 200
1178: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1179:
1180: #define TOL 2.0e-4
1181:
1182: #define CGOLD 0.3819660
1183: #define ZEPS 1.0e-10
1184: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1185:
1186: #define GOLD 1.618034
1187: #define GLIMIT 100.0
1188: #define TINY 1.0e-20
1189:
1190: static double maxarg1,maxarg2;
1191: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1192: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1193:
1194: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1195: #define rint(a) floor(a+0.5)
1.166 brouard 1196: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1197: #define mytinydouble 1.0e-16
1.166 brouard 1198: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1199: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1200: /* static double dsqrarg; */
1201: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1202: static double sqrarg;
1203: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1204: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1205: int agegomp= AGEGOMP;
1206:
1207: int imx;
1208: int stepm=1;
1209: /* Stepm, step in month: minimum step interpolation*/
1210:
1211: int estepm;
1212: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1213:
1214: int m,nb;
1215: long *num;
1.197 brouard 1216: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1217: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1218: covariate for which somebody answered excluding
1219: undefined. Usually 2: 0 and 1. */
1220: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1221: covariate for which somebody answered including
1222: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1223: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1224: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1225: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1226: double *ageexmed,*agecens;
1227: double dateintmean=0;
1228:
1229: double *weight;
1230: int **s; /* Status */
1.141 brouard 1231: double *agedc;
1.145 brouard 1232: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1233: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1234: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1235: double **coqvar; /* Fixed quantitative covariate nqv */
1236: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1237: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1238: double idx;
1239: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1240: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1241: /*k 1 2 3 4 5 6 7 8 9 */
1242: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1243: /* Tndvar[k] 1 2 3 4 5 */
1244: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1245: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1246: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1247: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1248: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1249: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1250: /* Tprod[i]=k 4 7 */
1251: /* Tage[i]=k 5 8 */
1252: /* */
1253: /* Type */
1254: /* V 1 2 3 4 5 */
1255: /* F F V V V */
1256: /* D Q D D Q */
1257: /* */
1258: int *TvarsD;
1259: int *TvarsDind;
1260: int *TvarsQ;
1261: int *TvarsQind;
1262:
1.235 brouard 1263: #define MAXRESULTLINES 10
1264: int nresult=0;
1.258 brouard 1265: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1266: int TKresult[MAXRESULTLINES];
1.237 brouard 1267: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1268: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1269: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1270: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1271: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1272: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1273:
1.234 brouard 1274: /* 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 1275: 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 */
1276: 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 */
1277: 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 */
1278: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1279: 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 */
1280: 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 1281: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1282: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1283: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1284: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1285: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1286: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1287: 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 */
1288: 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 */
1289:
1.230 brouard 1290: int *Tvarsel; /**< Selected covariates for output */
1291: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1292: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1293: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1294: 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 1295: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1296: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1297: int *Tage;
1.227 brouard 1298: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1299: 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 1300: 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*/
1301: 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 1302: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1303: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1304: int **Tvard;
1305: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1306: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1307: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1308: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1309: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1310: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1311: double *lsurv, *lpop, *tpop;
1312:
1.231 brouard 1313: #define FD 1; /* Fixed dummy covariate */
1314: #define FQ 2; /* Fixed quantitative covariate */
1315: #define FP 3; /* Fixed product covariate */
1316: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1317: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1318: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1319: #define VD 10; /* Varying dummy covariate */
1320: #define VQ 11; /* Varying quantitative covariate */
1321: #define VP 12; /* Varying product covariate */
1322: #define VPDD 13; /* Varying product dummy*dummy covariate */
1323: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1324: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1325: #define APFD 16; /* Age product * fixed dummy covariate */
1326: #define APFQ 17; /* Age product * fixed quantitative covariate */
1327: #define APVD 18; /* Age product * varying dummy covariate */
1328: #define APVQ 19; /* Age product * varying quantitative covariate */
1329:
1330: #define FTYPE 1; /* Fixed covariate */
1331: #define VTYPE 2; /* Varying covariate (loop in wave) */
1332: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1333:
1334: struct kmodel{
1335: int maintype; /* main type */
1336: int subtype; /* subtype */
1337: };
1338: struct kmodel modell[NCOVMAX];
1339:
1.143 brouard 1340: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1341: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1342:
1343: /**************** split *************************/
1344: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1345: {
1346: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1347: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1348: */
1349: char *ss; /* pointer */
1.186 brouard 1350: int l1=0, l2=0; /* length counters */
1.126 brouard 1351:
1352: l1 = strlen(path ); /* length of path */
1353: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1354: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1355: if ( ss == NULL ) { /* no directory, so determine current directory */
1356: strcpy( name, path ); /* we got the fullname name because no directory */
1357: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1358: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1359: /* get current working directory */
1360: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1361: #ifdef WIN32
1362: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1363: #else
1364: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1365: #endif
1.126 brouard 1366: return( GLOCK_ERROR_GETCWD );
1367: }
1368: /* got dirc from getcwd*/
1369: printf(" DIRC = %s \n",dirc);
1.205 brouard 1370: } else { /* strip directory from path */
1.126 brouard 1371: ss++; /* after this, the filename */
1372: l2 = strlen( ss ); /* length of filename */
1373: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1374: strcpy( name, ss ); /* save file name */
1375: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1376: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1377: printf(" DIRC2 = %s \n",dirc);
1378: }
1379: /* We add a separator at the end of dirc if not exists */
1380: l1 = strlen( dirc ); /* length of directory */
1381: if( dirc[l1-1] != DIRSEPARATOR ){
1382: dirc[l1] = DIRSEPARATOR;
1383: dirc[l1+1] = 0;
1384: printf(" DIRC3 = %s \n",dirc);
1385: }
1386: ss = strrchr( name, '.' ); /* find last / */
1387: if (ss >0){
1388: ss++;
1389: strcpy(ext,ss); /* save extension */
1390: l1= strlen( name);
1391: l2= strlen(ss)+1;
1392: strncpy( finame, name, l1-l2);
1393: finame[l1-l2]= 0;
1394: }
1395:
1396: return( 0 ); /* we're done */
1397: }
1398:
1399:
1400: /******************************************/
1401:
1402: void replace_back_to_slash(char *s, char*t)
1403: {
1404: int i;
1405: int lg=0;
1406: i=0;
1407: lg=strlen(t);
1408: for(i=0; i<= lg; i++) {
1409: (s[i] = t[i]);
1410: if (t[i]== '\\') s[i]='/';
1411: }
1412: }
1413:
1.132 brouard 1414: char *trimbb(char *out, char *in)
1.137 brouard 1415: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1416: char *s;
1417: s=out;
1418: while (*in != '\0'){
1.137 brouard 1419: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1420: in++;
1421: }
1422: *out++ = *in++;
1423: }
1424: *out='\0';
1425: return s;
1426: }
1427:
1.187 brouard 1428: /* char *substrchaine(char *out, char *in, char *chain) */
1429: /* { */
1430: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1431: /* char *s, *t; */
1432: /* t=in;s=out; */
1433: /* while ((*in != *chain) && (*in != '\0')){ */
1434: /* *out++ = *in++; */
1435: /* } */
1436:
1437: /* /\* *in matches *chain *\/ */
1438: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1439: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1440: /* } */
1441: /* in--; chain--; */
1442: /* while ( (*in != '\0')){ */
1443: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1444: /* *out++ = *in++; */
1445: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1446: /* } */
1447: /* *out='\0'; */
1448: /* out=s; */
1449: /* return out; */
1450: /* } */
1451: char *substrchaine(char *out, char *in, char *chain)
1452: {
1453: /* Substract chain 'chain' from 'in', return and output 'out' */
1454: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1455:
1456: char *strloc;
1457:
1458: strcpy (out, in);
1459: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1460: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1461: if(strloc != NULL){
1462: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1463: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1464: /* strcpy (strloc, strloc +strlen(chain));*/
1465: }
1466: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1467: return out;
1468: }
1469:
1470:
1.145 brouard 1471: char *cutl(char *blocc, char *alocc, char *in, char occ)
1472: {
1.187 brouard 1473: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1474: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1475: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1476: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1477: */
1.160 brouard 1478: char *s, *t;
1.145 brouard 1479: t=in;s=in;
1480: while ((*in != occ) && (*in != '\0')){
1481: *alocc++ = *in++;
1482: }
1483: if( *in == occ){
1484: *(alocc)='\0';
1485: s=++in;
1486: }
1487:
1488: if (s == t) {/* occ not found */
1489: *(alocc-(in-s))='\0';
1490: in=s;
1491: }
1492: while ( *in != '\0'){
1493: *blocc++ = *in++;
1494: }
1495:
1496: *blocc='\0';
1497: return t;
1498: }
1.137 brouard 1499: char *cutv(char *blocc, char *alocc, char *in, char occ)
1500: {
1.187 brouard 1501: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1502: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1503: gives blocc="abcdef2ghi" and alocc="j".
1504: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1505: */
1506: char *s, *t;
1507: t=in;s=in;
1508: while (*in != '\0'){
1509: while( *in == occ){
1510: *blocc++ = *in++;
1511: s=in;
1512: }
1513: *blocc++ = *in++;
1514: }
1515: if (s == t) /* occ not found */
1516: *(blocc-(in-s))='\0';
1517: else
1518: *(blocc-(in-s)-1)='\0';
1519: in=s;
1520: while ( *in != '\0'){
1521: *alocc++ = *in++;
1522: }
1523:
1524: *alocc='\0';
1525: return s;
1526: }
1527:
1.126 brouard 1528: int nbocc(char *s, char occ)
1529: {
1530: int i,j=0;
1531: int lg=20;
1532: i=0;
1533: lg=strlen(s);
1534: for(i=0; i<= lg; i++) {
1.234 brouard 1535: if (s[i] == occ ) j++;
1.126 brouard 1536: }
1537: return j;
1538: }
1539:
1.137 brouard 1540: /* void cutv(char *u,char *v, char*t, char occ) */
1541: /* { */
1542: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1543: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1544: /* gives u="abcdef2ghi" and v="j" *\/ */
1545: /* int i,lg,j,p=0; */
1546: /* i=0; */
1547: /* lg=strlen(t); */
1548: /* for(j=0; j<=lg-1; j++) { */
1549: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1550: /* } */
1.126 brouard 1551:
1.137 brouard 1552: /* for(j=0; j<p; j++) { */
1553: /* (u[j] = t[j]); */
1554: /* } */
1555: /* u[p]='\0'; */
1.126 brouard 1556:
1.137 brouard 1557: /* for(j=0; j<= lg; j++) { */
1558: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1559: /* } */
1560: /* } */
1.126 brouard 1561:
1.160 brouard 1562: #ifdef _WIN32
1563: char * strsep(char **pp, const char *delim)
1564: {
1565: char *p, *q;
1566:
1567: if ((p = *pp) == NULL)
1568: return 0;
1569: if ((q = strpbrk (p, delim)) != NULL)
1570: {
1571: *pp = q + 1;
1572: *q = '\0';
1573: }
1574: else
1575: *pp = 0;
1576: return p;
1577: }
1578: #endif
1579:
1.126 brouard 1580: /********************** nrerror ********************/
1581:
1582: void nrerror(char error_text[])
1583: {
1584: fprintf(stderr,"ERREUR ...\n");
1585: fprintf(stderr,"%s\n",error_text);
1586: exit(EXIT_FAILURE);
1587: }
1588: /*********************** vector *******************/
1589: double *vector(int nl, int nh)
1590: {
1591: double *v;
1592: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1593: if (!v) nrerror("allocation failure in vector");
1594: return v-nl+NR_END;
1595: }
1596:
1597: /************************ free vector ******************/
1598: void free_vector(double*v, int nl, int nh)
1599: {
1600: free((FREE_ARG)(v+nl-NR_END));
1601: }
1602:
1603: /************************ivector *******************************/
1604: int *ivector(long nl,long nh)
1605: {
1606: int *v;
1607: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1608: if (!v) nrerror("allocation failure in ivector");
1609: return v-nl+NR_END;
1610: }
1611:
1612: /******************free ivector **************************/
1613: void free_ivector(int *v, long nl, long nh)
1614: {
1615: free((FREE_ARG)(v+nl-NR_END));
1616: }
1617:
1618: /************************lvector *******************************/
1619: long *lvector(long nl,long nh)
1620: {
1621: long *v;
1622: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1623: if (!v) nrerror("allocation failure in ivector");
1624: return v-nl+NR_END;
1625: }
1626:
1627: /******************free lvector **************************/
1628: void free_lvector(long *v, long nl, long nh)
1629: {
1630: free((FREE_ARG)(v+nl-NR_END));
1631: }
1632:
1633: /******************* imatrix *******************************/
1634: int **imatrix(long nrl, long nrh, long ncl, long nch)
1635: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1636: {
1637: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1638: int **m;
1639:
1640: /* allocate pointers to rows */
1641: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1642: if (!m) nrerror("allocation failure 1 in matrix()");
1643: m += NR_END;
1644: m -= nrl;
1645:
1646:
1647: /* allocate rows and set pointers to them */
1648: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1649: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1650: m[nrl] += NR_END;
1651: m[nrl] -= ncl;
1652:
1653: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1654:
1655: /* return pointer to array of pointers to rows */
1656: return m;
1657: }
1658:
1659: /****************** free_imatrix *************************/
1660: void free_imatrix(m,nrl,nrh,ncl,nch)
1661: int **m;
1662: long nch,ncl,nrh,nrl;
1663: /* free an int matrix allocated by imatrix() */
1664: {
1665: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1666: free((FREE_ARG) (m+nrl-NR_END));
1667: }
1668:
1669: /******************* matrix *******************************/
1670: double **matrix(long nrl, long nrh, long ncl, long nch)
1671: {
1672: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1673: double **m;
1674:
1675: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1676: if (!m) nrerror("allocation failure 1 in matrix()");
1677: m += NR_END;
1678: m -= nrl;
1679:
1680: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1681: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1682: m[nrl] += NR_END;
1683: m[nrl] -= ncl;
1684:
1685: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1686: return m;
1.145 brouard 1687: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1688: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1689: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1690: */
1691: }
1692:
1693: /*************************free matrix ************************/
1694: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1695: {
1696: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1697: free((FREE_ARG)(m+nrl-NR_END));
1698: }
1699:
1700: /******************* ma3x *******************************/
1701: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1702: {
1703: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+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:
1718: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1719: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1720: m[nrl][ncl] += NR_END;
1721: m[nrl][ncl] -= nll;
1722: for (j=ncl+1; j<=nch; j++)
1723: m[nrl][j]=m[nrl][j-1]+nlay;
1724:
1725: for (i=nrl+1; i<=nrh; i++) {
1726: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1727: for (j=ncl+1; j<=nch; j++)
1728: m[i][j]=m[i][j-1]+nlay;
1729: }
1730: return m;
1731: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1732: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1733: */
1734: }
1735:
1736: /*************************free ma3x ************************/
1737: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1738: {
1739: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1740: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1741: free((FREE_ARG)(m+nrl-NR_END));
1742: }
1743:
1744: /*************** function subdirf ***********/
1745: char *subdirf(char fileres[])
1746: {
1747: /* Caution optionfilefiname is hidden */
1748: strcpy(tmpout,optionfilefiname);
1749: strcat(tmpout,"/"); /* Add to the right */
1750: strcat(tmpout,fileres);
1751: return tmpout;
1752: }
1753:
1754: /*************** function subdirf2 ***********/
1755: char *subdirf2(char fileres[], char *preop)
1756: {
1757:
1758: /* Caution optionfilefiname is hidden */
1759: strcpy(tmpout,optionfilefiname);
1760: strcat(tmpout,"/");
1761: strcat(tmpout,preop);
1762: strcat(tmpout,fileres);
1763: return tmpout;
1764: }
1765:
1766: /*************** function subdirf3 ***********/
1767: char *subdirf3(char fileres[], char *preop, char *preop2)
1768: {
1769:
1770: /* Caution optionfilefiname is hidden */
1771: strcpy(tmpout,optionfilefiname);
1772: strcat(tmpout,"/");
1773: strcat(tmpout,preop);
1774: strcat(tmpout,preop2);
1775: strcat(tmpout,fileres);
1776: return tmpout;
1777: }
1.213 brouard 1778:
1779: /*************** function subdirfext ***********/
1780: char *subdirfext(char fileres[], char *preop, char *postop)
1781: {
1782:
1783: strcpy(tmpout,preop);
1784: strcat(tmpout,fileres);
1785: strcat(tmpout,postop);
1786: return tmpout;
1787: }
1.126 brouard 1788:
1.213 brouard 1789: /*************** function subdirfext3 ***********/
1790: char *subdirfext3(char fileres[], char *preop, char *postop)
1791: {
1792:
1793: /* Caution optionfilefiname is hidden */
1794: strcpy(tmpout,optionfilefiname);
1795: strcat(tmpout,"/");
1796: strcat(tmpout,preop);
1797: strcat(tmpout,fileres);
1798: strcat(tmpout,postop);
1799: return tmpout;
1800: }
1801:
1.162 brouard 1802: char *asc_diff_time(long time_sec, char ascdiff[])
1803: {
1804: long sec_left, days, hours, minutes;
1805: days = (time_sec) / (60*60*24);
1806: sec_left = (time_sec) % (60*60*24);
1807: hours = (sec_left) / (60*60) ;
1808: sec_left = (sec_left) %(60*60);
1809: minutes = (sec_left) /60;
1810: sec_left = (sec_left) % (60);
1811: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1812: return ascdiff;
1813: }
1814:
1.126 brouard 1815: /***************** f1dim *************************/
1816: extern int ncom;
1817: extern double *pcom,*xicom;
1818: extern double (*nrfunc)(double []);
1819:
1820: double f1dim(double x)
1821: {
1822: int j;
1823: double f;
1824: double *xt;
1825:
1826: xt=vector(1,ncom);
1827: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1828: f=(*nrfunc)(xt);
1829: free_vector(xt,1,ncom);
1830: return f;
1831: }
1832:
1833: /*****************brent *************************/
1834: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1835: {
1836: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1837: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1838: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1839: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1840: * returned function value.
1841: */
1.126 brouard 1842: int iter;
1843: double a,b,d,etemp;
1.159 brouard 1844: double fu=0,fv,fw,fx;
1.164 brouard 1845: double ftemp=0.;
1.126 brouard 1846: double p,q,r,tol1,tol2,u,v,w,x,xm;
1847: double e=0.0;
1848:
1849: a=(ax < cx ? ax : cx);
1850: b=(ax > cx ? ax : cx);
1851: x=w=v=bx;
1852: fw=fv=fx=(*f)(x);
1853: for (iter=1;iter<=ITMAX;iter++) {
1854: xm=0.5*(a+b);
1855: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1856: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1857: printf(".");fflush(stdout);
1858: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1859: #ifdef DEBUGBRENT
1.126 brouard 1860: 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);
1861: 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);
1862: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1863: #endif
1864: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1865: *xmin=x;
1866: return fx;
1867: }
1868: ftemp=fu;
1869: if (fabs(e) > tol1) {
1870: r=(x-w)*(fx-fv);
1871: q=(x-v)*(fx-fw);
1872: p=(x-v)*q-(x-w)*r;
1873: q=2.0*(q-r);
1874: if (q > 0.0) p = -p;
1875: q=fabs(q);
1876: etemp=e;
1877: e=d;
1878: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1879: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1880: else {
1.224 brouard 1881: d=p/q;
1882: u=x+d;
1883: if (u-a < tol2 || b-u < tol2)
1884: d=SIGN(tol1,xm-x);
1.126 brouard 1885: }
1886: } else {
1887: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1888: }
1889: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1890: fu=(*f)(u);
1891: if (fu <= fx) {
1892: if (u >= x) a=x; else b=x;
1893: SHFT(v,w,x,u)
1.183 brouard 1894: SHFT(fv,fw,fx,fu)
1895: } else {
1896: if (u < x) a=u; else b=u;
1897: if (fu <= fw || w == x) {
1.224 brouard 1898: v=w;
1899: w=u;
1900: fv=fw;
1901: fw=fu;
1.183 brouard 1902: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1903: v=u;
1904: fv=fu;
1.183 brouard 1905: }
1906: }
1.126 brouard 1907: }
1908: nrerror("Too many iterations in brent");
1909: *xmin=x;
1910: return fx;
1911: }
1912:
1913: /****************** mnbrak ***********************/
1914:
1915: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1916: double (*func)(double))
1.183 brouard 1917: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1918: the downhill direction (defined by the function as evaluated at the initial points) and returns
1919: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1920: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1921: */
1.126 brouard 1922: double ulim,u,r,q, dum;
1923: double fu;
1.187 brouard 1924:
1925: double scale=10.;
1926: int iterscale=0;
1927:
1928: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1929: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1930:
1931:
1932: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1933: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1934: /* *bx = *ax - (*ax - *bx)/scale; */
1935: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1936: /* } */
1937:
1.126 brouard 1938: if (*fb > *fa) {
1939: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1940: SHFT(dum,*fb,*fa,dum)
1941: }
1.126 brouard 1942: *cx=(*bx)+GOLD*(*bx-*ax);
1943: *fc=(*func)(*cx);
1.183 brouard 1944: #ifdef DEBUG
1.224 brouard 1945: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1946: 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 1947: #endif
1.224 brouard 1948: 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 1949: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1950: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1951: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1952: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1953: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1954: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1955: fu=(*func)(u);
1.163 brouard 1956: #ifdef DEBUG
1957: /* f(x)=A(x-u)**2+f(u) */
1958: double A, fparabu;
1959: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1960: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1961: 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);
1962: 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 1963: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1964: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1965: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1966: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1967: #endif
1.184 brouard 1968: #ifdef MNBRAKORIGINAL
1.183 brouard 1969: #else
1.191 brouard 1970: /* if (fu > *fc) { */
1971: /* #ifdef DEBUG */
1972: /* printf("mnbrak4 fu > fc \n"); */
1973: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1974: /* #endif */
1975: /* /\* 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 *\\/ *\/ */
1976: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1977: /* dum=u; /\* Shifting c and u *\/ */
1978: /* u = *cx; */
1979: /* *cx = dum; */
1980: /* dum = fu; */
1981: /* fu = *fc; */
1982: /* *fc =dum; */
1983: /* } else { /\* end *\/ */
1984: /* #ifdef DEBUG */
1985: /* printf("mnbrak3 fu < fc \n"); */
1986: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1987: /* #endif */
1988: /* dum=u; /\* Shifting c and u *\/ */
1989: /* u = *cx; */
1990: /* *cx = dum; */
1991: /* dum = fu; */
1992: /* fu = *fc; */
1993: /* *fc =dum; */
1994: /* } */
1.224 brouard 1995: #ifdef DEBUGMNBRAK
1996: double A, fparabu;
1997: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1998: fparabu= *fa - A*(*ax-u)*(*ax-u);
1999: 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);
2000: 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 2001: #endif
1.191 brouard 2002: dum=u; /* Shifting c and u */
2003: u = *cx;
2004: *cx = dum;
2005: dum = fu;
2006: fu = *fc;
2007: *fc =dum;
1.183 brouard 2008: #endif
1.162 brouard 2009: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2010: #ifdef DEBUG
1.224 brouard 2011: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2012: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2013: #endif
1.126 brouard 2014: fu=(*func)(u);
2015: if (fu < *fc) {
1.183 brouard 2016: #ifdef DEBUG
1.224 brouard 2017: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2018: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2019: #endif
2020: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2021: SHFT(*fb,*fc,fu,(*func)(u))
2022: #ifdef DEBUG
2023: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2024: #endif
2025: }
1.162 brouard 2026: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2027: #ifdef DEBUG
1.224 brouard 2028: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2029: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2030: #endif
1.126 brouard 2031: u=ulim;
2032: fu=(*func)(u);
1.183 brouard 2033: } else { /* u could be left to b (if r > q parabola has a maximum) */
2034: #ifdef DEBUG
1.224 brouard 2035: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2036: 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 2037: #endif
1.126 brouard 2038: u=(*cx)+GOLD*(*cx-*bx);
2039: fu=(*func)(u);
1.224 brouard 2040: #ifdef DEBUG
2041: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2042: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2043: #endif
1.183 brouard 2044: } /* end tests */
1.126 brouard 2045: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2046: SHFT(*fa,*fb,*fc,fu)
2047: #ifdef DEBUG
1.224 brouard 2048: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2049: 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 2050: #endif
2051: } /* 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 2052: }
2053:
2054: /*************** linmin ************************/
1.162 brouard 2055: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2056: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2057: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2058: the value of func at the returned location p . This is actually all accomplished by calling the
2059: routines mnbrak and brent .*/
1.126 brouard 2060: int ncom;
2061: double *pcom,*xicom;
2062: double (*nrfunc)(double []);
2063:
1.224 brouard 2064: #ifdef LINMINORIGINAL
1.126 brouard 2065: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2066: #else
2067: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2068: #endif
1.126 brouard 2069: {
2070: double brent(double ax, double bx, double cx,
2071: double (*f)(double), double tol, double *xmin);
2072: double f1dim(double x);
2073: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2074: double *fc, double (*func)(double));
2075: int j;
2076: double xx,xmin,bx,ax;
2077: double fx,fb,fa;
1.187 brouard 2078:
1.203 brouard 2079: #ifdef LINMINORIGINAL
2080: #else
2081: double scale=10., axs, xxs; /* Scale added for infinity */
2082: #endif
2083:
1.126 brouard 2084: ncom=n;
2085: pcom=vector(1,n);
2086: xicom=vector(1,n);
2087: nrfunc=func;
2088: for (j=1;j<=n;j++) {
2089: pcom[j]=p[j];
1.202 brouard 2090: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2091: }
1.187 brouard 2092:
1.203 brouard 2093: #ifdef LINMINORIGINAL
2094: xx=1.;
2095: #else
2096: axs=0.0;
2097: xxs=1.;
2098: do{
2099: xx= xxs;
2100: #endif
1.187 brouard 2101: ax=0.;
2102: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2103: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2104: /* 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)) */
2105: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2106: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2107: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2108: /* 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 2109: #ifdef LINMINORIGINAL
2110: #else
2111: if (fx != fx){
1.224 brouard 2112: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2113: printf("|");
2114: fprintf(ficlog,"|");
1.203 brouard 2115: #ifdef DEBUGLINMIN
1.224 brouard 2116: 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 2117: #endif
2118: }
1.224 brouard 2119: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2120: #endif
2121:
1.191 brouard 2122: #ifdef DEBUGLINMIN
2123: 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 2124: 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 2125: #endif
1.224 brouard 2126: #ifdef LINMINORIGINAL
2127: #else
2128: if(fb == fx){ /* Flat function in the direction */
2129: xmin=xx;
2130: *flat=1;
2131: }else{
2132: *flat=0;
2133: #endif
2134: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2135: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2136: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2137: /* fmin = f(p[j] + xmin * xi[j]) */
2138: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2139: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2140: #ifdef DEBUG
1.224 brouard 2141: 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);
2142: 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);
2143: #endif
2144: #ifdef LINMINORIGINAL
2145: #else
2146: }
1.126 brouard 2147: #endif
1.191 brouard 2148: #ifdef DEBUGLINMIN
2149: printf("linmin end ");
1.202 brouard 2150: fprintf(ficlog,"linmin end ");
1.191 brouard 2151: #endif
1.126 brouard 2152: for (j=1;j<=n;j++) {
1.203 brouard 2153: #ifdef LINMINORIGINAL
2154: xi[j] *= xmin;
2155: #else
2156: #ifdef DEBUGLINMIN
2157: if(xxs <1.0)
2158: printf(" before xi[%d]=%12.8f", j,xi[j]);
2159: #endif
2160: 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) */
2161: #ifdef DEBUGLINMIN
2162: if(xxs <1.0)
2163: 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 );
2164: #endif
2165: #endif
1.187 brouard 2166: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2167: }
1.191 brouard 2168: #ifdef DEBUGLINMIN
1.203 brouard 2169: printf("\n");
1.191 brouard 2170: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2171: 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 2172: for (j=1;j<=n;j++) {
1.202 brouard 2173: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2174: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2175: if(j % ncovmodel == 0){
1.191 brouard 2176: printf("\n");
1.202 brouard 2177: fprintf(ficlog,"\n");
2178: }
1.191 brouard 2179: }
1.203 brouard 2180: #else
1.191 brouard 2181: #endif
1.126 brouard 2182: free_vector(xicom,1,n);
2183: free_vector(pcom,1,n);
2184: }
2185:
2186:
2187: /*************** powell ************************/
1.162 brouard 2188: /*
2189: Minimization of a function func of n variables. Input consists of an initial starting point
2190: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2191: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2192: such that failure to decrease by more than this amount on one iteration signals doneness. On
2193: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2194: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2195: */
1.224 brouard 2196: #ifdef LINMINORIGINAL
2197: #else
2198: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2199: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2200: #endif
1.126 brouard 2201: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2202: double (*func)(double []))
2203: {
1.224 brouard 2204: #ifdef LINMINORIGINAL
2205: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2206: double (*func)(double []));
1.224 brouard 2207: #else
1.241 brouard 2208: void linmin(double p[], double xi[], int n, double *fret,
2209: double (*func)(double []),int *flat);
1.224 brouard 2210: #endif
1.239 brouard 2211: int i,ibig,j,jk,k;
1.126 brouard 2212: double del,t,*pt,*ptt,*xit;
1.181 brouard 2213: double directest;
1.126 brouard 2214: double fp,fptt;
2215: double *xits;
2216: int niterf, itmp;
1.224 brouard 2217: #ifdef LINMINORIGINAL
2218: #else
2219:
2220: flatdir=ivector(1,n);
2221: for (j=1;j<=n;j++) flatdir[j]=0;
2222: #endif
1.126 brouard 2223:
2224: pt=vector(1,n);
2225: ptt=vector(1,n);
2226: xit=vector(1,n);
2227: xits=vector(1,n);
2228: *fret=(*func)(p);
2229: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2230: rcurr_time = time(NULL);
1.126 brouard 2231: for (*iter=1;;++(*iter)) {
1.187 brouard 2232: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2233: ibig=0;
2234: del=0.0;
1.157 brouard 2235: rlast_time=rcurr_time;
2236: /* (void) gettimeofday(&curr_time,&tzp); */
2237: rcurr_time = time(NULL);
2238: curr_time = *localtime(&rcurr_time);
2239: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2240: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2241: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2242: for (i=1;i<=n;i++) {
1.126 brouard 2243: fprintf(ficrespow," %.12lf", p[i]);
2244: }
1.239 brouard 2245: fprintf(ficrespow,"\n");fflush(ficrespow);
2246: printf("\n#model= 1 + age ");
2247: fprintf(ficlog,"\n#model= 1 + age ");
2248: if(nagesqr==1){
1.241 brouard 2249: printf(" + age*age ");
2250: fprintf(ficlog," + age*age ");
1.239 brouard 2251: }
2252: for(j=1;j <=ncovmodel-2;j++){
2253: if(Typevar[j]==0) {
2254: printf(" + V%d ",Tvar[j]);
2255: fprintf(ficlog," + V%d ",Tvar[j]);
2256: }else if(Typevar[j]==1) {
2257: printf(" + V%d*age ",Tvar[j]);
2258: fprintf(ficlog," + V%d*age ",Tvar[j]);
2259: }else if(Typevar[j]==2) {
2260: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2261: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2262: }
2263: }
1.126 brouard 2264: printf("\n");
1.239 brouard 2265: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2266: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2267: fprintf(ficlog,"\n");
1.239 brouard 2268: for(i=1,jk=1; i <=nlstate; i++){
2269: for(k=1; k <=(nlstate+ndeath); k++){
2270: if (k != i) {
2271: printf("%d%d ",i,k);
2272: fprintf(ficlog,"%d%d ",i,k);
2273: for(j=1; j <=ncovmodel; j++){
2274: printf("%12.7f ",p[jk]);
2275: fprintf(ficlog,"%12.7f ",p[jk]);
2276: jk++;
2277: }
2278: printf("\n");
2279: fprintf(ficlog,"\n");
2280: }
2281: }
2282: }
1.241 brouard 2283: if(*iter <=3 && *iter >1){
1.157 brouard 2284: tml = *localtime(&rcurr_time);
2285: strcpy(strcurr,asctime(&tml));
2286: rforecast_time=rcurr_time;
1.126 brouard 2287: itmp = strlen(strcurr);
2288: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2289: strcurr[itmp-1]='\0';
1.162 brouard 2290: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2291: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2292: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2293: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2294: forecast_time = *localtime(&rforecast_time);
2295: strcpy(strfor,asctime(&forecast_time));
2296: itmp = strlen(strfor);
2297: if(strfor[itmp-1]=='\n')
2298: strfor[itmp-1]='\0';
2299: 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);
2300: 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 2301: }
2302: }
1.187 brouard 2303: for (i=1;i<=n;i++) { /* For each direction i */
2304: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2305: fptt=(*fret);
2306: #ifdef DEBUG
1.203 brouard 2307: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2308: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2309: #endif
1.203 brouard 2310: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2311: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2312: #ifdef LINMINORIGINAL
1.188 brouard 2313: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2314: #else
2315: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2316: flatdir[i]=flat; /* Function is vanishing in that direction i */
2317: #endif
2318: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2319: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2320: /* because that direction will be replaced unless the gain del is small */
2321: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2322: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2323: /* with the new direction. */
2324: del=fabs(fptt-(*fret));
2325: ibig=i;
1.126 brouard 2326: }
2327: #ifdef DEBUG
2328: printf("%d %.12e",i,(*fret));
2329: fprintf(ficlog,"%d %.12e",i,(*fret));
2330: for (j=1;j<=n;j++) {
1.224 brouard 2331: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2332: printf(" x(%d)=%.12e",j,xit[j]);
2333: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2334: }
2335: for(j=1;j<=n;j++) {
1.225 brouard 2336: printf(" p(%d)=%.12e",j,p[j]);
2337: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2338: }
2339: printf("\n");
2340: fprintf(ficlog,"\n");
2341: #endif
1.187 brouard 2342: } /* end loop on each direction i */
2343: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2344: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2345: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2346: for(j=1;j<=n;j++) {
1.225 brouard 2347: if(flatdir[j] >0){
2348: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2349: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2350: }
2351: /* printf("\n"); */
2352: /* fprintf(ficlog,"\n"); */
2353: }
1.243 brouard 2354: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2355: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2356: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2357: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2358: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2359: /* decreased of more than 3.84 */
2360: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2361: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2362: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2363:
1.188 brouard 2364: /* Starting the program with initial values given by a former maximization will simply change */
2365: /* the scales of the directions and the directions, because the are reset to canonical directions */
2366: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2367: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2368: #ifdef DEBUG
2369: int k[2],l;
2370: k[0]=1;
2371: k[1]=-1;
2372: printf("Max: %.12e",(*func)(p));
2373: fprintf(ficlog,"Max: %.12e",(*func)(p));
2374: for (j=1;j<=n;j++) {
2375: printf(" %.12e",p[j]);
2376: fprintf(ficlog," %.12e",p[j]);
2377: }
2378: printf("\n");
2379: fprintf(ficlog,"\n");
2380: for(l=0;l<=1;l++) {
2381: for (j=1;j<=n;j++) {
2382: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2383: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2384: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2385: }
2386: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2387: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2388: }
2389: #endif
2390:
1.224 brouard 2391: #ifdef LINMINORIGINAL
2392: #else
2393: free_ivector(flatdir,1,n);
2394: #endif
1.126 brouard 2395: free_vector(xit,1,n);
2396: free_vector(xits,1,n);
2397: free_vector(ptt,1,n);
2398: free_vector(pt,1,n);
2399: return;
1.192 brouard 2400: } /* enough precision */
1.240 brouard 2401: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2402: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2403: ptt[j]=2.0*p[j]-pt[j];
2404: xit[j]=p[j]-pt[j];
2405: pt[j]=p[j];
2406: }
1.181 brouard 2407: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2408: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2409: if (*iter <=4) {
1.225 brouard 2410: #else
2411: #endif
1.224 brouard 2412: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2413: #else
1.161 brouard 2414: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2415: #endif
1.162 brouard 2416: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2417: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2418: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2419: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2420: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2421: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2422: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2423: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2424: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2425: /* Even if f3 <f1, directest can be negative and t >0 */
2426: /* mu² and del² are equal when f3=f1 */
2427: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2428: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2429: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2430: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2431: #ifdef NRCORIGINAL
2432: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2433: #else
2434: 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 2435: t= t- del*SQR(fp-fptt);
1.183 brouard 2436: #endif
1.202 brouard 2437: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2438: #ifdef DEBUG
1.181 brouard 2439: 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);
2440: 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 2441: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2442: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2443: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2444: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2445: 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);
2446: 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);
2447: #endif
1.183 brouard 2448: #ifdef POWELLORIGINAL
2449: if (t < 0.0) { /* Then we use it for new direction */
2450: #else
1.182 brouard 2451: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2452: 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 2453: 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 2454: 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 2455: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2456: }
1.181 brouard 2457: if (directest < 0.0) { /* Then we use it for new direction */
2458: #endif
1.191 brouard 2459: #ifdef DEBUGLINMIN
1.234 brouard 2460: printf("Before linmin in direction P%d-P0\n",n);
2461: for (j=1;j<=n;j++) {
2462: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2463: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2464: if(j % ncovmodel == 0){
2465: printf("\n");
2466: fprintf(ficlog,"\n");
2467: }
2468: }
1.224 brouard 2469: #endif
2470: #ifdef LINMINORIGINAL
1.234 brouard 2471: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2472: #else
1.234 brouard 2473: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2474: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2475: #endif
1.234 brouard 2476:
1.191 brouard 2477: #ifdef DEBUGLINMIN
1.234 brouard 2478: for (j=1;j<=n;j++) {
2479: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2480: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2481: if(j % ncovmodel == 0){
2482: printf("\n");
2483: fprintf(ficlog,"\n");
2484: }
2485: }
1.224 brouard 2486: #endif
1.234 brouard 2487: for (j=1;j<=n;j++) {
2488: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2489: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2490: }
1.224 brouard 2491: #ifdef LINMINORIGINAL
2492: #else
1.234 brouard 2493: for (j=1, flatd=0;j<=n;j++) {
2494: if(flatdir[j]>0)
2495: flatd++;
2496: }
2497: if(flatd >0){
1.255 brouard 2498: printf("%d flat directions: ",flatd);
2499: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2500: for (j=1;j<=n;j++) {
2501: if(flatdir[j]>0){
2502: printf("%d ",j);
2503: fprintf(ficlog,"%d ",j);
2504: }
2505: }
2506: printf("\n");
2507: fprintf(ficlog,"\n");
2508: }
1.191 brouard 2509: #endif
1.234 brouard 2510: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2511: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2512:
1.126 brouard 2513: #ifdef DEBUG
1.234 brouard 2514: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2515: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2516: for(j=1;j<=n;j++){
2517: printf(" %lf",xit[j]);
2518: fprintf(ficlog," %lf",xit[j]);
2519: }
2520: printf("\n");
2521: fprintf(ficlog,"\n");
1.126 brouard 2522: #endif
1.192 brouard 2523: } /* end of t or directest negative */
1.224 brouard 2524: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2525: #else
1.234 brouard 2526: } /* end if (fptt < fp) */
1.192 brouard 2527: #endif
1.225 brouard 2528: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2529: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2530: #else
1.224 brouard 2531: #endif
1.234 brouard 2532: } /* loop iteration */
1.126 brouard 2533: }
1.234 brouard 2534:
1.126 brouard 2535: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2536:
1.235 brouard 2537: 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 2538: {
1.279 brouard 2539: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2540: * (and selected quantitative values in nres)
2541: * by left multiplying the unit
2542: * matrix by transitions matrix until convergence is reached with precision ftolpl
2543: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2544: * Wx is row vector: population in state 1, population in state 2, population dead
2545: * or prevalence in state 1, prevalence in state 2, 0
2546: * newm is the matrix after multiplications, its rows are identical at a factor.
2547: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2548: * Output is prlim.
2549: * Initial matrix pimij
2550: */
1.206 brouard 2551: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2552: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2553: /* 0, 0 , 1} */
2554: /*
2555: * and after some iteration: */
2556: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2557: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2558: /* 0, 0 , 1} */
2559: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2560: /* {0.51571254859325999, 0.4842874514067399, */
2561: /* 0.51326036147820708, 0.48673963852179264} */
2562: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2563:
1.126 brouard 2564: int i, ii,j,k;
1.209 brouard 2565: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2566: /* double **matprod2(); */ /* test */
1.218 brouard 2567: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2568: double **newm;
1.209 brouard 2569: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2570: int ncvloop=0;
1.169 brouard 2571:
1.209 brouard 2572: min=vector(1,nlstate);
2573: max=vector(1,nlstate);
2574: meandiff=vector(1,nlstate);
2575:
1.218 brouard 2576: /* Starting with matrix unity */
1.126 brouard 2577: for (ii=1;ii<=nlstate+ndeath;ii++)
2578: for (j=1;j<=nlstate+ndeath;j++){
2579: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2580: }
1.169 brouard 2581:
2582: cov[1]=1.;
2583:
2584: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2585: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2586: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2587: ncvloop++;
1.126 brouard 2588: newm=savm;
2589: /* Covariates have to be included here again */
1.138 brouard 2590: cov[2]=agefin;
1.187 brouard 2591: if(nagesqr==1)
2592: cov[3]= agefin*agefin;;
1.234 brouard 2593: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2594: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2595: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2596: /* 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 2597: }
2598: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2599: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2600: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2601: /* 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 2602: }
1.237 brouard 2603: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2604: if(Dummy[Tvar[Tage[k]]]){
2605: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2606: } else{
1.235 brouard 2607: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2608: }
1.235 brouard 2609: /* 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 2610: }
1.237 brouard 2611: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2612: /* 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 2613: if(Dummy[Tvard[k][1]==0]){
2614: if(Dummy[Tvard[k][2]==0]){
2615: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2616: }else{
2617: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2618: }
2619: }else{
2620: if(Dummy[Tvard[k][2]==0]){
2621: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2622: }else{
2623: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2624: }
2625: }
1.234 brouard 2626: }
1.138 brouard 2627: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2628: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2629: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2630: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2631: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2632: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2633: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2634:
1.126 brouard 2635: savm=oldm;
2636: oldm=newm;
1.209 brouard 2637:
2638: for(j=1; j<=nlstate; j++){
2639: max[j]=0.;
2640: min[j]=1.;
2641: }
2642: for(i=1;i<=nlstate;i++){
2643: sumnew=0;
2644: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2645: for(j=1; j<=nlstate; j++){
2646: prlim[i][j]= newm[i][j]/(1-sumnew);
2647: max[j]=FMAX(max[j],prlim[i][j]);
2648: min[j]=FMIN(min[j],prlim[i][j]);
2649: }
2650: }
2651:
1.126 brouard 2652: maxmax=0.;
1.209 brouard 2653: for(j=1; j<=nlstate; j++){
2654: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2655: maxmax=FMAX(maxmax,meandiff[j]);
2656: /* 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 2657: } /* j loop */
1.203 brouard 2658: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2659: /* 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 2660: if(maxmax < ftolpl){
1.209 brouard 2661: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2662: free_vector(min,1,nlstate);
2663: free_vector(max,1,nlstate);
2664: free_vector(meandiff,1,nlstate);
1.126 brouard 2665: return prlim;
2666: }
1.169 brouard 2667: } /* age loop */
1.208 brouard 2668: /* After some age loop it doesn't converge */
1.209 brouard 2669: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\
1.208 brouard 2670: Earliest 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);
1.209 brouard 2671: /* 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); */
2672: free_vector(min,1,nlstate);
2673: free_vector(max,1,nlstate);
2674: free_vector(meandiff,1,nlstate);
1.208 brouard 2675:
1.169 brouard 2676: return prlim; /* should not reach here */
1.126 brouard 2677: }
2678:
1.217 brouard 2679:
2680: /**** Back Prevalence limit (stable or period prevalence) ****************/
2681:
1.218 brouard 2682: /* 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) */
2683: /* 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 2684: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2685: {
1.264 brouard 2686: /* 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 2687: matrix by transitions matrix until convergence is reached with precision ftolpl */
2688: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2689: /* Wx is row vector: population in state 1, population in state 2, population dead */
2690: /* or prevalence in state 1, prevalence in state 2, 0 */
2691: /* newm is the matrix after multiplications, its rows are identical at a factor */
2692: /* Initial matrix pimij */
2693: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2694: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2695: /* 0, 0 , 1} */
2696: /*
2697: * and after some iteration: */
2698: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2699: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2700: /* 0, 0 , 1} */
2701: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2702: /* {0.51571254859325999, 0.4842874514067399, */
2703: /* 0.51326036147820708, 0.48673963852179264} */
2704: /* If we start from prlim again, prlim tends to a constant matrix */
2705:
2706: int i, ii,j,k;
1.247 brouard 2707: int first=0;
1.217 brouard 2708: double *min, *max, *meandiff, maxmax,sumnew=0.;
2709: /* double **matprod2(); */ /* test */
2710: double **out, cov[NCOVMAX+1], **bmij();
2711: double **newm;
1.218 brouard 2712: double **dnewm, **doldm, **dsavm; /* for use */
2713: double **oldm, **savm; /* for use */
2714:
1.217 brouard 2715: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2716: int ncvloop=0;
2717:
2718: min=vector(1,nlstate);
2719: max=vector(1,nlstate);
2720: meandiff=vector(1,nlstate);
2721:
1.266 brouard 2722: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2723: oldm=oldms; savm=savms;
2724:
2725: /* Starting with matrix unity */
2726: for (ii=1;ii<=nlstate+ndeath;ii++)
2727: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2728: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2729: }
2730:
2731: cov[1]=1.;
2732:
2733: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2734: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2735: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2736: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2737: ncvloop++;
1.218 brouard 2738: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2739: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2740: /* Covariates have to be included here again */
2741: cov[2]=agefin;
2742: if(nagesqr==1)
2743: cov[3]= agefin*agefin;;
1.242 brouard 2744: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2745: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2746: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2747: /* 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 2748: }
2749: /* for (k=1; k<=cptcovn;k++) { */
2750: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2751: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2752: /* /\* 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])]); *\/ */
2753: /* } */
2754: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2755: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2756: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2757: /* 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]); */
2758: }
2759: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2760: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2761: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2762: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2763: for (k=1; k<=cptcovage;k++){ /* For product with age */
2764: if(Dummy[Tvar[Tage[k]]]){
2765: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2766: } else{
2767: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2768: }
2769: /* 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]); */
2770: }
2771: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2772: /* 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]); */
2773: if(Dummy[Tvard[k][1]==0]){
2774: if(Dummy[Tvard[k][2]==0]){
2775: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2776: }else{
2777: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2778: }
2779: }else{
2780: if(Dummy[Tvard[k][2]==0]){
2781: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2782: }else{
2783: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2784: }
2785: }
1.217 brouard 2786: }
2787:
2788: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2789: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2790: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2791: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2792: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2793: /* ij should be linked to the correct index of cov */
2794: /* age and covariate values ij are in 'cov', but we need to pass
2795: * ij for the observed prevalence at age and status and covariate
2796: * number: prevacurrent[(int)agefin][ii][ij]
2797: */
2798: /* 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 *\/ */
2799: /* 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 *\/ */
2800: 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 2801: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2802: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2803: /* for(i=1; i<=nlstate+ndeath; i++) { */
2804: /* printf("%d newm= ",i); */
2805: /* for(j=1;j<=nlstate+ndeath;j++) { */
2806: /* printf("%f ",newm[i][j]); */
2807: /* } */
2808: /* printf("oldm * "); */
2809: /* for(j=1;j<=nlstate+ndeath;j++) { */
2810: /* printf("%f ",oldm[i][j]); */
2811: /* } */
1.268 brouard 2812: /* printf(" bmmij "); */
1.266 brouard 2813: /* for(j=1;j<=nlstate+ndeath;j++) { */
2814: /* printf("%f ",pmmij[i][j]); */
2815: /* } */
2816: /* printf("\n"); */
2817: /* } */
2818: /* } */
1.217 brouard 2819: savm=oldm;
2820: oldm=newm;
1.266 brouard 2821:
1.217 brouard 2822: for(j=1; j<=nlstate; j++){
2823: max[j]=0.;
2824: min[j]=1.;
2825: }
2826: for(j=1; j<=nlstate; j++){
2827: for(i=1;i<=nlstate;i++){
1.234 brouard 2828: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2829: bprlim[i][j]= newm[i][j];
2830: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2831: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2832: }
2833: }
1.218 brouard 2834:
1.217 brouard 2835: maxmax=0.;
2836: for(i=1; i<=nlstate; i++){
2837: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2838: maxmax=FMAX(maxmax,meandiff[i]);
2839: /* 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 2840: } /* i loop */
1.217 brouard 2841: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2842: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2843: if(maxmax < ftolpl){
1.220 brouard 2844: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2845: free_vector(min,1,nlstate);
2846: free_vector(max,1,nlstate);
2847: free_vector(meandiff,1,nlstate);
2848: return bprlim;
2849: }
2850: } /* age loop */
2851: /* After some age loop it doesn't converge */
1.247 brouard 2852: if(first){
2853: first=1;
2854: 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\
2855: 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);
2856: }
2857: 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 2858: 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);
2859: /* 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); */
2860: free_vector(min,1,nlstate);
2861: free_vector(max,1,nlstate);
2862: free_vector(meandiff,1,nlstate);
2863:
2864: return bprlim; /* should not reach here */
2865: }
2866:
1.126 brouard 2867: /*************** transition probabilities ***************/
2868:
2869: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2870: {
1.138 brouard 2871: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2872: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2873: model to the ncovmodel covariates (including constant and age).
2874: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2875: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2876: ncth covariate in the global vector x is given by the formula:
2877: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2878: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2879: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2880: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2881: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2882: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2883: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2884: */
2885: double s1, lnpijopii;
1.126 brouard 2886: /*double t34;*/
1.164 brouard 2887: int i,j, nc, ii, jj;
1.126 brouard 2888:
1.223 brouard 2889: for(i=1; i<= nlstate; i++){
2890: for(j=1; j<i;j++){
2891: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2892: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2893: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2894: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2895: }
2896: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2897: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2898: }
2899: for(j=i+1; j<=nlstate+ndeath;j++){
2900: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2901: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2902: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2903: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2904: }
2905: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2906: }
2907: }
1.218 brouard 2908:
1.223 brouard 2909: for(i=1; i<= nlstate; i++){
2910: s1=0;
2911: for(j=1; j<i; j++){
2912: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2913: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2914: }
2915: for(j=i+1; j<=nlstate+ndeath; j++){
2916: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2917: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2918: }
2919: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2920: ps[i][i]=1./(s1+1.);
2921: /* Computing other pijs */
2922: for(j=1; j<i; j++)
2923: ps[i][j]= exp(ps[i][j])*ps[i][i];
2924: for(j=i+1; j<=nlstate+ndeath; j++)
2925: ps[i][j]= exp(ps[i][j])*ps[i][i];
2926: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2927: } /* end i */
1.218 brouard 2928:
1.223 brouard 2929: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2930: for(jj=1; jj<= nlstate+ndeath; jj++){
2931: ps[ii][jj]=0;
2932: ps[ii][ii]=1;
2933: }
2934: }
1.218 brouard 2935:
2936:
1.223 brouard 2937: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2938: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2939: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2940: /* } */
2941: /* printf("\n "); */
2942: /* } */
2943: /* printf("\n ");printf("%lf ",cov[2]);*/
2944: /*
2945: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2946: goto end;*/
1.266 brouard 2947: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2948: }
2949:
1.218 brouard 2950: /*************** backward transition probabilities ***************/
2951:
2952: /* 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 ) */
2953: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2954: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2955: {
1.266 brouard 2956: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2957: * 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 2958: */
1.218 brouard 2959: int i, ii, j,k;
1.222 brouard 2960:
2961: double **out, **pmij();
2962: double sumnew=0.;
1.218 brouard 2963: double agefin;
1.268 brouard 2964: double k3=0.; /* constant of the w_x diagonal matrixe (in order for B to sum to 1 even for death state) */
1.222 brouard 2965: double **dnewm, **dsavm, **doldm;
2966: double **bbmij;
2967:
1.218 brouard 2968: doldm=ddoldms; /* global pointers */
1.222 brouard 2969: dnewm=ddnewms;
2970: dsavm=ddsavms;
2971:
2972: agefin=cov[2];
1.268 brouard 2973: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2974: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2975: the observed prevalence (with this covariate ij) at beginning of transition */
2976: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 2977:
2978: /* P_x */
1.266 brouard 2979: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 2980: /* outputs pmmij which is a stochastic matrix in row */
2981:
2982: /* Diag(w_x) */
2983: /* Problem with prevacurrent which can be zero */
2984: sumnew=0.;
1.269 brouard 2985: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 2986: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 2987: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 2988: sumnew+=prevacurrent[(int)agefin][ii][ij];
2989: }
2990: if(sumnew >0.01){ /* At least some value in the prevalence */
2991: for (ii=1;ii<=nlstate+ndeath;ii++){
2992: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 2993: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 2994: }
2995: }else{
2996: for (ii=1;ii<=nlstate+ndeath;ii++){
2997: for (j=1;j<=nlstate+ndeath;j++)
2998: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
2999: }
3000: /* if(sumnew <0.9){ */
3001: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3002: /* } */
3003: }
3004: k3=0.0; /* We put the last diagonal to 0 */
3005: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3006: doldm[ii][ii]= k3;
3007: }
3008: /* End doldm, At the end doldm is diag[(w_i)] */
3009:
3010: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
3011: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
3012:
3013: /* Diag(Sum_i w^i_x p^ij_x */
3014: /* 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 3015: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3016: sumnew=0.;
1.222 brouard 3017: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3018: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3019: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3020: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3021: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3022: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3023: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3024: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3025: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3026: /* }else */
1.268 brouard 3027: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3028: } /*End ii */
3029: } /* 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 */
3030:
3031: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
3032: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3033: /* end bmij */
1.266 brouard 3034: return ps; /*pointer is unchanged */
1.218 brouard 3035: }
1.217 brouard 3036: /*************** transition probabilities ***************/
3037:
1.218 brouard 3038: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3039: {
3040: /* According to parameters values stored in x and the covariate's values stored in cov,
3041: computes the probability to be observed in state j being in state i by appying the
3042: model to the ncovmodel covariates (including constant and age).
3043: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3044: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3045: ncth covariate in the global vector x is given by the formula:
3046: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3047: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3048: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3049: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3050: Outputs ps[i][j] the probability to be observed in j being in j according to
3051: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3052: */
3053: double s1, lnpijopii;
3054: /*double t34;*/
3055: int i,j, nc, ii, jj;
3056:
1.234 brouard 3057: for(i=1; i<= nlstate; i++){
3058: for(j=1; j<i;j++){
3059: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3060: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3061: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3062: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3063: }
3064: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3065: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3066: }
3067: for(j=i+1; j<=nlstate+ndeath;j++){
3068: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3069: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3070: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3071: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3072: }
3073: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3074: }
3075: }
3076:
3077: for(i=1; i<= nlstate; i++){
3078: s1=0;
3079: for(j=1; j<i; j++){
3080: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3081: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3082: }
3083: for(j=i+1; j<=nlstate+ndeath; j++){
3084: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3085: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3086: }
3087: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3088: ps[i][i]=1./(s1+1.);
3089: /* Computing other pijs */
3090: for(j=1; j<i; j++)
3091: ps[i][j]= exp(ps[i][j])*ps[i][i];
3092: for(j=i+1; j<=nlstate+ndeath; j++)
3093: ps[i][j]= exp(ps[i][j])*ps[i][i];
3094: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3095: } /* end i */
3096:
3097: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3098: for(jj=1; jj<= nlstate+ndeath; jj++){
3099: ps[ii][jj]=0;
3100: ps[ii][ii]=1;
3101: }
3102: }
3103: /* Added for backcast */ /* Transposed matrix too */
3104: for(jj=1; jj<= nlstate+ndeath; jj++){
3105: s1=0.;
3106: for(ii=1; ii<= nlstate+ndeath; ii++){
3107: s1+=ps[ii][jj];
3108: }
3109: for(ii=1; ii<= nlstate; ii++){
3110: ps[ii][jj]=ps[ii][jj]/s1;
3111: }
3112: }
3113: /* Transposition */
3114: for(jj=1; jj<= nlstate+ndeath; jj++){
3115: for(ii=jj; ii<= nlstate+ndeath; ii++){
3116: s1=ps[ii][jj];
3117: ps[ii][jj]=ps[jj][ii];
3118: ps[jj][ii]=s1;
3119: }
3120: }
3121: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3122: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3123: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3124: /* } */
3125: /* printf("\n "); */
3126: /* } */
3127: /* printf("\n ");printf("%lf ",cov[2]);*/
3128: /*
3129: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3130: goto end;*/
3131: return ps;
1.217 brouard 3132: }
3133:
3134:
1.126 brouard 3135: /**************** Product of 2 matrices ******************/
3136:
1.145 brouard 3137: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3138: {
3139: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3140: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3141: /* in, b, out are matrice of pointers which should have been initialized
3142: before: only the contents of out is modified. The function returns
3143: a pointer to pointers identical to out */
1.145 brouard 3144: int i, j, k;
1.126 brouard 3145: for(i=nrl; i<= nrh; i++)
1.145 brouard 3146: for(k=ncolol; k<=ncoloh; k++){
3147: out[i][k]=0.;
3148: for(j=ncl; j<=nch; j++)
3149: out[i][k] +=in[i][j]*b[j][k];
3150: }
1.126 brouard 3151: return out;
3152: }
3153:
3154:
3155: /************* Higher Matrix Product ***************/
3156:
1.235 brouard 3157: 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 3158: {
1.218 brouard 3159: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3160: 'nhstepm*hstepm*stepm' months (i.e. until
3161: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3162: nhstepm*hstepm matrices.
3163: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3164: (typically every 2 years instead of every month which is too big
3165: for the memory).
3166: Model is determined by parameters x and covariates have to be
3167: included manually here.
3168:
3169: */
3170:
3171: int i, j, d, h, k;
1.131 brouard 3172: double **out, cov[NCOVMAX+1];
1.126 brouard 3173: double **newm;
1.187 brouard 3174: double agexact;
1.214 brouard 3175: double agebegin, ageend;
1.126 brouard 3176:
3177: /* Hstepm could be zero and should return the unit matrix */
3178: for (i=1;i<=nlstate+ndeath;i++)
3179: for (j=1;j<=nlstate+ndeath;j++){
3180: oldm[i][j]=(i==j ? 1.0 : 0.0);
3181: po[i][j][0]=(i==j ? 1.0 : 0.0);
3182: }
3183: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3184: for(h=1; h <=nhstepm; h++){
3185: for(d=1; d <=hstepm; d++){
3186: newm=savm;
3187: /* Covariates have to be included here again */
3188: cov[1]=1.;
1.214 brouard 3189: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3190: cov[2]=agexact;
3191: if(nagesqr==1)
1.227 brouard 3192: cov[3]= agexact*agexact;
1.235 brouard 3193: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3194: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3195: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3196: /* 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)); */
3197: }
3198: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3199: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3200: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3201: /* 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]); */
3202: }
3203: for (k=1; k<=cptcovage;k++){
3204: if(Dummy[Tvar[Tage[k]]]){
3205: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3206: } else{
3207: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3208: }
3209: /* 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]); */
3210: }
3211: for (k=1; k<=cptcovprod;k++){ /* */
3212: /* 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]); */
3213: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3214: }
3215: /* for (k=1; k<=cptcovn;k++) */
3216: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3217: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3218: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3219: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3220: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3221:
3222:
1.126 brouard 3223: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3224: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3225: /* right multiplication of oldm by the current matrix */
1.126 brouard 3226: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3227: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3228: /* if((int)age == 70){ */
3229: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3230: /* for(i=1; i<=nlstate+ndeath; i++) { */
3231: /* printf("%d pmmij ",i); */
3232: /* for(j=1;j<=nlstate+ndeath;j++) { */
3233: /* printf("%f ",pmmij[i][j]); */
3234: /* } */
3235: /* printf(" oldm "); */
3236: /* for(j=1;j<=nlstate+ndeath;j++) { */
3237: /* printf("%f ",oldm[i][j]); */
3238: /* } */
3239: /* printf("\n"); */
3240: /* } */
3241: /* } */
1.126 brouard 3242: savm=oldm;
3243: oldm=newm;
3244: }
3245: for(i=1; i<=nlstate+ndeath; i++)
3246: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3247: po[i][j][h]=newm[i][j];
3248: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3249: }
1.128 brouard 3250: /*printf("h=%d ",h);*/
1.126 brouard 3251: } /* end h */
1.267 brouard 3252: /* printf("\n H=%d \n",h); */
1.126 brouard 3253: return po;
3254: }
3255:
1.217 brouard 3256: /************* Higher Back Matrix Product ***************/
1.218 brouard 3257: /* 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 3258: 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 3259: {
1.266 brouard 3260: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3261: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3262: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3263: nhstepm*hstepm matrices.
3264: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3265: (typically every 2 years instead of every month which is too big
1.217 brouard 3266: for the memory).
1.218 brouard 3267: Model is determined by parameters x and covariates have to be
1.266 brouard 3268: included manually here. Then we use a call to bmij(x and cov)
3269: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3270: */
1.217 brouard 3271:
3272: int i, j, d, h, k;
1.266 brouard 3273: double **out, cov[NCOVMAX+1], **bmij();
3274: double **newm, ***newmm;
1.217 brouard 3275: double agexact;
3276: double agebegin, ageend;
1.222 brouard 3277: double **oldm, **savm;
1.217 brouard 3278:
1.266 brouard 3279: newmm=po; /* To be saved */
3280: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3281: /* Hstepm could be zero and should return the unit matrix */
3282: for (i=1;i<=nlstate+ndeath;i++)
3283: for (j=1;j<=nlstate+ndeath;j++){
3284: oldm[i][j]=(i==j ? 1.0 : 0.0);
3285: po[i][j][0]=(i==j ? 1.0 : 0.0);
3286: }
3287: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3288: for(h=1; h <=nhstepm; h++){
3289: for(d=1; d <=hstepm; d++){
3290: newm=savm;
3291: /* Covariates have to be included here again */
3292: cov[1]=1.;
1.271 brouard 3293: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3294: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3295: cov[2]=agexact;
3296: if(nagesqr==1)
1.222 brouard 3297: cov[3]= agexact*agexact;
1.266 brouard 3298: for (k=1; k<=cptcovn;k++){
3299: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3300: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3301: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3302: /* 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)); */
3303: }
1.267 brouard 3304: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3305: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3306: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3307: /* 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]); */
3308: }
3309: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3310: if(Dummy[Tvar[Tage[k]]]){
3311: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3312: } else{
3313: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3314: }
3315: /* 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]); */
3316: }
3317: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3318: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3319: }
1.217 brouard 3320: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3321: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3322:
1.218 brouard 3323: /* Careful transposed matrix */
1.266 brouard 3324: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3325: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3326: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3327: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3328: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3329: /* if((int)age == 70){ */
3330: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3331: /* for(i=1; i<=nlstate+ndeath; i++) { */
3332: /* printf("%d pmmij ",i); */
3333: /* for(j=1;j<=nlstate+ndeath;j++) { */
3334: /* printf("%f ",pmmij[i][j]); */
3335: /* } */
3336: /* printf(" oldm "); */
3337: /* for(j=1;j<=nlstate+ndeath;j++) { */
3338: /* printf("%f ",oldm[i][j]); */
3339: /* } */
3340: /* printf("\n"); */
3341: /* } */
3342: /* } */
3343: savm=oldm;
3344: oldm=newm;
3345: }
3346: for(i=1; i<=nlstate+ndeath; i++)
3347: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3348: po[i][j][h]=newm[i][j];
1.268 brouard 3349: /* if(h==nhstepm) */
3350: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3351: }
1.268 brouard 3352: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3353: } /* end h */
1.268 brouard 3354: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3355: return po;
3356: }
3357:
3358:
1.162 brouard 3359: #ifdef NLOPT
3360: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3361: double fret;
3362: double *xt;
3363: int j;
3364: myfunc_data *d2 = (myfunc_data *) pd;
3365: /* xt = (p1-1); */
3366: xt=vector(1,n);
3367: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3368:
3369: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3370: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3371: printf("Function = %.12lf ",fret);
3372: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3373: printf("\n");
3374: free_vector(xt,1,n);
3375: return fret;
3376: }
3377: #endif
1.126 brouard 3378:
3379: /*************** log-likelihood *************/
3380: double func( double *x)
3381: {
1.226 brouard 3382: int i, ii, j, k, mi, d, kk;
3383: int ioffset=0;
3384: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3385: double **out;
3386: double lli; /* Individual log likelihood */
3387: int s1, s2;
1.228 brouard 3388: 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 3389: double bbh, survp;
3390: long ipmx;
3391: double agexact;
3392: /*extern weight */
3393: /* We are differentiating ll according to initial status */
3394: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3395: /*for(i=1;i<imx;i++)
3396: printf(" %d\n",s[4][i]);
3397: */
1.162 brouard 3398:
1.226 brouard 3399: ++countcallfunc;
1.162 brouard 3400:
1.226 brouard 3401: cov[1]=1.;
1.126 brouard 3402:
1.226 brouard 3403: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3404: ioffset=0;
1.226 brouard 3405: if(mle==1){
3406: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3407: /* Computes the values of the ncovmodel covariates of the model
3408: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3409: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3410: to be observed in j being in i according to the model.
3411: */
1.243 brouard 3412: ioffset=2+nagesqr ;
1.233 brouard 3413: /* Fixed */
1.234 brouard 3414: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3415: 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)*/
3416: }
1.226 brouard 3417: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3418: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3419: has been calculated etc */
3420: /* For an individual i, wav[i] gives the number of effective waves */
3421: /* We compute the contribution to Likelihood of each effective transition
3422: mw[mi][i] is real wave of the mi th effectve wave */
3423: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3424: s2=s[mw[mi+1][i]][i];
3425: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3426: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3427: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3428: */
3429: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3430: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3431: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3432: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3433: }
3434: for (ii=1;ii<=nlstate+ndeath;ii++)
3435: for (j=1;j<=nlstate+ndeath;j++){
3436: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3437: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3438: }
3439: for(d=0; d<dh[mi][i]; d++){
3440: newm=savm;
3441: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3442: cov[2]=agexact;
3443: if(nagesqr==1)
3444: cov[3]= agexact*agexact; /* Should be changed here */
3445: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3446: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3447: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3448: else
3449: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3450: }
3451: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3452: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3453: savm=oldm;
3454: oldm=newm;
3455: } /* end mult */
3456:
3457: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3458: /* But now since version 0.9 we anticipate for bias at large stepm.
3459: * If stepm is larger than one month (smallest stepm) and if the exact delay
3460: * (in months) between two waves is not a multiple of stepm, we rounded to
3461: * the nearest (and in case of equal distance, to the lowest) interval but now
3462: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3463: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3464: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3465: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3466: * -stepm/2 to stepm/2 .
3467: * For stepm=1 the results are the same as for previous versions of Imach.
3468: * For stepm > 1 the results are less biased than in previous versions.
3469: */
1.234 brouard 3470: s1=s[mw[mi][i]][i];
3471: s2=s[mw[mi+1][i]][i];
3472: bbh=(double)bh[mi][i]/(double)stepm;
3473: /* bias bh is positive if real duration
3474: * is higher than the multiple of stepm and negative otherwise.
3475: */
3476: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3477: if( s2 > nlstate){
3478: /* i.e. if s2 is a death state and if the date of death is known
3479: then the contribution to the likelihood is the probability to
3480: die between last step unit time and current step unit time,
3481: which is also equal to probability to die before dh
3482: minus probability to die before dh-stepm .
3483: In version up to 0.92 likelihood was computed
3484: as if date of death was unknown. Death was treated as any other
3485: health state: the date of the interview describes the actual state
3486: and not the date of a change in health state. The former idea was
3487: to consider that at each interview the state was recorded
3488: (healthy, disable or death) and IMaCh was corrected; but when we
3489: introduced the exact date of death then we should have modified
3490: the contribution of an exact death to the likelihood. This new
3491: contribution is smaller and very dependent of the step unit
3492: stepm. It is no more the probability to die between last interview
3493: and month of death but the probability to survive from last
3494: interview up to one month before death multiplied by the
3495: probability to die within a month. Thanks to Chris
3496: Jackson for correcting this bug. Former versions increased
3497: mortality artificially. The bad side is that we add another loop
3498: which slows down the processing. The difference can be up to 10%
3499: lower mortality.
3500: */
3501: /* If, at the beginning of the maximization mostly, the
3502: cumulative probability or probability to be dead is
3503: constant (ie = 1) over time d, the difference is equal to
3504: 0. out[s1][3] = savm[s1][3]: probability, being at state
3505: s1 at precedent wave, to be dead a month before current
3506: wave is equal to probability, being at state s1 at
3507: precedent wave, to be dead at mont of the current
3508: wave. Then the observed probability (that this person died)
3509: is null according to current estimated parameter. In fact,
3510: it should be very low but not zero otherwise the log go to
3511: infinity.
3512: */
1.183 brouard 3513: /* #ifdef INFINITYORIGINAL */
3514: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3515: /* #else */
3516: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3517: /* lli=log(mytinydouble); */
3518: /* else */
3519: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3520: /* #endif */
1.226 brouard 3521: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3522:
1.226 brouard 3523: } else if ( s2==-1 ) { /* alive */
3524: for (j=1,survp=0. ; j<=nlstate; j++)
3525: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3526: /*survp += out[s1][j]; */
3527: lli= log(survp);
3528: }
3529: else if (s2==-4) {
3530: for (j=3,survp=0. ; j<=nlstate; j++)
3531: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3532: lli= log(survp);
3533: }
3534: else if (s2==-5) {
3535: for (j=1,survp=0. ; j<=2; j++)
3536: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3537: lli= log(survp);
3538: }
3539: else{
3540: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3541: /* 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 */
3542: }
3543: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3544: /*if(lli ==000.0)*/
3545: /*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); */
3546: ipmx +=1;
3547: sw += weight[i];
3548: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3549: /* if (lli < log(mytinydouble)){ */
3550: /* 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); */
3551: /* 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]); */
3552: /* } */
3553: } /* end of wave */
3554: } /* end of individual */
3555: } else if(mle==2){
3556: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3557: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3558: for(mi=1; mi<= wav[i]-1; mi++){
3559: for (ii=1;ii<=nlstate+ndeath;ii++)
3560: for (j=1;j<=nlstate+ndeath;j++){
3561: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3562: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3563: }
3564: for(d=0; d<=dh[mi][i]; d++){
3565: newm=savm;
3566: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3567: cov[2]=agexact;
3568: if(nagesqr==1)
3569: cov[3]= agexact*agexact;
3570: for (kk=1; kk<=cptcovage;kk++) {
3571: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3572: }
3573: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3574: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3575: savm=oldm;
3576: oldm=newm;
3577: } /* end mult */
3578:
3579: s1=s[mw[mi][i]][i];
3580: s2=s[mw[mi+1][i]][i];
3581: bbh=(double)bh[mi][i]/(double)stepm;
3582: 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 */
3583: ipmx +=1;
3584: sw += weight[i];
3585: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3586: } /* end of wave */
3587: } /* end of individual */
3588: } else if(mle==3){ /* exponential inter-extrapolation */
3589: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3590: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3591: for(mi=1; mi<= wav[i]-1; mi++){
3592: for (ii=1;ii<=nlstate+ndeath;ii++)
3593: for (j=1;j<=nlstate+ndeath;j++){
3594: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3595: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3596: }
3597: for(d=0; d<dh[mi][i]; d++){
3598: newm=savm;
3599: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3600: cov[2]=agexact;
3601: if(nagesqr==1)
3602: cov[3]= agexact*agexact;
3603: for (kk=1; kk<=cptcovage;kk++) {
3604: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3605: }
3606: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3607: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3608: savm=oldm;
3609: oldm=newm;
3610: } /* end mult */
3611:
3612: s1=s[mw[mi][i]][i];
3613: s2=s[mw[mi+1][i]][i];
3614: bbh=(double)bh[mi][i]/(double)stepm;
3615: 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 */
3616: ipmx +=1;
3617: sw += weight[i];
3618: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3619: } /* end of wave */
3620: } /* end of individual */
3621: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3622: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3623: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3624: for(mi=1; mi<= wav[i]-1; mi++){
3625: for (ii=1;ii<=nlstate+ndeath;ii++)
3626: for (j=1;j<=nlstate+ndeath;j++){
3627: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3628: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3629: }
3630: for(d=0; d<dh[mi][i]; d++){
3631: newm=savm;
3632: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3633: cov[2]=agexact;
3634: if(nagesqr==1)
3635: cov[3]= agexact*agexact;
3636: for (kk=1; kk<=cptcovage;kk++) {
3637: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3638: }
1.126 brouard 3639:
1.226 brouard 3640: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3641: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3642: savm=oldm;
3643: oldm=newm;
3644: } /* end mult */
3645:
3646: s1=s[mw[mi][i]][i];
3647: s2=s[mw[mi+1][i]][i];
3648: if( s2 > nlstate){
3649: lli=log(out[s1][s2] - savm[s1][s2]);
3650: } else if ( s2==-1 ) { /* alive */
3651: for (j=1,survp=0. ; j<=nlstate; j++)
3652: survp += out[s1][j];
3653: lli= log(survp);
3654: }else{
3655: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3656: }
3657: ipmx +=1;
3658: sw += weight[i];
3659: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3660: /* 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 3661: } /* end of wave */
3662: } /* end of individual */
3663: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3664: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3665: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3666: for(mi=1; mi<= wav[i]-1; mi++){
3667: for (ii=1;ii<=nlstate+ndeath;ii++)
3668: for (j=1;j<=nlstate+ndeath;j++){
3669: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3670: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3671: }
3672: for(d=0; d<dh[mi][i]; d++){
3673: newm=savm;
3674: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3675: cov[2]=agexact;
3676: if(nagesqr==1)
3677: cov[3]= agexact*agexact;
3678: for (kk=1; kk<=cptcovage;kk++) {
3679: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3680: }
1.126 brouard 3681:
1.226 brouard 3682: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3683: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3684: savm=oldm;
3685: oldm=newm;
3686: } /* end mult */
3687:
3688: s1=s[mw[mi][i]][i];
3689: s2=s[mw[mi+1][i]][i];
3690: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3691: ipmx +=1;
3692: sw += weight[i];
3693: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3694: /*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]);*/
3695: } /* end of wave */
3696: } /* end of individual */
3697: } /* End of if */
3698: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3699: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3700: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3701: return -l;
1.126 brouard 3702: }
3703:
3704: /*************** log-likelihood *************/
3705: double funcone( double *x)
3706: {
1.228 brouard 3707: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3708: int i, ii, j, k, mi, d, kk;
1.228 brouard 3709: int ioffset=0;
1.131 brouard 3710: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3711: double **out;
3712: double lli; /* Individual log likelihood */
3713: double llt;
3714: int s1, s2;
1.228 brouard 3715: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3716:
1.126 brouard 3717: double bbh, survp;
1.187 brouard 3718: double agexact;
1.214 brouard 3719: double agebegin, ageend;
1.126 brouard 3720: /*extern weight */
3721: /* We are differentiating ll according to initial status */
3722: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3723: /*for(i=1;i<imx;i++)
3724: printf(" %d\n",s[4][i]);
3725: */
3726: cov[1]=1.;
3727:
3728: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3729: ioffset=0;
3730: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3731: /* ioffset=2+nagesqr+cptcovage; */
3732: ioffset=2+nagesqr;
1.232 brouard 3733: /* Fixed */
1.224 brouard 3734: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3735: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3736: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3737: 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)*/
3738: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3739: /* cov[2+6]=covar[Tvar[6]][i]; */
3740: /* cov[2+6]=covar[2][i]; V2 */
3741: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3742: /* cov[2+7]=covar[Tvar[7]][i]; */
3743: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3744: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3745: /* cov[2+9]=covar[Tvar[9]][i]; */
3746: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3747: }
1.232 brouard 3748: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3749: /* 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?)*\/ */
3750: /* } */
1.231 brouard 3751: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3752: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3753: /* } */
1.225 brouard 3754:
1.233 brouard 3755:
3756: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3757: /* Wave varying (but not age varying) */
3758: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3759: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3760: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3761: }
1.232 brouard 3762: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3763: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3764: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3765: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3766: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3767: /* 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 3768: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3769: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3770: /* /\* 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]); *\/ */
3771: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3772: /* } */
1.126 brouard 3773: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3774: for (j=1;j<=nlstate+ndeath;j++){
3775: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3776: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3777: }
1.214 brouard 3778:
3779: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3780: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3781: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3782: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3783: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3784: and mw[mi+1][i]. dh depends on stepm.*/
3785: newm=savm;
1.247 brouard 3786: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3787: cov[2]=agexact;
3788: if(nagesqr==1)
3789: cov[3]= agexact*agexact;
3790: for (kk=1; kk<=cptcovage;kk++) {
3791: if(!FixedV[Tvar[Tage[kk]]])
3792: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3793: else
3794: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3795: }
3796: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3797: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3798: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3799: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3800: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3801: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3802: savm=oldm;
3803: oldm=newm;
1.126 brouard 3804: } /* end mult */
3805:
3806: s1=s[mw[mi][i]][i];
3807: s2=s[mw[mi+1][i]][i];
1.217 brouard 3808: /* if(s2==-1){ */
1.268 brouard 3809: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3810: /* /\* exit(1); *\/ */
3811: /* } */
1.126 brouard 3812: bbh=(double)bh[mi][i]/(double)stepm;
3813: /* bias is positive if real duration
3814: * is higher than the multiple of stepm and negative otherwise.
3815: */
3816: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3817: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3818: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3819: for (j=1,survp=0. ; j<=nlstate; j++)
3820: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3821: lli= log(survp);
1.126 brouard 3822: }else if (mle==1){
1.242 brouard 3823: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3824: } else if(mle==2){
1.242 brouard 3825: 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 3826: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3827: 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 3828: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3829: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3830: } else{ /* mle=0 back to 1 */
1.242 brouard 3831: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3832: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3833: } /* End of if */
3834: ipmx +=1;
3835: sw += weight[i];
3836: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3837: /*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 3838: if(globpr){
1.246 brouard 3839: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3840: %11.6f %11.6f %11.6f ", \
1.242 brouard 3841: 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 3842: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3843: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3844: llt +=ll[k]*gipmx/gsw;
3845: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3846: }
3847: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3848: }
1.232 brouard 3849: } /* end of wave */
3850: } /* end of individual */
3851: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3852: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3853: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3854: if(globpr==0){ /* First time we count the contributions and weights */
3855: gipmx=ipmx;
3856: gsw=sw;
3857: }
3858: return -l;
1.126 brouard 3859: }
3860:
3861:
3862: /*************** function likelione ***********/
3863: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3864: {
3865: /* This routine should help understanding what is done with
3866: the selection of individuals/waves and
3867: to check the exact contribution to the likelihood.
3868: Plotting could be done.
3869: */
3870: int k;
3871:
3872: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3873: strcpy(fileresilk,"ILK_");
1.202 brouard 3874: strcat(fileresilk,fileresu);
1.126 brouard 3875: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3876: printf("Problem with resultfile: %s\n", fileresilk);
3877: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3878: }
1.214 brouard 3879: 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");
3880: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3881: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3882: for(k=1; k<=nlstate; k++)
3883: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3884: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3885: }
3886:
3887: *fretone=(*funcone)(p);
3888: if(*globpri !=0){
3889: fclose(ficresilk);
1.205 brouard 3890: if (mle ==0)
3891: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3892: else if(mle >=1)
3893: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3894: 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 3895: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3896:
3897: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3898: 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 3899: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3900: }
1.207 brouard 3901: 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 3902: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3903: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3904: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3905: fflush(fichtm);
1.205 brouard 3906: }
1.126 brouard 3907: return;
3908: }
3909:
3910:
3911: /*********** Maximum Likelihood Estimation ***************/
3912:
3913: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3914: {
1.165 brouard 3915: int i,j, iter=0;
1.126 brouard 3916: double **xi;
3917: double fret;
3918: double fretone; /* Only one call to likelihood */
3919: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3920:
3921: #ifdef NLOPT
3922: int creturn;
3923: nlopt_opt opt;
3924: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3925: double *lb;
3926: double minf; /* the minimum objective value, upon return */
3927: double * p1; /* Shifted parameters from 0 instead of 1 */
3928: myfunc_data dinst, *d = &dinst;
3929: #endif
3930:
3931:
1.126 brouard 3932: xi=matrix(1,npar,1,npar);
3933: for (i=1;i<=npar;i++)
3934: for (j=1;j<=npar;j++)
3935: xi[i][j]=(i==j ? 1.0 : 0.0);
3936: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3937: strcpy(filerespow,"POW_");
1.126 brouard 3938: strcat(filerespow,fileres);
3939: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3940: printf("Problem with resultfile: %s\n", filerespow);
3941: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3942: }
3943: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3944: for (i=1;i<=nlstate;i++)
3945: for(j=1;j<=nlstate+ndeath;j++)
3946: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3947: fprintf(ficrespow,"\n");
1.162 brouard 3948: #ifdef POWELL
1.126 brouard 3949: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3950: #endif
1.126 brouard 3951:
1.162 brouard 3952: #ifdef NLOPT
3953: #ifdef NEWUOA
3954: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3955: #else
3956: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3957: #endif
3958: lb=vector(0,npar-1);
3959: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3960: nlopt_set_lower_bounds(opt, lb);
3961: nlopt_set_initial_step1(opt, 0.1);
3962:
3963: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3964: d->function = func;
3965: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3966: nlopt_set_min_objective(opt, myfunc, d);
3967: nlopt_set_xtol_rel(opt, ftol);
3968: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3969: printf("nlopt failed! %d\n",creturn);
3970: }
3971: else {
3972: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3973: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3974: iter=1; /* not equal */
3975: }
3976: nlopt_destroy(opt);
3977: #endif
1.126 brouard 3978: free_matrix(xi,1,npar,1,npar);
3979: fclose(ficrespow);
1.203 brouard 3980: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3981: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3982: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3983:
3984: }
3985:
3986: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3987: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3988: {
3989: double **a,**y,*x,pd;
1.203 brouard 3990: /* double **hess; */
1.164 brouard 3991: int i, j;
1.126 brouard 3992: int *indx;
3993:
3994: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3995: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3996: void lubksb(double **a, int npar, int *indx, double b[]) ;
3997: void ludcmp(double **a, int npar, int *indx, double *d) ;
3998: double gompertz(double p[]);
1.203 brouard 3999: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4000:
4001: printf("\nCalculation of the hessian matrix. Wait...\n");
4002: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4003: for (i=1;i<=npar;i++){
1.203 brouard 4004: printf("%d-",i);fflush(stdout);
4005: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4006:
4007: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4008:
4009: /* printf(" %f ",p[i]);
4010: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4011: }
4012:
4013: for (i=1;i<=npar;i++) {
4014: for (j=1;j<=npar;j++) {
4015: if (j>i) {
1.203 brouard 4016: printf(".%d-%d",i,j);fflush(stdout);
4017: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4018: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4019:
4020: hess[j][i]=hess[i][j];
4021: /*printf(" %lf ",hess[i][j]);*/
4022: }
4023: }
4024: }
4025: printf("\n");
4026: fprintf(ficlog,"\n");
4027:
4028: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4029: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4030:
4031: a=matrix(1,npar,1,npar);
4032: y=matrix(1,npar,1,npar);
4033: x=vector(1,npar);
4034: indx=ivector(1,npar);
4035: for (i=1;i<=npar;i++)
4036: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4037: ludcmp(a,npar,indx,&pd);
4038:
4039: for (j=1;j<=npar;j++) {
4040: for (i=1;i<=npar;i++) x[i]=0;
4041: x[j]=1;
4042: lubksb(a,npar,indx,x);
4043: for (i=1;i<=npar;i++){
4044: matcov[i][j]=x[i];
4045: }
4046: }
4047:
4048: printf("\n#Hessian matrix#\n");
4049: fprintf(ficlog,"\n#Hessian matrix#\n");
4050: for (i=1;i<=npar;i++) {
4051: for (j=1;j<=npar;j++) {
1.203 brouard 4052: printf("%.6e ",hess[i][j]);
4053: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4054: }
4055: printf("\n");
4056: fprintf(ficlog,"\n");
4057: }
4058:
1.203 brouard 4059: /* printf("\n#Covariance matrix#\n"); */
4060: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4061: /* for (i=1;i<=npar;i++) { */
4062: /* for (j=1;j<=npar;j++) { */
4063: /* printf("%.6e ",matcov[i][j]); */
4064: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4065: /* } */
4066: /* printf("\n"); */
4067: /* fprintf(ficlog,"\n"); */
4068: /* } */
4069:
1.126 brouard 4070: /* Recompute Inverse */
1.203 brouard 4071: /* for (i=1;i<=npar;i++) */
4072: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4073: /* ludcmp(a,npar,indx,&pd); */
4074:
4075: /* printf("\n#Hessian matrix recomputed#\n"); */
4076:
4077: /* for (j=1;j<=npar;j++) { */
4078: /* for (i=1;i<=npar;i++) x[i]=0; */
4079: /* x[j]=1; */
4080: /* lubksb(a,npar,indx,x); */
4081: /* for (i=1;i<=npar;i++){ */
4082: /* y[i][j]=x[i]; */
4083: /* printf("%.3e ",y[i][j]); */
4084: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4085: /* } */
4086: /* printf("\n"); */
4087: /* fprintf(ficlog,"\n"); */
4088: /* } */
4089:
4090: /* Verifying the inverse matrix */
4091: #ifdef DEBUGHESS
4092: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4093:
1.203 brouard 4094: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4095: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4096:
4097: for (j=1;j<=npar;j++) {
4098: for (i=1;i<=npar;i++){
1.203 brouard 4099: printf("%.2f ",y[i][j]);
4100: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4101: }
4102: printf("\n");
4103: fprintf(ficlog,"\n");
4104: }
1.203 brouard 4105: #endif
1.126 brouard 4106:
4107: free_matrix(a,1,npar,1,npar);
4108: free_matrix(y,1,npar,1,npar);
4109: free_vector(x,1,npar);
4110: free_ivector(indx,1,npar);
1.203 brouard 4111: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4112:
4113:
4114: }
4115:
4116: /*************** hessian matrix ****************/
4117: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4118: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4119: int i;
4120: int l=1, lmax=20;
1.203 brouard 4121: double k1,k2, res, fx;
1.132 brouard 4122: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4123: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4124: int k=0,kmax=10;
4125: double l1;
4126:
4127: fx=func(x);
4128: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4129: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4130: l1=pow(10,l);
4131: delts=delt;
4132: for(k=1 ; k <kmax; k=k+1){
4133: delt = delta*(l1*k);
4134: p2[theta]=x[theta] +delt;
1.145 brouard 4135: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4136: p2[theta]=x[theta]-delt;
4137: k2=func(p2)-fx;
4138: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4139: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4140:
1.203 brouard 4141: #ifdef DEBUGHESSII
1.126 brouard 4142: 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);
4143: 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);
4144: #endif
4145: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4146: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4147: k=kmax;
4148: }
4149: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4150: k=kmax; l=lmax*10;
1.126 brouard 4151: }
4152: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4153: delts=delt;
4154: }
1.203 brouard 4155: } /* End loop k */
1.126 brouard 4156: }
4157: delti[theta]=delts;
4158: return res;
4159:
4160: }
4161:
1.203 brouard 4162: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4163: {
4164: int i;
1.164 brouard 4165: int l=1, lmax=20;
1.126 brouard 4166: double k1,k2,k3,k4,res,fx;
1.132 brouard 4167: double p2[MAXPARM+1];
1.203 brouard 4168: int k, kmax=1;
4169: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4170:
4171: int firstime=0;
1.203 brouard 4172:
1.126 brouard 4173: fx=func(x);
1.203 brouard 4174: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4175: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4176: p2[thetai]=x[thetai]+delti[thetai]*k;
4177: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4178: k1=func(p2)-fx;
4179:
1.203 brouard 4180: p2[thetai]=x[thetai]+delti[thetai]*k;
4181: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4182: k2=func(p2)-fx;
4183:
1.203 brouard 4184: p2[thetai]=x[thetai]-delti[thetai]*k;
4185: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4186: k3=func(p2)-fx;
4187:
1.203 brouard 4188: p2[thetai]=x[thetai]-delti[thetai]*k;
4189: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4190: k4=func(p2)-fx;
1.203 brouard 4191: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4192: if(k1*k2*k3*k4 <0.){
1.208 brouard 4193: firstime=1;
1.203 brouard 4194: kmax=kmax+10;
1.208 brouard 4195: }
4196: if(kmax >=10 || firstime ==1){
1.246 brouard 4197: 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);
4198: 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 4199: 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);
4200: 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);
4201: }
4202: #ifdef DEBUGHESSIJ
4203: v1=hess[thetai][thetai];
4204: v2=hess[thetaj][thetaj];
4205: cv12=res;
4206: /* Computing eigen value of Hessian matrix */
4207: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4208: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4209: if ((lc2 <0) || (lc1 <0) ){
4210: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4211: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4212: 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);
4213: 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);
4214: }
1.126 brouard 4215: #endif
4216: }
4217: return res;
4218: }
4219:
1.203 brouard 4220: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4221: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4222: /* { */
4223: /* int i; */
4224: /* int l=1, lmax=20; */
4225: /* double k1,k2,k3,k4,res,fx; */
4226: /* double p2[MAXPARM+1]; */
4227: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4228: /* int k=0,kmax=10; */
4229: /* double l1; */
4230:
4231: /* fx=func(x); */
4232: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4233: /* l1=pow(10,l); */
4234: /* delts=delt; */
4235: /* for(k=1 ; k <kmax; k=k+1){ */
4236: /* delt = delti*(l1*k); */
4237: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4238: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4239: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4240: /* k1=func(p2)-fx; */
4241:
4242: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4243: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4244: /* k2=func(p2)-fx; */
4245:
4246: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4247: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4248: /* k3=func(p2)-fx; */
4249:
4250: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4251: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4252: /* k4=func(p2)-fx; */
4253: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4254: /* #ifdef DEBUGHESSIJ */
4255: /* 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); */
4256: /* 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); */
4257: /* #endif */
4258: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4259: /* k=kmax; */
4260: /* } */
4261: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4262: /* k=kmax; l=lmax*10; */
4263: /* } */
4264: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4265: /* delts=delt; */
4266: /* } */
4267: /* } /\* End loop k *\/ */
4268: /* } */
4269: /* delti[theta]=delts; */
4270: /* return res; */
4271: /* } */
4272:
4273:
1.126 brouard 4274: /************** Inverse of matrix **************/
4275: void ludcmp(double **a, int n, int *indx, double *d)
4276: {
4277: int i,imax,j,k;
4278: double big,dum,sum,temp;
4279: double *vv;
4280:
4281: vv=vector(1,n);
4282: *d=1.0;
4283: for (i=1;i<=n;i++) {
4284: big=0.0;
4285: for (j=1;j<=n;j++)
4286: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4287: if (big == 0.0){
4288: printf(" Singular Hessian matrix at row %d:\n",i);
4289: for (j=1;j<=n;j++) {
4290: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4291: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4292: }
4293: fflush(ficlog);
4294: fclose(ficlog);
4295: nrerror("Singular matrix in routine ludcmp");
4296: }
1.126 brouard 4297: vv[i]=1.0/big;
4298: }
4299: for (j=1;j<=n;j++) {
4300: for (i=1;i<j;i++) {
4301: sum=a[i][j];
4302: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4303: a[i][j]=sum;
4304: }
4305: big=0.0;
4306: for (i=j;i<=n;i++) {
4307: sum=a[i][j];
4308: for (k=1;k<j;k++)
4309: sum -= a[i][k]*a[k][j];
4310: a[i][j]=sum;
4311: if ( (dum=vv[i]*fabs(sum)) >= big) {
4312: big=dum;
4313: imax=i;
4314: }
4315: }
4316: if (j != imax) {
4317: for (k=1;k<=n;k++) {
4318: dum=a[imax][k];
4319: a[imax][k]=a[j][k];
4320: a[j][k]=dum;
4321: }
4322: *d = -(*d);
4323: vv[imax]=vv[j];
4324: }
4325: indx[j]=imax;
4326: if (a[j][j] == 0.0) a[j][j]=TINY;
4327: if (j != n) {
4328: dum=1.0/(a[j][j]);
4329: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4330: }
4331: }
4332: free_vector(vv,1,n); /* Doesn't work */
4333: ;
4334: }
4335:
4336: void lubksb(double **a, int n, int *indx, double b[])
4337: {
4338: int i,ii=0,ip,j;
4339: double sum;
4340:
4341: for (i=1;i<=n;i++) {
4342: ip=indx[i];
4343: sum=b[ip];
4344: b[ip]=b[i];
4345: if (ii)
4346: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4347: else if (sum) ii=i;
4348: b[i]=sum;
4349: }
4350: for (i=n;i>=1;i--) {
4351: sum=b[i];
4352: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4353: b[i]=sum/a[i][i];
4354: }
4355: }
4356:
4357: void pstamp(FILE *fichier)
4358: {
1.196 brouard 4359: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4360: }
4361:
1.253 brouard 4362:
4363:
1.126 brouard 4364: /************ Frequencies ********************/
1.251 brouard 4365: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4366: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4367: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4368: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4369:
1.265 brouard 4370: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4371: int iind=0, iage=0;
4372: int mi; /* Effective wave */
4373: int first;
4374: double ***freq; /* Frequencies */
1.268 brouard 4375: 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 */
4376: 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 4377: double *meanq, *stdq, *idq;
1.226 brouard 4378: double **meanqt;
4379: double *pp, **prop, *posprop, *pospropt;
4380: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4381: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4382: double agebegin, ageend;
4383:
4384: pp=vector(1,nlstate);
1.251 brouard 4385: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4386: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4387: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4388: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4389: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4390: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4391: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4392: meanqt=matrix(1,lastpass,1,nqtveff);
4393: strcpy(fileresp,"P_");
4394: strcat(fileresp,fileresu);
4395: /*strcat(fileresphtm,fileresu);*/
4396: if((ficresp=fopen(fileresp,"w"))==NULL) {
4397: printf("Problem with prevalence resultfile: %s\n", fileresp);
4398: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4399: exit(0);
4400: }
1.240 brouard 4401:
1.226 brouard 4402: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4403: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4404: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4405: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4406: fflush(ficlog);
4407: exit(70);
4408: }
4409: else{
4410: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4411: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4412: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4413: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4414: }
1.237 brouard 4415: 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 4416:
1.226 brouard 4417: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4418: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4419: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4420: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4421: fflush(ficlog);
4422: exit(70);
1.240 brouard 4423: } else{
1.226 brouard 4424: 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 4425: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4426: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4427: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4428: }
1.240 brouard 4429: 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);
4430:
1.253 brouard 4431: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4432: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4433: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4434: j1=0;
1.126 brouard 4435:
1.227 brouard 4436: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4437: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4438: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4439:
4440:
1.226 brouard 4441: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4442: reference=low_education V1=0,V2=0
4443: med_educ V1=1 V2=0,
4444: high_educ V1=0 V2=1
4445: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4446: */
1.249 brouard 4447: dateintsum=0;
4448: k2cpt=0;
4449:
1.253 brouard 4450: if(cptcoveff == 0 )
1.265 brouard 4451: nl=1; /* Constant and age model only */
1.253 brouard 4452: else
4453: nl=2;
1.265 brouard 4454:
4455: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4456: /* Loop on nj=1 or 2 if dummy covariates j!=0
4457: * Loop on j1(1 to 2**cptcoveff) covariate combination
4458: * freq[s1][s2][iage] =0.
4459: * Loop on iind
4460: * ++freq[s1][s2][iage] weighted
4461: * end iind
4462: * if covariate and j!0
4463: * headers Variable on one line
4464: * endif cov j!=0
4465: * header of frequency table by age
4466: * Loop on age
4467: * pp[s1]+=freq[s1][s2][iage] weighted
4468: * pos+=freq[s1][s2][iage] weighted
4469: * Loop on s1 initial state
4470: * fprintf(ficresp
4471: * end s1
4472: * end age
4473: * if j!=0 computes starting values
4474: * end compute starting values
4475: * end j1
4476: * end nl
4477: */
1.253 brouard 4478: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4479: if(nj==1)
4480: j=0; /* First pass for the constant */
1.265 brouard 4481: else{
1.253 brouard 4482: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4483: }
1.251 brouard 4484: first=1;
1.265 brouard 4485: 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 4486: posproptt=0.;
4487: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4488: scanf("%d", i);*/
4489: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4490: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4491: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4492: freq[i][s2][m]=0;
1.251 brouard 4493:
4494: for (i=1; i<=nlstate; i++) {
1.240 brouard 4495: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4496: prop[i][m]=0;
4497: posprop[i]=0;
4498: pospropt[i]=0;
4499: }
1.283 brouard 4500: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4501: idq[z1]=0.;
4502: meanq[z1]=0.;
4503: stdq[z1]=0.;
1.283 brouard 4504: }
4505: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4506: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4507: /* meanqt[m][z1]=0.; */
4508: /* } */
4509: /* } */
1.251 brouard 4510: /* dateintsum=0; */
4511: /* k2cpt=0; */
4512:
1.265 brouard 4513: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4514: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4515: bool=1;
4516: if(j !=0){
4517: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4518: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4519: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4520: /* if(Tvaraff[z1] ==-20){ */
4521: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4522: /* }else if(Tvaraff[z1] ==-10){ */
4523: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4524: /* }else */
4525: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4526: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4527: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4528: /* 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",
4529: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4530: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4531: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4532: } /* Onlyf fixed */
4533: } /* end z1 */
4534: } /* cptcovn > 0 */
4535: } /* end any */
4536: }/* end j==0 */
1.265 brouard 4537: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4538: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4539: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4540: m=mw[mi][iind];
4541: if(j!=0){
4542: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4543: for (z1=1; z1<=cptcoveff; z1++) {
4544: if( Fixed[Tmodelind[z1]]==1){
4545: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4546: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4547: value is -1, we don't select. It differs from the
4548: constant and age model which counts them. */
4549: bool=0; /* not selected */
4550: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4551: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4552: bool=0;
4553: }
4554: }
4555: }
4556: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4557: } /* end j==0 */
4558: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4559: if(bool==1){ /*Selected */
1.251 brouard 4560: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4561: and mw[mi+1][iind]. dh depends on stepm. */
4562: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4563: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4564: if(m >=firstpass && m <=lastpass){
4565: k2=anint[m][iind]+(mint[m][iind]/12.);
4566: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4567: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4568: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4569: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4570: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4571: if (m<lastpass) {
4572: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4573: /* 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]); */
4574: if(s[m][iind]==-1)
4575: 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.));
4576: 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 4577: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4578: idq[z1]=idq[z1]+weight[iind];
4579: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4580: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4581: }
1.251 brouard 4582: /* if((int)agev[m][iind] == 55) */
4583: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4584: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4585: 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 4586: }
1.251 brouard 4587: } /* end if between passes */
4588: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4589: dateintsum=dateintsum+k2; /* on all covariates ?*/
4590: k2cpt++;
4591: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4592: }
1.251 brouard 4593: }else{
4594: bool=1;
4595: }/* end bool 2 */
4596: } /* end m */
1.284 brouard 4597: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4598: /* idq[z1]=idq[z1]+weight[iind]; */
4599: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4600: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4601: /* } */
1.251 brouard 4602: } /* end bool */
4603: } /* end iind = 1 to imx */
4604: /* prop[s][age] is feeded for any initial and valid live state as well as
4605: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4606:
4607:
4608: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4609: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4610: pstamp(ficresp);
1.251 brouard 4611: if (cptcoveff>0 && j!=0){
1.265 brouard 4612: pstamp(ficresp);
1.251 brouard 4613: printf( "\n#********** Variable ");
4614: fprintf(ficresp, "\n#********** Variable ");
4615: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4616: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4617: fprintf(ficlog, "\n#********** Variable ");
4618: for (z1=1; z1<=cptcoveff; z1++){
4619: if(!FixedV[Tvaraff[z1]]){
4620: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4621: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4622: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4623: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4624: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4625: }else{
1.251 brouard 4626: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4627: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4628: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4629: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4630: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4631: }
4632: }
4633: printf( "**********\n#");
4634: fprintf(ficresp, "**********\n#");
4635: fprintf(ficresphtm, "**********</h3>\n");
4636: fprintf(ficresphtmfr, "**********</h3>\n");
4637: fprintf(ficlog, "**********\n");
4638: }
1.284 brouard 4639: /*
4640: Printing means of quantitative variables if any
4641: */
4642: for (z1=1; z1<= nqfveff; z1++) {
1.285 ! brouard 4643: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4644: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4645: if(weightopt==1){
4646: printf(" Weighted mean and standard deviation of");
4647: fprintf(ficlog," Weighted mean and standard deviation of");
4648: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4649: }
1.285 ! brouard 4650: 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]));
! 4651: 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]));
! 4652: 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 4653: }
4654: /* for (z1=1; z1<= nqtveff; z1++) { */
4655: /* for(m=1;m<=lastpass;m++){ */
4656: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4657: /* } */
4658: /* } */
1.283 brouard 4659:
1.251 brouard 4660: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4661: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4662: fprintf(ficresp, " Age");
4663: 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 4664: for(i=1; i<=nlstate;i++) {
1.265 brouard 4665: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4666: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4667: }
1.265 brouard 4668: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4669: fprintf(ficresphtm, "\n");
4670:
4671: /* Header of frequency table by age */
4672: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4673: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4674: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4675: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4676: if(s2!=0 && m!=0)
4677: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4678: }
1.226 brouard 4679: }
1.251 brouard 4680: fprintf(ficresphtmfr, "\n");
4681:
4682: /* For each age */
4683: for(iage=iagemin; iage <= iagemax+3; iage++){
4684: fprintf(ficresphtm,"<tr>");
4685: if(iage==iagemax+1){
4686: fprintf(ficlog,"1");
4687: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4688: }else if(iage==iagemax+2){
4689: fprintf(ficlog,"0");
4690: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4691: }else if(iage==iagemax+3){
4692: fprintf(ficlog,"Total");
4693: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4694: }else{
1.240 brouard 4695: if(first==1){
1.251 brouard 4696: first=0;
4697: printf("See log file for details...\n");
4698: }
4699: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4700: fprintf(ficlog,"Age %d", iage);
4701: }
1.265 brouard 4702: for(s1=1; s1 <=nlstate ; s1++){
4703: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4704: pp[s1] += freq[s1][m][iage];
1.251 brouard 4705: }
1.265 brouard 4706: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4707: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4708: pos += freq[s1][m][iage];
4709: if(pp[s1]>=1.e-10){
1.251 brouard 4710: if(first==1){
1.265 brouard 4711: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4712: }
1.265 brouard 4713: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4714: }else{
4715: if(first==1)
1.265 brouard 4716: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4717: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4718: }
4719: }
4720:
1.265 brouard 4721: for(s1=1; s1 <=nlstate ; s1++){
4722: /* posprop[s1]=0; */
4723: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4724: pp[s1] += freq[s1][m][iage];
4725: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4726:
4727: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4728: pos += pp[s1]; /* pos is the total number of transitions until this age */
4729: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4730: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4731: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4732: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4733: }
4734:
4735: /* Writing ficresp */
4736: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4737: if( iage <= iagemax){
4738: fprintf(ficresp," %d",iage);
4739: }
4740: }else if( nj==2){
4741: if( iage <= iagemax){
4742: fprintf(ficresp," %d",iage);
4743: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4744: }
1.240 brouard 4745: }
1.265 brouard 4746: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4747: if(pos>=1.e-5){
1.251 brouard 4748: if(first==1)
1.265 brouard 4749: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4750: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4751: }else{
4752: if(first==1)
1.265 brouard 4753: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4754: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4755: }
4756: if( iage <= iagemax){
4757: if(pos>=1.e-5){
1.265 brouard 4758: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4759: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4760: }else if( nj==2){
4761: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4762: }
4763: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4764: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4765: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4766: } else{
4767: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4768: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4769: }
1.240 brouard 4770: }
1.265 brouard 4771: pospropt[s1] +=posprop[s1];
4772: } /* end loop s1 */
1.251 brouard 4773: /* pospropt=0.; */
1.265 brouard 4774: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4775: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4776: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4777: if(first==1){
1.265 brouard 4778: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4779: }
1.265 brouard 4780: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4781: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4782: }
1.265 brouard 4783: if(s1!=0 && m!=0)
4784: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4785: }
1.265 brouard 4786: } /* end loop s1 */
1.251 brouard 4787: posproptt=0.;
1.265 brouard 4788: for(s1=1; s1 <=nlstate; s1++){
4789: posproptt += pospropt[s1];
1.251 brouard 4790: }
4791: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4792: fprintf(ficresphtm,"</tr>\n");
4793: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4794: if(iage <= iagemax)
4795: fprintf(ficresp,"\n");
1.240 brouard 4796: }
1.251 brouard 4797: if(first==1)
4798: printf("Others in log...\n");
4799: fprintf(ficlog,"\n");
4800: } /* end loop age iage */
1.265 brouard 4801:
1.251 brouard 4802: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4803: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4804: if(posproptt < 1.e-5){
1.265 brouard 4805: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4806: }else{
1.265 brouard 4807: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4808: }
1.226 brouard 4809: }
1.251 brouard 4810: fprintf(ficresphtm,"</tr>\n");
4811: fprintf(ficresphtm,"</table>\n");
4812: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4813: if(posproptt < 1.e-5){
1.251 brouard 4814: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4815: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4816: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4817: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4818: invalidvarcomb[j1]=1;
1.226 brouard 4819: }else{
1.251 brouard 4820: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4821: invalidvarcomb[j1]=0;
1.226 brouard 4822: }
1.251 brouard 4823: fprintf(ficresphtmfr,"</table>\n");
4824: fprintf(ficlog,"\n");
4825: if(j!=0){
4826: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4827: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4828: for(k=1; k <=(nlstate+ndeath); k++){
4829: if (k != i) {
1.265 brouard 4830: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4831: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4832: if(j1==1){ /* All dummy covariates to zero */
4833: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4834: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4835: printf("%d%d ",i,k);
4836: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4837: 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]));
4838: 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]));
4839: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4840: }
1.253 brouard 4841: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4842: for(iage=iagemin; iage <= iagemax+3; iage++){
4843: x[iage]= (double)iage;
4844: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4845: /* 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 4846: }
1.268 brouard 4847: /* Some are not finite, but linreg will ignore these ages */
4848: no=0;
1.253 brouard 4849: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4850: pstart[s1]=b;
4851: pstart[s1-1]=a;
1.252 brouard 4852: }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 */
4853: 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]);
4854: 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 4855: 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 4856: printf("%d%d ",i,k);
4857: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4858: 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 4859: }else{ /* Other cases, like quantitative fixed or varying covariates */
4860: ;
4861: }
4862: /* printf("%12.7f )", param[i][jj][k]); */
4863: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4864: s1++;
1.251 brouard 4865: } /* end jj */
4866: } /* end k!= i */
4867: } /* end k */
1.265 brouard 4868: } /* end i, s1 */
1.251 brouard 4869: } /* end j !=0 */
4870: } /* end selected combination of covariate j1 */
4871: if(j==0){ /* We can estimate starting values from the occurences in each case */
4872: printf("#Freqsummary: Starting values for the constants:\n");
4873: fprintf(ficlog,"\n");
1.265 brouard 4874: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4875: for(k=1; k <=(nlstate+ndeath); k++){
4876: if (k != i) {
4877: printf("%d%d ",i,k);
4878: fprintf(ficlog,"%d%d ",i,k);
4879: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4880: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4881: if(jj==1){ /* Age has to be done */
1.265 brouard 4882: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4883: 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]));
4884: 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 4885: }
4886: /* printf("%12.7f )", param[i][jj][k]); */
4887: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4888: s1++;
1.250 brouard 4889: }
1.251 brouard 4890: printf("\n");
4891: fprintf(ficlog,"\n");
1.250 brouard 4892: }
4893: }
1.284 brouard 4894: } /* end of state i */
1.251 brouard 4895: printf("#Freqsummary\n");
4896: fprintf(ficlog,"\n");
1.265 brouard 4897: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4898: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4899: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4900: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4901: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4902: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4903: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4904: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4905: /* } */
4906: }
1.265 brouard 4907: } /* end loop s1 */
1.251 brouard 4908:
4909: printf("\n");
4910: fprintf(ficlog,"\n");
4911: } /* end j=0 */
1.249 brouard 4912: } /* end j */
1.252 brouard 4913:
1.253 brouard 4914: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4915: for(i=1, jk=1; i <=nlstate; i++){
4916: for(j=1; j <=nlstate+ndeath; j++){
4917: if(j!=i){
4918: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4919: printf("%1d%1d",i,j);
4920: fprintf(ficparo,"%1d%1d",i,j);
4921: for(k=1; k<=ncovmodel;k++){
4922: /* printf(" %lf",param[i][j][k]); */
4923: /* fprintf(ficparo," %lf",param[i][j][k]); */
4924: p[jk]=pstart[jk];
4925: printf(" %f ",pstart[jk]);
4926: fprintf(ficparo," %f ",pstart[jk]);
4927: jk++;
4928: }
4929: printf("\n");
4930: fprintf(ficparo,"\n");
4931: }
4932: }
4933: }
4934: } /* end mle=-2 */
1.226 brouard 4935: dateintmean=dateintsum/k2cpt;
1.240 brouard 4936:
1.226 brouard 4937: fclose(ficresp);
4938: fclose(ficresphtm);
4939: fclose(ficresphtmfr);
1.283 brouard 4940: free_vector(idq,1,nqfveff);
1.226 brouard 4941: free_vector(meanq,1,nqfveff);
1.284 brouard 4942: free_vector(stdq,1,nqfveff);
1.226 brouard 4943: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4944: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4945: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4946: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4947: free_vector(pospropt,1,nlstate);
4948: free_vector(posprop,1,nlstate);
1.251 brouard 4949: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4950: free_vector(pp,1,nlstate);
4951: /* End of freqsummary */
4952: }
1.126 brouard 4953:
1.268 brouard 4954: /* Simple linear regression */
4955: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4956:
4957: /* y=a+bx regression */
4958: double sumx = 0.0; /* sum of x */
4959: double sumx2 = 0.0; /* sum of x**2 */
4960: double sumxy = 0.0; /* sum of x * y */
4961: double sumy = 0.0; /* sum of y */
4962: double sumy2 = 0.0; /* sum of y**2 */
4963: double sume2 = 0.0; /* sum of square or residuals */
4964: double yhat;
4965:
4966: double denom=0;
4967: int i;
4968: int ne=*no;
4969:
4970: for ( i=ifi, ne=0;i<=ila;i++) {
4971: if(!isfinite(x[i]) || !isfinite(y[i])){
4972: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4973: continue;
4974: }
4975: ne=ne+1;
4976: sumx += x[i];
4977: sumx2 += x[i]*x[i];
4978: sumxy += x[i] * y[i];
4979: sumy += y[i];
4980: sumy2 += y[i]*y[i];
4981: denom = (ne * sumx2 - sumx*sumx);
4982: /* 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); */
4983: }
4984:
4985: denom = (ne * sumx2 - sumx*sumx);
4986: if (denom == 0) {
4987: // vertical, slope m is infinity
4988: *b = INFINITY;
4989: *a = 0;
4990: if (r) *r = 0;
4991: return 1;
4992: }
4993:
4994: *b = (ne * sumxy - sumx * sumy) / denom;
4995: *a = (sumy * sumx2 - sumx * sumxy) / denom;
4996: if (r!=NULL) {
4997: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
4998: sqrt((sumx2 - sumx*sumx/ne) *
4999: (sumy2 - sumy*sumy/ne));
5000: }
5001: *no=ne;
5002: for ( i=ifi, ne=0;i<=ila;i++) {
5003: if(!isfinite(x[i]) || !isfinite(y[i])){
5004: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5005: continue;
5006: }
5007: ne=ne+1;
5008: yhat = y[i] - *a -*b* x[i];
5009: sume2 += yhat * yhat ;
5010:
5011: denom = (ne * sumx2 - sumx*sumx);
5012: /* 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); */
5013: }
5014: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5015: *sa= *sb * sqrt(sumx2/ne);
5016:
5017: return 0;
5018: }
5019:
1.126 brouard 5020: /************ Prevalence ********************/
1.227 brouard 5021: 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)
5022: {
5023: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5024: in each health status at the date of interview (if between dateprev1 and dateprev2).
5025: We still use firstpass and lastpass as another selection.
5026: */
1.126 brouard 5027:
1.227 brouard 5028: int i, m, jk, j1, bool, z1,j, iv;
5029: int mi; /* Effective wave */
5030: int iage;
5031: double agebegin, ageend;
5032:
5033: double **prop;
5034: double posprop;
5035: double y2; /* in fractional years */
5036: int iagemin, iagemax;
5037: int first; /** to stop verbosity which is redirected to log file */
5038:
5039: iagemin= (int) agemin;
5040: iagemax= (int) agemax;
5041: /*pp=vector(1,nlstate);*/
1.251 brouard 5042: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5043: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5044: j1=0;
1.222 brouard 5045:
1.227 brouard 5046: /*j=cptcoveff;*/
5047: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5048:
1.227 brouard 5049: first=1;
5050: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5051: for (i=1; i<=nlstate; i++)
1.251 brouard 5052: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5053: prop[i][iage]=0.0;
5054: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5055: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5056: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5057:
5058: for (i=1; i<=imx; i++) { /* Each individual */
5059: bool=1;
5060: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5061: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5062: m=mw[mi][i];
5063: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5064: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5065: for (z1=1; z1<=cptcoveff; z1++){
5066: if( Fixed[Tmodelind[z1]]==1){
5067: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5068: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5069: bool=0;
5070: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5071: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5072: bool=0;
5073: }
5074: }
5075: if(bool==1){ /* Otherwise we skip that wave/person */
5076: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5077: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5078: if(m >=firstpass && m <=lastpass){
5079: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5080: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5081: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5082: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5083: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5084: 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);
5085: exit(1);
5086: }
5087: if (s[m][i]>0 && s[m][i]<=nlstate) {
5088: /*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]]);*/
5089: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5090: prop[s[m][i]][iagemax+3] += weight[i];
5091: } /* end valid statuses */
5092: } /* end selection of dates */
5093: } /* end selection of waves */
5094: } /* end bool */
5095: } /* end wave */
5096: } /* end individual */
5097: for(i=iagemin; i <= iagemax+3; i++){
5098: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5099: posprop += prop[jk][i];
5100: }
5101:
5102: for(jk=1; jk <=nlstate ; jk++){
5103: if( i <= iagemax){
5104: if(posprop>=1.e-5){
5105: probs[i][jk][j1]= prop[jk][i]/posprop;
5106: } else{
5107: if(first==1){
5108: first=0;
1.266 brouard 5109: 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]);
5110: fprintf(ficlog,"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]);
5111: }else{
5112: fprintf(ficlog,"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]);
1.227 brouard 5113: }
5114: }
5115: }
5116: }/* end jk */
5117: }/* end i */
1.222 brouard 5118: /*} *//* end i1 */
1.227 brouard 5119: } /* end j1 */
1.222 brouard 5120:
1.227 brouard 5121: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5122: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5123: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5124: } /* End of prevalence */
1.126 brouard 5125:
5126: /************* Waves Concatenation ***************/
5127:
5128: 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)
5129: {
5130: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5131: Death is a valid wave (if date is known).
5132: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5133: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5134: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5135: */
1.126 brouard 5136:
1.224 brouard 5137: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5138: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5139: double sum=0., jmean=0.;*/
1.224 brouard 5140: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5141: int j, k=0,jk, ju, jl;
5142: double sum=0.;
5143: first=0;
1.214 brouard 5144: firstwo=0;
1.217 brouard 5145: firsthree=0;
1.218 brouard 5146: firstfour=0;
1.164 brouard 5147: jmin=100000;
1.126 brouard 5148: jmax=-1;
5149: jmean=0.;
1.224 brouard 5150:
5151: /* Treating live states */
1.214 brouard 5152: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5153: mi=0; /* First valid wave */
1.227 brouard 5154: mli=0; /* Last valid wave */
1.126 brouard 5155: m=firstpass;
1.214 brouard 5156: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5157: 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 */
5158: mli=m-1;/* mw[++mi][i]=m-1; */
5159: }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 */
5160: mw[++mi][i]=m;
5161: mli=m;
1.224 brouard 5162: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5163: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5164: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5165: }
1.227 brouard 5166: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5167: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5168: break;
1.224 brouard 5169: #else
1.227 brouard 5170: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5171: if(firsthree == 0){
1.262 brouard 5172: 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 5173: firsthree=1;
5174: }
1.262 brouard 5175: 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 5176: mw[++mi][i]=m;
5177: mli=m;
5178: }
5179: if(s[m][i]==-2){ /* Vital status is really unknown */
5180: nbwarn++;
5181: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5182: 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);
5183: 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);
5184: }
5185: break;
5186: }
5187: break;
1.224 brouard 5188: #endif
1.227 brouard 5189: }/* End m >= lastpass */
1.126 brouard 5190: }/* end while */
1.224 brouard 5191:
1.227 brouard 5192: /* 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 5193: /* After last pass */
1.224 brouard 5194: /* Treating death states */
1.214 brouard 5195: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5196: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5197: /* } */
1.126 brouard 5198: mi++; /* Death is another wave */
5199: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5200: /* Only death is a correct wave */
1.126 brouard 5201: mw[mi][i]=m;
1.257 brouard 5202: } /* else not in a death state */
1.224 brouard 5203: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5204: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5205: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5206: 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 */
5207: nbwarn++;
5208: if(firstfiv==0){
5209: 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 );
5210: firstfiv=1;
5211: }else{
5212: 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 );
5213: }
5214: }else{ /* Death occured afer last wave potential bias */
5215: nberr++;
5216: if(firstwo==0){
1.257 brouard 5217: 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 5218: firstwo=1;
5219: }
1.257 brouard 5220: 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 5221: }
1.257 brouard 5222: }else{ /* if date of interview is unknown */
1.227 brouard 5223: /* death is known but not confirmed by death status at any wave */
5224: if(firstfour==0){
5225: 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 );
5226: firstfour=1;
5227: }
5228: 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 5229: }
1.224 brouard 5230: } /* end if date of death is known */
5231: #endif
5232: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5233: /* wav[i]=mw[mi][i]; */
1.126 brouard 5234: if(mi==0){
5235: nbwarn++;
5236: if(first==0){
1.227 brouard 5237: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5238: first=1;
1.126 brouard 5239: }
5240: if(first==1){
1.227 brouard 5241: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5242: }
5243: } /* end mi==0 */
5244: } /* End individuals */
1.214 brouard 5245: /* wav and mw are no more changed */
1.223 brouard 5246:
1.214 brouard 5247:
1.126 brouard 5248: for(i=1; i<=imx; i++){
5249: for(mi=1; mi<wav[i];mi++){
5250: if (stepm <=0)
1.227 brouard 5251: dh[mi][i]=1;
1.126 brouard 5252: else{
1.260 brouard 5253: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5254: if (agedc[i] < 2*AGESUP) {
5255: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5256: if(j==0) j=1; /* Survives at least one month after exam */
5257: else if(j<0){
5258: nberr++;
5259: 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]);
5260: j=1; /* Temporary Dangerous patch */
5261: 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);
5262: 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]);
5263: 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);
5264: }
5265: k=k+1;
5266: if (j >= jmax){
5267: jmax=j;
5268: ijmax=i;
5269: }
5270: if (j <= jmin){
5271: jmin=j;
5272: ijmin=i;
5273: }
5274: sum=sum+j;
5275: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5276: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5277: }
5278: }
5279: else{
5280: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5281: /* 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 5282:
1.227 brouard 5283: k=k+1;
5284: if (j >= jmax) {
5285: jmax=j;
5286: ijmax=i;
5287: }
5288: else if (j <= jmin){
5289: jmin=j;
5290: ijmin=i;
5291: }
5292: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5293: /*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]);*/
5294: if(j<0){
5295: nberr++;
5296: 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]);
5297: 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]);
5298: }
5299: sum=sum+j;
5300: }
5301: jk= j/stepm;
5302: jl= j -jk*stepm;
5303: ju= j -(jk+1)*stepm;
5304: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5305: if(jl==0){
5306: dh[mi][i]=jk;
5307: bh[mi][i]=0;
5308: }else{ /* We want a negative bias in order to only have interpolation ie
5309: * to avoid the price of an extra matrix product in likelihood */
5310: dh[mi][i]=jk+1;
5311: bh[mi][i]=ju;
5312: }
5313: }else{
5314: if(jl <= -ju){
5315: dh[mi][i]=jk;
5316: bh[mi][i]=jl; /* bias is positive if real duration
5317: * is higher than the multiple of stepm and negative otherwise.
5318: */
5319: }
5320: else{
5321: dh[mi][i]=jk+1;
5322: bh[mi][i]=ju;
5323: }
5324: if(dh[mi][i]==0){
5325: dh[mi][i]=1; /* At least one step */
5326: bh[mi][i]=ju; /* At least one step */
5327: /* 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);*/
5328: }
5329: } /* end if mle */
1.126 brouard 5330: }
5331: } /* end wave */
5332: }
5333: jmean=sum/k;
5334: 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 5335: 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 5336: }
1.126 brouard 5337:
5338: /*********** Tricode ****************************/
1.220 brouard 5339: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5340: {
5341: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5342: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5343: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5344: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5345: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5346: */
1.130 brouard 5347:
1.242 brouard 5348: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5349: int modmaxcovj=0; /* Modality max of covariates j */
5350: int cptcode=0; /* Modality max of covariates j */
5351: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5352:
5353:
1.242 brouard 5354: /* cptcoveff=0; */
5355: /* *cptcov=0; */
1.126 brouard 5356:
1.242 brouard 5357: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 ! brouard 5358: for (k=1; k <= maxncov; k++)
! 5359: for(j=1; j<=2; j++)
! 5360: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5361:
1.242 brouard 5362: /* Loop on covariates without age and products and no quantitative variable */
5363: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
5364: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5365: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5366: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5367: switch(Fixed[k]) {
5368: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5369: 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*/
5370: ij=(int)(covar[Tvar[k]][i]);
5371: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5372: * If product of Vn*Vm, still boolean *:
5373: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5374: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5375: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5376: modality of the nth covariate of individual i. */
5377: if (ij > modmaxcovj)
5378: modmaxcovj=ij;
5379: else if (ij < modmincovj)
5380: modmincovj=ij;
5381: if ((ij < -1) && (ij > NCOVMAX)){
5382: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5383: exit(1);
5384: }else
5385: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5386: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5387: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5388: /* getting the maximum value of the modality of the covariate
5389: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5390: female ies 1, then modmaxcovj=1.
5391: */
5392: } /* end for loop on individuals i */
5393: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5394: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5395: cptcode=modmaxcovj;
5396: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5397: /*for (i=0; i<=cptcode; i++) {*/
5398: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5399: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5400: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5401: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5402: if( j != -1){
5403: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5404: covariate for which somebody answered excluding
5405: undefined. Usually 2: 0 and 1. */
5406: }
5407: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5408: covariate for which somebody answered including
5409: undefined. Usually 3: -1, 0 and 1. */
5410: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5411: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5412: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5413:
1.242 brouard 5414: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5415: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5416: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5417: /* modmincovj=3; modmaxcovj = 7; */
5418: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5419: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5420: /* defining two dummy variables: variables V1_1 and V1_2.*/
5421: /* nbcode[Tvar[j]][ij]=k; */
5422: /* nbcode[Tvar[j]][1]=0; */
5423: /* nbcode[Tvar[j]][2]=1; */
5424: /* nbcode[Tvar[j]][3]=2; */
5425: /* To be continued (not working yet). */
5426: ij=0; /* ij is similar to i but can jump over null modalities */
5427: 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*/
5428: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5429: break;
5430: }
5431: ij++;
5432: 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*/
5433: cptcode = ij; /* New max modality for covar j */
5434: } /* end of loop on modality i=-1 to 1 or more */
5435: break;
5436: case 1: /* Testing on varying covariate, could be simple and
5437: * should look at waves or product of fixed *
5438: * varying. No time to test -1, assuming 0 and 1 only */
5439: ij=0;
5440: for(i=0; i<=1;i++){
5441: nbcode[Tvar[k]][++ij]=i;
5442: }
5443: break;
5444: default:
5445: break;
5446: } /* end switch */
5447: } /* end dummy test */
5448:
5449: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
5450: /* /\*recode from 0 *\/ */
5451: /* k is a modality. If we have model=V1+V1*sex */
5452: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
5453: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
5454: /* } */
5455: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
5456: /* if (ij > ncodemax[j]) { */
5457: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5458: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5459: /* break; */
5460: /* } */
5461: /* } /\* end of loop on modality k *\/ */
5462: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
5463:
5464: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5465: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5466: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5467: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5468: 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 */
5469: 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 */
5470: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5471: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5472:
5473: ij=0;
5474: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5475: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5476: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5477: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5478: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5479: /* If product not in single variable we don't print results */
5480: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5481: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5482: 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*/
5483: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5484: 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 */
5485: if(Fixed[k]!=0)
5486: anyvaryingduminmodel=1;
5487: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5488: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5489: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5490: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5491: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5492: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5493: }
5494: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5495: /* ij--; */
5496: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5497: *cptcov=ij; /*Number of total real effective covariates: effective
5498: * because they can be excluded from the model and real
5499: * if in the model but excluded because missing values, but how to get k from ij?*/
5500: for(j=ij+1; j<= cptcovt; j++){
5501: Tvaraff[j]=0;
5502: Tmodelind[j]=0;
5503: }
5504: for(j=ntveff+1; j<= cptcovt; j++){
5505: TmodelInvind[j]=0;
5506: }
5507: /* To be sorted */
5508: ;
5509: }
1.126 brouard 5510:
1.145 brouard 5511:
1.126 brouard 5512: /*********** Health Expectancies ****************/
5513:
1.235 brouard 5514: 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 5515:
5516: {
5517: /* Health expectancies, no variances */
1.164 brouard 5518: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5519: int nhstepma, nstepma; /* Decreasing with age */
5520: double age, agelim, hf;
5521: double ***p3mat;
5522: double eip;
5523:
1.238 brouard 5524: /* pstamp(ficreseij); */
1.126 brouard 5525: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5526: fprintf(ficreseij,"# Age");
5527: for(i=1; i<=nlstate;i++){
5528: for(j=1; j<=nlstate;j++){
5529: fprintf(ficreseij," e%1d%1d ",i,j);
5530: }
5531: fprintf(ficreseij," e%1d. ",i);
5532: }
5533: fprintf(ficreseij,"\n");
5534:
5535:
5536: if(estepm < stepm){
5537: printf ("Problem %d lower than %d\n",estepm, stepm);
5538: }
5539: else hstepm=estepm;
5540: /* We compute the life expectancy from trapezoids spaced every estepm months
5541: * This is mainly to measure the difference between two models: for example
5542: * if stepm=24 months pijx are given only every 2 years and by summing them
5543: * we are calculating an estimate of the Life Expectancy assuming a linear
5544: * progression in between and thus overestimating or underestimating according
5545: * to the curvature of the survival function. If, for the same date, we
5546: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5547: * to compare the new estimate of Life expectancy with the same linear
5548: * hypothesis. A more precise result, taking into account a more precise
5549: * curvature will be obtained if estepm is as small as stepm. */
5550:
5551: /* For example we decided to compute the life expectancy with the smallest unit */
5552: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5553: nhstepm is the number of hstepm from age to agelim
5554: nstepm is the number of stepm from age to agelin.
1.270 brouard 5555: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5556: and note for a fixed period like estepm months */
5557: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5558: survival function given by stepm (the optimization length). Unfortunately it
5559: means that if the survival funtion is printed only each two years of age and if
5560: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5561: results. So we changed our mind and took the option of the best precision.
5562: */
5563: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5564:
5565: agelim=AGESUP;
5566: /* If stepm=6 months */
5567: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5568: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5569:
5570: /* nhstepm age range expressed in number of stepm */
5571: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5572: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5573: /* if (stepm >= YEARM) hstepm=1;*/
5574: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5575: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5576:
5577: for (age=bage; age<=fage; age ++){
5578: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5579: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5580: /* if (stepm >= YEARM) hstepm=1;*/
5581: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5582:
5583: /* If stepm=6 months */
5584: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5585: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5586:
1.235 brouard 5587: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5588:
5589: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5590:
5591: printf("%d|",(int)age);fflush(stdout);
5592: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5593:
5594: /* Computing expectancies */
5595: for(i=1; i<=nlstate;i++)
5596: for(j=1; j<=nlstate;j++)
5597: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5598: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5599:
5600: /* 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]);*/
5601:
5602: }
5603:
5604: fprintf(ficreseij,"%3.0f",age );
5605: for(i=1; i<=nlstate;i++){
5606: eip=0;
5607: for(j=1; j<=nlstate;j++){
5608: eip +=eij[i][j][(int)age];
5609: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5610: }
5611: fprintf(ficreseij,"%9.4f", eip );
5612: }
5613: fprintf(ficreseij,"\n");
5614:
5615: }
5616: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5617: printf("\n");
5618: fprintf(ficlog,"\n");
5619:
5620: }
5621:
1.235 brouard 5622: 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 5623:
5624: {
5625: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5626: to initial status i, ei. .
1.126 brouard 5627: */
5628: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5629: int nhstepma, nstepma; /* Decreasing with age */
5630: double age, agelim, hf;
5631: double ***p3matp, ***p3matm, ***varhe;
5632: double **dnewm,**doldm;
5633: double *xp, *xm;
5634: double **gp, **gm;
5635: double ***gradg, ***trgradg;
5636: int theta;
5637:
5638: double eip, vip;
5639:
5640: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5641: xp=vector(1,npar);
5642: xm=vector(1,npar);
5643: dnewm=matrix(1,nlstate*nlstate,1,npar);
5644: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5645:
5646: pstamp(ficresstdeij);
5647: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5648: fprintf(ficresstdeij,"# Age");
5649: for(i=1; i<=nlstate;i++){
5650: for(j=1; j<=nlstate;j++)
5651: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5652: fprintf(ficresstdeij," e%1d. ",i);
5653: }
5654: fprintf(ficresstdeij,"\n");
5655:
5656: pstamp(ficrescveij);
5657: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5658: fprintf(ficrescveij,"# Age");
5659: for(i=1; i<=nlstate;i++)
5660: for(j=1; j<=nlstate;j++){
5661: cptj= (j-1)*nlstate+i;
5662: for(i2=1; i2<=nlstate;i2++)
5663: for(j2=1; j2<=nlstate;j2++){
5664: cptj2= (j2-1)*nlstate+i2;
5665: if(cptj2 <= cptj)
5666: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5667: }
5668: }
5669: fprintf(ficrescveij,"\n");
5670:
5671: if(estepm < stepm){
5672: printf ("Problem %d lower than %d\n",estepm, stepm);
5673: }
5674: else hstepm=estepm;
5675: /* We compute the life expectancy from trapezoids spaced every estepm months
5676: * This is mainly to measure the difference between two models: for example
5677: * if stepm=24 months pijx are given only every 2 years and by summing them
5678: * we are calculating an estimate of the Life Expectancy assuming a linear
5679: * progression in between and thus overestimating or underestimating according
5680: * to the curvature of the survival function. If, for the same date, we
5681: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5682: * to compare the new estimate of Life expectancy with the same linear
5683: * hypothesis. A more precise result, taking into account a more precise
5684: * curvature will be obtained if estepm is as small as stepm. */
5685:
5686: /* For example we decided to compute the life expectancy with the smallest unit */
5687: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5688: nhstepm is the number of hstepm from age to agelim
5689: nstepm is the number of stepm from age to agelin.
5690: Look at hpijx to understand the reason of that which relies in memory size
5691: and note for a fixed period like estepm months */
5692: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5693: survival function given by stepm (the optimization length). Unfortunately it
5694: means that if the survival funtion is printed only each two years of age and if
5695: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5696: results. So we changed our mind and took the option of the best precision.
5697: */
5698: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5699:
5700: /* If stepm=6 months */
5701: /* nhstepm age range expressed in number of stepm */
5702: agelim=AGESUP;
5703: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5704: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5705: /* if (stepm >= YEARM) hstepm=1;*/
5706: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5707:
5708: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5709: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5710: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5711: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5712: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5713: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5714:
5715: for (age=bage; age<=fage; age ++){
5716: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5717: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5718: /* if (stepm >= YEARM) hstepm=1;*/
5719: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5720:
1.126 brouard 5721: /* If stepm=6 months */
5722: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5723: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5724:
5725: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5726:
1.126 brouard 5727: /* Computing Variances of health expectancies */
5728: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5729: decrease memory allocation */
5730: for(theta=1; theta <=npar; theta++){
5731: for(i=1; i<=npar; i++){
1.222 brouard 5732: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5733: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5734: }
1.235 brouard 5735: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5736: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5737:
1.126 brouard 5738: for(j=1; j<= nlstate; j++){
1.222 brouard 5739: for(i=1; i<=nlstate; i++){
5740: for(h=0; h<=nhstepm-1; h++){
5741: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5742: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5743: }
5744: }
1.126 brouard 5745: }
1.218 brouard 5746:
1.126 brouard 5747: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5748: for(h=0; h<=nhstepm-1; h++){
5749: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5750: }
1.126 brouard 5751: }/* End theta */
5752:
5753:
5754: for(h=0; h<=nhstepm-1; h++)
5755: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5756: for(theta=1; theta <=npar; theta++)
5757: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5758:
1.218 brouard 5759:
1.222 brouard 5760: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5761: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5762: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5763:
1.222 brouard 5764: printf("%d|",(int)age);fflush(stdout);
5765: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5766: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5767: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5768: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5769: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5770: for(ij=1;ij<=nlstate*nlstate;ij++)
5771: for(ji=1;ji<=nlstate*nlstate;ji++)
5772: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5773: }
5774: }
1.218 brouard 5775:
1.126 brouard 5776: /* Computing expectancies */
1.235 brouard 5777: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5778: for(i=1; i<=nlstate;i++)
5779: for(j=1; j<=nlstate;j++)
1.222 brouard 5780: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5781: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5782:
1.222 brouard 5783: /* 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 5784:
1.222 brouard 5785: }
1.269 brouard 5786:
5787: /* Standard deviation of expectancies ij */
1.126 brouard 5788: fprintf(ficresstdeij,"%3.0f",age );
5789: for(i=1; i<=nlstate;i++){
5790: eip=0.;
5791: vip=0.;
5792: for(j=1; j<=nlstate;j++){
1.222 brouard 5793: eip += eij[i][j][(int)age];
5794: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5795: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5796: 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 5797: }
5798: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5799: }
5800: fprintf(ficresstdeij,"\n");
1.218 brouard 5801:
1.269 brouard 5802: /* Variance of expectancies ij */
1.126 brouard 5803: fprintf(ficrescveij,"%3.0f",age );
5804: for(i=1; i<=nlstate;i++)
5805: for(j=1; j<=nlstate;j++){
1.222 brouard 5806: cptj= (j-1)*nlstate+i;
5807: for(i2=1; i2<=nlstate;i2++)
5808: for(j2=1; j2<=nlstate;j2++){
5809: cptj2= (j2-1)*nlstate+i2;
5810: if(cptj2 <= cptj)
5811: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5812: }
1.126 brouard 5813: }
5814: fprintf(ficrescveij,"\n");
1.218 brouard 5815:
1.126 brouard 5816: }
5817: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5818: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5819: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5820: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5821: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5822: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5823: printf("\n");
5824: fprintf(ficlog,"\n");
1.218 brouard 5825:
1.126 brouard 5826: free_vector(xm,1,npar);
5827: free_vector(xp,1,npar);
5828: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5829: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5830: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5831: }
1.218 brouard 5832:
1.126 brouard 5833: /************ Variance ******************/
1.235 brouard 5834: 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 5835: {
1.279 brouard 5836: /** Variance of health expectancies
5837: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5838: * double **newm;
5839: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5840: */
1.218 brouard 5841:
5842: /* int movingaverage(); */
5843: double **dnewm,**doldm;
5844: double **dnewmp,**doldmp;
5845: int i, j, nhstepm, hstepm, h, nstepm ;
5846: int k;
5847: double *xp;
1.279 brouard 5848: double **gp, **gm; /**< for var eij */
5849: double ***gradg, ***trgradg; /**< for var eij */
5850: double **gradgp, **trgradgp; /**< for var p point j */
5851: double *gpp, *gmp; /**< for var p point j */
5852: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5853: double ***p3mat;
5854: double age,agelim, hf;
5855: /* double ***mobaverage; */
5856: int theta;
5857: char digit[4];
5858: char digitp[25];
5859:
5860: char fileresprobmorprev[FILENAMELENGTH];
5861:
5862: if(popbased==1){
5863: if(mobilav!=0)
5864: strcpy(digitp,"-POPULBASED-MOBILAV_");
5865: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5866: }
5867: else
5868: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5869:
1.218 brouard 5870: /* if (mobilav!=0) { */
5871: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5872: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5873: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5874: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5875: /* } */
5876: /* } */
5877:
5878: strcpy(fileresprobmorprev,"PRMORPREV-");
5879: sprintf(digit,"%-d",ij);
5880: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5881: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5882: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5883: strcat(fileresprobmorprev,fileresu);
5884: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5885: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5886: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5887: }
5888: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5889: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5890: pstamp(ficresprobmorprev);
5891: 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 5892: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5893: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5894: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5895: }
5896: for(j=1;j<=cptcoveff;j++)
5897: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5898: fprintf(ficresprobmorprev,"\n");
5899:
1.218 brouard 5900: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5901: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5902: fprintf(ficresprobmorprev," p.%-d SE",j);
5903: for(i=1; i<=nlstate;i++)
5904: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5905: }
5906: fprintf(ficresprobmorprev,"\n");
5907:
5908: fprintf(ficgp,"\n# Routine varevsij");
5909: fprintf(ficgp,"\nunset title \n");
5910: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5911: 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");
5912: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5913:
1.218 brouard 5914: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5915: pstamp(ficresvij);
5916: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5917: if(popbased==1)
5918: 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);
5919: else
5920: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5921: fprintf(ficresvij,"# Age");
5922: for(i=1; i<=nlstate;i++)
5923: for(j=1; j<=nlstate;j++)
5924: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5925: fprintf(ficresvij,"\n");
5926:
5927: xp=vector(1,npar);
5928: dnewm=matrix(1,nlstate,1,npar);
5929: doldm=matrix(1,nlstate,1,nlstate);
5930: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5931: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5932:
5933: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5934: gpp=vector(nlstate+1,nlstate+ndeath);
5935: gmp=vector(nlstate+1,nlstate+ndeath);
5936: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5937:
1.218 brouard 5938: if(estepm < stepm){
5939: printf ("Problem %d lower than %d\n",estepm, stepm);
5940: }
5941: else hstepm=estepm;
5942: /* For example we decided to compute the life expectancy with the smallest unit */
5943: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5944: nhstepm is the number of hstepm from age to agelim
5945: nstepm is the number of stepm from age to agelim.
5946: Look at function hpijx to understand why because of memory size limitations,
5947: we decided (b) to get a life expectancy respecting the most precise curvature of the
5948: survival function given by stepm (the optimization length). Unfortunately it
5949: means that if the survival funtion is printed every two years of age and if
5950: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5951: results. So we changed our mind and took the option of the best precision.
5952: */
5953: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5954: agelim = AGESUP;
5955: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5956: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5957: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5958: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5959: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5960: gp=matrix(0,nhstepm,1,nlstate);
5961: gm=matrix(0,nhstepm,1,nlstate);
5962:
5963:
5964: for(theta=1; theta <=npar; theta++){
5965: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5966: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5967: }
1.279 brouard 5968: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
5969: * returns into prlim .
5970: */
1.242 brouard 5971: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 5972:
5973: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 5974: if (popbased==1) {
5975: if(mobilav ==0){
5976: for(i=1; i<=nlstate;i++)
5977: prlim[i][i]=probs[(int)age][i][ij];
5978: }else{ /* mobilav */
5979: for(i=1; i<=nlstate;i++)
5980: prlim[i][i]=mobaverage[(int)age][i][ij];
5981: }
5982: }
1.279 brouard 5983: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}_x\f$ at horizon h.
5984: */
5985: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
5986: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}_x\f$, which are the probability
5987: * at horizon h in state j including mortality.
5988: */
1.218 brouard 5989: for(j=1; j<= nlstate; j++){
5990: for(h=0; h<=nhstepm; h++){
5991: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5992: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5993: }
5994: }
1.279 brouard 5995: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 5996: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 5997: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 5998: */
5999: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6000: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6001: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6002: }
6003:
6004: /* Again with minus shift */
1.218 brouard 6005:
6006: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6007: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6008:
1.242 brouard 6009: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6010:
6011: if (popbased==1) {
6012: if(mobilav ==0){
6013: for(i=1; i<=nlstate;i++)
6014: prlim[i][i]=probs[(int)age][i][ij];
6015: }else{ /* mobilav */
6016: for(i=1; i<=nlstate;i++)
6017: prlim[i][i]=mobaverage[(int)age][i][ij];
6018: }
6019: }
6020:
1.235 brouard 6021: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6022:
6023: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6024: for(h=0; h<=nhstepm; h++){
6025: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6026: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6027: }
6028: }
6029: /* This for computing probability of death (h=1 means
6030: computed over hstepm matrices product = hstepm*stepm months)
6031: as a weighted average of prlim.
6032: */
6033: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6034: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6035: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6036: }
1.279 brouard 6037: /* end shifting computations */
6038:
6039: /**< Computing gradient matrix at horizon h
6040: */
1.218 brouard 6041: for(j=1; j<= nlstate; j++) /* vareij */
6042: for(h=0; h<=nhstepm; h++){
6043: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6044: }
1.279 brouard 6045: /**< Gradient of overall mortality p.3 (or p.j)
6046: */
6047: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6048: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6049: }
6050:
6051: } /* End theta */
1.279 brouard 6052:
6053: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6054: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6055:
6056: for(h=0; h<=nhstepm; h++) /* veij */
6057: for(j=1; j<=nlstate;j++)
6058: for(theta=1; theta <=npar; theta++)
6059: trgradg[h][j][theta]=gradg[h][theta][j];
6060:
6061: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6062: for(theta=1; theta <=npar; theta++)
6063: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6064: /**< as well as its transposed matrix
6065: */
1.218 brouard 6066:
6067: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6068: for(i=1;i<=nlstate;i++)
6069: for(j=1;j<=nlstate;j++)
6070: vareij[i][j][(int)age] =0.;
1.279 brouard 6071:
6072: /* Computing trgradg by matcov by gradg at age and summing over h
6073: * and k (nhstepm) formula 15 of article
6074: * Lievre-Brouard-Heathcote
6075: */
6076:
1.218 brouard 6077: for(h=0;h<=nhstepm;h++){
6078: for(k=0;k<=nhstepm;k++){
6079: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6080: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6081: for(i=1;i<=nlstate;i++)
6082: for(j=1;j<=nlstate;j++)
6083: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6084: }
6085: }
6086:
1.279 brouard 6087: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6088: * p.j overall mortality formula 49 but computed directly because
6089: * we compute the grad (wix pijx) instead of grad (pijx),even if
6090: * wix is independent of theta.
6091: */
1.218 brouard 6092: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6093: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6094: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6095: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6096: varppt[j][i]=doldmp[j][i];
6097: /* end ppptj */
6098: /* x centered again */
6099:
1.242 brouard 6100: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6101:
6102: if (popbased==1) {
6103: if(mobilav ==0){
6104: for(i=1; i<=nlstate;i++)
6105: prlim[i][i]=probs[(int)age][i][ij];
6106: }else{ /* mobilav */
6107: for(i=1; i<=nlstate;i++)
6108: prlim[i][i]=mobaverage[(int)age][i][ij];
6109: }
6110: }
6111:
6112: /* This for computing probability of death (h=1 means
6113: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6114: as a weighted average of prlim.
6115: */
1.235 brouard 6116: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6117: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6118: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6119: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6120: }
6121: /* end probability of death */
6122:
6123: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6124: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6125: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6126: for(i=1; i<=nlstate;i++){
6127: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6128: }
6129: }
6130: fprintf(ficresprobmorprev,"\n");
6131:
6132: fprintf(ficresvij,"%.0f ",age );
6133: for(i=1; i<=nlstate;i++)
6134: for(j=1; j<=nlstate;j++){
6135: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6136: }
6137: fprintf(ficresvij,"\n");
6138: free_matrix(gp,0,nhstepm,1,nlstate);
6139: free_matrix(gm,0,nhstepm,1,nlstate);
6140: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6141: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6142: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6143: } /* End age */
6144: free_vector(gpp,nlstate+1,nlstate+ndeath);
6145: free_vector(gmp,nlstate+1,nlstate+ndeath);
6146: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6147: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6148: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6149: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6150: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6151: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6152: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6153: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6154: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6155: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6156: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6157: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6158: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6159: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6160: 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);
6161: /* 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 6162: */
1.218 brouard 6163: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6164: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6165:
1.218 brouard 6166: free_vector(xp,1,npar);
6167: free_matrix(doldm,1,nlstate,1,nlstate);
6168: free_matrix(dnewm,1,nlstate,1,npar);
6169: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6170: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6171: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6172: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6173: fclose(ficresprobmorprev);
6174: fflush(ficgp);
6175: fflush(fichtm);
6176: } /* end varevsij */
1.126 brouard 6177:
6178: /************ Variance of prevlim ******************/
1.269 brouard 6179: 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 6180: {
1.205 brouard 6181: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6182: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6183:
1.268 brouard 6184: double **dnewmpar,**doldm;
1.126 brouard 6185: int i, j, nhstepm, hstepm;
6186: double *xp;
6187: double *gp, *gm;
6188: double **gradg, **trgradg;
1.208 brouard 6189: double **mgm, **mgp;
1.126 brouard 6190: double age,agelim;
6191: int theta;
6192:
6193: pstamp(ficresvpl);
6194: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 6195: fprintf(ficresvpl,"# Age ");
6196: if(nresult >=1)
6197: fprintf(ficresvpl," Result# ");
1.126 brouard 6198: for(i=1; i<=nlstate;i++)
6199: fprintf(ficresvpl," %1d-%1d",i,i);
6200: fprintf(ficresvpl,"\n");
6201:
6202: xp=vector(1,npar);
1.268 brouard 6203: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6204: doldm=matrix(1,nlstate,1,nlstate);
6205:
6206: hstepm=1*YEARM; /* Every year of age */
6207: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6208: agelim = AGESUP;
6209: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6210: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6211: if (stepm >= YEARM) hstepm=1;
6212: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6213: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6214: mgp=matrix(1,npar,1,nlstate);
6215: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6216: gp=vector(1,nlstate);
6217: gm=vector(1,nlstate);
6218:
6219: for(theta=1; theta <=npar; theta++){
6220: for(i=1; i<=npar; i++){ /* Computes gradient */
6221: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6222: }
1.209 brouard 6223: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6224: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6225: else
1.235 brouard 6226: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6227: for(i=1;i<=nlstate;i++){
1.126 brouard 6228: gp[i] = prlim[i][i];
1.208 brouard 6229: mgp[theta][i] = prlim[i][i];
6230: }
1.126 brouard 6231: for(i=1; i<=npar; i++) /* Computes gradient */
6232: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 6233: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6234: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6235: else
1.235 brouard 6236: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6237: for(i=1;i<=nlstate;i++){
1.126 brouard 6238: gm[i] = prlim[i][i];
1.208 brouard 6239: mgm[theta][i] = prlim[i][i];
6240: }
1.126 brouard 6241: for(i=1;i<=nlstate;i++)
6242: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6243: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6244: } /* End theta */
6245:
6246: trgradg =matrix(1,nlstate,1,npar);
6247:
6248: for(j=1; j<=nlstate;j++)
6249: for(theta=1; theta <=npar; theta++)
6250: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6251: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6252: /* printf("\nmgm mgp %d ",(int)age); */
6253: /* for(j=1; j<=nlstate;j++){ */
6254: /* printf(" %d ",j); */
6255: /* for(theta=1; theta <=npar; theta++) */
6256: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6257: /* printf("\n "); */
6258: /* } */
6259: /* } */
6260: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6261: /* printf("\n gradg %d ",(int)age); */
6262: /* for(j=1; j<=nlstate;j++){ */
6263: /* printf("%d ",j); */
6264: /* for(theta=1; theta <=npar; theta++) */
6265: /* printf("%d %lf ",theta,gradg[theta][j]); */
6266: /* printf("\n "); */
6267: /* } */
6268: /* } */
1.126 brouard 6269:
6270: for(i=1;i<=nlstate;i++)
6271: varpl[i][(int)age] =0.;
1.209 brouard 6272: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6273: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6274: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6275: }else{
1.268 brouard 6276: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6277: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6278: }
1.126 brouard 6279: for(i=1;i<=nlstate;i++)
6280: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6281:
6282: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6283: if(nresult >=1)
6284: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 6285: for(i=1; i<=nlstate;i++)
6286: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
6287: fprintf(ficresvpl,"\n");
6288: free_vector(gp,1,nlstate);
6289: free_vector(gm,1,nlstate);
1.208 brouard 6290: free_matrix(mgm,1,npar,1,nlstate);
6291: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6292: free_matrix(gradg,1,npar,1,nlstate);
6293: free_matrix(trgradg,1,nlstate,1,npar);
6294: } /* End age */
6295:
6296: free_vector(xp,1,npar);
6297: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6298: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6299:
6300: }
6301:
6302:
6303: /************ Variance of backprevalence limit ******************/
1.269 brouard 6304: 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 6305: {
6306: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6307: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6308:
6309: double **dnewmpar,**doldm;
6310: int i, j, nhstepm, hstepm;
6311: double *xp;
6312: double *gp, *gm;
6313: double **gradg, **trgradg;
6314: double **mgm, **mgp;
6315: double age,agelim;
6316: int theta;
6317:
6318: pstamp(ficresvbl);
6319: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6320: fprintf(ficresvbl,"# Age ");
6321: if(nresult >=1)
6322: fprintf(ficresvbl," Result# ");
6323: for(i=1; i<=nlstate;i++)
6324: fprintf(ficresvbl," %1d-%1d",i,i);
6325: fprintf(ficresvbl,"\n");
6326:
6327: xp=vector(1,npar);
6328: dnewmpar=matrix(1,nlstate,1,npar);
6329: doldm=matrix(1,nlstate,1,nlstate);
6330:
6331: hstepm=1*YEARM; /* Every year of age */
6332: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6333: agelim = AGEINF;
6334: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6335: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6336: if (stepm >= YEARM) hstepm=1;
6337: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6338: gradg=matrix(1,npar,1,nlstate);
6339: mgp=matrix(1,npar,1,nlstate);
6340: mgm=matrix(1,npar,1,nlstate);
6341: gp=vector(1,nlstate);
6342: gm=vector(1,nlstate);
6343:
6344: for(theta=1; theta <=npar; theta++){
6345: for(i=1; i<=npar; i++){ /* Computes gradient */
6346: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6347: }
6348: if(mobilavproj > 0 )
6349: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6350: else
6351: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6352: for(i=1;i<=nlstate;i++){
6353: gp[i] = bprlim[i][i];
6354: mgp[theta][i] = bprlim[i][i];
6355: }
6356: for(i=1; i<=npar; i++) /* Computes gradient */
6357: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6358: if(mobilavproj > 0 )
6359: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6360: else
6361: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6362: for(i=1;i<=nlstate;i++){
6363: gm[i] = bprlim[i][i];
6364: mgm[theta][i] = bprlim[i][i];
6365: }
6366: for(i=1;i<=nlstate;i++)
6367: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6368: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6369: } /* End theta */
6370:
6371: trgradg =matrix(1,nlstate,1,npar);
6372:
6373: for(j=1; j<=nlstate;j++)
6374: for(theta=1; theta <=npar; theta++)
6375: trgradg[j][theta]=gradg[theta][j];
6376: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6377: /* printf("\nmgm mgp %d ",(int)age); */
6378: /* for(j=1; j<=nlstate;j++){ */
6379: /* printf(" %d ",j); */
6380: /* for(theta=1; theta <=npar; theta++) */
6381: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6382: /* printf("\n "); */
6383: /* } */
6384: /* } */
6385: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6386: /* printf("\n gradg %d ",(int)age); */
6387: /* for(j=1; j<=nlstate;j++){ */
6388: /* printf("%d ",j); */
6389: /* for(theta=1; theta <=npar; theta++) */
6390: /* printf("%d %lf ",theta,gradg[theta][j]); */
6391: /* printf("\n "); */
6392: /* } */
6393: /* } */
6394:
6395: for(i=1;i<=nlstate;i++)
6396: varbpl[i][(int)age] =0.;
6397: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6398: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6399: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6400: }else{
6401: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6402: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6403: }
6404: for(i=1;i<=nlstate;i++)
6405: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6406:
6407: fprintf(ficresvbl,"%.0f ",age );
6408: if(nresult >=1)
6409: fprintf(ficresvbl,"%d ",nres );
6410: for(i=1; i<=nlstate;i++)
6411: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6412: fprintf(ficresvbl,"\n");
6413: free_vector(gp,1,nlstate);
6414: free_vector(gm,1,nlstate);
6415: free_matrix(mgm,1,npar,1,nlstate);
6416: free_matrix(mgp,1,npar,1,nlstate);
6417: free_matrix(gradg,1,npar,1,nlstate);
6418: free_matrix(trgradg,1,nlstate,1,npar);
6419: } /* End age */
6420:
6421: free_vector(xp,1,npar);
6422: free_matrix(doldm,1,nlstate,1,npar);
6423: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6424:
6425: }
6426:
6427: /************ Variance of one-step probabilities ******************/
6428: 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 6429: {
6430: int i, j=0, k1, l1, tj;
6431: int k2, l2, j1, z1;
6432: int k=0, l;
6433: int first=1, first1, first2;
6434: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6435: double **dnewm,**doldm;
6436: double *xp;
6437: double *gp, *gm;
6438: double **gradg, **trgradg;
6439: double **mu;
6440: double age, cov[NCOVMAX+1];
6441: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6442: int theta;
6443: char fileresprob[FILENAMELENGTH];
6444: char fileresprobcov[FILENAMELENGTH];
6445: char fileresprobcor[FILENAMELENGTH];
6446: double ***varpij;
6447:
6448: strcpy(fileresprob,"PROB_");
6449: strcat(fileresprob,fileres);
6450: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6451: printf("Problem with resultfile: %s\n", fileresprob);
6452: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6453: }
6454: strcpy(fileresprobcov,"PROBCOV_");
6455: strcat(fileresprobcov,fileresu);
6456: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6457: printf("Problem with resultfile: %s\n", fileresprobcov);
6458: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6459: }
6460: strcpy(fileresprobcor,"PROBCOR_");
6461: strcat(fileresprobcor,fileresu);
6462: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6463: printf("Problem with resultfile: %s\n", fileresprobcor);
6464: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6465: }
6466: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6467: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6468: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6469: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6470: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6471: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6472: pstamp(ficresprob);
6473: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6474: fprintf(ficresprob,"# Age");
6475: pstamp(ficresprobcov);
6476: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6477: fprintf(ficresprobcov,"# Age");
6478: pstamp(ficresprobcor);
6479: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6480: fprintf(ficresprobcor,"# Age");
1.126 brouard 6481:
6482:
1.222 brouard 6483: for(i=1; i<=nlstate;i++)
6484: for(j=1; j<=(nlstate+ndeath);j++){
6485: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6486: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6487: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6488: }
6489: /* fprintf(ficresprob,"\n");
6490: fprintf(ficresprobcov,"\n");
6491: fprintf(ficresprobcor,"\n");
6492: */
6493: xp=vector(1,npar);
6494: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6495: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6496: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6497: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6498: first=1;
6499: fprintf(ficgp,"\n# Routine varprob");
6500: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6501: fprintf(fichtm,"\n");
6502:
1.266 brouard 6503: 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. %s</li>\n",optionfilehtmcov,optionfilehtmcov);
1.222 brouard 6504: 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);
6505: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6506: and drawn. It helps understanding how is the covariance between two incidences.\
6507: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6508: 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 6509: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6510: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6511: standard deviations wide on each axis. <br>\
6512: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6513: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6514: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6515:
1.222 brouard 6516: cov[1]=1;
6517: /* tj=cptcoveff; */
1.225 brouard 6518: tj = (int) pow(2,cptcoveff);
1.222 brouard 6519: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6520: j1=0;
1.224 brouard 6521: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6522: if (cptcovn>0) {
6523: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6524: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6525: fprintf(ficresprob, "**********\n#\n");
6526: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6527: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6528: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6529:
1.222 brouard 6530: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6531: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6532: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6533:
6534:
1.222 brouard 6535: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6536: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6537: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6538:
1.222 brouard 6539: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6540: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6541: fprintf(ficresprobcor, "**********\n#");
6542: if(invalidvarcomb[j1]){
6543: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6544: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6545: continue;
6546: }
6547: }
6548: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6549: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6550: gp=vector(1,(nlstate)*(nlstate+ndeath));
6551: gm=vector(1,(nlstate)*(nlstate+ndeath));
6552: for (age=bage; age<=fage; age ++){
6553: cov[2]=age;
6554: if(nagesqr==1)
6555: cov[3]= age*age;
6556: for (k=1; k<=cptcovn;k++) {
6557: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6558: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6559: * 1 1 1 1 1
6560: * 2 2 1 1 1
6561: * 3 1 2 1 1
6562: */
6563: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6564: }
6565: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6566: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6567: for (k=1; k<=cptcovprod;k++)
6568: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6569:
6570:
1.222 brouard 6571: for(theta=1; theta <=npar; theta++){
6572: for(i=1; i<=npar; i++)
6573: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6574:
1.222 brouard 6575: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6576:
1.222 brouard 6577: k=0;
6578: for(i=1; i<= (nlstate); i++){
6579: for(j=1; j<=(nlstate+ndeath);j++){
6580: k=k+1;
6581: gp[k]=pmmij[i][j];
6582: }
6583: }
1.220 brouard 6584:
1.222 brouard 6585: for(i=1; i<=npar; i++)
6586: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6587:
1.222 brouard 6588: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6589: k=0;
6590: for(i=1; i<=(nlstate); i++){
6591: for(j=1; j<=(nlstate+ndeath);j++){
6592: k=k+1;
6593: gm[k]=pmmij[i][j];
6594: }
6595: }
1.220 brouard 6596:
1.222 brouard 6597: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6598: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6599: }
1.126 brouard 6600:
1.222 brouard 6601: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6602: for(theta=1; theta <=npar; theta++)
6603: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6604:
1.222 brouard 6605: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6606: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6607:
1.222 brouard 6608: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6609:
1.222 brouard 6610: k=0;
6611: for(i=1; i<=(nlstate); i++){
6612: for(j=1; j<=(nlstate+ndeath);j++){
6613: k=k+1;
6614: mu[k][(int) age]=pmmij[i][j];
6615: }
6616: }
6617: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6618: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6619: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6620:
1.222 brouard 6621: /*printf("\n%d ",(int)age);
6622: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6623: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6624: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6625: }*/
1.220 brouard 6626:
1.222 brouard 6627: fprintf(ficresprob,"\n%d ",(int)age);
6628: fprintf(ficresprobcov,"\n%d ",(int)age);
6629: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6630:
1.222 brouard 6631: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6632: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6633: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6634: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6635: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6636: }
6637: i=0;
6638: for (k=1; k<=(nlstate);k++){
6639: for (l=1; l<=(nlstate+ndeath);l++){
6640: i++;
6641: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6642: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6643: for (j=1; j<=i;j++){
6644: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6645: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6646: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6647: }
6648: }
6649: }/* end of loop for state */
6650: } /* end of loop for age */
6651: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6652: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6653: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6654: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6655:
6656: /* Confidence intervalle of pij */
6657: /*
6658: fprintf(ficgp,"\nunset parametric;unset label");
6659: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6660: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6661: 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);
6662: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6663: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6664: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6665: */
6666:
6667: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6668: first1=1;first2=2;
6669: for (k2=1; k2<=(nlstate);k2++){
6670: for (l2=1; l2<=(nlstate+ndeath);l2++){
6671: if(l2==k2) continue;
6672: j=(k2-1)*(nlstate+ndeath)+l2;
6673: for (k1=1; k1<=(nlstate);k1++){
6674: for (l1=1; l1<=(nlstate+ndeath);l1++){
6675: if(l1==k1) continue;
6676: i=(k1-1)*(nlstate+ndeath)+l1;
6677: if(i<=j) continue;
6678: for (age=bage; age<=fage; age ++){
6679: if ((int)age %5==0){
6680: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6681: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6682: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6683: mu1=mu[i][(int) age]/stepm*YEARM ;
6684: mu2=mu[j][(int) age]/stepm*YEARM;
6685: c12=cv12/sqrt(v1*v2);
6686: /* Computing eigen value of matrix of covariance */
6687: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6688: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6689: if ((lc2 <0) || (lc1 <0) ){
6690: if(first2==1){
6691: first1=0;
6692: 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);
6693: }
6694: 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);
6695: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6696: /* lc2=fabs(lc2); */
6697: }
1.220 brouard 6698:
1.222 brouard 6699: /* Eigen vectors */
1.280 brouard 6700: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6701: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6702: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6703: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6704: }else
6705: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6706: /*v21=sqrt(1.-v11*v11); *//* error */
6707: v21=(lc1-v1)/cv12*v11;
6708: v12=-v21;
6709: v22=v11;
6710: tnalp=v21/v11;
6711: if(first1==1){
6712: first1=0;
6713: 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);
6714: }
6715: 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);
6716: /*printf(fignu*/
6717: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6718: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6719: if(first==1){
6720: first=0;
6721: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6722: fprintf(ficgp,"\nset parametric;unset label");
6723: 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);
6724: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6725: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6726: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6727: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6728: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6729: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6730: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6731: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6732: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6733: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6734: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6735: 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 6736: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6737: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6738: }else{
6739: first=0;
6740: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6741: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6742: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6743: 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 6744: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6745: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6746: }/* if first */
6747: } /* age mod 5 */
6748: } /* end loop age */
6749: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6750: first=1;
6751: } /*l12 */
6752: } /* k12 */
6753: } /*l1 */
6754: }/* k1 */
6755: } /* loop on combination of covariates j1 */
6756: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6757: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6758: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6759: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6760: free_vector(xp,1,npar);
6761: fclose(ficresprob);
6762: fclose(ficresprobcov);
6763: fclose(ficresprobcor);
6764: fflush(ficgp);
6765: fflush(fichtmcov);
6766: }
1.126 brouard 6767:
6768:
6769: /******************* Printing html file ***********/
1.201 brouard 6770: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6771: int lastpass, int stepm, int weightopt, char model[],\
6772: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6773: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.273 brouard 6774: double jprev1, double mprev1,double anprev1, double dateprev1, double dateproj1, double dateback1, \
6775: double jprev2, double mprev2,double anprev2, double dateprev2, double dateproj2, double dateback2){
1.237 brouard 6776: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6777:
6778: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6779: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6780: </ul>");
1.237 brouard 6781: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6782: </ul>", model);
1.214 brouard 6783: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6784: 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",
6785: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6786: 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 6787: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6788: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6789: fprintf(fichtm,"\
6790: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6791: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6792: fprintf(fichtm,"\
1.217 brouard 6793: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6794: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6795: fprintf(fichtm,"\
1.126 brouard 6796: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6797: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6798: fprintf(fichtm,"\
1.217 brouard 6799: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6800: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6801: fprintf(fichtm,"\
1.211 brouard 6802: - (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 6803: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6804: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6805: if(prevfcast==1){
6806: fprintf(fichtm,"\
6807: - Prevalence projections by age and states: \
1.201 brouard 6808: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6809: }
1.126 brouard 6810:
6811:
1.225 brouard 6812: m=pow(2,cptcoveff);
1.222 brouard 6813: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6814:
1.264 brouard 6815: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6816:
6817: jj1=0;
6818:
6819: fprintf(fichtm," \n<ul>");
6820: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6821: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6822: if(m != 1 && TKresult[nres]!= k1)
6823: continue;
6824: jj1++;
6825: if (cptcovn > 0) {
6826: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6827: for (cpt=1; cpt<=cptcoveff;cpt++){
6828: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6829: }
6830: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6831: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6832: }
6833: fprintf(fichtm,"\">");
6834:
6835: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6836: fprintf(fichtm,"************ Results for covariates");
6837: for (cpt=1; cpt<=cptcoveff;cpt++){
6838: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6839: }
6840: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6841: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6842: }
6843: if(invalidvarcomb[k1]){
6844: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6845: continue;
6846: }
6847: fprintf(fichtm,"</a></li>");
6848: } /* cptcovn >0 */
6849: }
6850: fprintf(fichtm," \n</ul>");
6851:
1.222 brouard 6852: jj1=0;
1.237 brouard 6853:
6854: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6855: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6856: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6857: continue;
1.220 brouard 6858:
1.222 brouard 6859: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6860: jj1++;
6861: if (cptcovn > 0) {
1.264 brouard 6862: fprintf(fichtm,"\n<p><a name=\"rescov");
6863: for (cpt=1; cpt<=cptcoveff;cpt++){
6864: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6865: }
6866: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6867: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6868: }
6869: fprintf(fichtm,"\"</a>");
6870:
1.222 brouard 6871: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6872: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6873: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6874: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6875: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6876: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6877: }
1.237 brouard 6878: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6879: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6880: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6881: }
6882:
1.230 brouard 6883: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6884: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6885: if(invalidvarcomb[k1]){
6886: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6887: printf("\nCombination (%d) ignored because no cases \n",k1);
6888: continue;
6889: }
6890: }
6891: /* aij, bij */
1.259 brouard 6892: 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 6893: <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 6894: /* Pij */
1.241 brouard 6895: 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> \
6896: <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 6897: /* Quasi-incidences */
6898: 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 6899: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6900: 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 6901: 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> \
6902: <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 6903: /* Survival functions (period) in state j */
6904: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6905: fprintf(fichtm,"<br>\n- Survival functions in state %d. Or probability to survive 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> \
6906: <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 6907: }
6908: /* State specific survival functions (period) */
6909: for(cpt=1; cpt<=nlstate;cpt++){
6910: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6911: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.283 brouard 6912: <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 6913: }
6914: /* Period (stable) prevalence in each health state */
6915: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6916: 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> \
6917: <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 6918: }
6919: if(backcast==1){
6920: /* Period (stable) back prevalence in each health state */
6921: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6922: 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 6923: <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 6924: }
1.217 brouard 6925: }
1.222 brouard 6926: if(prevfcast==1){
6927: /* Projection of prevalence up to period (stable) prevalence in each health state */
6928: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6929: 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) 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> \
6930: <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 6931: }
6932: }
1.268 brouard 6933: if(backcast==1){
6934: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6935: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6936: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6937: 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 \
6938: 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) \
6939: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6940: <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 6941: }
6942: }
1.220 brouard 6943:
1.222 brouard 6944: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6945: 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> \
6946: <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 6947: }
6948: /* } /\* end i1 *\/ */
6949: }/* End k1 */
6950: fprintf(fichtm,"</ul>");
1.126 brouard 6951:
1.222 brouard 6952: fprintf(fichtm,"\
1.126 brouard 6953: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6954: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6955: - 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 6956: But because parameters are usually highly correlated (a higher incidence of disability \
6957: and a higher incidence of recovery can give very close observed transition) it might \
6958: be very useful to look not only at linear confidence intervals estimated from the \
6959: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6960: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6961: covariance matrix of the one-step probabilities. \
6962: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6963:
1.222 brouard 6964: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6965: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6966: fprintf(fichtm,"\
1.126 brouard 6967: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6968: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6969:
1.222 brouard 6970: fprintf(fichtm,"\
1.126 brouard 6971: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6972: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6973: fprintf(fichtm,"\
1.126 brouard 6974: - 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): \
6975: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6976: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6977: fprintf(fichtm,"\
1.126 brouard 6978: - (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): \
6979: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6980: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6981: fprintf(fichtm,"\
1.128 brouard 6982: - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), e<sup>ij</sup> are weighted by the 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 6983: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6984: fprintf(fichtm,"\
1.128 brouard 6985: - 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 6986: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6987: fprintf(fichtm,"\
1.126 brouard 6988: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6989: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6990:
6991: /* if(popforecast==1) fprintf(fichtm,"\n */
6992: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6993: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6994: /* <br>",fileres,fileres,fileres,fileres); */
6995: /* else */
6996: /* 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 6997: fflush(fichtm);
6998: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6999:
1.225 brouard 7000: m=pow(2,cptcoveff);
1.222 brouard 7001: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7002:
1.222 brouard 7003: jj1=0;
1.237 brouard 7004:
1.241 brouard 7005: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7006: for(k1=1; k1<=m;k1++){
1.253 brouard 7007: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7008: continue;
1.222 brouard 7009: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7010: jj1++;
1.126 brouard 7011: if (cptcovn > 0) {
7012: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7013: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7014: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7015: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7016: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7017: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7018: }
7019:
1.126 brouard 7020: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7021:
1.222 brouard 7022: if(invalidvarcomb[k1]){
7023: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7024: continue;
7025: }
1.126 brouard 7026: }
7027: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7028: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7029: 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 7030: <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 7031: }
7032: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7033: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7034: true period expectancies (those weighted with period prevalences are also\
7035: drawn in addition to the population based expectancies computed using\
1.241 brouard 7036: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7037: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7038: /* } /\* end i1 *\/ */
7039: }/* End k1 */
1.241 brouard 7040: }/* End nres */
1.222 brouard 7041: fprintf(fichtm,"</ul>");
7042: fflush(fichtm);
1.126 brouard 7043: }
7044:
7045: /******************* Gnuplot file **************/
1.270 brouard 7046: 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 7047:
7048: char dirfileres[132],optfileres[132];
1.264 brouard 7049: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7050: 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 7051: int lv=0, vlv=0, kl=0;
1.130 brouard 7052: int ng=0;
1.201 brouard 7053: int vpopbased;
1.223 brouard 7054: int ioffset; /* variable offset for columns */
1.270 brouard 7055: int iyearc=1; /* variable column for year of projection */
7056: int iagec=1; /* variable column for age of projection */
1.235 brouard 7057: int nres=0; /* Index of resultline */
1.266 brouard 7058: int istart=1; /* For starting graphs in projections */
1.219 brouard 7059:
1.126 brouard 7060: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7061: /* printf("Problem with file %s",optionfilegnuplot); */
7062: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7063: /* } */
7064:
7065: /*#ifdef windows */
7066: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7067: /*#endif */
1.225 brouard 7068: m=pow(2,cptcoveff);
1.126 brouard 7069:
1.274 brouard 7070: /* diagram of the model */
7071: fprintf(ficgp,"\n#Diagram of the model \n");
7072: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7073: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7074: 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);
7075:
7076: 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);
7077: fprintf(ficgp,"\n#show arrow\nunset label\n");
7078: 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);
7079: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7080: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7081: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7082: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7083:
1.202 brouard 7084: /* Contribution to likelihood */
7085: /* Plot the probability implied in the likelihood */
1.223 brouard 7086: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7087: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7088: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7089: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7090: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7091: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7092: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7093: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7094: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7095: 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));
7096: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7097: 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));
7098: for (i=1; i<= nlstate ; i ++) {
7099: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7100: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7101: 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);
7102: for (j=2; j<= nlstate+ndeath ; j ++) {
7103: 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);
7104: }
7105: fprintf(ficgp,";\nset out; unset ylabel;\n");
7106: }
7107: /* 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 */
7108: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7109: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7110: fprintf(ficgp,"\nset out;unset log\n");
7111: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7112:
1.126 brouard 7113: strcpy(dirfileres,optionfilefiname);
7114: strcpy(optfileres,"vpl");
1.223 brouard 7115: /* 1eme*/
1.238 brouard 7116: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7117: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7118: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7119: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7120: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7121: continue;
7122: /* We are interested in selected combination by the resultline */
1.246 brouard 7123: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.238 brouard 7124: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7125: strcpy(gplotlabel,"(");
1.238 brouard 7126: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7127: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7128: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7129: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7130: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7131: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7132: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7133: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7134: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7135: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7136: }
7137: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7138: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7139: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7140: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7141: }
7142: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7143: /* printf("\n#\n"); */
1.238 brouard 7144: fprintf(ficgp,"\n#\n");
7145: if(invalidvarcomb[k1]){
1.260 brouard 7146: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7147: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7148: continue;
7149: }
1.235 brouard 7150:
1.241 brouard 7151: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7152: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7153: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7154: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7155: 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);
7156: /* 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); */
7157: /* k1-1 error should be nres-1*/
1.238 brouard 7158: for (i=1; i<= nlstate ; i ++) {
7159: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7160: else fprintf(ficgp," %%*lf (%%*lf)");
7161: }
1.260 brouard 7162: fprintf(ficgp,"\" t\"Period (stable) 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 7163: for (i=1; i<= nlstate ; i ++) {
7164: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7165: else fprintf(ficgp," %%*lf (%%*lf)");
7166: }
1.260 brouard 7167: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7168: for (i=1; i<= nlstate ; i ++) {
7169: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7170: else fprintf(ficgp," %%*lf (%%*lf)");
7171: }
1.265 brouard 7172: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7173:
7174: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7175: if(cptcoveff ==0){
1.271 brouard 7176: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7177: }else{
7178: kl=0;
7179: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7180: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7181: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7182: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7183: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7184: vlv= nbcode[Tvaraff[k]][lv];
7185: kl++;
7186: /* 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 *\/ */
7187: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7188: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7189: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7190: if(k==cptcoveff){
7191: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7192: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7193: }else{
7194: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7195: kl++;
7196: }
7197: } /* end covariate */
7198: } /* end if no covariate */
7199:
1.238 brouard 7200: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7201: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7202: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7203: if(cptcoveff ==0){
1.245 brouard 7204: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7205: }else{
7206: kl=0;
7207: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7208: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7209: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7210: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7211: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7212: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7213: kl++;
1.238 brouard 7214: /* 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 *\/ */
7215: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7216: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7217: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7218: if(k==cptcoveff){
1.245 brouard 7219: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7220: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7221: }else{
7222: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7223: kl++;
7224: }
7225: } /* end covariate */
7226: } /* end if no covariate */
1.268 brouard 7227: if(backcast == 1){
7228: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7229: /* k1-1 error should be nres-1*/
7230: for (i=1; i<= nlstate ; i ++) {
7231: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7232: else fprintf(ficgp," %%*lf (%%*lf)");
7233: }
1.271 brouard 7234: 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 7235: for (i=1; i<= nlstate ; i ++) {
7236: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7237: else fprintf(ficgp," %%*lf (%%*lf)");
7238: }
1.276 brouard 7239: 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 7240: for (i=1; i<= nlstate ; i ++) {
7241: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7242: else fprintf(ficgp," %%*lf (%%*lf)");
7243: }
1.274 brouard 7244: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7245: } /* end if backprojcast */
1.238 brouard 7246: } /* end if backcast */
1.276 brouard 7247: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7248: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7249: } /* nres */
1.201 brouard 7250: } /* k1 */
7251: } /* cpt */
1.235 brouard 7252:
7253:
1.126 brouard 7254: /*2 eme*/
1.238 brouard 7255: for (k1=1; k1<= m ; k1 ++){
7256: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7257: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7258: continue;
7259: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7260: strcpy(gplotlabel,"(");
1.238 brouard 7261: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7262: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7263: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7264: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7265: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7266: vlv= nbcode[Tvaraff[k]][lv];
7267: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7268: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7269: }
1.237 brouard 7270: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7271: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7272: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7273: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7274: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7275: }
1.264 brouard 7276: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7277: fprintf(ficgp,"\n#\n");
1.223 brouard 7278: if(invalidvarcomb[k1]){
7279: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7280: continue;
7281: }
1.219 brouard 7282:
1.241 brouard 7283: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7284: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7285: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7286: if(vpopbased==0){
1.238 brouard 7287: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7288: }else
1.238 brouard 7289: fprintf(ficgp,"\nreplot ");
7290: for (i=1; i<= nlstate+1 ; i ++) {
7291: k=2*i;
1.261 brouard 7292: 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 7293: for (j=1; j<= nlstate+1 ; j ++) {
7294: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7295: else fprintf(ficgp," %%*lf (%%*lf)");
7296: }
7297: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7298: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7299: 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 7300: for (j=1; j<= nlstate+1 ; j ++) {
7301: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7302: else fprintf(ficgp," %%*lf (%%*lf)");
7303: }
7304: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7305: 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 7306: for (j=1; j<= nlstate+1 ; j ++) {
7307: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7308: else fprintf(ficgp," %%*lf (%%*lf)");
7309: }
7310: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7311: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7312: } /* state */
7313: } /* vpopbased */
1.264 brouard 7314: 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 7315: } /* end nres */
7316: } /* k1 end 2 eme*/
7317:
7318:
7319: /*3eme*/
7320: for (k1=1; k1<= m ; k1 ++){
7321: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7322: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7323: continue;
7324:
7325: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7326: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7327: strcpy(gplotlabel,"(");
1.238 brouard 7328: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7329: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7330: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7331: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7332: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7333: vlv= nbcode[Tvaraff[k]][lv];
7334: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7335: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7336: }
7337: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7338: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7339: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7340: }
1.264 brouard 7341: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7342: fprintf(ficgp,"\n#\n");
7343: if(invalidvarcomb[k1]){
7344: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7345: continue;
7346: }
7347:
7348: /* k=2+nlstate*(2*cpt-2); */
7349: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7350: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7351: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7352: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7353: 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 7354: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7355: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7356: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7357: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7358: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7359: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7360:
1.238 brouard 7361: */
7362: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7363: 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 7364: /* 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 7365:
1.238 brouard 7366: }
1.261 brouard 7367: 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 7368: }
1.264 brouard 7369: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7370: } /* end nres */
7371: } /* end kl 3eme */
1.126 brouard 7372:
1.223 brouard 7373: /* 4eme */
1.201 brouard 7374: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7375: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7376: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7377: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7378: continue;
1.238 brouard 7379: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7380: strcpy(gplotlabel,"(");
1.238 brouard 7381: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7382: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7383: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7384: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7385: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7386: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7387: vlv= nbcode[Tvaraff[k]][lv];
7388: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7389: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7390: }
7391: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7392: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7393: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7394: }
1.264 brouard 7395: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7396: fprintf(ficgp,"\n#\n");
7397: if(invalidvarcomb[k1]){
7398: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7399: continue;
1.223 brouard 7400: }
1.238 brouard 7401:
1.241 brouard 7402: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7403: 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 7404: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7405: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7406: k=3;
7407: for (i=1; i<= nlstate ; i ++){
7408: if(i==1){
7409: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7410: }else{
7411: fprintf(ficgp,", '' ");
7412: }
7413: l=(nlstate+ndeath)*(i-1)+1;
7414: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7415: for (j=2; j<= nlstate+ndeath ; j ++)
7416: fprintf(ficgp,"+$%d",k+l+j-1);
7417: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7418: } /* nlstate */
1.264 brouard 7419: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7420: } /* end cpt state*/
7421: } /* end nres */
7422: } /* end covariate k1 */
7423:
1.220 brouard 7424: /* 5eme */
1.201 brouard 7425: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7426: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7427: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7428: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7429: continue;
1.238 brouard 7430: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7431: strcpy(gplotlabel,"(");
1.238 brouard 7432: 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);
7433: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7434: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7435: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7436: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7437: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7438: vlv= nbcode[Tvaraff[k]][lv];
7439: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7440: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7441: }
7442: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7443: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7444: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7445: }
1.264 brouard 7446: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7447: fprintf(ficgp,"\n#\n");
7448: if(invalidvarcomb[k1]){
7449: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7450: continue;
7451: }
1.227 brouard 7452:
1.241 brouard 7453: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7454: 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 7455: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7456: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7457: k=3;
7458: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7459: if(j==1)
7460: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7461: else
7462: fprintf(ficgp,", '' ");
7463: l=(nlstate+ndeath)*(cpt-1) +j;
7464: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7465: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7466: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7467: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7468: } /* nlstate */
7469: fprintf(ficgp,", '' ");
7470: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7471: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7472: l=(nlstate+ndeath)*(cpt-1) +j;
7473: if(j < nlstate)
7474: fprintf(ficgp,"$%d +",k+l);
7475: else
7476: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7477: }
1.264 brouard 7478: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7479: } /* end cpt state*/
7480: } /* end covariate */
7481: } /* end nres */
1.227 brouard 7482:
1.220 brouard 7483: /* 6eme */
1.202 brouard 7484: /* CV preval stable (period) for each covariate */
1.237 brouard 7485: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7486: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7487: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7488: continue;
1.255 brouard 7489: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7490: strcpy(gplotlabel,"(");
1.211 brouard 7491: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7492: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7493: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7494: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7495: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7496: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7497: vlv= nbcode[Tvaraff[k]][lv];
7498: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7499: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7500: }
1.237 brouard 7501: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7502: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7503: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7504: }
1.264 brouard 7505: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7506: fprintf(ficgp,"\n#\n");
1.223 brouard 7507: if(invalidvarcomb[k1]){
1.227 brouard 7508: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7509: continue;
1.223 brouard 7510: }
1.227 brouard 7511:
1.241 brouard 7512: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7513: 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 7514: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7515: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7516: k=3; /* Offset */
1.255 brouard 7517: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7518: if(i==1)
7519: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7520: else
7521: fprintf(ficgp,", '' ");
1.255 brouard 7522: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7523: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7524: for (j=2; j<= nlstate ; j ++)
7525: fprintf(ficgp,"+$%d",k+l+j-1);
7526: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7527: } /* nlstate */
1.264 brouard 7528: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7529: } /* end cpt state*/
7530: } /* end covariate */
1.227 brouard 7531:
7532:
1.220 brouard 7533: /* 7eme */
1.218 brouard 7534: if(backcast == 1){
1.217 brouard 7535: /* CV back preval stable (period) for each covariate */
1.237 brouard 7536: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7537: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7538: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7539: continue;
1.268 brouard 7540: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7541: strcpy(gplotlabel,"(");
7542: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7543: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7544: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7545: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7546: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7547: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7548: vlv= nbcode[Tvaraff[k]][lv];
7549: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7550: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7551: }
1.237 brouard 7552: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7553: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7554: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7555: }
1.264 brouard 7556: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7557: fprintf(ficgp,"\n#\n");
7558: if(invalidvarcomb[k1]){
7559: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7560: continue;
7561: }
7562:
1.241 brouard 7563: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7564: 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 7565: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7566: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7567: k=3; /* Offset */
1.268 brouard 7568: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7569: if(i==1)
7570: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7571: else
7572: fprintf(ficgp,", '' ");
7573: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7574: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7575: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7576: /* 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 7577: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7578: /* for (j=2; j<= nlstate ; j ++) */
7579: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7580: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7581: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7582: } /* nlstate */
1.264 brouard 7583: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7584: } /* end cpt state*/
7585: } /* end covariate */
7586: } /* End if backcast */
7587:
1.223 brouard 7588: /* 8eme */
1.218 brouard 7589: if(prevfcast==1){
7590: /* Projection from cross-sectional to stable (period) for each covariate */
7591:
1.237 brouard 7592: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7593: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7594: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7595: continue;
1.211 brouard 7596: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7597: strcpy(gplotlabel,"(");
1.227 brouard 7598: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
7599: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7600: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7601: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7602: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7603: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7604: vlv= nbcode[Tvaraff[k]][lv];
7605: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7606: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7607: }
1.237 brouard 7608: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7609: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7610: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7611: }
1.264 brouard 7612: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7613: fprintf(ficgp,"\n#\n");
7614: if(invalidvarcomb[k1]){
7615: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7616: continue;
7617: }
7618:
7619: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7620: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7621: 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 7622: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7623: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7624:
7625: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7626: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7627: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7628: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7629: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7630: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7631: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7632: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7633: if(i==istart){
1.227 brouard 7634: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7635: }else{
7636: fprintf(ficgp,",\\\n '' ");
7637: }
7638: if(cptcoveff ==0){ /* No covariate */
7639: ioffset=2; /* Age is in 2 */
7640: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7641: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7642: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7643: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7644: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7645: if(i==nlstate+1){
1.270 brouard 7646: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7647: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7648: fprintf(ficgp,",\\\n '' ");
7649: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7650: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7651: offyear, \
1.268 brouard 7652: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7653: }else
1.227 brouard 7654: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7655: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7656: }else{ /* more than 2 covariates */
1.270 brouard 7657: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7658: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7659: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7660: iyearc=ioffset-1;
7661: iagec=ioffset;
1.227 brouard 7662: fprintf(ficgp," u %d:(",ioffset);
7663: kl=0;
7664: strcpy(gplotcondition,"(");
7665: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7666: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7667: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7668: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7669: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7670: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7671: kl++;
7672: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7673: kl++;
7674: if(k <cptcoveff && cptcoveff>1)
7675: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7676: }
7677: strcpy(gplotcondition+strlen(gplotcondition),")");
7678: /* 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 *\/ */
7679: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7680: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7681: /* '' 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*/
7682: if(i==nlstate+1){
1.270 brouard 7683: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7684: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7685: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7686: fprintf(ficgp," u %d:(",iagec);
7687: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7688: iyearc, iagec, offyear, \
7689: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7690: /* '' 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 7691: }else{
7692: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7693: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7694: }
7695: } /* end if covariate */
7696: } /* nlstate */
1.264 brouard 7697: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7698: } /* end cpt state*/
7699: } /* end covariate */
7700: } /* End if prevfcast */
1.227 brouard 7701:
1.268 brouard 7702: if(backcast==1){
7703: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7704:
7705: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7706: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7707: if(m != 1 && TKresult[nres]!= k1)
7708: continue;
7709: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7710: strcpy(gplotlabel,"(");
7711: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7712: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7713: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7714: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7715: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7716: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7717: vlv= nbcode[Tvaraff[k]][lv];
7718: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7719: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7720: }
7721: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7722: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7723: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7724: }
7725: strcpy(gplotlabel+strlen(gplotlabel),")");
7726: fprintf(ficgp,"\n#\n");
7727: if(invalidvarcomb[k1]){
7728: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7729: continue;
7730: }
7731:
7732: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7733: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7734: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7735: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7736: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7737:
7738: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7739: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7740: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7741: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7742: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7743: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7744: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7745: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7746: if(i==istart){
7747: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7748: }else{
7749: fprintf(ficgp,",\\\n '' ");
7750: }
7751: if(cptcoveff ==0){ /* No covariate */
7752: ioffset=2; /* Age is in 2 */
7753: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7754: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7755: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7756: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7757: fprintf(ficgp," u %d:(", ioffset);
7758: if(i==nlstate+1){
1.270 brouard 7759: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7760: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7761: fprintf(ficgp,",\\\n '' ");
7762: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7763: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7764: offbyear, \
7765: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7766: }else
7767: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7768: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7769: }else{ /* more than 2 covariates */
1.270 brouard 7770: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7771: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7772: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7773: iyearc=ioffset-1;
7774: iagec=ioffset;
1.268 brouard 7775: fprintf(ficgp," u %d:(",ioffset);
7776: kl=0;
7777: strcpy(gplotcondition,"(");
7778: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7779: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7780: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7781: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7782: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7783: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7784: kl++;
7785: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7786: kl++;
7787: if(k <cptcoveff && cptcoveff>1)
7788: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7789: }
7790: strcpy(gplotcondition+strlen(gplotcondition),")");
7791: /* 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 *\/ */
7792: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7793: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7794: /* '' 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*/
7795: if(i==nlstate+1){
1.270 brouard 7796: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7797: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7798: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7799: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7800: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7801: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7802: iyearc,iagec,offbyear, \
7803: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7804: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7805: }else{
7806: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7807: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7808: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7809: }
7810: } /* end if covariate */
7811: } /* nlstate */
7812: fprintf(ficgp,"\nset out; unset label;\n");
7813: } /* end cpt state*/
7814: } /* end covariate */
7815: } /* End if backcast */
7816:
1.227 brouard 7817:
1.238 brouard 7818: /* 9eme writing MLE parameters */
7819: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7820: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7821: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7822: for(k=1; k <=(nlstate+ndeath); k++){
7823: if (k != i) {
1.227 brouard 7824: fprintf(ficgp,"# current state %d\n",k);
7825: for(j=1; j <=ncovmodel; j++){
7826: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7827: jk++;
7828: }
7829: fprintf(ficgp,"\n");
1.126 brouard 7830: }
7831: }
1.223 brouard 7832: }
1.187 brouard 7833: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7834:
1.145 brouard 7835: /*goto avoid;*/
1.238 brouard 7836: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7837: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7838: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7839: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7840: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7841: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7842: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7843: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7844: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7845: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7846: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7847: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7848: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7849: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7850: fprintf(ficgp,"#\n");
1.223 brouard 7851: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7852: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7853: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7854: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7855: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7856: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7857: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7858: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7859: continue;
1.264 brouard 7860: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7861: strcpy(gplotlabel,"(");
1.276 brouard 7862: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7863: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7864: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7865: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7866: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7867: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7868: vlv= nbcode[Tvaraff[k]][lv];
7869: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7870: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7871: }
1.237 brouard 7872: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7873: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7874: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7875: }
1.264 brouard 7876: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7877: fprintf(ficgp,"\n#\n");
1.264 brouard 7878: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7879: fprintf(ficgp,"\nset key outside ");
7880: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7881: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7882: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7883: if (ng==1){
7884: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7885: fprintf(ficgp,"\nunset log y");
7886: }else if (ng==2){
7887: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7888: fprintf(ficgp,"\nset log y");
7889: }else if (ng==3){
7890: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7891: fprintf(ficgp,"\nset log y");
7892: }else
7893: fprintf(ficgp,"\nunset title ");
7894: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7895: i=1;
7896: for(k2=1; k2<=nlstate; k2++) {
7897: k3=i;
7898: for(k=1; k<=(nlstate+ndeath); k++) {
7899: if (k != k2){
7900: switch( ng) {
7901: case 1:
7902: if(nagesqr==0)
7903: fprintf(ficgp," p%d+p%d*x",i,i+1);
7904: else /* nagesqr =1 */
7905: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7906: break;
7907: case 2: /* ng=2 */
7908: if(nagesqr==0)
7909: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7910: else /* nagesqr =1 */
7911: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7912: break;
7913: case 3:
7914: if(nagesqr==0)
7915: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7916: else /* nagesqr =1 */
7917: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7918: break;
7919: }
7920: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7921: ijp=1; /* product no age */
7922: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7923: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7924: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7925: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7926: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7927: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7928: if(DummyV[j]==0){
7929: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7930: }else{ /* quantitative */
7931: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7932: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7933: }
7934: ij++;
1.237 brouard 7935: }
1.268 brouard 7936: }
7937: }else if(cptcovprod >0){
7938: if(j==Tprod[ijp]) { /* */
7939: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7940: if(ijp <=cptcovprod) { /* Product */
7941: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7942: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7943: /* 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)]); */
7944: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7945: }else{ /* Vn is dummy and Vm is quanti */
7946: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7947: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7948: }
7949: }else{ /* Vn*Vm Vn is quanti */
7950: if(DummyV[Tvard[ijp][2]]==0){
7951: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7952: }else{ /* Both quanti */
7953: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7954: }
1.237 brouard 7955: }
1.268 brouard 7956: ijp++;
1.237 brouard 7957: }
1.268 brouard 7958: } /* end Tprod */
1.237 brouard 7959: } else{ /* simple covariate */
1.264 brouard 7960: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7961: if(Dummy[j]==0){
7962: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7963: }else{ /* quantitative */
7964: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7965: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7966: }
1.237 brouard 7967: } /* end simple */
7968: } /* end j */
1.223 brouard 7969: }else{
7970: i=i-ncovmodel;
7971: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7972: fprintf(ficgp," (1.");
7973: }
1.227 brouard 7974:
1.223 brouard 7975: if(ng != 1){
7976: fprintf(ficgp,")/(1");
1.227 brouard 7977:
1.264 brouard 7978: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7979: if(nagesqr==0)
1.264 brouard 7980: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7981: else /* nagesqr =1 */
1.264 brouard 7982: 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 7983:
1.223 brouard 7984: ij=1;
7985: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 7986: if(cptcovage >0){
7987: if((j-2)==Tage[ij]) { /* Bug valgrind */
7988: if(ij <=cptcovage) { /* Bug valgrind */
7989: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
7990: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7991: ij++;
7992: }
7993: }
7994: }else
7995: 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 7996: }
7997: fprintf(ficgp,")");
7998: }
7999: fprintf(ficgp,")");
8000: if(ng ==2)
1.276 brouard 8001: 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 8002: else /* ng= 3 */
1.276 brouard 8003: 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 8004: }else{ /* end ng <> 1 */
8005: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8006: 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 8007: }
8008: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8009: fprintf(ficgp,",");
8010: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8011: fprintf(ficgp,",");
8012: i=i+ncovmodel;
8013: } /* end k */
8014: } /* end k2 */
1.276 brouard 8015: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8016: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8017: } /* end k1 */
1.223 brouard 8018: } /* end ng */
8019: /* avoid: */
8020: fflush(ficgp);
1.126 brouard 8021: } /* end gnuplot */
8022:
8023:
8024: /*************** Moving average **************/
1.219 brouard 8025: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8026: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8027:
1.222 brouard 8028: int i, cpt, cptcod;
8029: int modcovmax =1;
8030: int mobilavrange, mob;
8031: int iage=0;
8032:
1.266 brouard 8033: double sum=0., sumr=0.;
1.222 brouard 8034: double age;
1.266 brouard 8035: double *sumnewp, *sumnewm, *sumnewmr;
8036: double *agemingood, *agemaxgood;
8037: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8038:
8039:
1.278 brouard 8040: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8041: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8042:
8043: sumnewp = vector(1,ncovcombmax);
8044: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8045: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8046: agemingood = vector(1,ncovcombmax);
1.266 brouard 8047: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8048: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8049: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8050:
8051: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8052: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8053: sumnewp[cptcod]=0.;
1.266 brouard 8054: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8055: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8056: }
8057: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8058:
1.266 brouard 8059: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8060: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8061: else mobilavrange=mobilav;
8062: for (age=bage; age<=fage; age++)
8063: for (i=1; i<=nlstate;i++)
8064: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8065: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8066: /* We keep the original values on the extreme ages bage, fage and for
8067: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8068: we use a 5 terms etc. until the borders are no more concerned.
8069: */
8070: for (mob=3;mob <=mobilavrange;mob=mob+2){
8071: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8072: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8073: sumnewm[cptcod]=0.;
8074: for (i=1; i<=nlstate;i++){
1.222 brouard 8075: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8076: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8077: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8078: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8079: }
8080: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8081: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8082: } /* end i */
8083: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8084: } /* end cptcod */
1.222 brouard 8085: }/* end age */
8086: }/* end mob */
1.266 brouard 8087: }else{
8088: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8089: return -1;
1.266 brouard 8090: }
8091:
8092: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8093: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8094: if(invalidvarcomb[cptcod]){
8095: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8096: continue;
8097: }
1.219 brouard 8098:
1.266 brouard 8099: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8100: sumnewm[cptcod]=0.;
8101: sumnewmr[cptcod]=0.;
8102: for (i=1; i<=nlstate;i++){
8103: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8104: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8105: }
8106: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8107: agemingoodr[cptcod]=age;
8108: }
8109: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8110: agemingood[cptcod]=age;
8111: }
8112: } /* age */
8113: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8114: sumnewm[cptcod]=0.;
1.266 brouard 8115: sumnewmr[cptcod]=0.;
1.222 brouard 8116: for (i=1; i<=nlstate;i++){
8117: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8118: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8119: }
8120: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8121: agemaxgoodr[cptcod]=age;
1.222 brouard 8122: }
8123: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8124: agemaxgood[cptcod]=age;
8125: }
8126: } /* age */
8127: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8128: /* but they will change */
8129: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8130: sumnewm[cptcod]=0.;
8131: sumnewmr[cptcod]=0.;
8132: for (i=1; i<=nlstate;i++){
8133: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8134: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8135: }
8136: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8137: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8138: agemaxgoodr[cptcod]=age; /* age min */
8139: for (i=1; i<=nlstate;i++)
8140: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8141: }else{ /* bad we change the value with the values of good ages */
8142: for (i=1; i<=nlstate;i++){
8143: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8144: } /* i */
8145: } /* end bad */
8146: }else{
8147: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8148: agemaxgood[cptcod]=age;
8149: }else{ /* bad we change the value with the values of good ages */
8150: for (i=1; i<=nlstate;i++){
8151: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8152: } /* i */
8153: } /* end bad */
8154: }/* end else */
8155: sum=0.;sumr=0.;
8156: for (i=1; i<=nlstate;i++){
8157: sum+=mobaverage[(int)age][i][cptcod];
8158: sumr+=probs[(int)age][i][cptcod];
8159: }
8160: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8161: 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\n",cptcod,sumr, (int)age, (int)bage);
1.266 brouard 8162: } /* end bad */
8163: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8164: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8165: 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\n",cptcod,sumr, (int)age, (int)bage);
1.222 brouard 8166: } /* end bad */
8167: }/* age */
1.266 brouard 8168:
8169: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8170: sumnewm[cptcod]=0.;
1.266 brouard 8171: sumnewmr[cptcod]=0.;
1.222 brouard 8172: for (i=1; i<=nlstate;i++){
8173: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8174: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8175: }
8176: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8177: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8178: agemingoodr[cptcod]=age;
8179: for (i=1; i<=nlstate;i++)
8180: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8181: }else{ /* bad we change the value with the values of good ages */
8182: for (i=1; i<=nlstate;i++){
8183: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8184: } /* i */
8185: } /* end bad */
8186: }else{
8187: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8188: agemingood[cptcod]=age;
8189: }else{ /* bad */
8190: for (i=1; i<=nlstate;i++){
8191: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8192: } /* i */
8193: } /* end bad */
8194: }/* end else */
8195: sum=0.;sumr=0.;
8196: for (i=1; i<=nlstate;i++){
8197: sum+=mobaverage[(int)age][i][cptcod];
8198: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8199: }
1.266 brouard 8200: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8201: 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 8202: } /* end bad */
8203: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8204: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8205: 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 8206: } /* end bad */
8207: }/* age */
1.266 brouard 8208:
1.222 brouard 8209:
8210: for (age=bage; age<=fage; age++){
1.235 brouard 8211: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8212: sumnewp[cptcod]=0.;
8213: sumnewm[cptcod]=0.;
8214: for (i=1; i<=nlstate;i++){
8215: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8216: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8217: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8218: }
8219: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8220: }
8221: /* printf("\n"); */
8222: /* } */
1.266 brouard 8223:
1.222 brouard 8224: /* brutal averaging */
1.266 brouard 8225: /* for (i=1; i<=nlstate;i++){ */
8226: /* for (age=1; age<=bage; age++){ */
8227: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8228: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8229: /* } */
8230: /* for (age=fage; age<=AGESUP; age++){ */
8231: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8232: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8233: /* } */
8234: /* } /\* end i status *\/ */
8235: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8236: /* for (age=1; age<=AGESUP; age++){ */
8237: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8238: /* mobaverage[(int)age][i][cptcod]=0.; */
8239: /* } */
8240: /* } */
1.222 brouard 8241: }/* end cptcod */
1.266 brouard 8242: free_vector(agemaxgoodr,1, ncovcombmax);
8243: free_vector(agemaxgood,1, ncovcombmax);
8244: free_vector(agemingood,1, ncovcombmax);
8245: free_vector(agemingoodr,1, ncovcombmax);
8246: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8247: free_vector(sumnewm,1, ncovcombmax);
8248: free_vector(sumnewp,1, ncovcombmax);
8249: return 0;
8250: }/* End movingaverage */
1.218 brouard 8251:
1.126 brouard 8252:
8253: /************** Forecasting ******************/
1.269 brouard 8254: 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 8255: /* proj1, year, month, day of starting projection
8256: agemin, agemax range of age
8257: dateprev1 dateprev2 range of dates during which prevalence is computed
8258: anproj2 year of en of projection (same day and month as proj1).
8259: */
1.267 brouard 8260: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8261: double agec; /* generic age */
8262: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8263: double *popeffectif,*popcount;
8264: double ***p3mat;
1.218 brouard 8265: /* double ***mobaverage; */
1.126 brouard 8266: char fileresf[FILENAMELENGTH];
8267:
8268: agelim=AGESUP;
1.211 brouard 8269: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8270: in each health status at the date of interview (if between dateprev1 and dateprev2).
8271: We still use firstpass and lastpass as another selection.
8272: */
1.214 brouard 8273: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8274: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8275:
1.201 brouard 8276: strcpy(fileresf,"F_");
8277: strcat(fileresf,fileresu);
1.126 brouard 8278: if((ficresf=fopen(fileresf,"w"))==NULL) {
8279: printf("Problem with forecast resultfile: %s\n", fileresf);
8280: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8281: }
1.235 brouard 8282: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8283: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8284:
1.225 brouard 8285: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8286:
8287:
8288: stepsize=(int) (stepm+YEARM-1)/YEARM;
8289: if (stepm<=12) stepsize=1;
8290: if(estepm < stepm){
8291: printf ("Problem %d lower than %d\n",estepm, stepm);
8292: }
1.270 brouard 8293: else{
8294: hstepm=estepm;
8295: }
8296: if(estepm > stepm){ /* Yes every two year */
8297: stepsize=2;
8298: }
1.126 brouard 8299:
8300: hstepm=hstepm/stepm;
8301: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8302: fractional in yp1 */
8303: anprojmean=yp;
8304: yp2=modf((yp1*12),&yp);
8305: mprojmean=yp;
8306: yp1=modf((yp2*30.5),&yp);
8307: jprojmean=yp;
8308: if(jprojmean==0) jprojmean=1;
8309: if(mprojmean==0) jprojmean=1;
8310:
1.227 brouard 8311: i1=pow(2,cptcoveff);
1.126 brouard 8312: if (cptcovn < 1){i1=1;}
8313:
8314: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8315:
8316: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8317:
1.126 brouard 8318: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8319: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8320: for(k=1; k<=i1;k++){
1.253 brouard 8321: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8322: continue;
1.227 brouard 8323: if(invalidvarcomb[k]){
8324: printf("\nCombination (%d) projection ignored because no cases \n",k);
8325: continue;
8326: }
8327: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8328: for(j=1;j<=cptcoveff;j++) {
8329: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8330: }
1.235 brouard 8331: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8332: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8333: }
1.227 brouard 8334: fprintf(ficresf," yearproj age");
8335: for(j=1; j<=nlstate+ndeath;j++){
8336: for(i=1; i<=nlstate;i++)
8337: fprintf(ficresf," p%d%d",i,j);
8338: fprintf(ficresf," wp.%d",j);
8339: }
8340: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8341: fprintf(ficresf,"\n");
8342: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8343: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8344: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8345: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8346: nhstepm = nhstepm/hstepm;
8347: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8348: oldm=oldms;savm=savms;
1.268 brouard 8349: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8350: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8351: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8352: for (h=0; h<=nhstepm; h++){
8353: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8354: break;
8355: }
8356: }
8357: fprintf(ficresf,"\n");
8358: for(j=1;j<=cptcoveff;j++)
8359: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8360: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8361:
8362: for(j=1; j<=nlstate+ndeath;j++) {
8363: ppij=0.;
8364: for(i=1; i<=nlstate;i++) {
1.278 brouard 8365: if (mobilav>=1)
8366: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8367: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8368: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8369: }
1.268 brouard 8370: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8371: } /* end i */
8372: fprintf(ficresf," %.3f", ppij);
8373: }/* end j */
1.227 brouard 8374: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8375: } /* end agec */
1.266 brouard 8376: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8377: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8378: } /* end yearp */
8379: } /* end k */
1.219 brouard 8380:
1.126 brouard 8381: fclose(ficresf);
1.215 brouard 8382: printf("End of Computing forecasting \n");
8383: fprintf(ficlog,"End of Computing forecasting\n");
8384:
1.126 brouard 8385: }
8386:
1.269 brouard 8387: /************** Back Forecasting ******************/
8388: 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 8389: /* back1, year, month, day of starting backection
8390: agemin, agemax range of age
8391: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8392: anback2 year of end of backprojection (same day and month as back1).
8393: prevacurrent and prev are prevalences.
1.267 brouard 8394: */
8395: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8396: double agec; /* generic age */
1.268 brouard 8397: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8398: double *popeffectif,*popcount;
8399: double ***p3mat;
8400: /* double ***mobaverage; */
8401: char fileresfb[FILENAMELENGTH];
8402:
1.268 brouard 8403: agelim=AGEINF;
1.267 brouard 8404: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8405: in each health status at the date of interview (if between dateprev1 and dateprev2).
8406: We still use firstpass and lastpass as another selection.
8407: */
8408: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8409: /* firstpass, lastpass, stepm, weightopt, model); */
8410:
8411: /*Do we need to compute prevalence again?*/
8412:
8413: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8414:
8415: strcpy(fileresfb,"FB_");
8416: strcat(fileresfb,fileresu);
8417: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8418: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8419: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8420: }
8421: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8422: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8423:
8424: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8425:
8426:
8427: stepsize=(int) (stepm+YEARM-1)/YEARM;
8428: if (stepm<=12) stepsize=1;
8429: if(estepm < stepm){
8430: printf ("Problem %d lower than %d\n",estepm, stepm);
8431: }
1.270 brouard 8432: else{
8433: hstepm=estepm;
8434: }
8435: if(estepm >= stepm){ /* Yes every two year */
8436: stepsize=2;
8437: }
1.267 brouard 8438:
8439: hstepm=hstepm/stepm;
8440: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8441: fractional in yp1 */
8442: anprojmean=yp;
8443: yp2=modf((yp1*12),&yp);
8444: mprojmean=yp;
8445: yp1=modf((yp2*30.5),&yp);
8446: jprojmean=yp;
8447: if(jprojmean==0) jprojmean=1;
8448: if(mprojmean==0) jprojmean=1;
8449:
8450: i1=pow(2,cptcoveff);
8451: if (cptcovn < 1){i1=1;}
8452:
8453: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8454: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8455:
8456: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8457:
8458: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8459: for(k=1; k<=i1;k++){
8460: if(i1 != 1 && TKresult[nres]!= k)
8461: continue;
8462: if(invalidvarcomb[k]){
8463: printf("\nCombination (%d) projection ignored because no cases \n",k);
8464: continue;
8465: }
1.268 brouard 8466: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8467: for(j=1;j<=cptcoveff;j++) {
8468: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8469: }
8470: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8471: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8472: }
8473: fprintf(ficresfb," yearbproj age");
8474: for(j=1; j<=nlstate+ndeath;j++){
8475: for(i=1; i<=nlstate;i++)
1.268 brouard 8476: fprintf(ficresfb," b%d%d",i,j);
8477: fprintf(ficresfb," b.%d",j);
1.267 brouard 8478: }
8479: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8480: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8481: fprintf(ficresfb,"\n");
8482: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.273 brouard 8483: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8484: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8485: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8486: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8487: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8488: nhstepm = nhstepm/hstepm;
8489: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8490: oldm=oldms;savm=savms;
1.268 brouard 8491: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8492: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8493: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8494: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8495: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8496: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8497: for (h=0; h<=nhstepm; h++){
1.268 brouard 8498: if (h*hstepm/YEARM*stepm ==-yearp) {
8499: break;
8500: }
8501: }
8502: fprintf(ficresfb,"\n");
8503: for(j=1;j<=cptcoveff;j++)
8504: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8505: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8506: for(i=1; i<=nlstate+ndeath;i++) {
8507: ppij=0.;ppi=0.;
8508: for(j=1; j<=nlstate;j++) {
8509: /* if (mobilav==1) */
1.269 brouard 8510: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8511: ppi=ppi+prevacurrent[(int)agec][j][k];
8512: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8513: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8514: /* else { */
8515: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8516: /* } */
1.268 brouard 8517: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8518: } /* end j */
8519: if(ppi <0.99){
8520: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8521: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8522: }
8523: fprintf(ficresfb," %.3f", ppij);
8524: }/* end j */
1.267 brouard 8525: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8526: } /* end agec */
8527: } /* end yearp */
8528: } /* end k */
1.217 brouard 8529:
1.267 brouard 8530: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8531:
1.267 brouard 8532: fclose(ficresfb);
8533: printf("End of Computing Back forecasting \n");
8534: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8535:
1.267 brouard 8536: }
1.217 brouard 8537:
1.269 brouard 8538: /* Variance of prevalence limit: varprlim */
8539: 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){
8540: /*------- Variance of period (stable) prevalence------*/
8541:
8542: char fileresvpl[FILENAMELENGTH];
8543: FILE *ficresvpl;
8544: double **oldm, **savm;
8545: double **varpl; /* Variances of prevalence limits by age */
8546: int i1, k, nres, j ;
8547:
8548: strcpy(fileresvpl,"VPL_");
8549: strcat(fileresvpl,fileresu);
8550: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
8551: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
8552: exit(0);
8553: }
8554: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8555: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
8556:
8557: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8558: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8559:
8560: i1=pow(2,cptcoveff);
8561: if (cptcovn < 1){i1=1;}
8562:
8563: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8564: for(k=1; k<=i1;k++){
8565: if(i1 != 1 && TKresult[nres]!= k)
8566: continue;
8567: fprintf(ficresvpl,"\n#****** ");
8568: printf("\n#****** ");
8569: fprintf(ficlog,"\n#****** ");
8570: for(j=1;j<=cptcoveff;j++) {
8571: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8572: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8573: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8574: }
8575: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8576: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8577: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8578: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8579: }
8580: fprintf(ficresvpl,"******\n");
8581: printf("******\n");
8582: fprintf(ficlog,"******\n");
8583:
8584: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8585: oldm=oldms;savm=savms;
8586: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8587: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8588: /*}*/
8589: }
8590:
8591: fclose(ficresvpl);
8592: printf("done variance-covariance of period prevalence\n");fflush(stdout);
8593: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
8594:
8595: }
8596: /* Variance of back prevalence: varbprlim */
8597: 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){
8598: /*------- Variance of back (stable) prevalence------*/
8599:
8600: char fileresvbl[FILENAMELENGTH];
8601: FILE *ficresvbl;
8602:
8603: double **oldm, **savm;
8604: double **varbpl; /* Variances of back prevalence limits by age */
8605: int i1, k, nres, j ;
8606:
8607: strcpy(fileresvbl,"VBL_");
8608: strcat(fileresvbl,fileresu);
8609: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8610: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8611: exit(0);
8612: }
8613: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8614: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8615:
8616:
8617: i1=pow(2,cptcoveff);
8618: if (cptcovn < 1){i1=1;}
8619:
8620: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8621: for(k=1; k<=i1;k++){
8622: if(i1 != 1 && TKresult[nres]!= k)
8623: continue;
8624: fprintf(ficresvbl,"\n#****** ");
8625: printf("\n#****** ");
8626: fprintf(ficlog,"\n#****** ");
8627: for(j=1;j<=cptcoveff;j++) {
8628: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8629: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8630: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8631: }
8632: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8633: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8634: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8635: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8636: }
8637: fprintf(ficresvbl,"******\n");
8638: printf("******\n");
8639: fprintf(ficlog,"******\n");
8640:
8641: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8642: oldm=oldms;savm=savms;
8643:
8644: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8645: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8646: /*}*/
8647: }
8648:
8649: fclose(ficresvbl);
8650: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8651: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8652:
8653: } /* End of varbprlim */
8654:
1.126 brouard 8655: /************** Forecasting *****not tested NB*************/
1.227 brouard 8656: /* 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 8657:
1.227 brouard 8658: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8659: /* int *popage; */
8660: /* double calagedatem, agelim, kk1, kk2; */
8661: /* double *popeffectif,*popcount; */
8662: /* double ***p3mat,***tabpop,***tabpopprev; */
8663: /* /\* double ***mobaverage; *\/ */
8664: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8665:
1.227 brouard 8666: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8667: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8668: /* agelim=AGESUP; */
8669: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8670:
1.227 brouard 8671: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8672:
8673:
1.227 brouard 8674: /* strcpy(filerespop,"POP_"); */
8675: /* strcat(filerespop,fileresu); */
8676: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8677: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8678: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8679: /* } */
8680: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8681: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8682:
1.227 brouard 8683: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8684:
1.227 brouard 8685: /* /\* if (mobilav!=0) { *\/ */
8686: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8687: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8688: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8689: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8690: /* /\* } *\/ */
8691: /* /\* } *\/ */
1.126 brouard 8692:
1.227 brouard 8693: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8694: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8695:
1.227 brouard 8696: /* agelim=AGESUP; */
1.126 brouard 8697:
1.227 brouard 8698: /* hstepm=1; */
8699: /* hstepm=hstepm/stepm; */
1.218 brouard 8700:
1.227 brouard 8701: /* if (popforecast==1) { */
8702: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8703: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8704: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8705: /* } */
8706: /* popage=ivector(0,AGESUP); */
8707: /* popeffectif=vector(0,AGESUP); */
8708: /* popcount=vector(0,AGESUP); */
1.126 brouard 8709:
1.227 brouard 8710: /* i=1; */
8711: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8712:
1.227 brouard 8713: /* imx=i; */
8714: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8715: /* } */
1.218 brouard 8716:
1.227 brouard 8717: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8718: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8719: /* k=k+1; */
8720: /* fprintf(ficrespop,"\n#******"); */
8721: /* for(j=1;j<=cptcoveff;j++) { */
8722: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8723: /* } */
8724: /* fprintf(ficrespop,"******\n"); */
8725: /* fprintf(ficrespop,"# Age"); */
8726: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8727: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8728:
1.227 brouard 8729: /* for (cpt=0; cpt<=0;cpt++) { */
8730: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8731:
1.227 brouard 8732: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8733: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8734: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8735:
1.227 brouard 8736: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8737: /* oldm=oldms;savm=savms; */
8738: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8739:
1.227 brouard 8740: /* for (h=0; h<=nhstepm; h++){ */
8741: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8742: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8743: /* } */
8744: /* for(j=1; j<=nlstate+ndeath;j++) { */
8745: /* kk1=0.;kk2=0; */
8746: /* for(i=1; i<=nlstate;i++) { */
8747: /* if (mobilav==1) */
8748: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8749: /* else { */
8750: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8751: /* } */
8752: /* } */
8753: /* if (h==(int)(calagedatem+12*cpt)){ */
8754: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8755: /* /\*fprintf(ficrespop," %.3f", kk1); */
8756: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8757: /* } */
8758: /* } */
8759: /* for(i=1; i<=nlstate;i++){ */
8760: /* kk1=0.; */
8761: /* for(j=1; j<=nlstate;j++){ */
8762: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8763: /* } */
8764: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8765: /* } */
1.218 brouard 8766:
1.227 brouard 8767: /* if (h==(int)(calagedatem+12*cpt)) */
8768: /* for(j=1; j<=nlstate;j++) */
8769: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8770: /* } */
8771: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8772: /* } */
8773: /* } */
1.218 brouard 8774:
1.227 brouard 8775: /* /\******\/ */
1.218 brouard 8776:
1.227 brouard 8777: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8778: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8779: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8780: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8781: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8782:
1.227 brouard 8783: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8784: /* oldm=oldms;savm=savms; */
8785: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8786: /* for (h=0; h<=nhstepm; h++){ */
8787: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8788: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8789: /* } */
8790: /* for(j=1; j<=nlstate+ndeath;j++) { */
8791: /* kk1=0.;kk2=0; */
8792: /* for(i=1; i<=nlstate;i++) { */
8793: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8794: /* } */
8795: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8796: /* } */
8797: /* } */
8798: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8799: /* } */
8800: /* } */
8801: /* } */
8802: /* } */
1.218 brouard 8803:
1.227 brouard 8804: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8805:
1.227 brouard 8806: /* if (popforecast==1) { */
8807: /* free_ivector(popage,0,AGESUP); */
8808: /* free_vector(popeffectif,0,AGESUP); */
8809: /* free_vector(popcount,0,AGESUP); */
8810: /* } */
8811: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8812: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8813: /* fclose(ficrespop); */
8814: /* } /\* End of popforecast *\/ */
1.218 brouard 8815:
1.126 brouard 8816: int fileappend(FILE *fichier, char *optionfich)
8817: {
8818: if((fichier=fopen(optionfich,"a"))==NULL) {
8819: printf("Problem with file: %s\n", optionfich);
8820: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8821: return (0);
8822: }
8823: fflush(fichier);
8824: return (1);
8825: }
8826:
8827:
8828: /**************** function prwizard **********************/
8829: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8830: {
8831:
8832: /* Wizard to print covariance matrix template */
8833:
1.164 brouard 8834: char ca[32], cb[32];
8835: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8836: int numlinepar;
8837:
8838: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8839: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8840: for(i=1; i <=nlstate; i++){
8841: jj=0;
8842: for(j=1; j <=nlstate+ndeath; j++){
8843: if(j==i) continue;
8844: jj++;
8845: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8846: printf("%1d%1d",i,j);
8847: fprintf(ficparo,"%1d%1d",i,j);
8848: for(k=1; k<=ncovmodel;k++){
8849: /* printf(" %lf",param[i][j][k]); */
8850: /* fprintf(ficparo," %lf",param[i][j][k]); */
8851: printf(" 0.");
8852: fprintf(ficparo," 0.");
8853: }
8854: printf("\n");
8855: fprintf(ficparo,"\n");
8856: }
8857: }
8858: printf("# Scales (for hessian or gradient estimation)\n");
8859: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8860: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8861: for(i=1; i <=nlstate; i++){
8862: jj=0;
8863: for(j=1; j <=nlstate+ndeath; j++){
8864: if(j==i) continue;
8865: jj++;
8866: fprintf(ficparo,"%1d%1d",i,j);
8867: printf("%1d%1d",i,j);
8868: fflush(stdout);
8869: for(k=1; k<=ncovmodel;k++){
8870: /* printf(" %le",delti3[i][j][k]); */
8871: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8872: printf(" 0.");
8873: fprintf(ficparo," 0.");
8874: }
8875: numlinepar++;
8876: printf("\n");
8877: fprintf(ficparo,"\n");
8878: }
8879: }
8880: printf("# Covariance matrix\n");
8881: /* # 121 Var(a12)\n\ */
8882: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8883: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8884: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8885: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8886: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8887: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8888: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8889: fflush(stdout);
8890: fprintf(ficparo,"# Covariance matrix\n");
8891: /* # 121 Var(a12)\n\ */
8892: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8893: /* # ...\n\ */
8894: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8895:
8896: for(itimes=1;itimes<=2;itimes++){
8897: jj=0;
8898: for(i=1; i <=nlstate; i++){
8899: for(j=1; j <=nlstate+ndeath; j++){
8900: if(j==i) continue;
8901: for(k=1; k<=ncovmodel;k++){
8902: jj++;
8903: ca[0]= k+'a'-1;ca[1]='\0';
8904: if(itimes==1){
8905: printf("#%1d%1d%d",i,j,k);
8906: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8907: }else{
8908: printf("%1d%1d%d",i,j,k);
8909: fprintf(ficparo,"%1d%1d%d",i,j,k);
8910: /* printf(" %.5le",matcov[i][j]); */
8911: }
8912: ll=0;
8913: for(li=1;li <=nlstate; li++){
8914: for(lj=1;lj <=nlstate+ndeath; lj++){
8915: if(lj==li) continue;
8916: for(lk=1;lk<=ncovmodel;lk++){
8917: ll++;
8918: if(ll<=jj){
8919: cb[0]= lk +'a'-1;cb[1]='\0';
8920: if(ll<jj){
8921: if(itimes==1){
8922: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8923: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8924: }else{
8925: printf(" 0.");
8926: fprintf(ficparo," 0.");
8927: }
8928: }else{
8929: if(itimes==1){
8930: printf(" Var(%s%1d%1d)",ca,i,j);
8931: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8932: }else{
8933: printf(" 0.");
8934: fprintf(ficparo," 0.");
8935: }
8936: }
8937: }
8938: } /* end lk */
8939: } /* end lj */
8940: } /* end li */
8941: printf("\n");
8942: fprintf(ficparo,"\n");
8943: numlinepar++;
8944: } /* end k*/
8945: } /*end j */
8946: } /* end i */
8947: } /* end itimes */
8948:
8949: } /* end of prwizard */
8950: /******************* Gompertz Likelihood ******************************/
8951: double gompertz(double x[])
8952: {
8953: double A,B,L=0.0,sump=0.,num=0.;
8954: int i,n=0; /* n is the size of the sample */
8955:
1.220 brouard 8956: for (i=1;i<=imx ; i++) {
1.126 brouard 8957: sump=sump+weight[i];
8958: /* sump=sump+1;*/
8959: num=num+1;
8960: }
8961:
8962:
8963: /* for (i=0; i<=imx; i++)
8964: 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]);*/
8965:
8966: for (i=1;i<=imx ; i++)
8967: {
8968: if (cens[i] == 1 && wav[i]>1)
8969: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8970:
8971: if (cens[i] == 0 && wav[i]>1)
8972: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8973: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8974:
8975: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8976: if (wav[i] > 1 ) { /* ??? */
8977: L=L+A*weight[i];
8978: /* 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]);*/
8979: }
8980: }
8981:
8982: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8983:
8984: return -2*L*num/sump;
8985: }
8986:
1.136 brouard 8987: #ifdef GSL
8988: /******************* Gompertz_f Likelihood ******************************/
8989: double gompertz_f(const gsl_vector *v, void *params)
8990: {
8991: double A,B,LL=0.0,sump=0.,num=0.;
8992: double *x= (double *) v->data;
8993: int i,n=0; /* n is the size of the sample */
8994:
8995: for (i=0;i<=imx-1 ; i++) {
8996: sump=sump+weight[i];
8997: /* sump=sump+1;*/
8998: num=num+1;
8999: }
9000:
9001:
9002: /* for (i=0; i<=imx; i++)
9003: if (wav[i]>0) printf("i=%d ageex=%lf agecens=%lf agedc=%lf cens=%d %d\n" ,i,ageexmed[i],agecens[i],agedc[i],cens[i],wav[i]);*/
9004: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9005: for (i=1;i<=imx ; i++)
9006: {
9007: if (cens[i] == 1 && wav[i]>1)
9008: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9009:
9010: if (cens[i] == 0 && wav[i]>1)
9011: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9012: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9013:
9014: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9015: if (wav[i] > 1 ) { /* ??? */
9016: LL=LL+A*weight[i];
9017: /* printf("\ni=%d A=%f L=%lf x[1]=%lf x[2]=%lf ageex=%lf agecens=%lf cens=%d agedc=%lf weight=%lf\n",i,A,L,x[1],x[2],ageexmed[i]*12,agecens[i]*12,cens[i],agedc[i]*12,weight[i]);*/
9018: }
9019: }
9020:
9021: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9022: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9023:
9024: return -2*LL*num/sump;
9025: }
9026: #endif
9027:
1.126 brouard 9028: /******************* Printing html file ***********/
1.201 brouard 9029: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9030: int lastpass, int stepm, int weightopt, char model[],\
9031: int imx, double p[],double **matcov,double agemortsup){
9032: int i,k;
9033:
9034: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9035: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9036: for (i=1;i<=2;i++)
9037: 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 9038: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9039: fprintf(fichtm,"</ul>");
9040:
9041: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9042:
9043: 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>");
9044:
9045: for (k=agegomp;k<(agemortsup-2);k++)
9046: 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]);
9047:
9048:
9049: fflush(fichtm);
9050: }
9051:
9052: /******************* Gnuplot file **************/
1.201 brouard 9053: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9054:
9055: char dirfileres[132],optfileres[132];
1.164 brouard 9056:
1.126 brouard 9057: int ng;
9058:
9059:
9060: /*#ifdef windows */
9061: fprintf(ficgp,"cd \"%s\" \n",pathc);
9062: /*#endif */
9063:
9064:
9065: strcpy(dirfileres,optionfilefiname);
9066: strcpy(optfileres,"vpl");
1.199 brouard 9067: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9068: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9069: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9070: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9071: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9072:
9073: }
9074:
1.136 brouard 9075: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9076: {
1.126 brouard 9077:
1.136 brouard 9078: /*-------- data file ----------*/
9079: FILE *fic;
9080: char dummy[]=" ";
1.240 brouard 9081: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9082: int lstra;
1.136 brouard 9083: int linei, month, year,iout;
9084: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9085: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9086: char *stratrunc;
1.223 brouard 9087:
1.240 brouard 9088: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9089: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9090:
1.240 brouard 9091: for(v=1; v <=ncovcol;v++){
9092: DummyV[v]=0;
9093: FixedV[v]=0;
9094: }
9095: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9096: DummyV[v]=1;
9097: FixedV[v]=0;
9098: }
9099: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9100: DummyV[v]=0;
9101: FixedV[v]=1;
9102: }
9103: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9104: DummyV[v]=1;
9105: FixedV[v]=1;
9106: }
9107: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9108: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9109: 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]);
9110: }
1.126 brouard 9111:
1.136 brouard 9112: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9113: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9114: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9115: }
1.126 brouard 9116:
1.136 brouard 9117: i=1;
9118: linei=0;
9119: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9120: linei=linei+1;
9121: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9122: if(line[j] == '\t')
9123: line[j] = ' ';
9124: }
9125: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9126: ;
9127: };
9128: line[j+1]=0; /* Trims blanks at end of line */
9129: if(line[0]=='#'){
9130: fprintf(ficlog,"Comment line\n%s\n",line);
9131: printf("Comment line\n%s\n",line);
9132: continue;
9133: }
9134: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9135: strcpy(line, linetmp);
1.223 brouard 9136:
9137: /* Loops on waves */
9138: for (j=maxwav;j>=1;j--){
9139: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9140: cutv(stra, strb, line, ' ');
9141: if(strb[0]=='.') { /* Missing value */
9142: lval=-1;
9143: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9144: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9145: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9146: 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);
9147: 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);
9148: return 1;
9149: }
9150: }else{
9151: errno=0;
9152: /* what_kind_of_number(strb); */
9153: dval=strtod(strb,&endptr);
9154: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9155: /* if(strb != endptr && *endptr == '\0') */
9156: /* dval=dlval; */
9157: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9158: if( strb[0]=='\0' || (*endptr != '\0')){
9159: 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);
9160: 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);
9161: return 1;
9162: }
9163: cotqvar[j][iv][i]=dval;
9164: cotvar[j][ntv+iv][i]=dval;
9165: }
9166: strcpy(line,stra);
1.223 brouard 9167: }/* end loop ntqv */
1.225 brouard 9168:
1.223 brouard 9169: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9170: cutv(stra, strb, line, ' ');
9171: if(strb[0]=='.') { /* Missing value */
9172: lval=-1;
9173: }else{
9174: errno=0;
9175: lval=strtol(strb,&endptr,10);
9176: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9177: if( strb[0]=='\0' || (*endptr != '\0')){
9178: 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);
9179: 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);
9180: return 1;
9181: }
9182: }
9183: if(lval <-1 || lval >1){
9184: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9185: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9186: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9187: For example, for multinomial values like 1, 2 and 3,\n \
9188: build V1=0 V2=0 for the reference value (1),\n \
9189: V1=1 V2=0 for (2) \n \
1.223 brouard 9190: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9191: output of IMaCh is often meaningless.\n \
1.223 brouard 9192: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9193: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9194: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9195: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9196: For example, for multinomial values like 1, 2 and 3,\n \
9197: build V1=0 V2=0 for the reference value (1),\n \
9198: V1=1 V2=0 for (2) \n \
1.223 brouard 9199: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9200: output of IMaCh is often meaningless.\n \
1.223 brouard 9201: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9202: return 1;
9203: }
9204: cotvar[j][iv][i]=(double)(lval);
9205: strcpy(line,stra);
1.223 brouard 9206: }/* end loop ntv */
1.225 brouard 9207:
1.223 brouard 9208: /* Statuses at wave */
1.137 brouard 9209: cutv(stra, strb, line, ' ');
1.223 brouard 9210: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9211: lval=-1;
1.136 brouard 9212: }else{
1.238 brouard 9213: errno=0;
9214: lval=strtol(strb,&endptr,10);
9215: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9216: if( strb[0]=='\0' || (*endptr != '\0')){
9217: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a status of wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,j,maxwav);
9218: 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);
9219: return 1;
9220: }
1.136 brouard 9221: }
1.225 brouard 9222:
1.136 brouard 9223: s[j][i]=lval;
1.225 brouard 9224:
1.223 brouard 9225: /* Date of Interview */
1.136 brouard 9226: strcpy(line,stra);
9227: cutv(stra, strb,line,' ');
1.169 brouard 9228: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9229: }
1.169 brouard 9230: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9231: month=99;
9232: year=9999;
1.136 brouard 9233: }else{
1.225 brouard 9234: 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);
9235: 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);
9236: return 1;
1.136 brouard 9237: }
9238: anint[j][i]= (double) year;
9239: mint[j][i]= (double)month;
9240: strcpy(line,stra);
1.223 brouard 9241: } /* End loop on waves */
1.225 brouard 9242:
1.223 brouard 9243: /* Date of death */
1.136 brouard 9244: cutv(stra, strb,line,' ');
1.169 brouard 9245: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9246: }
1.169 brouard 9247: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9248: month=99;
9249: year=9999;
9250: }else{
1.141 brouard 9251: 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 9252: 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);
9253: return 1;
1.136 brouard 9254: }
9255: andc[i]=(double) year;
9256: moisdc[i]=(double) month;
9257: strcpy(line,stra);
9258:
1.223 brouard 9259: /* Date of birth */
1.136 brouard 9260: cutv(stra, strb,line,' ');
1.169 brouard 9261: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9262: }
1.169 brouard 9263: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9264: month=99;
9265: year=9999;
9266: }else{
1.141 brouard 9267: 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);
9268: 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 9269: return 1;
1.136 brouard 9270: }
9271: if (year==9999) {
1.141 brouard 9272: 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);
9273: 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 9274: return 1;
9275:
1.136 brouard 9276: }
9277: annais[i]=(double)(year);
9278: moisnais[i]=(double)(month);
9279: strcpy(line,stra);
1.225 brouard 9280:
1.223 brouard 9281: /* Sample weight */
1.136 brouard 9282: cutv(stra, strb,line,' ');
9283: errno=0;
9284: dval=strtod(strb,&endptr);
9285: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9286: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9287: 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 9288: fflush(ficlog);
9289: return 1;
9290: }
9291: weight[i]=dval;
9292: strcpy(line,stra);
1.225 brouard 9293:
1.223 brouard 9294: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9295: cutv(stra, strb, line, ' ');
9296: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9297: lval=-1;
1.223 brouard 9298: }else{
1.225 brouard 9299: errno=0;
9300: /* what_kind_of_number(strb); */
9301: dval=strtod(strb,&endptr);
9302: /* if(strb != endptr && *endptr == '\0') */
9303: /* dval=dlval; */
9304: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9305: if( strb[0]=='\0' || (*endptr != '\0')){
9306: 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);
9307: 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);
9308: return 1;
9309: }
9310: coqvar[iv][i]=dval;
1.226 brouard 9311: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9312: }
9313: strcpy(line,stra);
9314: }/* end loop nqv */
1.136 brouard 9315:
1.223 brouard 9316: /* Covariate values */
1.136 brouard 9317: for (j=ncovcol;j>=1;j--){
9318: cutv(stra, strb,line,' ');
1.223 brouard 9319: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9320: lval=-1;
1.136 brouard 9321: }else{
1.225 brouard 9322: errno=0;
9323: lval=strtol(strb,&endptr,10);
9324: if( strb[0]=='\0' || (*endptr != '\0')){
9325: 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);
9326: 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);
9327: return 1;
9328: }
1.136 brouard 9329: }
9330: if(lval <-1 || lval >1){
1.225 brouard 9331: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9332: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9333: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9334: For example, for multinomial values like 1, 2 and 3,\n \
9335: build V1=0 V2=0 for the reference value (1),\n \
9336: V1=1 V2=0 for (2) \n \
1.136 brouard 9337: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9338: output of IMaCh is often meaningless.\n \
1.136 brouard 9339: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9340: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9341: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9342: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9343: For example, for multinomial values like 1, 2 and 3,\n \
9344: build V1=0 V2=0 for the reference value (1),\n \
9345: V1=1 V2=0 for (2) \n \
1.136 brouard 9346: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9347: output of IMaCh is often meaningless.\n \
1.136 brouard 9348: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9349: return 1;
1.136 brouard 9350: }
9351: covar[j][i]=(double)(lval);
9352: strcpy(line,stra);
9353: }
9354: lstra=strlen(stra);
1.225 brouard 9355:
1.136 brouard 9356: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9357: stratrunc = &(stra[lstra-9]);
9358: num[i]=atol(stratrunc);
9359: }
9360: else
9361: num[i]=atol(stra);
9362: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9363: 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;}*/
9364:
9365: i=i+1;
9366: } /* End loop reading data */
1.225 brouard 9367:
1.136 brouard 9368: *imax=i-1; /* Number of individuals */
9369: fclose(fic);
1.225 brouard 9370:
1.136 brouard 9371: return (0);
1.164 brouard 9372: /* endread: */
1.225 brouard 9373: printf("Exiting readdata: ");
9374: fclose(fic);
9375: return (1);
1.223 brouard 9376: }
1.126 brouard 9377:
1.234 brouard 9378: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9379: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9380: while (*p2 == ' ')
1.234 brouard 9381: p2++;
9382: /* while ((*p1++ = *p2++) !=0) */
9383: /* ; */
9384: /* do */
9385: /* while (*p2 == ' ') */
9386: /* p2++; */
9387: /* while (*p1++ == *p2++); */
9388: *stri=p2;
1.145 brouard 9389: }
9390:
1.235 brouard 9391: int decoderesult ( char resultline[], int nres)
1.230 brouard 9392: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9393: {
1.235 brouard 9394: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9395: char resultsav[MAXLINE];
1.234 brouard 9396: int resultmodel[MAXLINE];
9397: int modelresult[MAXLINE];
1.230 brouard 9398: char stra[80], strb[80], strc[80], strd[80],stre[80];
9399:
1.234 brouard 9400: removefirstspace(&resultline);
1.233 brouard 9401: printf("decoderesult:%s\n",resultline);
1.230 brouard 9402:
9403: if (strstr(resultline,"v") !=0){
9404: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9405: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9406: return 1;
9407: }
9408: trimbb(resultsav, resultline);
9409: if (strlen(resultsav) >1){
9410: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9411: }
1.253 brouard 9412: if(j == 0){ /* Resultline but no = */
9413: TKresult[nres]=0; /* Combination for the nresult and the model */
9414: return (0);
9415: }
9416:
1.234 brouard 9417: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9418: 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);
9419: 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);
9420: }
9421: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9422: if(nbocc(resultsav,'=') >1){
9423: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9424: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9425: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9426: }else
9427: cutl(strc,strd,resultsav,'=');
1.230 brouard 9428: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9429:
1.230 brouard 9430: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9431: Tvarsel[k]=atoi(strc);
9432: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9433: /* cptcovsel++; */
9434: if (nbocc(stra,'=') >0)
9435: strcpy(resultsav,stra); /* and analyzes it */
9436: }
1.235 brouard 9437: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9438: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9439: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9440: match=0;
1.236 brouard 9441: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9442: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9443: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9444: match=1;
9445: break;
9446: }
9447: }
9448: if(match == 0){
9449: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9450: }
9451: }
9452: }
1.235 brouard 9453: /* Checking for missing or useless values in comparison of current model needs */
9454: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9455: match=0;
1.235 brouard 9456: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9457: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9458: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9459: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9460: ++match;
9461: }
9462: }
9463: }
9464: if(match == 0){
9465: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9466: }else if(match > 1){
9467: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9468: }
9469: }
1.235 brouard 9470:
1.234 brouard 9471: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9472: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9473: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9474: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9475: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9476: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9477: /* 1 0 0 0 */
9478: /* 2 1 0 0 */
9479: /* 3 0 1 0 */
9480: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9481: /* 5 0 0 1 */
9482: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9483: /* 7 0 1 1 */
9484: /* 8 1 1 1 */
1.237 brouard 9485: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9486: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9487: /* V5*age V5 known which value for nres? */
9488: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9489: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9490: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9491: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9492: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9493: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9494: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9495: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9496: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9497: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9498: k4++;;
9499: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9500: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9501: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9502: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9503: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9504: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9505: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9506: k4q++;;
9507: }
9508: }
1.234 brouard 9509:
1.235 brouard 9510: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9511: return (0);
9512: }
1.235 brouard 9513:
1.230 brouard 9514: int decodemodel( char model[], int lastobs)
9515: /**< This routine decodes the model and returns:
1.224 brouard 9516: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9517: * - nagesqr = 1 if age*age in the model, otherwise 0.
9518: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9519: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9520: * - cptcovage number of covariates with age*products =2
9521: * - cptcovs number of simple covariates
9522: * - 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
9523: * which is a new column after the 9 (ncovcol) variables.
9524: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9525: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9526: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9527: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9528: */
1.136 brouard 9529: {
1.238 brouard 9530: int i, j, k, ks, v;
1.227 brouard 9531: int j1, k1, k2, k3, k4;
1.136 brouard 9532: char modelsav[80];
1.145 brouard 9533: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9534: char *strpt;
1.136 brouard 9535:
1.145 brouard 9536: /*removespace(model);*/
1.136 brouard 9537: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9538: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9539: if (strstr(model,"AGE") !=0){
1.192 brouard 9540: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9541: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9542: return 1;
9543: }
1.141 brouard 9544: if (strstr(model,"v") !=0){
9545: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9546: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9547: return 1;
9548: }
1.187 brouard 9549: strcpy(modelsav,model);
9550: if ((strpt=strstr(model,"age*age")) !=0){
9551: printf(" strpt=%s, model=%s\n",strpt, model);
9552: if(strpt != model){
1.234 brouard 9553: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9554: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9555: corresponding column of parameters.\n",model);
1.234 brouard 9556: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9557: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9558: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9559: return 1;
1.225 brouard 9560: }
1.187 brouard 9561: nagesqr=1;
9562: if (strstr(model,"+age*age") !=0)
1.234 brouard 9563: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9564: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9565: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9566: else
1.234 brouard 9567: substrchaine(modelsav, model, "age*age");
1.187 brouard 9568: }else
9569: nagesqr=0;
9570: if (strlen(modelsav) >1){
9571: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9572: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9573: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9574: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9575: * cst, age and age*age
9576: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9577: /* including age products which are counted in cptcovage.
9578: * but the covariates which are products must be treated
9579: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9580: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9581: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9582:
9583:
1.187 brouard 9584: /* Design
9585: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9586: * < ncovcol=8 >
9587: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9588: * k= 1 2 3 4 5 6 7 8
9589: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9590: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9591: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9592: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9593: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9594: * Tage[++cptcovage]=k
9595: * if products, new covar are created after ncovcol with k1
9596: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9597: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9598: * 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
9599: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9600: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9601: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9602: * < ncovcol=8 >
9603: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9604: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9605: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9606: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9607: * p Tprod[1]@2={ 6, 5}
9608: *p Tvard[1][1]@4= {7, 8, 5, 6}
9609: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9610: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9611: *How to reorganize?
9612: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9613: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9614: * {2, 1, 4, 8, 5, 6, 3, 7}
9615: * Struct []
9616: */
1.225 brouard 9617:
1.187 brouard 9618: /* This loop fills the array Tvar from the string 'model'.*/
9619: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9620: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9621: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9622: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9623: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9624: /* k=1 Tvar[1]=2 (from V2) */
9625: /* k=5 Tvar[5] */
9626: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9627: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9628: /* } */
1.198 brouard 9629: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9630: /*
9631: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9632: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9633: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9634: }
1.187 brouard 9635: cptcovage=0;
9636: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9637: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9638: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9639: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9640: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9641: /*scanf("%d",i);*/
9642: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9643: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9644: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9645: /* covar is not filled and then is empty */
9646: cptcovprod--;
9647: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9648: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9649: Typevar[k]=1; /* 1 for age product */
9650: cptcovage++; /* Sums the number of covariates which include age as a product */
9651: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9652: /*printf("stre=%s ", stre);*/
9653: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9654: cptcovprod--;
9655: cutl(stre,strb,strc,'V');
9656: Tvar[k]=atoi(stre);
9657: Typevar[k]=1; /* 1 for age product */
9658: cptcovage++;
9659: Tage[cptcovage]=k;
9660: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9661: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9662: cptcovn++;
9663: cptcovprodnoage++;k1++;
9664: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9665: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9666: because this model-covariate is a construction we invent a new column
9667: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9668: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9669: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9670: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9671: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9672: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9673: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9674: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9675: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9676: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9677: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9678: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9679: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9680: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9681: for (i=1; i<=lastobs;i++){
9682: /* Computes the new covariate which is a product of
9683: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9684: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9685: }
9686: } /* End age is not in the model */
9687: } /* End if model includes a product */
9688: else { /* no more sum */
9689: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9690: /* scanf("%d",i);*/
9691: cutl(strd,strc,strb,'V');
9692: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9693: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9694: Tvar[k]=atoi(strd);
9695: Typevar[k]=0; /* 0 for simple covariates */
9696: }
9697: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9698: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9699: scanf("%d",i);*/
1.187 brouard 9700: } /* end of loop + on total covariates */
9701: } /* end if strlen(modelsave == 0) age*age might exist */
9702: } /* end if strlen(model == 0) */
1.136 brouard 9703:
9704: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9705: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9706:
1.136 brouard 9707: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9708: printf("cptcovprod=%d ", cptcovprod);
9709: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9710: scanf("%d ",i);*/
9711:
9712:
1.230 brouard 9713: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9714: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9715: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9716: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9717: k = 1 2 3 4 5 6 7 8 9
9718: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9719: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9720: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9721: Dummy[k] 1 0 0 0 3 1 1 2 3
9722: Tmodelind[combination of covar]=k;
1.225 brouard 9723: */
9724: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9725: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9726: /* 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 9727: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9728: printf("Model=%s\n\
9729: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9730: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9731: 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);
9732: fprintf(ficlog,"Model=%s\n\
9733: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9734: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9735: 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 9736: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9737: 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 */
9738: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9739: Fixed[k]= 0;
9740: Dummy[k]= 0;
1.225 brouard 9741: ncoveff++;
1.232 brouard 9742: ncovf++;
1.234 brouard 9743: nsd++;
9744: modell[k].maintype= FTYPE;
9745: TvarsD[nsd]=Tvar[k];
9746: TvarsDind[nsd]=k;
9747: TvarF[ncovf]=Tvar[k];
9748: TvarFind[ncovf]=k;
9749: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9750: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9751: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9752: Fixed[k]= 0;
9753: Dummy[k]= 0;
9754: ncoveff++;
9755: ncovf++;
9756: modell[k].maintype= FTYPE;
9757: TvarF[ncovf]=Tvar[k];
9758: TvarFind[ncovf]=k;
1.230 brouard 9759: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9760: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9761: }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 9762: Fixed[k]= 0;
9763: Dummy[k]= 1;
1.230 brouard 9764: nqfveff++;
1.234 brouard 9765: modell[k].maintype= FTYPE;
9766: modell[k].subtype= FQ;
9767: nsq++;
9768: TvarsQ[nsq]=Tvar[k];
9769: TvarsQind[nsq]=k;
1.232 brouard 9770: ncovf++;
1.234 brouard 9771: TvarF[ncovf]=Tvar[k];
9772: TvarFind[ncovf]=k;
1.231 brouard 9773: 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 9774: 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 9775: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9776: Fixed[k]= 1;
9777: Dummy[k]= 0;
1.225 brouard 9778: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9779: modell[k].maintype= VTYPE;
9780: modell[k].subtype= VD;
9781: nsd++;
9782: TvarsD[nsd]=Tvar[k];
9783: TvarsDind[nsd]=k;
9784: ncovv++; /* Only simple time varying variables */
9785: TvarV[ncovv]=Tvar[k];
1.242 brouard 9786: 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 9787: 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 */
9788: 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 9789: 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);
9790: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9791: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9792: Fixed[k]= 1;
9793: Dummy[k]= 1;
9794: nqtveff++;
9795: modell[k].maintype= VTYPE;
9796: modell[k].subtype= VQ;
9797: ncovv++; /* Only simple time varying variables */
9798: nsq++;
9799: TvarsQ[nsq]=Tvar[k];
9800: TvarsQind[nsq]=k;
9801: TvarV[ncovv]=Tvar[k];
1.242 brouard 9802: 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 9803: 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 */
9804: 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 9805: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9806: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9807: 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 9808: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9809: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9810: ncova++;
9811: TvarA[ncova]=Tvar[k];
9812: TvarAind[ncova]=k;
1.231 brouard 9813: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9814: Fixed[k]= 2;
9815: Dummy[k]= 2;
9816: modell[k].maintype= ATYPE;
9817: modell[k].subtype= APFD;
9818: /* ncoveff++; */
1.227 brouard 9819: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9820: Fixed[k]= 2;
9821: Dummy[k]= 3;
9822: modell[k].maintype= ATYPE;
9823: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9824: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9825: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9826: Fixed[k]= 3;
9827: Dummy[k]= 2;
9828: modell[k].maintype= ATYPE;
9829: modell[k].subtype= APVD; /* Product age * varying dummy */
9830: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9831: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9832: Fixed[k]= 3;
9833: Dummy[k]= 3;
9834: modell[k].maintype= ATYPE;
9835: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9836: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9837: }
9838: }else if (Typevar[k] == 2) { /* product without age */
9839: k1=Tposprod[k];
9840: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9841: if(Tvard[k1][2] <=ncovcol){
9842: Fixed[k]= 1;
9843: Dummy[k]= 0;
9844: modell[k].maintype= FTYPE;
9845: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9846: ncovf++; /* Fixed variables without age */
9847: TvarF[ncovf]=Tvar[k];
9848: TvarFind[ncovf]=k;
9849: }else if(Tvard[k1][2] <=ncovcol+nqv){
9850: Fixed[k]= 0; /* or 2 ?*/
9851: Dummy[k]= 1;
9852: modell[k].maintype= FTYPE;
9853: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9854: ncovf++; /* Varying variables without age */
9855: TvarF[ncovf]=Tvar[k];
9856: TvarFind[ncovf]=k;
9857: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9858: Fixed[k]= 1;
9859: Dummy[k]= 0;
9860: modell[k].maintype= VTYPE;
9861: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9862: ncovv++; /* Varying variables without age */
9863: TvarV[ncovv]=Tvar[k];
9864: TvarVind[ncovv]=k;
9865: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9866: Fixed[k]= 1;
9867: Dummy[k]= 1;
9868: modell[k].maintype= VTYPE;
9869: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9870: ncovv++; /* Varying variables without age */
9871: TvarV[ncovv]=Tvar[k];
9872: TvarVind[ncovv]=k;
9873: }
1.227 brouard 9874: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9875: if(Tvard[k1][2] <=ncovcol){
9876: Fixed[k]= 0; /* or 2 ?*/
9877: Dummy[k]= 1;
9878: modell[k].maintype= FTYPE;
9879: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9880: ncovf++; /* Fixed variables without age */
9881: TvarF[ncovf]=Tvar[k];
9882: TvarFind[ncovf]=k;
9883: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9884: Fixed[k]= 1;
9885: Dummy[k]= 1;
9886: modell[k].maintype= VTYPE;
9887: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9888: ncovv++; /* Varying variables without age */
9889: TvarV[ncovv]=Tvar[k];
9890: TvarVind[ncovv]=k;
9891: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9892: Fixed[k]= 1;
9893: Dummy[k]= 1;
9894: modell[k].maintype= VTYPE;
9895: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9896: ncovv++; /* Varying variables without age */
9897: TvarV[ncovv]=Tvar[k];
9898: TvarVind[ncovv]=k;
9899: ncovv++; /* Varying variables without age */
9900: TvarV[ncovv]=Tvar[k];
9901: TvarVind[ncovv]=k;
9902: }
1.227 brouard 9903: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9904: if(Tvard[k1][2] <=ncovcol){
9905: Fixed[k]= 1;
9906: Dummy[k]= 1;
9907: modell[k].maintype= VTYPE;
9908: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9909: ncovv++; /* Varying variables without age */
9910: TvarV[ncovv]=Tvar[k];
9911: TvarVind[ncovv]=k;
9912: }else if(Tvard[k1][2] <=ncovcol+nqv){
9913: Fixed[k]= 1;
9914: Dummy[k]= 1;
9915: modell[k].maintype= VTYPE;
9916: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9917: ncovv++; /* Varying variables without age */
9918: TvarV[ncovv]=Tvar[k];
9919: TvarVind[ncovv]=k;
9920: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9921: Fixed[k]= 1;
9922: Dummy[k]= 0;
9923: modell[k].maintype= VTYPE;
9924: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9925: ncovv++; /* Varying variables without age */
9926: TvarV[ncovv]=Tvar[k];
9927: TvarVind[ncovv]=k;
9928: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9929: Fixed[k]= 1;
9930: Dummy[k]= 1;
9931: modell[k].maintype= VTYPE;
9932: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9933: ncovv++; /* Varying variables without age */
9934: TvarV[ncovv]=Tvar[k];
9935: TvarVind[ncovv]=k;
9936: }
1.227 brouard 9937: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9938: if(Tvard[k1][2] <=ncovcol){
9939: Fixed[k]= 1;
9940: Dummy[k]= 1;
9941: modell[k].maintype= VTYPE;
9942: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9943: ncovv++; /* Varying variables without age */
9944: TvarV[ncovv]=Tvar[k];
9945: TvarVind[ncovv]=k;
9946: }else if(Tvard[k1][2] <=ncovcol+nqv){
9947: Fixed[k]= 1;
9948: Dummy[k]= 1;
9949: modell[k].maintype= VTYPE;
9950: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9951: ncovv++; /* Varying variables without age */
9952: TvarV[ncovv]=Tvar[k];
9953: TvarVind[ncovv]=k;
9954: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9955: Fixed[k]= 1;
9956: Dummy[k]= 1;
9957: modell[k].maintype= VTYPE;
9958: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9959: ncovv++; /* Varying variables without age */
9960: TvarV[ncovv]=Tvar[k];
9961: TvarVind[ncovv]=k;
9962: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9963: Fixed[k]= 1;
9964: Dummy[k]= 1;
9965: modell[k].maintype= VTYPE;
9966: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9967: ncovv++; /* Varying variables without age */
9968: TvarV[ncovv]=Tvar[k];
9969: TvarVind[ncovv]=k;
9970: }
1.227 brouard 9971: }else{
1.240 brouard 9972: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9973: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9974: } /*end k1*/
1.225 brouard 9975: }else{
1.226 brouard 9976: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
9977: 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 9978: }
1.227 brouard 9979: 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 9980: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 9981: 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]);
9982: }
9983: /* Searching for doublons in the model */
9984: for(k1=1; k1<= cptcovt;k1++){
9985: for(k2=1; k2 <k1;k2++){
1.285 ! brouard 9986: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
! 9987: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 9988: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
9989: if(Tvar[k1]==Tvar[k2]){
1.285 ! brouard 9990: 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]);
! 9991: 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 9992: return(1);
9993: }
9994: }else if (Typevar[k1] ==2){
9995: k3=Tposprod[k1];
9996: k4=Tposprod[k2];
9997: 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])) ){
9998: 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]]);
9999: 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);
10000: return(1);
10001: }
10002: }
1.227 brouard 10003: }
10004: }
1.225 brouard 10005: }
10006: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10007: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10008: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10009: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10010: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10011: /*endread:*/
1.225 brouard 10012: printf("Exiting decodemodel: ");
10013: return (1);
1.136 brouard 10014: }
10015:
1.169 brouard 10016: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10017: {/* Check ages at death */
1.136 brouard 10018: int i, m;
1.218 brouard 10019: int firstone=0;
10020:
1.136 brouard 10021: for (i=1; i<=imx; i++) {
10022: for(m=2; (m<= maxwav); m++) {
10023: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10024: anint[m][i]=9999;
1.216 brouard 10025: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10026: s[m][i]=-1;
1.136 brouard 10027: }
10028: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10029: *nberr = *nberr + 1;
1.218 brouard 10030: if(firstone == 0){
10031: firstone=1;
1.260 brouard 10032: 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 10033: }
1.262 brouard 10034: 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 10035: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10036: }
10037: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10038: (*nberr)++;
1.259 brouard 10039: 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 10040: 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 10041: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10042: }
10043: }
10044: }
10045:
10046: for (i=1; i<=imx; i++) {
10047: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10048: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10049: 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 10050: if (s[m][i] >= nlstate+1) {
1.169 brouard 10051: if(agedc[i]>0){
10052: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10053: agev[m][i]=agedc[i];
1.214 brouard 10054: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10055: }else {
1.136 brouard 10056: if ((int)andc[i]!=9999){
10057: nbwarn++;
10058: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10059: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10060: agev[m][i]=-1;
10061: }
10062: }
1.169 brouard 10063: } /* agedc > 0 */
1.214 brouard 10064: } /* end if */
1.136 brouard 10065: else if(s[m][i] !=9){ /* Standard case, age in fractional
10066: years but with the precision of a month */
10067: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10068: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10069: agev[m][i]=1;
10070: else if(agev[m][i] < *agemin){
10071: *agemin=agev[m][i];
10072: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10073: }
10074: else if(agev[m][i] >*agemax){
10075: *agemax=agev[m][i];
1.156 brouard 10076: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10077: }
10078: /*agev[m][i]=anint[m][i]-annais[i];*/
10079: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10080: } /* en if 9*/
1.136 brouard 10081: else { /* =9 */
1.214 brouard 10082: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10083: agev[m][i]=1;
10084: s[m][i]=-1;
10085: }
10086: }
1.214 brouard 10087: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10088: agev[m][i]=1;
1.214 brouard 10089: else{
10090: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10091: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10092: agev[m][i]=0;
10093: }
10094: } /* End for lastpass */
10095: }
1.136 brouard 10096:
10097: for (i=1; i<=imx; i++) {
10098: for(m=firstpass; (m<=lastpass); m++){
10099: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10100: (*nberr)++;
1.136 brouard 10101: 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);
10102: 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);
10103: return 1;
10104: }
10105: }
10106: }
10107:
10108: /*for (i=1; i<=imx; i++){
10109: for (m=firstpass; (m<lastpass); m++){
10110: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10111: }
10112:
10113: }*/
10114:
10115:
1.139 brouard 10116: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10117: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10118:
10119: return (0);
1.164 brouard 10120: /* endread:*/
1.136 brouard 10121: printf("Exiting calandcheckages: ");
10122: return (1);
10123: }
10124:
1.172 brouard 10125: #if defined(_MSC_VER)
10126: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10127: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10128: //#include "stdafx.h"
10129: //#include <stdio.h>
10130: //#include <tchar.h>
10131: //#include <windows.h>
10132: //#include <iostream>
10133: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10134:
10135: LPFN_ISWOW64PROCESS fnIsWow64Process;
10136:
10137: BOOL IsWow64()
10138: {
10139: BOOL bIsWow64 = FALSE;
10140:
10141: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10142: // (HANDLE, PBOOL);
10143:
10144: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10145:
10146: HMODULE module = GetModuleHandle(_T("kernel32"));
10147: const char funcName[] = "IsWow64Process";
10148: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10149: GetProcAddress(module, funcName);
10150:
10151: if (NULL != fnIsWow64Process)
10152: {
10153: if (!fnIsWow64Process(GetCurrentProcess(),
10154: &bIsWow64))
10155: //throw std::exception("Unknown error");
10156: printf("Unknown error\n");
10157: }
10158: return bIsWow64 != FALSE;
10159: }
10160: #endif
1.177 brouard 10161:
1.191 brouard 10162: void syscompilerinfo(int logged)
1.167 brouard 10163: {
10164: /* #include "syscompilerinfo.h"*/
1.185 brouard 10165: /* command line Intel compiler 32bit windows, XP compatible:*/
10166: /* /GS /W3 /Gy
10167: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10168: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10169: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10170: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10171: */
10172: /* 64 bits */
1.185 brouard 10173: /*
10174: /GS /W3 /Gy
10175: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10176: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10177: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10178: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10179: /* Optimization are useless and O3 is slower than O2 */
10180: /*
10181: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10182: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10183: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10184: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10185: */
1.186 brouard 10186: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10187: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10188: /PDB:"visual studio
10189: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10190: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10191: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10192: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10193: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10194: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10195: uiAccess='false'"
10196: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10197: /NOLOGO /TLBID:1
10198: */
1.177 brouard 10199: #if defined __INTEL_COMPILER
1.178 brouard 10200: #if defined(__GNUC__)
10201: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10202: #endif
1.177 brouard 10203: #elif defined(__GNUC__)
1.179 brouard 10204: #ifndef __APPLE__
1.174 brouard 10205: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10206: #endif
1.177 brouard 10207: struct utsname sysInfo;
1.178 brouard 10208: int cross = CROSS;
10209: if (cross){
10210: printf("Cross-");
1.191 brouard 10211: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10212: }
1.174 brouard 10213: #endif
10214:
1.171 brouard 10215: #include <stdint.h>
1.178 brouard 10216:
1.191 brouard 10217: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10218: #if defined(__clang__)
1.191 brouard 10219: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10220: #endif
10221: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10222: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10223: #endif
10224: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10225: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10226: #endif
10227: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10228: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10229: #endif
10230: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10231: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10232: #endif
10233: #if defined(_MSC_VER)
1.191 brouard 10234: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10235: #endif
10236: #if defined(__PGI)
1.191 brouard 10237: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10238: #endif
10239: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10240: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10241: #endif
1.191 brouard 10242: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10243:
1.167 brouard 10244: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10245: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10246: // Windows (x64 and x86)
1.191 brouard 10247: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10248: #elif __unix__ // all unices, not all compilers
10249: // Unix
1.191 brouard 10250: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10251: #elif __linux__
10252: // linux
1.191 brouard 10253: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10254: #elif __APPLE__
1.174 brouard 10255: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10256: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10257: #endif
10258:
10259: /* __MINGW32__ */
10260: /* __CYGWIN__ */
10261: /* __MINGW64__ */
10262: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10263: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10264: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10265: /* _WIN64 // Defined for applications for Win64. */
10266: /* _M_X64 // Defined for compilations that target x64 processors. */
10267: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10268:
1.167 brouard 10269: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10270: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10271: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10272: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10273: #else
1.191 brouard 10274: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10275: #endif
10276:
1.169 brouard 10277: #if defined(__GNUC__)
10278: # if defined(__GNUC_PATCHLEVEL__)
10279: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10280: + __GNUC_MINOR__ * 100 \
10281: + __GNUC_PATCHLEVEL__)
10282: # else
10283: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10284: + __GNUC_MINOR__ * 100)
10285: # endif
1.174 brouard 10286: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10287: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10288:
10289: if (uname(&sysInfo) != -1) {
10290: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10291: 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 10292: }
10293: else
10294: perror("uname() error");
1.179 brouard 10295: //#ifndef __INTEL_COMPILER
10296: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10297: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10298: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10299: #endif
1.169 brouard 10300: #endif
1.172 brouard 10301:
10302: // void main()
10303: // {
1.169 brouard 10304: #if defined(_MSC_VER)
1.174 brouard 10305: if (IsWow64()){
1.191 brouard 10306: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10307: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10308: }
10309: else{
1.191 brouard 10310: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10311: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10312: }
1.172 brouard 10313: // printf("\nPress Enter to continue...");
10314: // getchar();
10315: // }
10316:
1.169 brouard 10317: #endif
10318:
1.167 brouard 10319:
1.219 brouard 10320: }
1.136 brouard 10321:
1.219 brouard 10322: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 10323: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 10324: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10325: /* double ftolpl = 1.e-10; */
1.180 brouard 10326: double age, agebase, agelim;
1.203 brouard 10327: double tot;
1.180 brouard 10328:
1.202 brouard 10329: strcpy(filerespl,"PL_");
10330: strcat(filerespl,fileresu);
10331: if((ficrespl=fopen(filerespl,"w"))==NULL) {
10332: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10333: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10334: }
1.227 brouard 10335: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
10336: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10337: pstamp(ficrespl);
1.203 brouard 10338: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10339: fprintf(ficrespl,"#Age ");
10340: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10341: fprintf(ficrespl,"\n");
1.180 brouard 10342:
1.219 brouard 10343: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10344:
1.219 brouard 10345: agebase=ageminpar;
10346: agelim=agemaxpar;
1.180 brouard 10347:
1.227 brouard 10348: /* i1=pow(2,ncoveff); */
1.234 brouard 10349: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10350: if (cptcovn < 1){i1=1;}
1.180 brouard 10351:
1.238 brouard 10352: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10353: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10354: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10355: continue;
1.235 brouard 10356:
1.238 brouard 10357: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10358: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10359: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10360: /* k=k+1; */
10361: /* to clean */
10362: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10363: fprintf(ficrespl,"#******");
10364: printf("#******");
10365: fprintf(ficlog,"#******");
10366: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10367: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10368: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10369: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10370: }
10371: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10372: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10373: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10374: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10375: }
10376: fprintf(ficrespl,"******\n");
10377: printf("******\n");
10378: fprintf(ficlog,"******\n");
10379: if(invalidvarcomb[k]){
10380: printf("\nCombination (%d) ignored because no case \n",k);
10381: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10382: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10383: continue;
10384: }
1.219 brouard 10385:
1.238 brouard 10386: fprintf(ficrespl,"#Age ");
10387: for(j=1;j<=cptcoveff;j++) {
10388: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10389: }
10390: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10391: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10392:
1.238 brouard 10393: for (age=agebase; age<=agelim; age++){
10394: /* for (age=agebase; age<=agebase; age++){ */
10395: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10396: fprintf(ficrespl,"%.0f ",age );
10397: for(j=1;j<=cptcoveff;j++)
10398: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10399: tot=0.;
10400: for(i=1; i<=nlstate;i++){
10401: tot += prlim[i][i];
10402: fprintf(ficrespl," %.5f", prlim[i][i]);
10403: }
10404: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10405: } /* Age */
10406: /* was end of cptcod */
10407: } /* cptcov */
10408: } /* nres */
1.219 brouard 10409: return 0;
1.180 brouard 10410: }
10411:
1.218 brouard 10412: 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){
10413: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
10414:
10415: /* Computes the back prevalence limit for any combination of covariate values
10416: * at any age between ageminpar and agemaxpar
10417: */
1.235 brouard 10418: int i, j, k, i1, nres=0 ;
1.217 brouard 10419: /* double ftolpl = 1.e-10; */
10420: double age, agebase, agelim;
10421: double tot;
1.218 brouard 10422: /* double ***mobaverage; */
10423: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10424:
10425: strcpy(fileresplb,"PLB_");
10426: strcat(fileresplb,fileresu);
10427: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
10428: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10429: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10430: }
10431: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10432: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10433: pstamp(ficresplb);
10434: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
10435: fprintf(ficresplb,"#Age ");
10436: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10437: fprintf(ficresplb,"\n");
10438:
1.218 brouard 10439:
10440: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10441:
10442: agebase=ageminpar;
10443: agelim=agemaxpar;
10444:
10445:
1.227 brouard 10446: i1=pow(2,cptcoveff);
1.218 brouard 10447: if (cptcovn < 1){i1=1;}
1.227 brouard 10448:
1.238 brouard 10449: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10450: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10451: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10452: continue;
10453: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10454: fprintf(ficresplb,"#******");
10455: printf("#******");
10456: fprintf(ficlog,"#******");
10457: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10458: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10459: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10460: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10461: }
10462: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10463: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10464: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10465: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10466: }
10467: fprintf(ficresplb,"******\n");
10468: printf("******\n");
10469: fprintf(ficlog,"******\n");
10470: if(invalidvarcomb[k]){
10471: printf("\nCombination (%d) ignored because no cases \n",k);
10472: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10473: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10474: continue;
10475: }
1.218 brouard 10476:
1.238 brouard 10477: fprintf(ficresplb,"#Age ");
10478: for(j=1;j<=cptcoveff;j++) {
10479: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10480: }
10481: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10482: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10483:
10484:
1.238 brouard 10485: for (age=agebase; age<=agelim; age++){
10486: /* for (age=agebase; age<=agebase; age++){ */
10487: if(mobilavproj > 0){
10488: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10489: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10490: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10491: }else if (mobilavproj == 0){
10492: 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);
10493: 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);
10494: exit(1);
10495: }else{
10496: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10497: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10498: /* printf("TOTOT\n"); */
10499: /* exit(1); */
1.238 brouard 10500: }
10501: fprintf(ficresplb,"%.0f ",age );
10502: for(j=1;j<=cptcoveff;j++)
10503: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10504: tot=0.;
10505: for(i=1; i<=nlstate;i++){
10506: tot += bprlim[i][i];
10507: fprintf(ficresplb," %.5f", bprlim[i][i]);
10508: }
10509: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10510: } /* Age */
10511: /* was end of cptcod */
1.255 brouard 10512: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10513: } /* end of any combination */
10514: } /* end of nres */
1.218 brouard 10515: /* hBijx(p, bage, fage); */
10516: /* fclose(ficrespijb); */
10517:
10518: return 0;
1.217 brouard 10519: }
1.218 brouard 10520:
1.180 brouard 10521: int hPijx(double *p, int bage, int fage){
10522: /*------------- h Pij x at various ages ------------*/
10523:
10524: int stepsize;
10525: int agelim;
10526: int hstepm;
10527: int nhstepm;
1.235 brouard 10528: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10529:
10530: double agedeb;
10531: double ***p3mat;
10532:
1.201 brouard 10533: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10534: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10535: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10536: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10537: }
10538: printf("Computing pij: result on file '%s' \n", filerespij);
10539: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10540:
10541: stepsize=(int) (stepm+YEARM-1)/YEARM;
10542: /*if (stepm<=24) stepsize=2;*/
10543:
10544: agelim=AGESUP;
10545: hstepm=stepsize*YEARM; /* Every year of age */
10546: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10547:
1.180 brouard 10548: /* hstepm=1; aff par mois*/
10549: pstamp(ficrespij);
10550: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10551: i1= pow(2,cptcoveff);
1.218 brouard 10552: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10553: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10554: /* k=k+1; */
1.235 brouard 10555: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10556: for(k=1; k<=i1;k++){
1.253 brouard 10557: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10558: continue;
1.183 brouard 10559: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10560: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10561: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10562: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10563: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10564: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10565: }
1.183 brouard 10566: fprintf(ficrespij,"******\n");
10567:
10568: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10569: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10570: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10571:
10572: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10573:
1.183 brouard 10574: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10575: oldm=oldms;savm=savms;
1.235 brouard 10576: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10577: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10578: for(i=1; i<=nlstate;i++)
10579: for(j=1; j<=nlstate+ndeath;j++)
10580: fprintf(ficrespij," %1d-%1d",i,j);
10581: fprintf(ficrespij,"\n");
10582: for (h=0; h<=nhstepm; h++){
10583: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10584: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10585: for(i=1; i<=nlstate;i++)
10586: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10587: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10588: fprintf(ficrespij,"\n");
10589: }
1.183 brouard 10590: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10591: fprintf(ficrespij,"\n");
10592: }
1.180 brouard 10593: /*}*/
10594: }
1.218 brouard 10595: return 0;
1.180 brouard 10596: }
1.218 brouard 10597:
10598: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10599: /*------------- h Bij x at various ages ------------*/
10600:
10601: int stepsize;
1.218 brouard 10602: /* int agelim; */
10603: int ageminl;
1.217 brouard 10604: int hstepm;
10605: int nhstepm;
1.238 brouard 10606: int h, i, i1, j, k, nres;
1.218 brouard 10607:
1.217 brouard 10608: double agedeb;
10609: double ***p3mat;
1.218 brouard 10610:
10611: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10612: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10613: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10614: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10615: }
10616: printf("Computing pij back: result on file '%s' \n", filerespijb);
10617: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10618:
10619: stepsize=(int) (stepm+YEARM-1)/YEARM;
10620: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10621:
1.218 brouard 10622: /* agelim=AGESUP; */
10623: ageminl=30;
10624: hstepm=stepsize*YEARM; /* Every year of age */
10625: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10626:
10627: /* hstepm=1; aff par mois*/
10628: pstamp(ficrespijb);
1.255 brouard 10629: 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 10630: i1= pow(2,cptcoveff);
1.218 brouard 10631: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10632: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10633: /* k=k+1; */
1.238 brouard 10634: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10635: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10636: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10637: continue;
10638: fprintf(ficrespijb,"\n#****** ");
10639: for(j=1;j<=cptcoveff;j++)
10640: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10641: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10642: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10643: }
10644: fprintf(ficrespijb,"******\n");
1.264 brouard 10645: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10646: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10647: continue;
10648: }
10649:
10650: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10651: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10652: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10653: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10654: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10655:
10656: /* nhstepm=nhstepm*YEARM; aff par mois*/
10657:
1.266 brouard 10658: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10659: /* and memory limitations if stepm is small */
10660:
1.238 brouard 10661: /* oldm=oldms;savm=savms; */
10662: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10663: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10664: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10665: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10666: for(i=1; i<=nlstate;i++)
10667: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10668: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10669: fprintf(ficrespijb,"\n");
1.238 brouard 10670: for (h=0; h<=nhstepm; h++){
10671: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10672: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10673: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10674: for(i=1; i<=nlstate;i++)
10675: for(j=1; j<=nlstate+ndeath;j++)
10676: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10677: fprintf(ficrespijb,"\n");
10678: }
10679: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10680: fprintf(ficrespijb,"\n");
10681: } /* end age deb */
10682: } /* end combination */
10683: } /* end nres */
1.218 brouard 10684: return 0;
10685: } /* hBijx */
1.217 brouard 10686:
1.180 brouard 10687:
1.136 brouard 10688: /***********************************************/
10689: /**************** Main Program *****************/
10690: /***********************************************/
10691:
10692: int main(int argc, char *argv[])
10693: {
10694: #ifdef GSL
10695: const gsl_multimin_fminimizer_type *T;
10696: size_t iteri = 0, it;
10697: int rval = GSL_CONTINUE;
10698: int status = GSL_SUCCESS;
10699: double ssval;
10700: #endif
10701: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10702: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10703: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10704: int jj, ll, li, lj, lk;
1.136 brouard 10705: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10706: int num_filled;
1.136 brouard 10707: int itimes;
10708: int NDIM=2;
10709: int vpopbased=0;
1.235 brouard 10710: int nres=0;
1.258 brouard 10711: int endishere=0;
1.277 brouard 10712: int noffset=0;
1.274 brouard 10713: int ncurrv=0; /* Temporary variable */
10714:
1.164 brouard 10715: char ca[32], cb[32];
1.136 brouard 10716: /* FILE *fichtm; *//* Html File */
10717: /* FILE *ficgp;*/ /*Gnuplot File */
10718: struct stat info;
1.191 brouard 10719: double agedeb=0.;
1.194 brouard 10720:
10721: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10722: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10723:
1.165 brouard 10724: double fret;
1.191 brouard 10725: double dum=0.; /* Dummy variable */
1.136 brouard 10726: double ***p3mat;
1.218 brouard 10727: /* double ***mobaverage; */
1.164 brouard 10728:
10729: char line[MAXLINE];
1.197 brouard 10730: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10731:
1.234 brouard 10732: char modeltemp[MAXLINE];
1.230 brouard 10733: char resultline[MAXLINE];
10734:
1.136 brouard 10735: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10736: char *tok, *val; /* pathtot */
1.136 brouard 10737: int firstobs=1, lastobs=10;
1.195 brouard 10738: int c, h , cpt, c2;
1.191 brouard 10739: int jl=0;
10740: int i1, j1, jk, stepsize=0;
1.194 brouard 10741: int count=0;
10742:
1.164 brouard 10743: int *tab;
1.136 brouard 10744: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10745: int backcast=0;
1.136 brouard 10746: int mobilav=0,popforecast=0;
1.191 brouard 10747: int hstepm=0, nhstepm=0;
1.136 brouard 10748: int agemortsup;
10749: float sumlpop=0.;
10750: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10751: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10752:
1.191 brouard 10753: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10754: double ftolpl=FTOL;
10755: double **prlim;
1.217 brouard 10756: double **bprlim;
1.136 brouard 10757: double ***param; /* Matrix of parameters */
1.251 brouard 10758: double ***paramstart; /* Matrix of starting parameter values */
10759: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10760: double **matcov; /* Matrix of covariance */
1.203 brouard 10761: double **hess; /* Hessian matrix */
1.136 brouard 10762: double ***delti3; /* Scale */
10763: double *delti; /* Scale */
10764: double ***eij, ***vareij;
10765: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10766:
1.136 brouard 10767: double *epj, vepp;
1.164 brouard 10768:
1.273 brouard 10769: double dateprev1, dateprev2;
10770: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0;
10771: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0;
1.217 brouard 10772:
1.136 brouard 10773: double **ximort;
1.145 brouard 10774: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10775: int *dcwave;
10776:
1.164 brouard 10777: char z[1]="c";
1.136 brouard 10778:
10779: /*char *strt;*/
10780: char strtend[80];
1.126 brouard 10781:
1.164 brouard 10782:
1.126 brouard 10783: /* setlocale (LC_ALL, ""); */
10784: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10785: /* textdomain (PACKAGE); */
10786: /* setlocale (LC_CTYPE, ""); */
10787: /* setlocale (LC_MESSAGES, ""); */
10788:
10789: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10790: rstart_time = time(NULL);
10791: /* (void) gettimeofday(&start_time,&tzp);*/
10792: start_time = *localtime(&rstart_time);
1.126 brouard 10793: curr_time=start_time;
1.157 brouard 10794: /*tml = *localtime(&start_time.tm_sec);*/
10795: /* strcpy(strstart,asctime(&tml)); */
10796: strcpy(strstart,asctime(&start_time));
1.126 brouard 10797:
10798: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10799: /* tp.tm_sec = tp.tm_sec +86400; */
10800: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10801: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10802: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10803: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10804: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10805: /* strt=asctime(&tmg); */
10806: /* printf("Time(after) =%s",strstart); */
10807: /* (void) time (&time_value);
10808: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10809: * tm = *localtime(&time_value);
10810: * strstart=asctime(&tm);
10811: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10812: */
10813:
10814: nberr=0; /* Number of errors and warnings */
10815: nbwarn=0;
1.184 brouard 10816: #ifdef WIN32
10817: _getcwd(pathcd, size);
10818: #else
1.126 brouard 10819: getcwd(pathcd, size);
1.184 brouard 10820: #endif
1.191 brouard 10821: syscompilerinfo(0);
1.196 brouard 10822: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10823: if(argc <=1){
10824: printf("\nEnter the parameter file name: ");
1.205 brouard 10825: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10826: printf("ERROR Empty parameter file name\n");
10827: goto end;
10828: }
1.126 brouard 10829: i=strlen(pathr);
10830: if(pathr[i-1]=='\n')
10831: pathr[i-1]='\0';
1.156 brouard 10832: i=strlen(pathr);
1.205 brouard 10833: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10834: pathr[i-1]='\0';
1.205 brouard 10835: }
10836: i=strlen(pathr);
10837: if( i==0 ){
10838: printf("ERROR Empty parameter file name\n");
10839: goto end;
10840: }
10841: for (tok = pathr; tok != NULL; ){
1.126 brouard 10842: printf("Pathr |%s|\n",pathr);
10843: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10844: printf("val= |%s| pathr=%s\n",val,pathr);
10845: strcpy (pathtot, val);
10846: if(pathr[0] == '\0') break; /* Dirty */
10847: }
10848: }
1.281 brouard 10849: else if (argc<=2){
10850: strcpy(pathtot,argv[1]);
10851: }
1.126 brouard 10852: else{
10853: strcpy(pathtot,argv[1]);
1.281 brouard 10854: strcpy(z,argv[2]);
10855: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10856: }
10857: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10858: /*cygwin_split_path(pathtot,path,optionfile);
10859: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10860: /* cutv(path,optionfile,pathtot,'\\');*/
10861:
10862: /* Split argv[0], imach program to get pathimach */
10863: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10864: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10865: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10866: /* strcpy(pathimach,argv[0]); */
10867: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10868: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10869: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10870: #ifdef WIN32
10871: _chdir(path); /* Can be a relative path */
10872: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10873: #else
1.126 brouard 10874: chdir(path); /* Can be a relative path */
1.184 brouard 10875: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10876: #endif
10877: printf("Current directory %s!\n",pathcd);
1.126 brouard 10878: strcpy(command,"mkdir ");
10879: strcat(command,optionfilefiname);
10880: if((outcmd=system(command)) != 0){
1.169 brouard 10881: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10882: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10883: /* fclose(ficlog); */
10884: /* exit(1); */
10885: }
10886: /* if((imk=mkdir(optionfilefiname))<0){ */
10887: /* perror("mkdir"); */
10888: /* } */
10889:
10890: /*-------- arguments in the command line --------*/
10891:
1.186 brouard 10892: /* Main Log file */
1.126 brouard 10893: strcat(filelog, optionfilefiname);
10894: strcat(filelog,".log"); /* */
10895: if((ficlog=fopen(filelog,"w"))==NULL) {
10896: printf("Problem with logfile %s\n",filelog);
10897: goto end;
10898: }
10899: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10900: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10901: fprintf(ficlog,"\nEnter the parameter file name: \n");
10902: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10903: path=%s \n\
10904: optionfile=%s\n\
10905: optionfilext=%s\n\
1.156 brouard 10906: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10907:
1.197 brouard 10908: syscompilerinfo(1);
1.167 brouard 10909:
1.126 brouard 10910: printf("Local time (at start):%s",strstart);
10911: fprintf(ficlog,"Local time (at start): %s",strstart);
10912: fflush(ficlog);
10913: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10914: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10915:
10916: /* */
10917: strcpy(fileres,"r");
10918: strcat(fileres, optionfilefiname);
1.201 brouard 10919: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10920: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10921: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10922:
1.186 brouard 10923: /* Main ---------arguments file --------*/
1.126 brouard 10924:
10925: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10926: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10927: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10928: fflush(ficlog);
1.149 brouard 10929: /* goto end; */
10930: exit(70);
1.126 brouard 10931: }
10932:
10933: strcpy(filereso,"o");
1.201 brouard 10934: strcat(filereso,fileresu);
1.126 brouard 10935: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10936: printf("Problem with Output resultfile: %s\n", filereso);
10937: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10938: fflush(ficlog);
10939: goto end;
10940: }
1.278 brouard 10941: /*-------- Rewriting parameter file ----------*/
10942: strcpy(rfileres,"r"); /* "Rparameterfile */
10943: strcat(rfileres,optionfilefiname); /* Parameter file first name */
10944: strcat(rfileres,"."); /* */
10945: strcat(rfileres,optionfilext); /* Other files have txt extension */
10946: if((ficres =fopen(rfileres,"w"))==NULL) {
10947: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10948: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
10949: fflush(ficlog);
10950: goto end;
10951: }
10952: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 10953:
1.278 brouard 10954:
1.126 brouard 10955: /* Reads comments: lines beginning with '#' */
10956: numlinepar=0;
1.277 brouard 10957: /* Is it a BOM UTF-8 Windows file? */
10958: /* First parameter line */
1.197 brouard 10959: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 10960: noffset=0;
10961: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10962: {
10963: noffset=noffset+3;
10964: printf("# File is an UTF8 Bom.\n"); // 0xBF
10965: }
10966: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
10967: {
10968: noffset=noffset+2;
10969: printf("# File is an UTF16BE BOM file\n");
10970: }
10971: else if( line[0] == 0 && line[1] == 0)
10972: {
10973: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10974: noffset=noffset+4;
10975: printf("# File is an UTF16BE BOM file\n");
10976: }
10977: } else{
10978: ;/*printf(" Not a BOM file\n");*/
10979: }
10980:
1.197 brouard 10981: /* If line starts with a # it is a comment */
1.277 brouard 10982: if (line[noffset] == '#') {
1.197 brouard 10983: numlinepar++;
10984: fputs(line,stdout);
10985: fputs(line,ficparo);
1.278 brouard 10986: fputs(line,ficres);
1.197 brouard 10987: fputs(line,ficlog);
10988: continue;
10989: }else
10990: break;
10991: }
10992: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
10993: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
10994: if (num_filled != 5) {
10995: printf("Should be 5 parameters\n");
1.283 brouard 10996: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 10997: }
1.126 brouard 10998: numlinepar++;
1.197 brouard 10999: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11000: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11001: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11002: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11003: }
11004: /* Second parameter line */
11005: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11006: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11007: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11008: if (line[0] == '#') {
11009: numlinepar++;
1.283 brouard 11010: printf("%s",line);
11011: fprintf(ficres,"%s",line);
11012: fprintf(ficparo,"%s",line);
11013: fprintf(ficlog,"%s",line);
1.197 brouard 11014: continue;
11015: }else
11016: break;
11017: }
1.223 brouard 11018: 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", \
11019: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11020: if (num_filled != 11) {
11021: 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 11022: printf("but line=%s\n",line);
1.283 brouard 11023: 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");
11024: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11025: }
1.223 brouard 11026: 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 11027: 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);
11028: 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, mle, weightopt);
11029: 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 11030: }
1.203 brouard 11031: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11032: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11033: /* Third parameter line */
11034: while(fgets(line, MAXLINE, ficpar)) {
11035: /* If line starts with a # it is a comment */
11036: if (line[0] == '#') {
11037: numlinepar++;
1.283 brouard 11038: printf("%s",line);
11039: fprintf(ficres,"%s",line);
11040: fprintf(ficparo,"%s",line);
11041: fprintf(ficlog,"%s",line);
1.197 brouard 11042: continue;
11043: }else
11044: break;
11045: }
1.201 brouard 11046: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11047: if (num_filled != 1){
11048: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11049: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11050: model[0]='\0';
11051: goto end;
11052: }
11053: else{
11054: if (model[0]=='+'){
11055: for(i=1; i<=strlen(model);i++)
11056: modeltemp[i-1]=model[i];
1.201 brouard 11057: strcpy(model,modeltemp);
1.197 brouard 11058: }
11059: }
1.199 brouard 11060: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11061: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11062: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11063: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11064: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11065: }
11066: /* 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); */
11067: /* numlinepar=numlinepar+3; /\* In general *\/ */
11068: /* 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 11069: /* 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); */
11070: /* 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 11071: fflush(ficlog);
1.190 brouard 11072: /* if(model[0]=='#'|| model[0]== '\0'){ */
11073: if(model[0]=='#'){
1.279 brouard 11074: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11075: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11076: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11077: if(mle != -1){
1.279 brouard 11078: 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 11079: exit(1);
11080: }
11081: }
1.126 brouard 11082: while((c=getc(ficpar))=='#' && c!= EOF){
11083: ungetc(c,ficpar);
11084: fgets(line, MAXLINE, ficpar);
11085: numlinepar++;
1.195 brouard 11086: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11087: z[0]=line[1];
11088: }
11089: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11090: fputs(line, stdout);
11091: //puts(line);
1.126 brouard 11092: fputs(line,ficparo);
11093: fputs(line,ficlog);
11094: }
11095: ungetc(c,ficpar);
11096:
11097:
1.145 brouard 11098: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 brouard 11099: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
11100: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
11101: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11102: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11103: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11104: v1+v2*age+v2*v3 makes cptcovn = 3
11105: */
11106: if (strlen(model)>1)
1.187 brouard 11107: 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 11108: else
1.187 brouard 11109: ncovmodel=2; /* Constant and age */
1.133 brouard 11110: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11111: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11112: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11113: 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);
11114: 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);
11115: fflush(stdout);
11116: fclose (ficlog);
11117: goto end;
11118: }
1.126 brouard 11119: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11120: delti=delti3[1][1];
11121: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11122: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11123: /* We could also provide initial parameters values giving by simple logistic regression
11124: * only one way, that is without matrix product. We will have nlstate maximizations */
11125: /* for(i=1;i<nlstate;i++){ */
11126: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11127: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11128: /* } */
1.126 brouard 11129: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11130: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11131: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11132: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11133: fclose (ficparo);
11134: fclose (ficlog);
11135: goto end;
11136: exit(0);
1.220 brouard 11137: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11138: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11139: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11140: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11141: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11142: matcov=matrix(1,npar,1,npar);
1.203 brouard 11143: hess=matrix(1,npar,1,npar);
1.220 brouard 11144: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11145: /* Read guessed parameters */
1.126 brouard 11146: /* Reads comments: lines beginning with '#' */
11147: while((c=getc(ficpar))=='#' && c!= EOF){
11148: ungetc(c,ficpar);
11149: fgets(line, MAXLINE, ficpar);
11150: numlinepar++;
1.141 brouard 11151: fputs(line,stdout);
1.126 brouard 11152: fputs(line,ficparo);
11153: fputs(line,ficlog);
11154: }
11155: ungetc(c,ficpar);
11156:
11157: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11158: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11159: for(i=1; i <=nlstate; i++){
1.234 brouard 11160: j=0;
1.126 brouard 11161: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11162: if(jj==i) continue;
11163: j++;
11164: fscanf(ficpar,"%1d%1d",&i1,&j1);
11165: if ((i1 != i) || (j1 != jj)){
11166: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11167: It might be a problem of design; if ncovcol and the model are correct\n \
11168: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11169: exit(1);
11170: }
11171: fprintf(ficparo,"%1d%1d",i1,j1);
11172: if(mle==1)
11173: printf("%1d%1d",i,jj);
11174: fprintf(ficlog,"%1d%1d",i,jj);
11175: for(k=1; k<=ncovmodel;k++){
11176: fscanf(ficpar," %lf",¶m[i][j][k]);
11177: if(mle==1){
11178: printf(" %lf",param[i][j][k]);
11179: fprintf(ficlog," %lf",param[i][j][k]);
11180: }
11181: else
11182: fprintf(ficlog," %lf",param[i][j][k]);
11183: fprintf(ficparo," %lf",param[i][j][k]);
11184: }
11185: fscanf(ficpar,"\n");
11186: numlinepar++;
11187: if(mle==1)
11188: printf("\n");
11189: fprintf(ficlog,"\n");
11190: fprintf(ficparo,"\n");
1.126 brouard 11191: }
11192: }
11193: fflush(ficlog);
1.234 brouard 11194:
1.251 brouard 11195: /* Reads parameters values */
1.126 brouard 11196: p=param[1][1];
1.251 brouard 11197: pstart=paramstart[1][1];
1.126 brouard 11198:
11199: /* Reads comments: lines beginning with '#' */
11200: while((c=getc(ficpar))=='#' && c!= EOF){
11201: ungetc(c,ficpar);
11202: fgets(line, MAXLINE, ficpar);
11203: numlinepar++;
1.141 brouard 11204: fputs(line,stdout);
1.126 brouard 11205: fputs(line,ficparo);
11206: fputs(line,ficlog);
11207: }
11208: ungetc(c,ficpar);
11209:
11210: for(i=1; i <=nlstate; i++){
11211: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11212: fscanf(ficpar,"%1d%1d",&i1,&j1);
11213: if ( (i1-i) * (j1-j) != 0){
11214: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11215: exit(1);
11216: }
11217: printf("%1d%1d",i,j);
11218: fprintf(ficparo,"%1d%1d",i1,j1);
11219: fprintf(ficlog,"%1d%1d",i1,j1);
11220: for(k=1; k<=ncovmodel;k++){
11221: fscanf(ficpar,"%le",&delti3[i][j][k]);
11222: printf(" %le",delti3[i][j][k]);
11223: fprintf(ficparo," %le",delti3[i][j][k]);
11224: fprintf(ficlog," %le",delti3[i][j][k]);
11225: }
11226: fscanf(ficpar,"\n");
11227: numlinepar++;
11228: printf("\n");
11229: fprintf(ficparo,"\n");
11230: fprintf(ficlog,"\n");
1.126 brouard 11231: }
11232: }
11233: fflush(ficlog);
1.234 brouard 11234:
1.145 brouard 11235: /* Reads covariance matrix */
1.126 brouard 11236: delti=delti3[1][1];
1.220 brouard 11237:
11238:
1.126 brouard 11239: /* 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 11240:
1.126 brouard 11241: /* Reads comments: lines beginning with '#' */
11242: while((c=getc(ficpar))=='#' && c!= EOF){
11243: ungetc(c,ficpar);
11244: fgets(line, MAXLINE, ficpar);
11245: numlinepar++;
1.141 brouard 11246: fputs(line,stdout);
1.126 brouard 11247: fputs(line,ficparo);
11248: fputs(line,ficlog);
11249: }
11250: ungetc(c,ficpar);
1.220 brouard 11251:
1.126 brouard 11252: matcov=matrix(1,npar,1,npar);
1.203 brouard 11253: hess=matrix(1,npar,1,npar);
1.131 brouard 11254: for(i=1; i <=npar; i++)
11255: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11256:
1.194 brouard 11257: /* Scans npar lines */
1.126 brouard 11258: for(i=1; i <=npar; i++){
1.226 brouard 11259: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11260: if(count != 3){
1.226 brouard 11261: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11262: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11263: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11264: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11265: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11266: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11267: exit(1);
1.220 brouard 11268: }else{
1.226 brouard 11269: if(mle==1)
11270: printf("%1d%1d%d",i1,j1,jk);
11271: }
11272: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11273: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11274: for(j=1; j <=i; j++){
1.226 brouard 11275: fscanf(ficpar," %le",&matcov[i][j]);
11276: if(mle==1){
11277: printf(" %.5le",matcov[i][j]);
11278: }
11279: fprintf(ficlog," %.5le",matcov[i][j]);
11280: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11281: }
11282: fscanf(ficpar,"\n");
11283: numlinepar++;
11284: if(mle==1)
1.220 brouard 11285: printf("\n");
1.126 brouard 11286: fprintf(ficlog,"\n");
11287: fprintf(ficparo,"\n");
11288: }
1.194 brouard 11289: /* End of read covariance matrix npar lines */
1.126 brouard 11290: for(i=1; i <=npar; i++)
11291: for(j=i+1;j<=npar;j++)
1.226 brouard 11292: matcov[i][j]=matcov[j][i];
1.126 brouard 11293:
11294: if(mle==1)
11295: printf("\n");
11296: fprintf(ficlog,"\n");
11297:
11298: fflush(ficlog);
11299:
11300: } /* End of mle != -3 */
1.218 brouard 11301:
1.186 brouard 11302: /* Main data
11303: */
1.126 brouard 11304: n= lastobs;
11305: num=lvector(1,n);
11306: moisnais=vector(1,n);
11307: annais=vector(1,n);
11308: moisdc=vector(1,n);
11309: andc=vector(1,n);
1.220 brouard 11310: weight=vector(1,n);
1.126 brouard 11311: agedc=vector(1,n);
11312: cod=ivector(1,n);
1.220 brouard 11313: for(i=1;i<=n;i++){
1.234 brouard 11314: num[i]=0;
11315: moisnais[i]=0;
11316: annais[i]=0;
11317: moisdc[i]=0;
11318: andc[i]=0;
11319: agedc[i]=0;
11320: cod[i]=0;
11321: weight[i]=1.0; /* Equal weights, 1 by default */
11322: }
1.126 brouard 11323: mint=matrix(1,maxwav,1,n);
11324: anint=matrix(1,maxwav,1,n);
1.131 brouard 11325: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11326: tab=ivector(1,NCOVMAX);
1.144 brouard 11327: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11328: 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 11329:
1.136 brouard 11330: /* Reads data from file datafile */
11331: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11332: goto end;
11333:
11334: /* Calculation of the number of parameters from char model */
1.234 brouard 11335: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11336: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11337: k=3 V4 Tvar[k=3]= 4 (from V4)
11338: k=2 V1 Tvar[k=2]= 1 (from V1)
11339: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11340: */
11341:
11342: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11343: TvarsDind=ivector(1,NCOVMAX); /* */
11344: TvarsD=ivector(1,NCOVMAX); /* */
11345: TvarsQind=ivector(1,NCOVMAX); /* */
11346: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11347: TvarF=ivector(1,NCOVMAX); /* */
11348: TvarFind=ivector(1,NCOVMAX); /* */
11349: TvarV=ivector(1,NCOVMAX); /* */
11350: TvarVind=ivector(1,NCOVMAX); /* */
11351: TvarA=ivector(1,NCOVMAX); /* */
11352: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11353: TvarFD=ivector(1,NCOVMAX); /* */
11354: TvarFDind=ivector(1,NCOVMAX); /* */
11355: TvarFQ=ivector(1,NCOVMAX); /* */
11356: TvarFQind=ivector(1,NCOVMAX); /* */
11357: TvarVD=ivector(1,NCOVMAX); /* */
11358: TvarVDind=ivector(1,NCOVMAX); /* */
11359: TvarVQ=ivector(1,NCOVMAX); /* */
11360: TvarVQind=ivector(1,NCOVMAX); /* */
11361:
1.230 brouard 11362: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11363: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11364: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11365: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11366: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11367: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11368: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11369: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11370: */
11371: /* For model-covariate k tells which data-covariate to use but
11372: because this model-covariate is a construction we invent a new column
11373: ncovcol + k1
11374: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11375: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11376: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11377: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11378: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11379: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11380: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11381: */
1.145 brouard 11382: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11383: 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 11384: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11385: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11386: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11387: 4 covariates (3 plus signs)
11388: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11389: */
1.230 brouard 11390: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11391: * individual dummy, fixed or varying:
11392: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11393: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11394: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11395: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11396: * Tmodelind[1]@9={9,0,3,2,}*/
11397: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11398: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11399: * individual quantitative, fixed or varying:
11400: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11401: * 3, 1, 0, 0, 0, 0, 0, 0},
11402: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11403: /* Main decodemodel */
11404:
1.187 brouard 11405:
1.223 brouard 11406: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11407: goto end;
11408:
1.137 brouard 11409: if((double)(lastobs-imx)/(double)imx > 1.10){
11410: nbwarn++;
11411: 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);
11412: 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);
11413: }
1.136 brouard 11414: /* if(mle==1){*/
1.137 brouard 11415: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11416: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11417: }
11418:
11419: /*-calculation of age at interview from date of interview and age at death -*/
11420: agev=matrix(1,maxwav,1,imx);
11421:
11422: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11423: goto end;
11424:
1.126 brouard 11425:
1.136 brouard 11426: agegomp=(int)agemin;
11427: free_vector(moisnais,1,n);
11428: free_vector(annais,1,n);
1.126 brouard 11429: /* free_matrix(mint,1,maxwav,1,n);
11430: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11431: /* free_vector(moisdc,1,n); */
11432: /* free_vector(andc,1,n); */
1.145 brouard 11433: /* */
11434:
1.126 brouard 11435: wav=ivector(1,imx);
1.214 brouard 11436: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11437: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11438: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11439: 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.*/
11440: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11441: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11442:
11443: /* Concatenates waves */
1.214 brouard 11444: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11445: Death is a valid wave (if date is known).
11446: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11447: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11448: and mw[mi+1][i]. dh depends on stepm.
11449: */
11450:
1.126 brouard 11451: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11452: /* Concatenates waves */
1.145 brouard 11453:
1.215 brouard 11454: free_vector(moisdc,1,n);
11455: free_vector(andc,1,n);
11456:
1.126 brouard 11457: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11458: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11459: ncodemax[1]=1;
1.145 brouard 11460: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11461: cptcoveff=0;
1.220 brouard 11462: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11463: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11464: }
11465:
11466: ncovcombmax=pow(2,cptcoveff);
11467: invalidvarcomb=ivector(1, ncovcombmax);
11468: for(i=1;i<ncovcombmax;i++)
11469: invalidvarcomb[i]=0;
11470:
1.211 brouard 11471: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11472: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11473: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11474:
1.200 brouard 11475: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11476: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11477: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11478: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11479: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11480: * (currently 0 or 1) in the data.
11481: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11482: * corresponding modality (h,j).
11483: */
11484:
1.145 brouard 11485: h=0;
11486: /*if (cptcovn > 0) */
1.126 brouard 11487: m=pow(2,cptcoveff);
11488:
1.144 brouard 11489: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11490: * For k=4 covariates, h goes from 1 to m=2**k
11491: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11492: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11493: * h\k 1 2 3 4
1.143 brouard 11494: *______________________________
11495: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11496: * 2 2 1 1 1
11497: * 3 i=2 1 2 1 1
11498: * 4 2 2 1 1
11499: * 5 i=3 1 i=2 1 2 1
11500: * 6 2 1 2 1
11501: * 7 i=4 1 2 2 1
11502: * 8 2 2 2 1
1.197 brouard 11503: * 9 i=5 1 i=3 1 i=2 1 2
11504: * 10 2 1 1 2
11505: * 11 i=6 1 2 1 2
11506: * 12 2 2 1 2
11507: * 13 i=7 1 i=4 1 2 2
11508: * 14 2 1 2 2
11509: * 15 i=8 1 2 2 2
11510: * 16 2 2 2 2
1.143 brouard 11511: */
1.212 brouard 11512: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11513: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11514: * and the value of each covariate?
11515: * V1=1, V2=1, V3=2, V4=1 ?
11516: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11517: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11518: * In order to get the real value in the data, we use nbcode
11519: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11520: * We are keeping this crazy system in order to be able (in the future?)
11521: * to have more than 2 values (0 or 1) for a covariate.
11522: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11523: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11524: * bbbbbbbb
11525: * 76543210
11526: * h-1 00000101 (6-1=5)
1.219 brouard 11527: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11528: * &
11529: * 1 00000001 (1)
1.219 brouard 11530: * 00000000 = 1 & ((h-1) >> (k-1))
11531: * +1= 00000001 =1
1.211 brouard 11532: *
11533: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11534: * h' 1101 =2^3+2^2+0x2^1+2^0
11535: * >>k' 11
11536: * & 00000001
11537: * = 00000001
11538: * +1 = 00000010=2 = codtabm(14,3)
11539: * Reverse h=6 and m=16?
11540: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11541: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11542: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11543: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11544: * V3=decodtabm(14,3,2**4)=2
11545: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11546: *(h-1) >> (j-1) 0011 =13 >> 2
11547: * &1 000000001
11548: * = 000000001
11549: * +1= 000000010 =2
11550: * 2211
11551: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11552: * V3=2
1.220 brouard 11553: * codtabm and decodtabm are identical
1.211 brouard 11554: */
11555:
1.145 brouard 11556:
11557: free_ivector(Ndum,-1,NCOVMAX);
11558:
11559:
1.126 brouard 11560:
1.186 brouard 11561: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11562: strcpy(optionfilegnuplot,optionfilefiname);
11563: if(mle==-3)
1.201 brouard 11564: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11565: strcat(optionfilegnuplot,".gp");
11566:
11567: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11568: printf("Problem with file %s",optionfilegnuplot);
11569: }
11570: else{
1.204 brouard 11571: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11572: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11573: //fprintf(ficgp,"set missing 'NaNq'\n");
11574: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11575: }
11576: /* fclose(ficgp);*/
1.186 brouard 11577:
11578:
11579: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11580:
11581: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11582: if(mle==-3)
1.201 brouard 11583: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11584: strcat(optionfilehtm,".htm");
11585: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11586: printf("Problem with %s \n",optionfilehtm);
11587: exit(0);
1.126 brouard 11588: }
11589:
11590: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11591: strcat(optionfilehtmcov,"-cov.htm");
11592: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11593: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11594: }
11595: else{
11596: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11597: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11598: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11599: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11600: }
11601:
1.213 brouard 11602: 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 11603: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11604: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11605: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11606: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11607: \n\
11608: <hr size=\"2\" color=\"#EC5E5E\">\
11609: <ul><li><h4>Parameter files</h4>\n\
11610: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11611: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11612: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11613: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11614: - Date and time at start: %s</ul>\n",\
11615: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11616: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11617: fileres,fileres,\
11618: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11619: fflush(fichtm);
11620:
11621: strcpy(pathr,path);
11622: strcat(pathr,optionfilefiname);
1.184 brouard 11623: #ifdef WIN32
11624: _chdir(optionfilefiname); /* Move to directory named optionfile */
11625: #else
1.126 brouard 11626: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11627: #endif
11628:
1.126 brouard 11629:
1.220 brouard 11630: /* Calculates basic frequencies. Computes observed prevalence at single age
11631: and for any valid combination of covariates
1.126 brouard 11632: and prints on file fileres'p'. */
1.251 brouard 11633: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11634: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11635:
11636: fprintf(fichtm,"\n");
1.274 brouard 11637: fprintf(fichtm,"<h4>Parameter line 2</h4><ul><li>Tolerance for the convergence of the likelihood: ftol=%f \n<li>Interval for the elementary matrix (in month): stepm=%d",\
11638: ftol, stepm);
11639: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11640: ncurrv=1;
11641: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11642: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11643: ncurrv=i;
11644: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
11645: fprintf(fichtm,"\n<li> Number of time varying (wave varying) covariates: ntv=%d ", ntv);
11646: ncurrv=i;
11647: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
11648: fprintf(fichtm,"\n<li>Number of quantitative time varying covariates: nqtv=%d ", nqtv);
11649: ncurrv=i;
11650: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11651: 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", \
11652: nlstate, ndeath, maxwav, mle, weightopt);
11653:
11654: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11655: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11656:
11657:
11658: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11659: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11660: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11661: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11662: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11663: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11664: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11665: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11666: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11667:
1.126 brouard 11668: /* For Powell, parameters are in a vector p[] starting at p[1]
11669: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11670: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11671:
11672: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11673: /* For mortality only */
1.126 brouard 11674: if (mle==-3){
1.136 brouard 11675: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11676: for(i=1;i<=NDIM;i++)
11677: for(j=1;j<=NDIM;j++)
11678: ximort[i][j]=0.;
1.186 brouard 11679: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11680: cens=ivector(1,n);
11681: ageexmed=vector(1,n);
11682: agecens=vector(1,n);
11683: dcwave=ivector(1,n);
1.223 brouard 11684:
1.126 brouard 11685: for (i=1; i<=imx; i++){
11686: dcwave[i]=-1;
11687: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11688: if (s[m][i]>nlstate) {
11689: dcwave[i]=m;
11690: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11691: break;
11692: }
1.126 brouard 11693: }
1.226 brouard 11694:
1.126 brouard 11695: for (i=1; i<=imx; i++) {
11696: if (wav[i]>0){
1.226 brouard 11697: ageexmed[i]=agev[mw[1][i]][i];
11698: j=wav[i];
11699: agecens[i]=1.;
11700:
11701: if (ageexmed[i]> 1 && wav[i] > 0){
11702: agecens[i]=agev[mw[j][i]][i];
11703: cens[i]= 1;
11704: }else if (ageexmed[i]< 1)
11705: cens[i]= -1;
11706: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11707: cens[i]=0 ;
1.126 brouard 11708: }
11709: else cens[i]=-1;
11710: }
11711:
11712: for (i=1;i<=NDIM;i++) {
11713: for (j=1;j<=NDIM;j++)
1.226 brouard 11714: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11715: }
11716:
1.145 brouard 11717: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11718: /*printf("%lf %lf", p[1], p[2]);*/
11719:
11720:
1.136 brouard 11721: #ifdef GSL
11722: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11723: #else
1.126 brouard 11724: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11725: #endif
1.201 brouard 11726: strcpy(filerespow,"POW-MORT_");
11727: strcat(filerespow,fileresu);
1.126 brouard 11728: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11729: printf("Problem with resultfile: %s\n", filerespow);
11730: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11731: }
1.136 brouard 11732: #ifdef GSL
11733: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11734: #else
1.126 brouard 11735: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11736: #endif
1.126 brouard 11737: /* for (i=1;i<=nlstate;i++)
11738: for(j=1;j<=nlstate+ndeath;j++)
11739: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11740: */
11741: fprintf(ficrespow,"\n");
1.136 brouard 11742: #ifdef GSL
11743: /* gsl starts here */
11744: T = gsl_multimin_fminimizer_nmsimplex;
11745: gsl_multimin_fminimizer *sfm = NULL;
11746: gsl_vector *ss, *x;
11747: gsl_multimin_function minex_func;
11748:
11749: /* Initial vertex size vector */
11750: ss = gsl_vector_alloc (NDIM);
11751:
11752: if (ss == NULL){
11753: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11754: }
11755: /* Set all step sizes to 1 */
11756: gsl_vector_set_all (ss, 0.001);
11757:
11758: /* Starting point */
1.126 brouard 11759:
1.136 brouard 11760: x = gsl_vector_alloc (NDIM);
11761:
11762: if (x == NULL){
11763: gsl_vector_free(ss);
11764: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11765: }
11766:
11767: /* Initialize method and iterate */
11768: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11769: /* gsl_vector_set(x, 0, 0.0268); */
11770: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11771: gsl_vector_set(x, 0, p[1]);
11772: gsl_vector_set(x, 1, p[2]);
11773:
11774: minex_func.f = &gompertz_f;
11775: minex_func.n = NDIM;
11776: minex_func.params = (void *)&p; /* ??? */
11777:
11778: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11779: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11780:
11781: printf("Iterations beginning .....\n\n");
11782: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11783:
11784: iteri=0;
11785: while (rval == GSL_CONTINUE){
11786: iteri++;
11787: status = gsl_multimin_fminimizer_iterate(sfm);
11788:
11789: if (status) printf("error: %s\n", gsl_strerror (status));
11790: fflush(0);
11791:
11792: if (status)
11793: break;
11794:
11795: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11796: ssval = gsl_multimin_fminimizer_size (sfm);
11797:
11798: if (rval == GSL_SUCCESS)
11799: printf ("converged to a local maximum at\n");
11800:
11801: printf("%5d ", iteri);
11802: for (it = 0; it < NDIM; it++){
11803: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11804: }
11805: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11806: }
11807:
11808: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11809:
11810: gsl_vector_free(x); /* initial values */
11811: gsl_vector_free(ss); /* inital step size */
11812: for (it=0; it<NDIM; it++){
11813: p[it+1]=gsl_vector_get(sfm->x,it);
11814: fprintf(ficrespow," %.12lf", p[it]);
11815: }
11816: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11817: #endif
11818: #ifdef POWELL
11819: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11820: #endif
1.126 brouard 11821: fclose(ficrespow);
11822:
1.203 brouard 11823: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11824:
11825: for(i=1; i <=NDIM; i++)
11826: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11827: matcov[i][j]=matcov[j][i];
1.126 brouard 11828:
11829: printf("\nCovariance matrix\n ");
1.203 brouard 11830: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11831: for(i=1; i <=NDIM; i++) {
11832: for(j=1;j<=NDIM;j++){
1.220 brouard 11833: printf("%f ",matcov[i][j]);
11834: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11835: }
1.203 brouard 11836: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11837: }
11838:
11839: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11840: for (i=1;i<=NDIM;i++) {
1.126 brouard 11841: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11842: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11843: }
1.126 brouard 11844: lsurv=vector(1,AGESUP);
11845: lpop=vector(1,AGESUP);
11846: tpop=vector(1,AGESUP);
11847: lsurv[agegomp]=100000;
11848:
11849: for (k=agegomp;k<=AGESUP;k++) {
11850: agemortsup=k;
11851: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11852: }
11853:
11854: for (k=agegomp;k<agemortsup;k++)
11855: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11856:
11857: for (k=agegomp;k<agemortsup;k++){
11858: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11859: sumlpop=sumlpop+lpop[k];
11860: }
11861:
11862: tpop[agegomp]=sumlpop;
11863: for (k=agegomp;k<(agemortsup-3);k++){
11864: /* tpop[k+1]=2;*/
11865: tpop[k+1]=tpop[k]-lpop[k];
11866: }
11867:
11868:
11869: printf("\nAge lx qx dx Lx Tx e(x)\n");
11870: for (k=agegomp;k<(agemortsup-2);k++)
11871: 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]);
11872:
11873:
11874: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11875: ageminpar=50;
11876: agemaxpar=100;
1.194 brouard 11877: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11878: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11879: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11880: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11881: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11882: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11883: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11884: }else{
11885: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11886: 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 11887: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11888: }
1.201 brouard 11889: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11890: stepm, weightopt,\
11891: model,imx,p,matcov,agemortsup);
11892:
11893: free_vector(lsurv,1,AGESUP);
11894: free_vector(lpop,1,AGESUP);
11895: free_vector(tpop,1,AGESUP);
1.220 brouard 11896: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11897: free_ivector(cens,1,n);
11898: free_vector(agecens,1,n);
11899: free_ivector(dcwave,1,n);
1.220 brouard 11900: #ifdef GSL
1.136 brouard 11901: #endif
1.186 brouard 11902: } /* Endof if mle==-3 mortality only */
1.205 brouard 11903: /* Standard */
11904: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11905: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11906: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11907: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11908: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11909: for (k=1; k<=npar;k++)
11910: printf(" %d %8.5f",k,p[k]);
11911: printf("\n");
1.205 brouard 11912: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11913: /* mlikeli uses func not funcone */
1.247 brouard 11914: /* for(i=1;i<nlstate;i++){ */
11915: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11916: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11917: /* } */
1.205 brouard 11918: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11919: }
11920: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11921: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11922: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11923: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11924: }
11925: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11926: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11927: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11928: for (k=1; k<=npar;k++)
11929: printf(" %d %8.5f",k,p[k]);
11930: printf("\n");
11931:
11932: /*--------- results files --------------*/
1.283 brouard 11933: /* 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 11934:
11935:
11936: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11937: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11938: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11939: for(i=1,jk=1; i <=nlstate; i++){
11940: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11941: if (k != i) {
11942: printf("%d%d ",i,k);
11943: fprintf(ficlog,"%d%d ",i,k);
11944: fprintf(ficres,"%1d%1d ",i,k);
11945: for(j=1; j <=ncovmodel; j++){
11946: printf("%12.7f ",p[jk]);
11947: fprintf(ficlog,"%12.7f ",p[jk]);
11948: fprintf(ficres,"%12.7f ",p[jk]);
11949: jk++;
11950: }
11951: printf("\n");
11952: fprintf(ficlog,"\n");
11953: fprintf(ficres,"\n");
11954: }
1.126 brouard 11955: }
11956: }
1.203 brouard 11957: if(mle != 0){
11958: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11959: ftolhess=ftol; /* Usually correct */
1.203 brouard 11960: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11961: 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");
11962: 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");
11963: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11964: for(k=1; k <=(nlstate+ndeath); k++){
11965: if (k != i) {
11966: printf("%d%d ",i,k);
11967: fprintf(ficlog,"%d%d ",i,k);
11968: for(j=1; j <=ncovmodel; j++){
11969: 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]));
11970: 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]));
11971: jk++;
11972: }
11973: printf("\n");
11974: fprintf(ficlog,"\n");
11975: }
11976: }
1.193 brouard 11977: }
1.203 brouard 11978: } /* end of hesscov and Wald tests */
1.225 brouard 11979:
1.203 brouard 11980: /* */
1.126 brouard 11981: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
11982: printf("# Scales (for hessian or gradient estimation)\n");
11983: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
11984: for(i=1,jk=1; i <=nlstate; i++){
11985: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 11986: if (j!=i) {
11987: fprintf(ficres,"%1d%1d",i,j);
11988: printf("%1d%1d",i,j);
11989: fprintf(ficlog,"%1d%1d",i,j);
11990: for(k=1; k<=ncovmodel;k++){
11991: printf(" %.5e",delti[jk]);
11992: fprintf(ficlog," %.5e",delti[jk]);
11993: fprintf(ficres," %.5e",delti[jk]);
11994: jk++;
11995: }
11996: printf("\n");
11997: fprintf(ficlog,"\n");
11998: fprintf(ficres,"\n");
11999: }
1.126 brouard 12000: }
12001: }
12002:
12003: 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 12004: if(mle >= 1) /* To big for the screen */
1.126 brouard 12005: 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");
12006: 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");
12007: /* # 121 Var(a12)\n\ */
12008: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12009: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12010: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12011: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12012: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12013: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12014: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12015:
12016:
12017: /* Just to have a covariance matrix which will be more understandable
12018: even is we still don't want to manage dictionary of variables
12019: */
12020: for(itimes=1;itimes<=2;itimes++){
12021: jj=0;
12022: for(i=1; i <=nlstate; i++){
1.225 brouard 12023: for(j=1; j <=nlstate+ndeath; j++){
12024: if(j==i) continue;
12025: for(k=1; k<=ncovmodel;k++){
12026: jj++;
12027: ca[0]= k+'a'-1;ca[1]='\0';
12028: if(itimes==1){
12029: if(mle>=1)
12030: printf("#%1d%1d%d",i,j,k);
12031: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12032: fprintf(ficres,"#%1d%1d%d",i,j,k);
12033: }else{
12034: if(mle>=1)
12035: printf("%1d%1d%d",i,j,k);
12036: fprintf(ficlog,"%1d%1d%d",i,j,k);
12037: fprintf(ficres,"%1d%1d%d",i,j,k);
12038: }
12039: ll=0;
12040: for(li=1;li <=nlstate; li++){
12041: for(lj=1;lj <=nlstate+ndeath; lj++){
12042: if(lj==li) continue;
12043: for(lk=1;lk<=ncovmodel;lk++){
12044: ll++;
12045: if(ll<=jj){
12046: cb[0]= lk +'a'-1;cb[1]='\0';
12047: if(ll<jj){
12048: if(itimes==1){
12049: if(mle>=1)
12050: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12051: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12052: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12053: }else{
12054: if(mle>=1)
12055: printf(" %.5e",matcov[jj][ll]);
12056: fprintf(ficlog," %.5e",matcov[jj][ll]);
12057: fprintf(ficres," %.5e",matcov[jj][ll]);
12058: }
12059: }else{
12060: if(itimes==1){
12061: if(mle>=1)
12062: printf(" Var(%s%1d%1d)",ca,i,j);
12063: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12064: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12065: }else{
12066: if(mle>=1)
12067: printf(" %.7e",matcov[jj][ll]);
12068: fprintf(ficlog," %.7e",matcov[jj][ll]);
12069: fprintf(ficres," %.7e",matcov[jj][ll]);
12070: }
12071: }
12072: }
12073: } /* end lk */
12074: } /* end lj */
12075: } /* end li */
12076: if(mle>=1)
12077: printf("\n");
12078: fprintf(ficlog,"\n");
12079: fprintf(ficres,"\n");
12080: numlinepar++;
12081: } /* end k*/
12082: } /*end j */
1.126 brouard 12083: } /* end i */
12084: } /* end itimes */
12085:
12086: fflush(ficlog);
12087: fflush(ficres);
1.225 brouard 12088: while(fgets(line, MAXLINE, ficpar)) {
12089: /* If line starts with a # it is a comment */
12090: if (line[0] == '#') {
12091: numlinepar++;
12092: fputs(line,stdout);
12093: fputs(line,ficparo);
12094: fputs(line,ficlog);
12095: continue;
12096: }else
12097: break;
12098: }
12099:
1.209 brouard 12100: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12101: /* ungetc(c,ficpar); */
12102: /* fgets(line, MAXLINE, ficpar); */
12103: /* fputs(line,stdout); */
12104: /* fputs(line,ficparo); */
12105: /* } */
12106: /* ungetc(c,ficpar); */
1.126 brouard 12107:
12108: estepm=0;
1.209 brouard 12109: 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 12110:
12111: if (num_filled != 6) {
12112: 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);
12113: 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);
12114: goto end;
12115: }
12116: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12117: }
12118: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12119: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12120:
1.209 brouard 12121: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12122: if (estepm==0 || estepm < stepm) estepm=stepm;
12123: if (fage <= 2) {
12124: bage = ageminpar;
12125: fage = agemaxpar;
12126: }
12127:
12128: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12129: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12130: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12131:
1.186 brouard 12132: /* Other stuffs, more or less useful */
1.254 brouard 12133: while(fgets(line, MAXLINE, ficpar)) {
12134: /* If line starts with a # it is a comment */
12135: if (line[0] == '#') {
12136: numlinepar++;
12137: fputs(line,stdout);
12138: fputs(line,ficparo);
12139: fputs(line,ficlog);
12140: continue;
12141: }else
12142: break;
12143: }
12144:
12145: 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){
12146:
12147: if (num_filled != 7) {
12148: 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);
12149: 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);
12150: goto end;
12151: }
12152: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12153: 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);
12154: 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);
12155: 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 12156: }
1.254 brouard 12157:
12158: while(fgets(line, MAXLINE, ficpar)) {
12159: /* If line starts with a # it is a comment */
12160: if (line[0] == '#') {
12161: numlinepar++;
12162: fputs(line,stdout);
12163: fputs(line,ficparo);
12164: fputs(line,ficlog);
12165: continue;
12166: }else
12167: break;
1.126 brouard 12168: }
12169:
12170:
12171: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12172: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12173:
1.254 brouard 12174: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12175: if (num_filled != 1) {
12176: 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);
12177: 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);
12178: goto end;
12179: }
12180: printf("pop_based=%d\n",popbased);
12181: fprintf(ficlog,"pop_based=%d\n",popbased);
12182: fprintf(ficparo,"pop_based=%d\n",popbased);
12183: fprintf(ficres,"pop_based=%d\n",popbased);
12184: }
12185:
1.258 brouard 12186: /* Results */
12187: nresult=0;
12188: do{
12189: if(!fgets(line, MAXLINE, ficpar)){
12190: endishere=1;
12191: parameterline=14;
12192: }else if (line[0] == '#') {
12193: /* If line starts with a # it is a comment */
1.254 brouard 12194: numlinepar++;
12195: fputs(line,stdout);
12196: fputs(line,ficparo);
12197: fputs(line,ficlog);
12198: continue;
1.258 brouard 12199: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12200: parameterline=11;
12201: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12202: parameterline=12;
12203: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12204: parameterline=13;
12205: else{
12206: parameterline=14;
1.254 brouard 12207: }
1.258 brouard 12208: switch (parameterline){
12209: case 11:
12210: 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){
12211: if (num_filled != 8) {
12212: 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);
12213: 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);
12214: goto end;
12215: }
12216: 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);
12217: 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);
12218: 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);
12219: 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);
12220: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12221: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12222: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
12223:
1.258 brouard 12224: }
1.254 brouard 12225: break;
1.258 brouard 12226: case 12:
12227: /*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);*/
12228: 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){
12229: if (num_filled != 8) {
1.262 brouard 12230: 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);
12231: 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 12232: goto end;
12233: }
12234: 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);
12235: 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);
12236: 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);
12237: 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);
12238: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12239: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12240: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.258 brouard 12241: }
1.230 brouard 12242: break;
1.258 brouard 12243: case 13:
12244: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12245: if (num_filled == 0){
12246: resultline[0]='\0';
12247: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12248: 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);
12249: break;
12250: } else if (num_filled != 1){
12251: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12252: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12253: }
12254: nresult++; /* Sum of resultlines */
12255: printf("Result %d: result=%s\n",nresult, resultline);
12256: if(nresult > MAXRESULTLINES){
12257: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12258: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12259: goto end;
12260: }
12261: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12262: fprintf(ficparo,"result: %s\n",resultline);
12263: fprintf(ficres,"result: %s\n",resultline);
12264: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12265: break;
1.258 brouard 12266: case 14:
1.259 brouard 12267: if(ncovmodel >2 && nresult==0 ){
12268: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12269: goto end;
12270: }
1.259 brouard 12271: break;
1.258 brouard 12272: default:
12273: nresult=1;
12274: decoderesult(".",nresult ); /* No covariate */
12275: }
12276: } /* End switch parameterline */
12277: }while(endishere==0); /* End do */
1.126 brouard 12278:
1.230 brouard 12279: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12280: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12281:
12282: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12283: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12284: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12285: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12286: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12287: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12288: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12289: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12290: }else{
1.270 brouard 12291: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12292: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12293: }
12294: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12295: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.273 brouard 12296: jprev1,mprev1,anprev1,dateprev1, dateproj1, dateback1,jprev2,mprev2,anprev2,dateprev2,dateproj2, dateback2);
1.220 brouard 12297:
1.225 brouard 12298: /*------------ free_vector -------------*/
12299: /* chdir(path); */
1.220 brouard 12300:
1.215 brouard 12301: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12302: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12303: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12304: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 12305: free_lvector(num,1,n);
12306: free_vector(agedc,1,n);
12307: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12308: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12309: fclose(ficparo);
12310: fclose(ficres);
1.220 brouard 12311:
12312:
1.186 brouard 12313: /* Other results (useful)*/
1.220 brouard 12314:
12315:
1.126 brouard 12316: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12317: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12318: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12319: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12320: fclose(ficrespl);
12321:
12322: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12323: /*#include "hpijx.h"*/
12324: hPijx(p, bage, fage);
1.145 brouard 12325: fclose(ficrespij);
1.227 brouard 12326:
1.220 brouard 12327: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12328: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12329: k=1;
1.126 brouard 12330: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12331:
1.269 brouard 12332: /* Prevalence for each covariate combination in probs[age][status][cov] */
12333: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12334: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12335: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12336: for(k=1;k<=ncovcombmax;k++)
12337: probs[i][j][k]=0.;
1.269 brouard 12338: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12339: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12340: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12341: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12342: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12343: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12344: for(k=1;k<=ncovcombmax;k++)
12345: mobaverages[i][j][k]=0.;
1.219 brouard 12346: mobaverage=mobaverages;
12347: if (mobilav!=0) {
1.235 brouard 12348: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12349: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12350: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12351: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12352: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12353: }
1.269 brouard 12354: } else if (mobilavproj !=0) {
1.235 brouard 12355: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12356: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12357: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12358: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12359: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12360: }
1.269 brouard 12361: }else{
12362: printf("Internal error moving average\n");
12363: fflush(stdout);
12364: exit(1);
1.219 brouard 12365: }
12366: }/* end if moving average */
1.227 brouard 12367:
1.126 brouard 12368: /*---------- Forecasting ------------------*/
12369: if(prevfcast==1){
12370: /* if(stepm ==1){*/
1.269 brouard 12371: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12372: }
1.269 brouard 12373:
12374: /* Backcasting */
1.217 brouard 12375: if(backcast==1){
1.219 brouard 12376: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12377: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12378: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12379:
12380: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12381:
12382: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12383:
1.219 brouard 12384: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12385: fclose(ficresplb);
12386:
1.222 brouard 12387: hBijx(p, bage, fage, mobaverage);
12388: fclose(ficrespijb);
1.219 brouard 12389:
1.269 brouard 12390: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12391: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12392: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12393:
12394:
1.269 brouard 12395: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12396: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12397: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12398: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12399: } /* end Backcasting */
1.268 brouard 12400:
1.186 brouard 12401:
12402: /* ------ Other prevalence ratios------------ */
1.126 brouard 12403:
1.215 brouard 12404: free_ivector(wav,1,imx);
12405: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12406: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12407: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12408:
12409:
1.127 brouard 12410: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12411:
1.201 brouard 12412: strcpy(filerese,"E_");
12413: strcat(filerese,fileresu);
1.126 brouard 12414: if((ficreseij=fopen(filerese,"w"))==NULL) {
12415: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12416: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12417: }
1.208 brouard 12418: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12419: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12420:
12421: pstamp(ficreseij);
1.219 brouard 12422:
1.235 brouard 12423: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12424: if (cptcovn < 1){i1=1;}
12425:
12426: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12427: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12428: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12429: continue;
1.219 brouard 12430: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12431: printf("\n#****** ");
1.225 brouard 12432: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12433: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12434: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12435: }
12436: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12437: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12438: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12439: }
12440: fprintf(ficreseij,"******\n");
1.235 brouard 12441: printf("******\n");
1.219 brouard 12442:
12443: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12444: oldm=oldms;savm=savms;
1.235 brouard 12445: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12446:
1.219 brouard 12447: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12448: }
12449: fclose(ficreseij);
1.208 brouard 12450: printf("done evsij\n");fflush(stdout);
12451: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12452:
1.218 brouard 12453:
1.227 brouard 12454: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12455:
1.201 brouard 12456: strcpy(filerest,"T_");
12457: strcat(filerest,fileresu);
1.127 brouard 12458: if((ficrest=fopen(filerest,"w"))==NULL) {
12459: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12460: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12461: }
1.208 brouard 12462: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12463: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12464: strcpy(fileresstde,"STDE_");
12465: strcat(fileresstde,fileresu);
1.126 brouard 12466: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12467: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12468: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12469: }
1.227 brouard 12470: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12471: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12472:
1.201 brouard 12473: strcpy(filerescve,"CVE_");
12474: strcat(filerescve,fileresu);
1.126 brouard 12475: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12476: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12477: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12478: }
1.227 brouard 12479: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12480: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12481:
1.201 brouard 12482: strcpy(fileresv,"V_");
12483: strcat(fileresv,fileresu);
1.126 brouard 12484: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12485: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12486: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12487: }
1.227 brouard 12488: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12489: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12490:
1.235 brouard 12491: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12492: if (cptcovn < 1){i1=1;}
12493:
12494: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12495: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12496: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12497: continue;
1.242 brouard 12498: printf("\n#****** Result for:");
12499: fprintf(ficrest,"\n#****** Result for:");
12500: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12501: for(j=1;j<=cptcoveff;j++){
12502: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12503: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12504: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12505: }
1.235 brouard 12506: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12507: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12508: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12509: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12510: }
1.208 brouard 12511: fprintf(ficrest,"******\n");
1.227 brouard 12512: fprintf(ficlog,"******\n");
12513: printf("******\n");
1.208 brouard 12514:
12515: fprintf(ficresstdeij,"\n#****** ");
12516: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12517: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12518: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12519: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12520: }
1.235 brouard 12521: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12522: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12523: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12524: }
1.208 brouard 12525: fprintf(ficresstdeij,"******\n");
12526: fprintf(ficrescveij,"******\n");
12527:
12528: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12529: /* pstamp(ficresvij); */
1.225 brouard 12530: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12531: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12532: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12533: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12534: }
1.208 brouard 12535: fprintf(ficresvij,"******\n");
12536:
12537: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12538: oldm=oldms;savm=savms;
1.235 brouard 12539: printf(" cvevsij ");
12540: fprintf(ficlog, " cvevsij ");
12541: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12542: printf(" end cvevsij \n ");
12543: fprintf(ficlog, " end cvevsij \n ");
12544:
12545: /*
12546: */
12547: /* goto endfree; */
12548:
12549: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12550: pstamp(ficrest);
12551:
1.269 brouard 12552: epj=vector(1,nlstate+1);
1.208 brouard 12553: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12554: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12555: cptcod= 0; /* To be deleted */
12556: printf("varevsij vpopbased=%d \n",vpopbased);
12557: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12558: 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 12559: 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 ");
12560: if(vpopbased==1)
12561: 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);
12562: else
12563: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
12564: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12565: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12566: fprintf(ficrest,"\n");
12567: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
12568: printf("Computing age specific period (stable) prevalences in each health state \n");
12569: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
12570: for(age=bage; age <=fage ;age++){
1.235 brouard 12571: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12572: if (vpopbased==1) {
12573: if(mobilav ==0){
12574: for(i=1; i<=nlstate;i++)
12575: prlim[i][i]=probs[(int)age][i][k];
12576: }else{ /* mobilav */
12577: for(i=1; i<=nlstate;i++)
12578: prlim[i][i]=mobaverage[(int)age][i][k];
12579: }
12580: }
1.219 brouard 12581:
1.227 brouard 12582: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12583: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12584: /* printf(" age %4.0f ",age); */
12585: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12586: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12587: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12588: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12589: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12590: }
12591: epj[nlstate+1] +=epj[j];
12592: }
12593: /* printf(" age %4.0f \n",age); */
1.219 brouard 12594:
1.227 brouard 12595: for(i=1, vepp=0.;i <=nlstate;i++)
12596: for(j=1;j <=nlstate;j++)
12597: vepp += vareij[i][j][(int)age];
12598: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12599: for(j=1;j <=nlstate;j++){
12600: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12601: }
12602: fprintf(ficrest,"\n");
12603: }
1.208 brouard 12604: } /* End vpopbased */
1.269 brouard 12605: free_vector(epj,1,nlstate+1);
1.208 brouard 12606: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12607: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12608: printf("done selection\n");fflush(stdout);
12609: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12610:
1.235 brouard 12611: } /* End k selection */
1.227 brouard 12612:
12613: printf("done State-specific expectancies\n");fflush(stdout);
12614: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12615:
1.269 brouard 12616: /* variance-covariance of period prevalence*/
12617: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12618:
1.227 brouard 12619:
12620: free_vector(weight,1,n);
12621: free_imatrix(Tvard,1,NCOVMAX,1,2);
12622: free_imatrix(s,1,maxwav+1,1,n);
12623: free_matrix(anint,1,maxwav,1,n);
12624: free_matrix(mint,1,maxwav,1,n);
12625: free_ivector(cod,1,n);
12626: free_ivector(tab,1,NCOVMAX);
12627: fclose(ficresstdeij);
12628: fclose(ficrescveij);
12629: fclose(ficresvij);
12630: fclose(ficrest);
12631: fclose(ficpar);
12632:
12633:
1.126 brouard 12634: /*---------- End : free ----------------*/
1.219 brouard 12635: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12636: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12637: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12638: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12639: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12640: } /* mle==-3 arrives here for freeing */
1.227 brouard 12641: /* endfree:*/
12642: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12643: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12644: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 brouard 12645: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
12646: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
12647: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12648: free_matrix(covar,0,NCOVMAX,1,n);
12649: free_matrix(matcov,1,npar,1,npar);
12650: free_matrix(hess,1,npar,1,npar);
12651: /*free_vector(delti,1,npar);*/
12652: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12653: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12654: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12655: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12656:
12657: free_ivector(ncodemax,1,NCOVMAX);
12658: free_ivector(ncodemaxwundef,1,NCOVMAX);
12659: free_ivector(Dummy,-1,NCOVMAX);
12660: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12661: free_ivector(DummyV,1,NCOVMAX);
12662: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12663: free_ivector(Typevar,-1,NCOVMAX);
12664: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12665: free_ivector(TvarsQ,1,NCOVMAX);
12666: free_ivector(TvarsQind,1,NCOVMAX);
12667: free_ivector(TvarsD,1,NCOVMAX);
12668: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12669: free_ivector(TvarFD,1,NCOVMAX);
12670: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12671: free_ivector(TvarF,1,NCOVMAX);
12672: free_ivector(TvarFind,1,NCOVMAX);
12673: free_ivector(TvarV,1,NCOVMAX);
12674: free_ivector(TvarVind,1,NCOVMAX);
12675: free_ivector(TvarA,1,NCOVMAX);
12676: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12677: free_ivector(TvarFQ,1,NCOVMAX);
12678: free_ivector(TvarFQind,1,NCOVMAX);
12679: free_ivector(TvarVD,1,NCOVMAX);
12680: free_ivector(TvarVDind,1,NCOVMAX);
12681: free_ivector(TvarVQ,1,NCOVMAX);
12682: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12683: free_ivector(Tvarsel,1,NCOVMAX);
12684: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12685: free_ivector(Tposprod,1,NCOVMAX);
12686: free_ivector(Tprod,1,NCOVMAX);
12687: free_ivector(Tvaraff,1,NCOVMAX);
12688: free_ivector(invalidvarcomb,1,ncovcombmax);
12689: free_ivector(Tage,1,NCOVMAX);
12690: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12691: free_ivector(TmodelInvind,1,NCOVMAX);
12692: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12693:
12694: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12695: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12696: fflush(fichtm);
12697: fflush(ficgp);
12698:
1.227 brouard 12699:
1.126 brouard 12700: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12701: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12702: 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 12703: }else{
12704: printf("End of Imach\n");
12705: fprintf(ficlog,"End of Imach\n");
12706: }
12707: printf("See log file on %s\n",filelog);
12708: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12709: /*(void) gettimeofday(&end_time,&tzp);*/
12710: rend_time = time(NULL);
12711: end_time = *localtime(&rend_time);
12712: /* tml = *localtime(&end_time.tm_sec); */
12713: strcpy(strtend,asctime(&end_time));
1.126 brouard 12714: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12715: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12716: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12717:
1.157 brouard 12718: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12719: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12720: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12721: /* printf("Total time was %d uSec.\n", total_usecs);*/
12722: /* if(fileappend(fichtm,optionfilehtm)){ */
12723: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12724: fclose(fichtm);
12725: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12726: fclose(fichtmcov);
12727: fclose(ficgp);
12728: fclose(ficlog);
12729: /*------ End -----------*/
1.227 brouard 12730:
1.281 brouard 12731:
12732: /* Executes gnuplot */
1.227 brouard 12733:
12734: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12735: #ifdef WIN32
1.227 brouard 12736: if (_chdir(pathcd) != 0)
12737: printf("Can't move to directory %s!\n",path);
12738: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12739: #else
1.227 brouard 12740: if(chdir(pathcd) != 0)
12741: printf("Can't move to directory %s!\n", path);
12742: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12743: #endif
1.126 brouard 12744: printf("Current directory %s!\n",pathcd);
12745: /*strcat(plotcmd,CHARSEPARATOR);*/
12746: sprintf(plotcmd,"gnuplot");
1.157 brouard 12747: #ifdef _WIN32
1.126 brouard 12748: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12749: #endif
12750: if(!stat(plotcmd,&info)){
1.158 brouard 12751: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12752: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12753: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12754: }else
12755: strcpy(pplotcmd,plotcmd);
1.157 brouard 12756: #ifdef __unix
1.126 brouard 12757: strcpy(plotcmd,GNUPLOTPROGRAM);
12758: if(!stat(plotcmd,&info)){
1.158 brouard 12759: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12760: }else
12761: strcpy(pplotcmd,plotcmd);
12762: #endif
12763: }else
12764: strcpy(pplotcmd,plotcmd);
12765:
12766: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12767: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12768:
1.126 brouard 12769: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12770: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12771: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12772: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12773: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12774: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12775: }
1.158 brouard 12776: printf(" Successful, please wait...");
1.126 brouard 12777: while (z[0] != 'q') {
12778: /* chdir(path); */
1.154 brouard 12779: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12780: scanf("%s",z);
12781: /* if (z[0] == 'c') system("./imach"); */
12782: if (z[0] == 'e') {
1.158 brouard 12783: #ifdef __APPLE__
1.152 brouard 12784: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12785: #elif __linux
12786: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12787: #else
1.152 brouard 12788: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12789: #endif
12790: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12791: system(pplotcmd);
1.126 brouard 12792: }
12793: else if (z[0] == 'g') system(plotcmd);
12794: else if (z[0] == 'q') exit(0);
12795: }
1.227 brouard 12796: end:
1.126 brouard 12797: while (z[0] != 'q') {
1.195 brouard 12798: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12799: scanf("%s",z);
12800: }
1.283 brouard 12801: printf("End\n");
1.282 brouard 12802: exit(0);
1.126 brouard 12803: }
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